Dataset Viewer
problems
dict |
|---|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Water-borne diseases such as diarrhea, cholera, typhoid, and hepatitis A are prevalent in many rural areas and tribal belts of the Northeastern Region (NER), especially during the monsoon season. These outbreaks are often linked to contaminated water sources, poor sanitation infrastructure, and delayed medical response. The terrain and remoteness of many villages make it difficult for health workers to monitor and respond to emerging health threats in time.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "A digital health platform that includes:\n\n• A mobile app for data collection and community health reporting.\n• AI-based outbreak prediction engine using health and environmental data.\n• Integration with low-cost water quality sensors or manual test kits.\n• Alert system for health authorities and local leaders.\n• Educational modules for hygiene awareness and disease prevention.\n• Offline functionality and support for tribal languages.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": "This problem statement proposes the development of a Smart Health Surveillance and Early Warning System that can detect, monitor, and help prevent outbreaks of water-borne diseases in vulnerable communities. The system can be:\n\n• Collect health data from local clinics, ASHA workers, and community volunteers via mobile apps or SMS.\n• Use AI/ML models to detect patterns and predict potential outbreaks based on symptoms, water quality reports, and seasonal trends.\n• Integrate with water testing kits or IoT sensors to monitor water source contamination (e.g., turbidity, pH, bacterial presence).\n• Provide real-time alerts to district health officials and local governance bodies.\n• Include a multilingual mobile interface for community reporting and awareness campaigns.\n• Offer dashboards for health departments to visualize hotspots, track interventions, and allocate resources.",
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Development of North Eastern Region",
"problem_description": "This problem statement proposes the development of a Smart Health Surveillance and Early Warning System that can detect, monitor, and help prevent outbreaks of water-borne diseases in vulnerable communities. The system can be:\n\n• Collect health data from local clinics, ASHA workers, and community volunteers via mobile apps or SMS.\n• Use AI/ML models to detect patterns and predict potential outbreaks based on symptoms, water quality reports, and seasonal trends.\n• Integrate with water testing kits or IoT sensors to monitor water source contamination (e.g., turbidity, pH, bacterial presence).\n• Provide real-time alerts to district health officials and local governance bodies.\n• Include a multilingual mobile interface for community reporting and awareness campaigns.\n• Offer dashboards for health departments to visualize hotspots, track interventions, and allocate resources.\n\nBackground\n\nWater-borne diseases such as diarrhea, cholera, typhoid, and hepatitis A are prevalent in many rural areas and tribal belts of the Northeastern Region (NER), especially during the monsoon season. These outbreaks are often linked to contaminated water sources, poor sanitation infrastructure, and delayed medical response. The terrain and remoteness of many villages make it difficult for health workers to monitor and respond to emerging health threats in time.\n\nExpected Solution\n\nA digital health platform that includes:\n\n• A mobile app for data collection and community health reporting.\n• AI-based outbreak prediction engine using health and environmental data.\n• Integration with low-cost water quality sensors or manual test kits.\n• Alert system for health authorities and local leaders.\n• Educational modules for hygiene awareness and disease prevention.\n• Offline functionality and support for tribal languages.",
"ps_number": "SIH25001",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "MedTech / BioTech / HealthTech",
"title": "Smart Community Health Monitoring and Early Warning System for Water-Borne Diseases in Rural Northeast India"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": "• Detect sudden location drop-offs, prolonged inactivity, or deviation from planned routes.\n• Flag missing, silent, or distress behaviour for investigations.",
"background": "In regions like the Northeast, where tourism is a key economic driver, ensuring the safety of visitors is paramount. Traditional policing and manual tracking methods are insufficient in remote and high-risk areas. There is a pressing need for a smart, technology-driven solution that ensures real-time monitoring, rapid response, and secure identity verification for tourists, while maintaining privacy and ease of travel.",
"conclusion": null,
"data_privacy_&_security": "• End-to-end encryption and compliance with data protection laws.\n• Blockchain ensures tamper-proof identity and travel records.",
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": "• A secure blockchain-based system that issues digital IDs to tourists at entry points (airports, hotels, check-posts).\n• These IDs should include basic KYC (Aadhaar/passport), trip itinerary, and emergency contacts, and be valid only for the duration of the visit.",
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "A robust digital ecosystem comprising:\n\n• Web portal and mobile app for tourists and authorities.\n• AI/ML models for behaviour tracking and predictive alerts.\n• Blockchain-based ID generation and verification.\n• Real-time dashboards for police/tourism departments.\n• Optional IoT wearable integration for enhanced safety.\n• Automated alert dispatch and evidence logging systems.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": "This problem statement proposes the development of a Smart Tourist Safety Monitoring & Incident Response System that leverages AI, Blockchain, and Geo-Fencing technologies. The system should include:",
"iot_integration_optional": "• Smart bands or tags for tourists in high-risk areas (e.g., caves, forests).\n• Continuous health/location signals and manual SOS feature.",
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": "• Auto-assign a Tourist Safety Score based on travel patterns and area sensitivity.\n• Geo-fencing alerts when tourists enter high-risk or restricted zones.\n• Panic Button with live location sharing to nearest police unit and emergency contacts.\n• Optional real-time tracking feature (opt-in) for families and law enforcement.",
"multilingual_support": "• App and platform available in 10+ Indian languages and English.\n• Voice/text emergency access for elderly or disabled travellers.",
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": "• Real-time visualizations of tourist clusters and heat maps of high-risk zones.\n• Access to digital ID records, alert history, and last known locations.\n• Automated E-FIR generation for missing person cases."
},
"organization": "Ministry of Development of North Eastern Region",
"problem_description": "This problem statement proposes the development of a Smart Tourist Safety Monitoring & Incident Response System that leverages AI, Blockchain, and Geo-Fencing technologies. The system should include:\n\nDigital Tourist ID Generation Platform\n• A secure blockchain-based system that issues digital IDs to tourists at entry points (airports, hotels, check-posts).\n• These IDs should include basic KYC (Aadhaar/passport), trip itinerary, and emergency contacts, and be valid only for the duration of the visit.\n\nMobile Application for Tourists\n• Auto-assign a Tourist Safety Score based on travel patterns and area sensitivity.\n• Geo-fencing alerts when tourists enter high-risk or restricted zones.\n• Panic Button with live location sharing to nearest police unit and emergency contacts.\n• Optional real-time tracking feature (opt-in) for families and law enforcement.\n\nAI-Based Anomaly Detection\n• Detect sudden location drop-offs, prolonged inactivity, or deviation from planned routes.\n• Flag missing, silent, or distress behaviour for investigations.\n\nTourism Department & Police Dashboard\n• Real-time visualizations of tourist clusters and heat maps of high-risk zones.\n• Access to digital ID records, alert history, and last known locations.\n• Automated E-FIR generation for missing person cases.\n\nIoT Integration (Optional)\n• Smart bands or tags for tourists in high-risk areas (e.g., caves, forests).\n• Continuous health/location signals and manual SOS feature.\n\nMultilingual Support\n• App and platform available in 10+ Indian languages and English.\n• Voice/text emergency access for elderly or disabled travellers.\n\nData Privacy & Security\n• End-to-end encryption and compliance with data protection laws.\n• Blockchain ensures tamper-proof identity and travel records.\n\nBackground\n\nIn regions like the Northeast, where tourism is a key economic driver, ensuring the safety of visitors is paramount. Traditional policing and manual tracking methods are insufficient in remote and high-risk areas. There is a pressing need for a smart, technology-driven solution that ensures real-time monitoring, rapid response, and secure identity verification for tourists, while maintaining privacy and ease of travel.\n\nExpected Solution\n\nA robust digital ecosystem comprising:\n\n• Web portal and mobile app for tourists and authorities.\n• AI/ML models for behaviour tracking and predictive alerts.\n• Blockchain-based ID generation and verification.\n• Real-time dashboards for police/tourism departments.\n• Optional IoT wearable integration for enhanced safety.\n• Automated alert dispatch and evidence logging systems.",
"ps_number": "SIH25002",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Travel & Tourism",
"title": "Smart Tourist Safety Monitoring & Incident Response System using AI Geo-Fencing and Blockchain-based Digital ID"
}
|
{
"category": "Hardware",
"details": {
"ai-based_anomaly_detection": null,
"background": "The Northeastern Region faces persistent challenges in building and maintaining rural roads due to difficult terrain, high rainfall, and limited access to conventional construction materials. Simultaneously, plastic waste management remains a growing concern in both urban and semi-urban pockets of the region. Bamboo, abundantly available in NER, offers high tensile strength and flexibility, while recycled plastic enhances water resistance and durability when used in road surfacing. Combining these two materials presents a unique opportunity to create sustainable, modular road infrastructure tailored for NER's needs.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "• A prototype modular panel system combining bamboo and recycled plastic.\n• A deployment guide for constructing 100-200 meter stretches in rural terrain.\n• Cost-benefit analysis compared to conventional road-building methods.\n• Environmental impact assessment and scalability roadmap.\n• Optional integration with IoT-based monitoring for wear and tear tracking.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": "This problem statement proposes the design and development of prefabricated modular road panels that use bamboo reinforcement and plastic waste-infused composites to build durable, erosion-resistant roads in remote and hilly areas. The solution may be:\n\n• Utilize bamboo mesh or strips as structural reinforcement within concrete or stabilized soil panels.\n• Incorporate processed plastic waste (Low-Density Polyethylene - LDPE, High-Density Polyethylene - HDPE) into the mix to improve water resistance and flexibility.\n• Include drainage features, slope adaptation mechanisms, and anti-slip surfacing.",
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Development of North Eastern Region",
"problem_description": "This problem statement proposes the design and development of prefabricated modular road panels that use bamboo reinforcement and plastic waste-infused composites to build durable, erosion-resistant roads in remote and hilly areas. The solution may be:\n\n• Utilize bamboo mesh or strips as structural reinforcement within concrete or stabilized soil panels.\n• Incorporate processed plastic waste (Low-Density Polyethylene - LDPE, High-Density Polyethylene - HDPE) into the mix to improve water resistance and flexibility.\n• Include drainage features, slope adaptation mechanisms, and anti-slip surfacing.\n\nBackground\n\nThe Northeastern Region faces persistent challenges in building and maintaining rural roads due to difficult terrain, high rainfall, and limited access to conventional construction materials. Simultaneously, plastic waste management remains a growing concern in both urban and semi-urban pockets of the region. Bamboo, abundantly available in NER, offers high tensile strength and flexibility, while recycled plastic enhances water resistance and durability when used in road surfacing. Combining these two materials presents a unique opportunity to create sustainable, modular road infrastructure tailored for NER's needs.\n\nExpected Solution\n\n• A prototype modular panel system combining bamboo and recycled plastic.\n• A deployment guide for constructing 100-200 meter stretches in rural terrain.\n• Cost-benefit analysis compared to conventional road-building methods.\n• Environmental impact assessment and scalability roadmap.\n• Optional integration with IoT-based monitoring for wear and tear tracking.",
"ps_number": "SIH25003",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Transportation & Logistics",
"title": "Low-Cost smart transportation solution for Agri produce from remote farms to nearest motorable road in NER Region"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "The Government of India is implementing the Bharat Pashudhan App (BPA) for systematic data recording of breeding, health, and nutrition of dairy animals. Field Level Workers (FLWs) are responsible for capturing animal data on the ground. However, despite multiple training programs, a recurring issue is the incorrect identification and registration of animal breeds of cattle and buffaloes. This misclassification significantly affects the integrity and usability of the data for research, policy planning, and targeted interventions.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": "Breed identification errors in BPA often arise due to manual judgment and lack of breed-specific awareness among FLWs. India, being home to a diverse array of indigenous and crossbred cattle and buffalo breeds, presents a complex challenge for accurate breed identification. Incorrect entries compromise the value of collected data and, in turn, impact the effectiveness of genetic improvement, nutrition planning, disease control, and overall program outcomes.\n\nTo address this, an AI-driven solution that can identify the breed of an animal using its image can prove extremely valuable. By using image recognition and machine learning techniques, the software can standardize breed identification and minimize manual errors. If successfully developed and validated, such a system can be integrated with the BPA to act as a decision-support tool for FLWs during registration.",
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "• Uses Artificial Intelligence (AI) and image analysis to recognize and classify the breed of cattle and buffaloes based on images.\n• Can handle diverse environmental backgrounds, lighting conditions, and varying animal poses.\n• Maintains a breed database (for the most common Indian cattle and buffalo breeds and their crosses).\n• Provides breed suggestions or confirmations at the time of registration in BPA.\n• Can be seamlessly integrated with the BPA platform to support real-time validation or correction of breed entries.\n• Includes a user-friendly interface for FLWs with minimal technical training requirements.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Fisheries Animal Husbandry & Dairying",
"problem_description": "Background\n\nThe Government of India is implementing the Bharat Pashudhan App (BPA) for systematic data recording of breeding, health, and nutrition of dairy animals. Field Level Workers (FLWs) are responsible for capturing animal data on the ground. However, despite multiple training programs, a recurring issue is the incorrect identification and registration of animal breeds of cattle and buffaloes. This misclassification significantly affects the integrity and usability of the data for research, policy planning, and targeted interventions.\n\nDescription\n\nBreed identification errors in BPA often arise due to manual judgment and lack of breed-specific awareness among FLWs. India, being home to a diverse array of indigenous and crossbred cattle and buffalo breeds, presents a complex challenge for accurate breed identification. Incorrect entries compromise the value of collected data and, in turn, impact the effectiveness of genetic improvement, nutrition planning, disease control, and overall program outcomes.\n\nTo address this, an AI-driven solution that can identify the breed of an animal using its image can prove extremely valuable. By using image recognition and machine learning techniques, the software can standardize breed identification and minimize manual errors. If successfully developed and validated, such a system can be integrated with the BPA to act as a decision-support tool for FLWs during registration.\n\nExpected Solution\n\n• Uses Artificial Intelligence (AI) and image analysis to recognize and classify the breed of cattle and buffaloes based on images.\n• Can handle diverse environmental backgrounds, lighting conditions, and varying animal poses.\n• Maintains a breed database (for the most common Indian cattle and buffalo breeds and their crosses).\n• Provides breed suggestions or confirmations at the time of registration in BPA.\n• Can be seamlessly integrated with the BPA platform to support real-time validation or correction of breed entries.\n• Includes a user-friendly interface for FLWs with minimal technical training requirements.",
"ps_number": "SIH25004",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Agriculture FoodTech & Rural Development",
"title": "Image based breed recognition for cattle and buffaloes of India"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": "Background: In dairy farming, evaluating the body structure of animals is vital to predict their longevity, productivity, and reproductive efficiency. Traditionally, Animal Type Classification (ATC)—which involves scoring animals for physical traits—is conducted by trained personnel through visual inspection and manual measurement of specific body parts. However, this manual method is prone to human error and subjectivity, even with trained professionals, resulting in inconsistent and potentially unreliable data.\n\nWith advances in Artificial Intelligence (AI) and image processing technologies, there is an opportunity to automate this process. Automated scoring based on images can ensure standardization, minimize observer bias, and improve the reliability of data captured for scientific and breeding purposes.\n\nDescription: The Government of India is implementing the Rashtriya Gokul Mission (RGM) since December 2014, aiming to conserve and develop indigenous bovine breeds, genetically upgrade the bovine population, and enhance milk productivity. Under this mission, Progeny Testing (PT) and Pedigree Selection (PS) programs are being carried out in key dairy breeds across the country to produce high genetic merit bulls for breeding purposes.\n\nAnimal Type Classification (ATC) is a crucial step in identifying top-performing elite dams, which are potential mothers of future breeding bulls. Currently, ATC is performed manually by a trained Animal Typer who visually examines and measures physical traits, and then records the scores in the Bharat Pashudhan App (BPA). Despite training, errors due to fatigue, bias, or measurement inaccuracies can adversely affect data quality and scientific analysis.\n\nThere is a need for an AI-driven solution that can automate this classification process by analyzing animal images, extracting body structure parameters, and assigning standardized scores with minimal human intervention. If integrated with BPA, such a solution would enhance the accuracy, efficiency, and scientific validity of animal evaluation under PT and PS programs.\n\nExpected Solution: Students are expected to develop an AI-based Auto Recording of Animal Type Classification System that can:\n\nUse images of cattle and buffaloes to evaluate physical traits relevant to Animal Type Classification.\nExtract and quantify specific body structure parameters (e.g., body length, height at withers, chest width, rump angle, etc.) using AI and image processing techniques.\nGenerate objective and consistent classification scores.\nAuto-record and store the classification data in a structured format.\nProvide seamless integration with BPA to auto-save the classification records at the time of evaluation.\nBe user-friendly and operable by field personnel with minimal technical skills.",
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Fisheries Animal Husbandry & Dairying",
"problem_description": "Background: In dairy farming, evaluating the body structure of animals is vital to predict their longevity, productivity, and reproductive efficiency. Traditionally, Animal Type Classification (ATC)—which involves scoring animals for physical traits—is conducted by trained personnel through visual inspection and manual measurement of specific body parts. However, this manual method is prone to human error and subjectivity, even with trained professionals, resulting in inconsistent and potentially unreliable data.\n\nWith advances in Artificial Intelligence (AI) and image processing technologies, there is an opportunity to automate this process. Automated scoring based on images can ensure standardization, minimize observer bias, and improve the reliability of data captured for scientific and breeding purposes.\n\nDescription: The Government of India is implementing the Rashtriya Gokul Mission (RGM) since December 2014, aiming to conserve and develop indigenous bovine breeds, genetically upgrade the bovine population, and enhance milk productivity. Under this mission, Progeny Testing (PT) and Pedigree Selection (PS) programs are being carried out in key dairy breeds across the country to produce high genetic merit bulls for breeding purposes.\n\nAnimal Type Classification (ATC) is a crucial step in identifying top-performing elite dams, which are potential mothers of future breeding bulls. Currently, ATC is performed manually by a trained Animal Typer who visually examines and measures physical traits, and then records the scores in the Bharat Pashudhan App (BPA). Despite training, errors due to fatigue, bias, or measurement inaccuracies can adversely affect data quality and scientific analysis.\n\nThere is a need for an AI-driven solution that can automate this classification process by analyzing animal images, extracting body structure parameters, and assigning standardized scores with minimal human intervention. If integrated with BPA, such a solution would enhance the accuracy, efficiency, and scientific validity of animal evaluation under PT and PS programs.\n\nExpected Solution: Students are expected to develop an AI-based Auto Recording of Animal Type Classification System that can:\n\nUse images of cattle and buffaloes to evaluate physical traits relevant to Animal Type Classification.\nExtract and quantify specific body structure parameters (e.g., body length, height at withers, chest width, rump angle, etc.) using AI and image processing techniques.\nGenerate objective and consistent classification scores.\nAuto-record and store the classification data in a structured format.\nProvide seamless integration with BPA to auto-save the classification records at the time of evaluation.\nBe user-friendly and operable by field personnel with minimal technical skills.",
"ps_number": "SIH25005",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Agriculture FoodTech & Rural Development",
"title": "Image based Animal Type Classification for cattle and buffaloes"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Biosecurity is a cornerstone of animal health management, particularly in the pig and poultry sectors, where disease outbreaks such as Avian Influenza and African Swine Fever can cause significant economic losses, threaten food security, and disrupt rural livelihoods. Despite its importance, many farmers—especially smallholders in resource-limited areas—struggle to access practical, actionable information on biosecurity protocols, risk assessment tools, and regulatory compliance requirements.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• Enhanced farmer awareness and education on biosecurity.\n• Improved risk management at the farm level as well as self-assessment.\n• Easy access to customized biosecurity protocols and guidelines.\n• Digital record-keeping and compliance tracking.\n• Timely alerts and disease notifications to farmers.\n• Healthier livestock and increased farm productivity.\n• Empowerment of small and marginal farmers with limited resources.\n• Support to authorities in data-driven surveillance and policy making.\n• Stronger collaboration across the livestock ecosystem.\n• Improved national preparedness for zoonotic and transboundary diseases.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "There is an urgent need for a user-friendly, digital platform that empowers farmers to implement, monitor, and sustain robust biosecurity practices on their farms. This portal should offer end-to-end solutions for farm-level biosecurity management by integrating:\n\n• Customizable risk assessment tools based on local epidemiological conditions.\n• Interactive training modules and best practice guidelines tailored for pig and poultry production systems.\n• Compliance tracking features aligned with regulatory frameworks to help farmers work toward disease-free compartment recognition.\n• Real-time alerts and monitoring dashboards for disease outbreaks and biosecurity breaches.\n• Multilingual and mobile-first design to ensure accessibility in remote and rural areas.\n\nThe platform should also enable data collection and analysis for policy support, foster collaborative networking among stakeholders (farmers, veterinarians, extension workers, etc.), and promote long-term resilience and sustainability in the livestock sector.",
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Fisheries Animal Husbandry & Dairying",
"problem_description": "Background\n\nBiosecurity is a cornerstone of animal health management, particularly in the pig and poultry sectors, where disease outbreaks such as Avian Influenza and African Swine Fever can cause significant economic losses, threaten food security, and disrupt rural livelihoods. Despite its importance, many farmers—especially smallholders in resource-limited areas—struggle to access practical, actionable information on biosecurity protocols, risk assessment tools, and regulatory compliance requirements.\n\nProblem Description\n\nThere is an urgent need for a user-friendly, digital platform that empowers farmers to implement, monitor, and sustain robust biosecurity practices on their farms. This portal should offer end-to-end solutions for farm-level biosecurity management by integrating:\n\n• Customizable risk assessment tools based on local epidemiological conditions.\n• Interactive training modules and best practice guidelines tailored for pig and poultry production systems.\n• Compliance tracking features aligned with regulatory frameworks to help farmers work toward disease-free compartment recognition.\n• Real-time alerts and monitoring dashboards for disease outbreaks and biosecurity breaches.\n• Multilingual and mobile-first design to ensure accessibility in remote and rural areas.\n\nThe platform should also enable data collection and analysis for policy support, foster collaborative networking among stakeholders (farmers, veterinarians, extension workers, etc.), and promote long-term resilience and sustainability in the livestock sector.\n\nExpected Outcomes\n\n• Enhanced farmer awareness and education on biosecurity.\n• Improved risk management at the farm level as well as self-assessment.\n• Easy access to customized biosecurity protocols and guidelines.\n• Digital record-keeping and compliance tracking.\n• Timely alerts and disease notifications to farmers.\n• Healthier livestock and increased farm productivity.\n• Empowerment of small and marginal farmers with limited resources.\n• Support to authorities in data-driven surveillance and policy making.\n• Stronger collaboration across the livestock ecosystem.\n• Improved national preparedness for zoonotic and transboundary diseases.",
"ps_number": "SIH25006",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Agriculture FoodTech & Rural Development",
"title": "Development of a Digital Farm Management Portal for Implementing Biosecurity Measures in Pig and Poultry Farms"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Antimicrobials are vital in ensuring animal health and productivity in modern livestock systems. However, inappropriate and excessive use of these drugs can result in antimicrobial residues in animal-derived food products and contribute to the rise of antimicrobial resistance (AMR)—a major global threat to both animal and public health. Monitoring antimicrobial usage (AMU) and ensuring compliance with Maximum Residue Limits (MRL) is crucial to promoting responsible drug use and safeguarding food safety.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• Improved antimicrobial stewardship practices at the farm level.\n• Enhanced compliance with MRL norms and regulatory frameworks.\n• Real-time availability of data on AMU for authorities and stakeholders.\n• Data-driven decision-making to inform policy and farm-level action.\n• Capability for trend analysis and automated reporting.\n• Healthier livestock and reduction in antimicrobial residues in food.\n• Improved public health protection and consumer confidence.\n• Contribution to global AMR reduction efforts.\n• Better engagement of farmers and veterinarians through digital tools.\n• Promotion of sustainable and responsible livestock farming practices.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "There is a growing need for a digital solution that can help track, monitor, and manage antimicrobial usage across livestock farms while ensuring adherence to MRL standards. The proposed system should serve as a centralized digital portal that facilitates:\n\n• Recording and tracking the types, dosages, frequency, and reasons for antimicrobial use in animals both in treatment and through feed.\n• Integration with veterinary prescriptions and treatment logs to monitor compliance.\n• Alert systems for withdrawal periods and MRL compliance prior to the sale or processing of animal products.\n• Real-time dashboards and data visualization tools for analysis of AMU trends across species, regions, and time periods.\n• Use of blockchain or other secure technologies to ensure data integrity and traceability.\n• Mobile app interfaces for easy data entry by farmers and veterinarians in field conditions.\n\nThis digital platform would contribute to improved antimicrobial stewardship, better regulatory enforcement, and help India align with global AMR mitigation strategies, while also strengthening public trust in livestock products.",
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Fisheries Animal Husbandry & Dairying",
"problem_description": "Background\n\nAntimicrobials are vital in ensuring animal health and productivity in modern livestock systems. However, inappropriate and excessive use of these drugs can result in antimicrobial residues in animal-derived food products and contribute to the rise of antimicrobial resistance (AMR)—a major global threat to both animal and public health. Monitoring antimicrobial usage (AMU) and ensuring compliance with Maximum Residue Limits (MRL) is crucial to promoting responsible drug use and safeguarding food safety.\n\nProblem Description\n\nThere is a growing need for a digital solution that can help track, monitor, and manage antimicrobial usage across livestock farms while ensuring adherence to MRL standards. The proposed system should serve as a centralized digital portal that facilitates:\n\n• Recording and tracking the types, dosages, frequency, and reasons for antimicrobial use in animals both in treatment and through feed.\n• Integration with veterinary prescriptions and treatment logs to monitor compliance.\n• Alert systems for withdrawal periods and MRL compliance prior to the sale or processing of animal products.\n• Real-time dashboards and data visualization tools for analysis of AMU trends across species, regions, and time periods.\n• Use of blockchain or other secure technologies to ensure data integrity and traceability.\n• Mobile app interfaces for easy data entry by farmers and veterinarians in field conditions.\n\nThis digital platform would contribute to improved antimicrobial stewardship, better regulatory enforcement, and help India align with global AMR mitigation strategies, while also strengthening public trust in livestock products.\n\nExpected Outcomes\n\n• Improved antimicrobial stewardship practices at the farm level.\n• Enhanced compliance with MRL norms and regulatory frameworks.\n• Real-time availability of data on AMU for authorities and stakeholders.\n• Data-driven decision-making to inform policy and farm-level action.\n• Capability for trend analysis and automated reporting.\n• Healthier livestock and reduction in antimicrobial residues in food.\n• Improved public health protection and consumer confidence.\n• Contribution to global AMR reduction efforts.\n• Better engagement of farmers and veterinarians through digital tools.\n• Promotion of sustainable and responsible livestock farming practices.",
"ps_number": "SIH25007",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Agriculture FoodTech & Rural Development",
"title": "Development of a Digital Farm Management Portal for Monitoring Maximum Residue Limits (MRL) and Antimicrobial Usage (AMU) in Livestock"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A digital platform or app that offers interactive disaster education modules, region-specific alerts, and virtual drills.\n• Gamified learning experiences to improve engagement.\n• Emergency contact directories and real-time communication tools during disasters.\n• Dashboards for school administrators to track preparedness scores and drill participation.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "Lack of awareness and preparedness leads to panic, chaos, and potentially fatal outcomes during emergencies. By integrating disaster education into regular learning, institutions can equip students and staff with life-saving knowledge and skills. This is especially critical in areas prone to natural calamities.\n\nEmpowering young people with this knowledge not only makes campuses safer but also contributes to a more disaster-resilient society.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "In India, schools and colleges are often unprepared for natural disasters such as earthquakes, floods, and fires. While emergency guidelines exist on paper, there is a lack of structured disaster management education integrated into the curriculum. Institutions lack digital tools to simulate disaster scenarios or conduct virtual drills to train students and staff on safety protocols.\n\nFurthermore, there’s a gap in localized awareness—many students are unaware of how to react during disasters specific to their region. Manual drills, where they occur, are infrequent and often poorly coordinated, failing to instill practical preparedness.",
"relevant_stakeholders___beneficiaries": "• Students (K-12 and higher education)\n• Teachers and administrative staff\n• Educational institutions and local disaster response teams\n• Parents and guardians\n• Government departments (NDMA, Education Ministry)",
"supporting_data": "• NDMA reports show low awareness levels in schools despite India’s high disaster vulnerability index.\n• UNDRR has recommended integrating disaster risk reduction in education policies (Ref: National Disaster Management Authority).",
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nIn India, schools and colleges are often unprepared for natural disasters such as earthquakes, floods, and fires. While emergency guidelines exist on paper, there is a lack of structured disaster management education integrated into the curriculum. Institutions lack digital tools to simulate disaster scenarios or conduct virtual drills to train students and staff on safety protocols.\n\nFurthermore, there’s a gap in localized awareness—many students are unaware of how to react during disasters specific to their region. Manual drills, where they occur, are infrequent and often poorly coordinated, failing to instill practical preparedness.\n\nImpact / Why this problem needs to be solved\n\nLack of awareness and preparedness leads to panic, chaos, and potentially fatal outcomes during emergencies. By integrating disaster education into regular learning, institutions can equip students and staff with life-saving knowledge and skills. This is especially critical in areas prone to natural calamities.\n\nEmpowering young people with this knowledge not only makes campuses safer but also contributes to a more disaster-resilient society.\n\nExpected Outcomes\n\n• A digital platform or app that offers interactive disaster education modules, region-specific alerts, and virtual drills.\n• Gamified learning experiences to improve engagement.\n• Emergency contact directories and real-time communication tools during disasters.\n• Dashboards for school administrators to track preparedness scores and drill participation.\n\nRelevant Stakeholders / Beneficiaries\n\n• Students (K-12 and higher education)\n• Teachers and administrative staff\n• Educational institutions and local disaster response teams\n• Parents and guardians\n• Government departments (NDMA, Education Ministry)\n\nSupporting Data\n\n• NDMA reports show low awareness levels in schools despite India’s high disaster vulnerability index.\n• UNDRR has recommended integrating disaster risk reduction in education policies (Ref: National Disaster Management Authority).",
"ps_number": "SIH25008",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Disaster Management",
"title": "Disaster Preparedness and Response Education System for Schools and Colleges"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A gamified mobile/web platform or app that teaches students about environmental issues through interactive lessons, challenges, quizzes, and real-world tasks (e.g., tree-planting, waste segregation).\n• Tracking of eco-points, enabling school-level competitions.\n• Rewards for sustainable practices through digital badges and recognition.",
"expected_solution": null,
"impact": "As future decision-makers, students must be environmentally literate and empowered to take meaningful actions. Without innovative education methods, we risk raising a generation unaware of sustainability challenges.\n\nAn interactive, practical approach to environmental learning will foster long-term behavioral change, local involvement, and a ripple effect across families and communities. This aligns with India's SDG goals and NEP 2020's emphasis on experiential learning.",
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Despite the rising urgency of climate change and environmental degradation, environmental education remains largely theoretical in many Indian schools and colleges. Students are often taught textbook-based content with little emphasis on real-world application, local ecological issues, or personal responsibility.\n\nThere is a lack of engaging tools that motivate students to adopt eco-friendly practices or understand the direct consequences of their lifestyle choices. Traditional methods fail to instill sustainable habits or inspire youth participation in local environmental efforts.",
"relevant_stakeholders___beneficiaries": "• School and college students\n• Teachers and eco-club coordinators\n• Environmental NGOs and government departments",
"supporting_data": "• UNESCO reports that experiential, gamified learning increases student retention and engagement by over 70%.\n• NEP 2020 encourages integration of environmental awareness into the curriculum.",
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nDespite the rising urgency of climate change and environmental degradation, environmental education remains largely theoretical in many Indian schools and colleges. Students are often taught textbook-based content with little emphasis on real-world application, local ecological issues, or personal responsibility.\n\nThere is a lack of engaging tools that motivate students to adopt eco-friendly practices or understand the direct consequences of their lifestyle choices. Traditional methods fail to instill sustainable habits or inspire youth participation in local environmental efforts.\n\nImpact\n\nAs future decision-makers, students must be environmentally literate and empowered to take meaningful actions. Without innovative education methods, we risk raising a generation unaware of sustainability challenges.\n\nAn interactive, practical approach to environmental learning will foster long-term behavioral change, local involvement, and a ripple effect across families and communities. This aligns with India's SDG goals and NEP 2020's emphasis on experiential learning.\n\nExpected Outcomes\n\n• A gamified mobile/web platform or app that teaches students about environmental issues through interactive lessons, challenges, quizzes, and real-world tasks (e.g., tree-planting, waste segregation).\n• Tracking of eco-points, enabling school-level competitions.\n• Rewards for sustainable practices through digital badges and recognition.\n\nRelevant Stakeholders / Beneficiaries\n\n• School and college students\n• Teachers and eco-club coordinators\n• Environmental NGOs and government departments\n\nSupporting Data\n\n• UNESCO reports that experiential, gamified learning increases student retention and engagement by over 70%.\n• NEP 2020 encourages integration of environmental awareness into the curriculum.",
"ps_number": "SIH25009",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "Gamified Environmental Education Platform for Schools and Colleges"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A multilingual, AI-based mobile app or chatbot that provides real-time, location-specific crop advisory.\n• Soil health recommendations and fertilizer guidance.\n• Weather-based alerts and predictive insights.\n• Pest/disease detection via image uploads.\n• Market price tracking.\n• Voice support for low-literate users.\n• Feedback and usage data collection for continuous improvement.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "Helping small farmers make informed decisions can significantly increase productivity, reduce costs, and improve livelihoods. It also contributes to sustainable farming practices, food security, and environmental conservation. A smart advisory solution can empower farmers with scientific insights in their native language and reduce dependency on unreliable third-party advice.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "A majority of small and marginal farmers in India rely on traditional knowledge, local shopkeepers, or guesswork for crop selection, pest control, and fertilizer use. They lack access to personalized, real-time advisory services that account for soil type, weather conditions, and crop history.\n\nThis often leads to poor yield, excessive input costs, and environmental degradation due to overuse of chemicals. Language barriers, low digital literacy, and absence of localized tools further limit their access to modern agri-tech resources.",
"relevant_stakeholders___beneficiaries": "• Small and marginal farmers\n• Agricultural extension officers\n• Government agriculture departments\n• NGOs and cooperatives\n• Agri-tech startups",
"supporting_data": "• 86% of Indian farmers are small or marginal (NABARD Report, 2022).\n• Studies show ICT-based advisories can increase crop yield by 20–30%.",
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nA majority of small and marginal farmers in India rely on traditional knowledge, local shopkeepers, or guesswork for crop selection, pest control, and fertilizer use. They lack access to personalized, real-time advisory services that account for soil type, weather conditions, and crop history.\n\nThis often leads to poor yield, excessive input costs, and environmental degradation due to overuse of chemicals. Language barriers, low digital literacy, and absence of localized tools further limit their access to modern agri-tech resources.\n\nImpact / Why this problem needs to be solved\n\nHelping small farmers make informed decisions can significantly increase productivity, reduce costs, and improve livelihoods. It also contributes to sustainable farming practices, food security, and environmental conservation. A smart advisory solution can empower farmers with scientific insights in their native language and reduce dependency on unreliable third-party advice.\n\nExpected Outcomes\n\n• A multilingual, AI-based mobile app or chatbot that provides real-time, location-specific crop advisory.\n• Soil health recommendations and fertilizer guidance.\n• Weather-based alerts and predictive insights.\n• Pest/disease detection via image uploads.\n• Market price tracking.\n• Voice support for low-literate users.\n• Feedback and usage data collection for continuous improvement.\n\nRelevant Stakeholders / Beneficiaries\n\n• Small and marginal farmers\n• Agricultural extension officers\n• Government agriculture departments\n• NGOs and cooperatives\n• Agri-tech startups\n\nSupporting Data\n\n• 86% of Indian farmers are small or marginal (NABARD Report, 2022).\n• Studies show ICT-based advisories can increase crop yield by 20–30%.",
"ps_number": "SIH25010",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Agriculture FoodTech & Rural Development",
"title": "Smart Crop Advisory System for Small and Marginal Farmers"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• Automatically marks student attendance based on the daily timetable using QR code, Bluetooth/Wi-Fi proximity, or face recognition.\n• Displays real-time attendance on a classroom screen.\n• Suggests personalized academic tasks during free periods based on the student's interests, strengths, and career goals.\n• Generates a daily routine combining class schedule, free time, and long-term personal goals.\n\nThe app will require minimal infrastructure and be usable by both students and staff with basic training.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "This issue impacts both administrative efficiency and student development. Automating attendance saves teachers' time and ensures more accurate records. Additionally, providing students with structured personal development activities during free time helps improve productivity, goal clarity, and learning outcomes. Institutions can also gain better insight into student behavior and engagement, allowing for more targeted support.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Many educational institutions still depend on manual attendance systems, which are time-consuming and error-prone. Teachers spend a significant portion of class time marking attendance, reducing valuable instructional hours. Additionally, students often waste free periods with unproductive activities due to a lack of structured guidance. This leads to poor time management and reduced alignment with long-term academic or career goals. There is also a gap in personalized learning support during idle classroom hours. Institutions currently lack tools that integrate daily schedules with individual student planning and automated tracking.",
"relevant_stakeholders___beneficiaries": "• Students\n• Teachers\n• College administrators\n• Career counselors\n• Education departments",
"supporting_data": "• Surveys and reports on classroom time usage, student productivity, and NEP 2020 recommendations emphasizing personalized and experiential learning.",
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nMany educational institutions still depend on manual attendance systems, which are time-consuming and error-prone. Teachers spend a significant portion of class time marking attendance, reducing valuable instructional hours. Additionally, students often waste free periods with unproductive activities due to a lack of structured guidance. This leads to poor time management and reduced alignment with long-term academic or career goals. There is also a gap in personalized learning support during idle classroom hours. Institutions currently lack tools that integrate daily schedules with individual student planning and automated tracking.\n\nImpact / Why this problem needs to be solved\n\nThis issue impacts both administrative efficiency and student development. Automating attendance saves teachers' time and ensures more accurate records. Additionally, providing students with structured personal development activities during free time helps improve productivity, goal clarity, and learning outcomes. Institutions can also gain better insight into student behavior and engagement, allowing for more targeted support.\n\nExpected Outcomes\n\n• Automatically marks student attendance based on the daily timetable using QR code, Bluetooth/Wi-Fi proximity, or face recognition.\n• Displays real-time attendance on a classroom screen.\n• Suggests personalized academic tasks during free periods based on the student's interests, strengths, and career goals.\n• Generates a daily routine combining class schedule, free time, and long-term personal goals.\n\nThe app will require minimal infrastructure and be usable by both students and staff with basic training.\n\nRelevant Stakeholders / Beneficiaries\n\n• Students\n• Teachers\n• College administrators\n• Career counselors\n• Education departments\n\nSupporting Data\n\n• Surveys and reports on classroom time usage, student productivity, and NEP 2020 recommendations emphasizing personalized and experiential learning.",
"ps_number": "SIH25011",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "Smart Curriculum Activity & Attendance App"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A low-cost, user-friendly software or mobile application that automates attendance using facial recognition or RFID-based systems.\n• Requires minimal infrastructure and training for deployment in rural schools.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "This issue affects over 50% of rural schools, impacting millions of students and teachers. It leads to inefficiencies, delays in reporting, and potential mismanagement of resources. Solving this will save time, improve accuracy, and enhance resource allocation.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Many rural schools in India rely on manual attendance systems, which are time-consuming and prone to errors. Teachers spend significant time marking attendance, reducing instructional time. Additionally, inaccurate records can lead to discrepancies in government reporting for schemes like mid-day meals. This problem is prevalent in under-resourced schools with limited access to technology, affecting administrative efficiency and student tracking.",
"relevant_stakeholders___beneficiaries": "• School administrators\n• Teachers\n• Students\n• Government education departments",
"supporting_data": "• Annual Status of Education Report (ASER) 2024, highlighting administrative challenges in rural schools.",
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nMany rural schools in India rely on manual attendance systems, which are time-consuming and prone to errors. Teachers spend significant time marking attendance, reducing instructional time. Additionally, inaccurate records can lead to discrepancies in government reporting for schemes like mid-day meals. This problem is prevalent in under-resourced schools with limited access to technology, affecting administrative efficiency and student tracking.\n\nImpact / Why this problem needs to be solved\n\nThis issue affects over 50% of rural schools, impacting millions of students and teachers. It leads to inefficiencies, delays in reporting, and potential mismanagement of resources. Solving this will save time, improve accuracy, and enhance resource allocation.\n\nExpected Outcomes\n\n• A low-cost, user-friendly software or mobile application that automates attendance using facial recognition or RFID-based systems.\n• Requires minimal infrastructure and training for deployment in rural schools.\n\nRelevant Stakeholders / Beneficiaries\n\n• School administrators\n• Teachers\n• Students\n• Government education departments\n\nSupporting Data\n\n• Annual Status of Education Report (ASER) 2024, highlighting administrative challenges in rural schools.",
"ps_number": "SIH25012",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "Automated Attendance System for Rural Schools"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A mobile app or web platform integrating GPS-based real-time tracking of buses.\n• Display estimated arrival times and route information.\n• Optimized for low-bandwidth environments to ensure accessibility in smaller towns.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "Over 60% of commuters in small cities face delays due to lack of real-time information, reducing public transport usage and increasing private vehicle dependency, which worsens traffic and pollution. A solution would enhance commuter experience and promote sustainable transport.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "In small cities and tier-2 towns, public transport systems lack real-time tracking, causing inconvenience to commuters who face unpredictable bus schedules. This leads to overcrowding, wasted time, and reduced reliance on public transport. The problem is acute in cities with growing populations but limited digital infrastructure for transport management.",
"relevant_stakeholders___beneficiaries": "• Commuters\n• Local transport authorities\n• Municipal corporations",
"supporting_data": "• Urban Mobility India Report 2024, emphasizing transport inefficiencies in tier-2 cities.",
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nIn small cities and tier-2 towns, public transport systems lack real-time tracking, causing inconvenience to commuters who face unpredictable bus schedules. This leads to overcrowding, wasted time, and reduced reliance on public transport. The problem is acute in cities with growing populations but limited digital infrastructure for transport management.\n\nImpact / Why this problem needs to be solved\n\nOver 60% of commuters in small cities face delays due to lack of real-time information, reducing public transport usage and increasing private vehicle dependency, which worsens traffic and pollution. A solution would enhance commuter experience and promote sustainable transport.\n\nExpected Outcomes\n\n• A mobile app or web platform integrating GPS-based real-time tracking of buses.\n• Display estimated arrival times and route information.\n• Optimized for low-bandwidth environments to ensure accessibility in smaller towns.\n\nRelevant Stakeholders / Beneficiaries\n\n• Commuters\n• Local transport authorities\n• Municipal corporations\n\nSupporting Data\n\n• Urban Mobility India Report 2024, emphasizing transport inefficiencies in tier-2 cities.",
"ps_number": "SIH25013",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Transportation & Logistics",
"title": "Real-Time Public Transport Tracking for Small Cities"
}
|
{
"category": "Hardware",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• IoT-based system or mobile app to monitor segregation at collection points.\n• Provide real-time feedback to households on compliance.\n• Generate compliance reports for local authorities to enforce better waste management.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "Improper segregation affects nearly 70% of urban waste management systems, increasing recycling costs and environmental pollution. A solution would improve waste processing efficiency and reduce landfill dependency.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Urban local bodies struggle with improper waste segregation at the household level, leading to inefficiencies in waste processing and increased landfill burden. Despite awareness campaigns, compliance remains low due to lack of monitoring and feedback mechanisms. This issue is widespread in urban areas with high waste generation.",
"relevant_stakeholders___beneficiaries": "• Urban local bodies\n• Residents\n• Waste management agencies\n• Environmental organizations",
"supporting_data": "Swachh Bharat Mission Urban 2.0 Report, highlighting segregation challenges.",
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nUrban local bodies struggle with improper waste segregation at the household level, leading to inefficiencies in waste processing and increased landfill burden. Despite awareness campaigns, compliance remains low due to lack of monitoring and feedback mechanisms. This issue is widespread in urban areas with high waste generation.\n\nImpact / Why this problem needs to be solved\n\nImproper segregation affects nearly 70% of urban waste management systems, increasing recycling costs and environmental pollution. A solution would improve waste processing efficiency and reduce landfill dependency.\n\nExpected Outcomes\n\n• IoT-based system or mobile app to monitor segregation at collection points.\n• Provide real-time feedback to households on compliance.\n• Generate compliance reports for local authorities to enforce better waste management.\n\nRelevant Stakeholders / Beneficiaries\n\n• Urban local bodies\n• Residents\n• Waste management agencies\n• Environmental organizations\n\nSupporting Data\n\nSwachh Bharat Mission Urban 2.0 Report, highlighting segregation challenges.",
"ps_number": "SIH25014",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Clean & Green Technology",
"title": "Waste Segregation Monitoring System for Urban Local Bodies"
}
|
{
"category": "Hardware",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A smart automated system with sensors, cameras, and AI algorithms to detect infection levels.\n• IoT-controlled sprayer to dispense pesticides only where and when needed.\n• Mobile or web interface for farmers to monitor plant health and control the system remotely.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "• Reduces excessive pesticide usage and lowers farming costs.\n• Protects soil and water quality, while minimizing harm to non-target organisms.\n• Improves crop yield and quality through precise and timely treatment.\n• Supports small and marginal farmers with cost savings and better farm sustainability.\n• Contributes to safe and eco-friendly food production.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Excessive and indiscriminate application of pesticides in agriculture creates soil degradation, water contamination, damage to useful insects, and health risks for humans and animals. Regardless of whether the plant is healthy or infected, traditional pesticide spraying methods are used evenly, leading to waste and contamination. Many farmers lack affordable, automated systems to monitor crop health and control pesticide usage accordingly. This issue occurs on both large and small farms where manual inspections and sprays are labor-intensive, inefficient, and often inaccurate.\n\nAn intelligent system is required to recognize pest or disease infection in individual plants and regulate the amount of pesticide sprayed. This ensures optimal use of chemicals, reduces environmental impact, and promotes sustainable agriculture.",
"relevant_stakeholders___beneficiaries": "• Farmers (small, medium, and large scale)\n• Agricultural extension officers\n• Agrochemical companies\n• Environmental agencies\n• Consumers demanding residue-free produce\n• Government bodies promoting sustainable farming",
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nExcessive and indiscriminate application of pesticides in agriculture creates soil degradation, water contamination, damage to useful insects, and health risks for humans and animals. Regardless of whether the plant is healthy or infected, traditional pesticide spraying methods are used evenly, leading to waste and contamination. Many farmers lack affordable, automated systems to monitor crop health and control pesticide usage accordingly. This issue occurs on both large and small farms where manual inspections and sprays are labor-intensive, inefficient, and often inaccurate.\n\nAn intelligent system is required to recognize pest or disease infection in individual plants and regulate the amount of pesticide sprayed. This ensures optimal use of chemicals, reduces environmental impact, and promotes sustainable agriculture.\n\nImpact / Why this problem needs to be solved\n\n• Reduces excessive pesticide usage and lowers farming costs.\n• Protects soil and water quality, while minimizing harm to non-target organisms.\n• Improves crop yield and quality through precise and timely treatment.\n• Supports small and marginal farmers with cost savings and better farm sustainability.\n• Contributes to safe and eco-friendly food production.\n\nExpected Outcomes\n\n• A smart automated system with sensors, cameras, and AI algorithms to detect infection levels.\n• IoT-controlled sprayer to dispense pesticides only where and when needed.\n• Mobile or web interface for farmers to monitor plant health and control the system remotely.\n\nRelevant Stakeholders / Beneficiaries\n\n• Farmers (small, medium, and large scale)\n• Agricultural extension officers\n• Agrochemical companies\n• Environmental agencies\n• Consumers demanding residue-free produce\n• Government bodies promoting sustainable farming",
"ps_number": "SIH25015",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Agriculture FoodTech & Rural Development",
"title": "Intelligent Pesticide Sprinkling System Determined by the Infection Level of a Plant"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• Automated attendance system using QR codes, biometrics, or facial recognition.\n• Cloud-based dashboard for administrators and faculty to review attendance records.\n• Analytics to identify attendance trends and student engagement levels.\n• Compatibility with both offline and online classes.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "• Saves valuable teaching time otherwise wasted on manual attendance.\n• Reduces errors and eliminates the problem of proxy attendance.\n• Provides actionable insights for faculty to identify disengaged or struggling students.\n• Enhances transparency and accountability in academic processes.\n• Supports digital transformation of higher education institutions.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Attendance tracking in most colleges is still done manually, usually through roll calls or paper registers. This consumes valuable teaching time and often leads to errors such as incorrect entries or proxy attendance. In larger classes, the issue becomes even harder to manage.\n\nAdditionally, faculty and administrators lack easy access to attendance insights, making it difficult to identify students at risk or to track patterns in engagement. As education undergoes digital transformation, continuing to rely on outdated systems creates unnecessary inefficiencies and delays.\n\nThere is a clear need for a solution that not only automates attendance but also provides analytics for better academic planning. Such a system should be user-friendly, reliable, and work seamlessly in both in-person and online settings.",
"relevant_stakeholders___beneficiaries": "• Students\n• Faculty and academic administrators\n• College management bodies\n• Education departments and policymakers",
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nAttendance tracking in most colleges is still done manually, usually through roll calls or paper registers. This consumes valuable teaching time and often leads to errors such as incorrect entries or proxy attendance. In larger classes, the issue becomes even harder to manage.\n\nAdditionally, faculty and administrators lack easy access to attendance insights, making it difficult to identify students at risk or to track patterns in engagement. As education undergoes digital transformation, continuing to rely on outdated systems creates unnecessary inefficiencies and delays.\n\nThere is a clear need for a solution that not only automates attendance but also provides analytics for better academic planning. Such a system should be user-friendly, reliable, and work seamlessly in both in-person and online settings.\n\nImpact / Why this problem needs to be solved\n\n• Saves valuable teaching time otherwise wasted on manual attendance.\n• Reduces errors and eliminates the problem of proxy attendance.\n• Provides actionable insights for faculty to identify disengaged or struggling students.\n• Enhances transparency and accountability in academic processes.\n• Supports digital transformation of higher education institutions.\n\nExpected Outcomes\n\n• Automated attendance system using QR codes, biometrics, or facial recognition.\n• Cloud-based dashboard for administrators and faculty to review attendance records.\n• Analytics to identify attendance trends and student engagement levels.\n• Compatibility with both offline and online classes.\n\nRelevant Stakeholders / Beneficiaries\n\n• Students\n• Faculty and academic administrators\n• College management bodies\n• Education departments and policymakers",
"ps_number": "SIH25016",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "Automated Student Attendance Monitoring and Analytics System for Colleges"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A centralized alumni management platform to store and update alumni data.\n• Features for communication, networking, and event management.\n• Secure system for tracking career progress, mentorship opportunities, and donations.\n• Easy-to-use interface for both administrators and alumni.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "• Strengthens alumni engagement and builds long-term institutional relationships.\n• Provides opportunities for mentorship, internships, and collaborations.\n• Enhances fundraising potential through better alumni outreach.\n• Increases institutional credibility and community building.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Most educational institutions do not have a reliable or centralized system to manage their alumni data. Once students graduate, their contact information, academic records, and career updates are often scattered across multiple platforms or lost entirely. In many cases, alumni communication is restricted to informal WhatsApp groups or outdated mailing lists, making long-term engagement difficult.\n\nThis lack of a structured system limits the potential of alumni relationships. Institutions miss opportunities to involve alumni in events, mentoring, internships, or fundraising. In a digitally connected world, the absence of a proper alumni management system creates a significant gap in outreach and growth.",
"relevant_stakeholders___beneficiaries": "• Alumni\n• Current students (through mentorship and internships)\n• Faculty and institution administrators\n• College/university management bodies\n• Employers and recruiters\nOrganization",
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nMost educational institutions do not have a reliable or centralized system to manage their alumni data. Once students graduate, their contact information, academic records, and career updates are often scattered across multiple platforms or lost entirely. In many cases, alumni communication is restricted to informal WhatsApp groups or outdated mailing lists, making long-term engagement difficult.\n\nThis lack of a structured system limits the potential of alumni relationships. Institutions miss opportunities to involve alumni in events, mentoring, internships, or fundraising. In a digitally connected world, the absence of a proper alumni management system creates a significant gap in outreach and growth.\n\nImpact / Why this problem needs to be solved\n\n• Strengthens alumni engagement and builds long-term institutional relationships.\n• Provides opportunities for mentorship, internships, and collaborations.\n• Enhances fundraising potential through better alumni outreach.\n• Increases institutional credibility and community building.\n\nExpected Outcomes\n\n• A centralized alumni management platform to store and update alumni data.\n• Features for communication, networking, and event management.\n• Secure system for tracking career progress, mentorship opportunities, and donations.\n• Easy-to-use interface for both administrators and alumni.\n\nRelevant Stakeholders / Beneficiaries\n\n• Alumni\n• Current students (through mentorship and internships)\n• Faculty and institution administrators\n• College/university management bodies\n• Employers and recruiters\nOrganization",
"ps_number": "SIH25017",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "Digital Platform for Centralized Alumni Data Management and Engagement"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A multilingual telemedicine app for video consultations with doctors.\n• Digital health records accessible offline for rural patients.\n• Real-time updates on medicine availability at local pharmacies.\n• AI-powered symptom checker optimized for low-bandwidth areas.\n• A scalable solution for other rural regions in India.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "This problem directly affects the health and livelihood of thousands of rural residents, especially daily-wage earners and farmers. Lack of accessible healthcare leads to preventable complications, financial losses, and overall decline in community well-being. Addressing this issue would improve healthcare delivery, reduce unnecessary travel, and enhance quality of life for a large, underserved population.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Nabha and its surrounding rural areas face significant healthcare challenges. The local Civil Hospital operates at less than 50% staff capacity, with only 11 doctors for 23 sanctioned posts. Patients from 173 villages travel long distances, often missing work, only to find that specialists are unavailable or medicines are out of stock. Poor road conditions and sanitation further hinder access. Many residents lack timely medical care, leading to worsened health outcomes and increased financial strain.",
"relevant_stakeholders___beneficiaries": "• Rural patients in Nabha and surrounding villages.\n• Nabha Civil Hospital staff.\n• Punjab Health Department.\n• Local pharmacies.\n• Daily-wage workers and farmers.",
"supporting_data": "• Nabha Civil Hospital serves 173 villages but has only 11 out of 23 sanctioned doctors.\n• Only 31% of rural Punjab households have internet access, highlighting the need for offline features.\n• Telemedicine adoption in India is growing at a 31% CAGR (2020–2025).\n• Sources: Local news reports and government health statistics.",
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nNabha and its surrounding rural areas face significant healthcare challenges. The local Civil Hospital operates at less than 50% staff capacity, with only 11 doctors for 23 sanctioned posts. Patients from 173 villages travel long distances, often missing work, only to find that specialists are unavailable or medicines are out of stock. Poor road conditions and sanitation further hinder access. Many residents lack timely medical care, leading to worsened health outcomes and increased financial strain.\n\nImpact / Why this problem needs to be solved\n\nThis problem directly affects the health and livelihood of thousands of rural residents, especially daily-wage earners and farmers. Lack of accessible healthcare leads to preventable complications, financial losses, and overall decline in community well-being. Addressing this issue would improve healthcare delivery, reduce unnecessary travel, and enhance quality of life for a large, underserved population.\n\nExpected Outcomes\n\n• A multilingual telemedicine app for video consultations with doctors.\n• Digital health records accessible offline for rural patients.\n• Real-time updates on medicine availability at local pharmacies.\n• AI-powered symptom checker optimized for low-bandwidth areas.\n• A scalable solution for other rural regions in India.\n\nRelevant Stakeholders / Beneficiaries\n\n• Rural patients in Nabha and surrounding villages.\n• Nabha Civil Hospital staff.\n• Punjab Health Department.\n• Local pharmacies.\n• Daily-wage workers and farmers.\n\nSupporting Data\n\n• Nabha Civil Hospital serves 173 villages but has only 11 out of 23 sanctioned doctors.\n• Only 31% of rural Punjab households have internet access, highlighting the need for offline features.\n• Telemedicine adoption in India is growing at a 31% CAGR (2020–2025).\n• Sources: Local news reports and government health statistics.",
"ps_number": "SIH25018",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "MedTech / BioTech / HealthTech",
"title": "Telemedicine Access for Rural Healthcare in Nabha"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": "• A mobile and web-based digital learning app that works offline.\n• Interactive lessons in local languages to improve engagement.\n• Digital literacy modules tailored for rural students.\n• Teacher dashboards to track student progress.\n• Optimized for low-end devices and poor connectivity.",
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": "The lack of digital resources and skills limits students’ academic growth and future employability. With the increasing importance of digital literacy, students in rural Nabha risk being left behind, perpetuating cycles of educational and economic disadvantage. Addressing this problem is urgent to ensure equitable access to quality education and to empower rural youth with skills for the modern world.",
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": "Many government schools in Nabha and nearby rural areas lack updated computer infrastructure, reliable internet connectivity, and access to quality digital educational resources. Teachers and students struggle to use outdated systems, and digital literacy remains low. As a result, students face difficulties in learning essential digital skills and accessing modern educational content, leading to a widening gap between rural and urban education standards.",
"relevant_stakeholders___beneficiaries": "• Rural school students and teachers in Nabha.\n• School administrators.\n• Parents.\n• Punjab Education Department.",
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Punjab",
"problem_description": "Problem Description\n\nMany government schools in Nabha and nearby rural areas lack updated computer infrastructure, reliable internet connectivity, and access to quality digital educational resources. Teachers and students struggle to use outdated systems, and digital literacy remains low. As a result, students face difficulties in learning essential digital skills and accessing modern educational content, leading to a widening gap between rural and urban education standards.\n\nImpact / Why this problem needs to be solved\n\nThe lack of digital resources and skills limits students’ academic growth and future employability. With the increasing importance of digital literacy, students in rural Nabha risk being left behind, perpetuating cycles of educational and economic disadvantage. Addressing this problem is urgent to ensure equitable access to quality education and to empower rural youth with skills for the modern world.\n\nExpected Outcomes\n\n• A mobile and web-based digital learning app that works offline.\n• Interactive lessons in local languages to improve engagement.\n• Digital literacy modules tailored for rural students.\n• Teacher dashboards to track student progress.\n• Optimized for low-end devices and poor connectivity.\n\nRelevant Stakeholders / Beneficiaries\n\n• Rural school students and teachers in Nabha.\n• School administrators.\n• Parents.\n• Punjab Education Department.",
"ps_number": "SIH25019",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "Digital Learning Platform for Rural School Students in Nabha"
}
|
{
"category": "Hardware",
"details": {
"ai-based_anomaly_detection": null,
"background": "Indian Railways employs Track Recording Cars (TRCs) for periodic assessment of track geometry to ensure safety, ride comfort, and operational efficiency. While some TRCs still use outdated, contact-based systems, others rely on imported contactless technologies—typically laser-based solutions integrated with proprietary software.\n\nThese foreign systems pose several challenges:\n• High procurement and maintenance costs\n• Limited customization capabilities\n• Dependency on external vendors and closed-source software\n\nTo address these issues and promote self-reliance, Indian Railways invites proposals for the Development of indigenous contactless Integrated Track Monitoring Systems (ITMS) for Track Recording on Indian Railways.",
"conclusion": "This initiative is a step toward achieving technological independence in railway infrastructure monitoring. By fostering domestic innovation, Indian Railways aims to reduce reliance on foreign systems, cut long-term costs, and deploy tailored solutions better suited to India’s operational context.",
"data_privacy_&_security": null,
"deliverables": "Successful participants must submit:\n• A fully functional prototype (hardware + software)\n• Comprehensive technical documentation\n• Validation report demonstrating standards compliance\n• Video demonstration (lab/field performance)\n• Cost analysis and scalability roadmap",
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": "Open to:\n• Startups\n• Entrepreneurs\n• Academic & research institutions\n• Industry professionals and R&D organizations\n• Collaborative consortia involving any of the above",
"evaluation_criteria": "• Technical feasibility and innovation – 10 marks\n• Standards compliance (EN 13848 & RDSO TM/IM/448, Rev. 1:2023) – 40 marks\n• Hardware robustness, modularity & compactness – 20 marks\n• Software usability & architecture – 10 marks\n• Scalability, maintainability & upgradability – 10 marks\n• Cost-effectiveness – 10 marks\nTotal = 100 marks",
"expected_outcomes": null,
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": "• Maximum Speed: 200 km/h\n• Sampling Rate: 25 cm\n• Accuracy: As per EN 13848 Part 2 & RDSO TM/IM/448, Rev. 1: 2023\n• Real-time Processing: Required\n• Chainage Mapping: Mandatory (via axle encoder)",
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": "Design and develop a comprehensive, indigenous Integrated Track Monitoring System that:\n• Fully complies with RDSO Specification TM/IM/448, Rev. 1: 2023 and EN 13848 standards.\n• Supports modularity, ease of maintenance, and cost efficiency.",
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": "Sub-systems:\n• Track geometry measurement system\n• Full rail profile and wear measurement system\n• Condition monitoring of track components\n• Acceleration measurement system\n• Infringement measurement to MMD/SOD\n• Rear window video recording system\n\nData Acquisition & Sampling:\n• Sampling interval: 25 cm\n• Operable under dynamic loads at speeds from 0–200 km/h\n• Real-time acquisition and processing capability\n\nData Processing & Analysis:\n• Onboard server for real-time data filtering and analysis\n• Software must:\n– Eliminate environmental and operational noise\n– Extract and analyze track geometry parameters & track component conditions\n– Comply with EN 13848 Part 1 & 2 and RDSO TM/IM/448, Rev. 1: 2023 accuracy standards\n\nOutput & Storage:\n• Chainage-mapped outputs for:\n– Track Geometry: Gauge, alignment, unevenness, twist, cross level, curve\n– Dynamic Parameters: Vertical & lateral acceleration\n– Rail Condition: Profile and wear\n– Track Components: Rail surface, fastenings, ballast, sleepers\n– Synchronized rear-view video footage\n– Exportable data in standard formats (CSV, XML, JPEG, AVI)\n• Secure storage and archival capability",
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Railways",
"problem_description": "Background\n\nIndian Railways employs Track Recording Cars (TRCs) for periodic assessment of track geometry to ensure safety, ride comfort, and operational efficiency. While some TRCs still use outdated, contact-based systems, others rely on imported contactless technologies—typically laser-based solutions integrated with proprietary software.\n\nThese foreign systems pose several challenges:\n• High procurement and maintenance costs\n• Limited customization capabilities\n• Dependency on external vendors and closed-source software\n\nTo address these issues and promote self-reliance, Indian Railways invites proposals for the Development of indigenous contactless Integrated Track Monitoring Systems (ITMS) for Track Recording on Indian Railways.\n\nObjective\n\nDesign and develop a comprehensive, indigenous Integrated Track Monitoring System that:\n• Fully complies with RDSO Specification TM/IM/448, Rev. 1: 2023 and EN 13848 standards.\n• Supports modularity, ease of maintenance, and cost efficiency.\n\nTechnical Scope\n\nSub-systems:\n• Track geometry measurement system\n• Full rail profile and wear measurement system\n• Condition monitoring of track components\n• Acceleration measurement system\n• Infringement measurement to MMD/SOD\n• Rear window video recording system\n\nData Acquisition & Sampling:\n• Sampling interval: 25 cm\n• Operable under dynamic loads at speeds from 0–200 km/h\n• Real-time acquisition and processing capability\n\nData Processing & Analysis:\n• Onboard server for real-time data filtering and analysis\n• Software must:\n– Eliminate environmental and operational noise\n– Extract and analyze track geometry parameters & track component conditions\n– Comply with EN 13848 Part 1 & 2 and RDSO TM/IM/448, Rev. 1: 2023 accuracy standards\n\nOutput & Storage:\n• Chainage-mapped outputs for:\n– Track Geometry: Gauge, alignment, unevenness, twist, cross level, curve\n– Dynamic Parameters: Vertical & lateral acceleration\n– Rail Condition: Profile and wear\n– Track Components: Rail surface, fastenings, ballast, sleepers\n– Synchronized rear-view video footage\n– Exportable data in standard formats (CSV, XML, JPEG, AVI)\n• Secure storage and archival capability\n\nKey Performance Parameters\n\n• Maximum Speed: 200 km/h\n• Sampling Rate: 25 cm\n• Accuracy: As per EN 13848 Part 2 & RDSO TM/IM/448, Rev. 1: 2023\n• Real-time Processing: Required\n• Chainage Mapping: Mandatory (via axle encoder)\n\nEligibility\n\nOpen to:\n• Startups\n• Entrepreneurs\n• Academic & research institutions\n• Industry professionals and R&D organizations\n• Collaborative consortia involving any of the above\n\nEvaluation Criteria\n\n• Technical feasibility and innovation – 10 marks\n• Standards compliance (EN 13848 & RDSO TM/IM/448, Rev. 1:2023) – 40 marks\n• Hardware robustness, modularity & compactness – 20 marks\n• Software usability & architecture – 10 marks\n• Scalability, maintainability & upgradability – 10 marks\n• Cost-effectiveness – 10 marks\nTotal = 100 marks\n\nDeliverables\n\nSuccessful participants must submit:\n• A fully functional prototype (hardware + software)\n• Comprehensive technical documentation\n• Validation report demonstrating standards compliance\n• Video demonstration (lab/field performance)\n• Cost analysis and scalability roadmap\n\nConclusion\n\nThis initiative is a step toward achieving technological independence in railway infrastructure monitoring. By fostering domestic innovation, Indian Railways aims to reduce reliance on foreign systems, cut long-term costs, and deploy tailored solutions better suited to India’s operational context.",
"ps_number": "SIH25020",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Automation",
"title": "Development of indigenous contactless Integrated Track Monitoring Systems (ITMS) for Track Recording on Indian Railways"
}
|
{
"category": "Hardware",
"details": {
"ai-based_anomaly_detection": null,
"background": "Indian Railways procures about 10 crore Elastic Rail Clips, 5 crore liners, and 8.5 crore rail pads annually. There is currently no system for identification of these track fittings—i.e., elastic rail clips, rail pads, liners—and sleepers, with integration to the UDM portal enabling mobile-based scanning for vendor lot number, date of supply, warranty period, inspection dates, etc. This gap is critical for quality assessment and performance management of fittings.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": "This problem statement envisages a unified system for laser-based QR code marking on track fittings to enable mobile scanning and identification of elastic rail clips, rail pads, liners, and sleepers, along with integration to the UDM (User Depot Module) on www.ireps.gov.in and the TMS (Track Management System) on www.irecept.gov.in. With the use of AI, the system should extract all essential details of each fitting item, including inspections at all stages—from manufacturing and supply to in-service performance—and pinpoint exceptions for quality monitoring. Laser-based QR codes are already prevalent in other industries.",
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "Innovative solutions are invited through Smart India Hackathon 2025 to develop and implement a system addressing identification of bulk supply materials, their performance issues, and effective inventory management and quality monitoring actions for safety performance of fittings.\n\n• Hardware Solution: Design and implement laser-based QR code imprints on bulk supply items of track fittings and sleepers.\n• Software Solution: Develop QR code linkage and integrate with the UDM and TMS portals; enable mobile scans to generate AI-based reports related to vendor, supply, warranty, inspections, and support inventory management, etc.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Railways",
"problem_description": "Background\n\nIndian Railways procures about 10 crore Elastic Rail Clips, 5 crore liners, and 8.5 crore rail pads annually. There is currently no system for identification of these track fittings—i.e., elastic rail clips, rail pads, liners—and sleepers, with integration to the UDM portal enabling mobile-based scanning for vendor lot number, date of supply, warranty period, inspection dates, etc. This gap is critical for quality assessment and performance management of fittings.\n\nDescription\n\nThis problem statement envisages a unified system for laser-based QR code marking on track fittings to enable mobile scanning and identification of elastic rail clips, rail pads, liners, and sleepers, along with integration to the UDM (User Depot Module) on www.ireps.gov.in and the TMS (Track Management System) on www.irecept.gov.in. With the use of AI, the system should extract all essential details of each fitting item, including inspections at all stages—from manufacturing and supply to in-service performance—and pinpoint exceptions for quality monitoring. Laser-based QR codes are already prevalent in other industries.\n\nExpected Solution\n\nInnovative solutions are invited through Smart India Hackathon 2025 to develop and implement a system addressing identification of bulk supply materials, their performance issues, and effective inventory management and quality monitoring actions for safety performance of fittings.\n\n• Hardware Solution: Design and implement laser-based QR code imprints on bulk supply items of track fittings and sleepers.\n• Software Solution: Develop QR code linkage and integrate with the UDM and TMS portals; enable mobile scans to generate AI-based reports related to vendor, supply, warranty, inspections, and support inventory management, etc.",
"ps_number": "SIH25021",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Transportation & Logistics",
"title": "AI based development of Laser based QR Code marking on track fittings on Indian Railways"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Indian Railways manages train movements primarily through the experience of train traffic controllers. While effective, this manual approach faces limitations as network congestion and operational complexity grow. Trains of varying types and priorities must share limited track infrastructure across space and time, making optimal allocation a significant challenge. The problem is a large-scale combinatorial optimization task with numerous constraints such as safety, track resources, system of working, signalling system, platform availability, train schedules, and train priorities. As real-time decisions become increasingly complex, there is a growing need for intelligent, data-driven systems powered by optimization algorithms and AI to enhance efficiency, punctuality, and utilization of railway infrastructure.\n\nDetailed Description\n\nCurrently, experienced traffic controllers oversee operations and take real-time decisions—whether a train should proceed, halt, or be rerouted—based on operational conditions and institutional knowledge. With rising traffic volumes and higher expectations for punctuality, safety, and efficiency, manual decision-making alone is becoming insufficient.\n\nThe network is constrained by finite infrastructure—limited track sections, junctions, crossings, and platform capacities—shared by long-distance express, suburban local, freight, maintenance blocks, and unscheduled specials. Coordinating these movements across spatial (network layout) and temporal (scheduling) dimensions while maintaining safety and minimizing delays is formidable.\n\nWithin a section managed by a section controller, the core problem is to decide train precedence and crossings to maximize throughput and minimize overall train travel time, considering section characteristics (e.g., line capacity, gradients, signal placements) and varying train priorities. This represents a dynamic, large-scale combinatorial optimization problem with an exponentially large solution space, further complicated by real-time disruptions (breakdowns, weather, rolling stock delays). Human intuition alone is no longer sufficient; intelligent decision-support tools are required to improve precision, scalability, and responsiveness.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "An intelligent decision-support system that assists section controllers in making optimized, real-time decisions for train precedence and crossings. The system should:\n\n• Leverage operations research and AI to model constraints, train priorities, and operational rules, producing conflict-free, feasible schedules dynamically.\n• Maximize section throughput and minimize overall train travel time, with the ability to re-optimize rapidly under disruptions (e.g., incidents, delays, weather).\n• Support what-if simulation and scenario analysis to evaluate alternative routings, holding strategies, and platform allocations.\n• Provide a user-friendly interface for controllers with clear recommendations, explanations, and override capabilities.\n• Integrate with existing railway control systems and data sources (signalling, TMS, timetables, rolling stock status) via secure APIs.\n• Include audit trails, performance dashboards, and KPIs (punctuality, average delay, throughput, utilization) for continuous improvement.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
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"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
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"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Railways",
"problem_description": "Background\n\nIndian Railways manages train movements primarily through the experience of train traffic controllers. While effective, this manual approach faces limitations as network congestion and operational complexity grow. Trains of varying types and priorities must share limited track infrastructure across space and time, making optimal allocation a significant challenge. The problem is a large-scale combinatorial optimization task with numerous constraints such as safety, track resources, system of working, signalling system, platform availability, train schedules, and train priorities. As real-time decisions become increasingly complex, there is a growing need for intelligent, data-driven systems powered by optimization algorithms and AI to enhance efficiency, punctuality, and utilization of railway infrastructure.\n\nDetailed Description\n\nCurrently, experienced traffic controllers oversee operations and take real-time decisions—whether a train should proceed, halt, or be rerouted—based on operational conditions and institutional knowledge. With rising traffic volumes and higher expectations for punctuality, safety, and efficiency, manual decision-making alone is becoming insufficient.\n\nThe network is constrained by finite infrastructure—limited track sections, junctions, crossings, and platform capacities—shared by long-distance express, suburban local, freight, maintenance blocks, and unscheduled specials. Coordinating these movements across spatial (network layout) and temporal (scheduling) dimensions while maintaining safety and minimizing delays is formidable.\n\nWithin a section managed by a section controller, the core problem is to decide train precedence and crossings to maximize throughput and minimize overall train travel time, considering section characteristics (e.g., line capacity, gradients, signal placements) and varying train priorities. This represents a dynamic, large-scale combinatorial optimization problem with an exponentially large solution space, further complicated by real-time disruptions (breakdowns, weather, rolling stock delays). Human intuition alone is no longer sufficient; intelligent decision-support tools are required to improve precision, scalability, and responsiveness.\n\nExpected Solution\n\nAn intelligent decision-support system that assists section controllers in making optimized, real-time decisions for train precedence and crossings. The system should:\n\n• Leverage operations research and AI to model constraints, train priorities, and operational rules, producing conflict-free, feasible schedules dynamically.\n• Maximize section throughput and minimize overall train travel time, with the ability to re-optimize rapidly under disruptions (e.g., incidents, delays, weather).\n• Support what-if simulation and scenario analysis to evaluate alternative routings, holding strategies, and platform allocations.\n• Provide a user-friendly interface for controllers with clear recommendations, explanations, and override capabilities.\n• Integrate with existing railway control systems and data sources (signalling, TMS, timetables, rolling stock status) via secure APIs.\n• Include audit trails, performance dashboards, and KPIs (punctuality, average delay, throughput, utilization) for continuous improvement.",
"ps_number": "SIH25022",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Transportation & Logistics",
"title": "Maximizing Section Throughput Using AI-Powered Precise Train Traffic Control"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": null,
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
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"impact": null,
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"introduction": "Background:- Panchakarma is gaining global recognition for detoxification, rejuvenation, and chronic disease management, contributing significantly to the projected USD 16 billion Ayurveda market by 2026. However, the lack of dedicated management software leads to: -Inefficient manual scheduling and documentation -Inconsistent therapy quality across centers -Limited digital patient management Advancements in healthcare IT and digital therapeutics present a timely opportunity to develop a software solution that integrates traditional authenticity with modern efficiency. Description:- The Panchakarma Management Software will feature automated therapy scheduling and provide notifications to patients regarding the necessary pre- and post-procedure precautions. The software will include: -Automated therapy scheduling system – to plan and manage therapy sessions automatically. -Notification system – to alert patients about pre-procedure and post-procedure precautions they need to follow. Innovative Features:- -Real-Time Therapy Tracking: Allow patients and practitioners to view therapy progress, upcoming sessions and personalized recovery milestones. -Visualization Tools: Use graphs and progress bars to track improvements based on patient responses and feedback. -Integrated Feedback Loop: Enable patients to report symptoms, side effects or improvements after each session, refining schedules or precautions as needed. Expected solution:- The software should address both core functionality and innovative enhancements to ensure usability, efficiency and patient-centric care. Platform should contain:- •The platform should have automated therapy scheduling Feature for both patients and practitioners to schedule, modify, and view upcoming therapy sessions. Pre- and Post-Procedure Notification System:- •Automated alerts and reminders to patients regarding the necessary precautions before and after procedures. •Customizable notification channels (in-app, SMS, email)",
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
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"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Ayush",
"problem_description": "Background:- Panchakarma is gaining global recognition for detoxification, rejuvenation, and chronic disease management, contributing significantly to the projected USD 16 billion Ayurveda market by 2026. However, the lack of dedicated management software leads to: -Inefficient manual scheduling and documentation -Inconsistent therapy quality across centers -Limited digital patient management Advancements in healthcare IT and digital therapeutics present a timely opportunity to develop a software solution that integrates traditional authenticity with modern efficiency. Description:- The Panchakarma Management Software will feature automated therapy scheduling and provide notifications to patients regarding the necessary pre- and post-procedure precautions. The software will include: -Automated therapy scheduling system – to plan and manage therapy sessions automatically. -Notification system – to alert patients about pre-procedure and post-procedure precautions they need to follow. Innovative Features:- -Real-Time Therapy Tracking: Allow patients and practitioners to view therapy progress, upcoming sessions and personalized recovery milestones. -Visualization Tools: Use graphs and progress bars to track improvements based on patient responses and feedback. -Integrated Feedback Loop: Enable patients to report symptoms, side effects or improvements after each session, refining schedules or precautions as needed. Expected solution:- The software should address both core functionality and innovative enhancements to ensure usability, efficiency and patient-centric care. Platform should contain:- •The platform should have automated therapy scheduling Feature for both patients and practitioners to schedule, modify, and view upcoming therapy sessions. Pre- and Post-Procedure Notification System:- •Automated alerts and reminders to patients regarding the necessary precautions before and after procedures. •Customizable notification channels (in-app, SMS, email)",
"ps_number": "SIH25023",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "MedTech / BioTech / HealthTech",
"title": "AyurSutra- Panchakarma Patient Management and therapy scheduling Software"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Currently, in Ayurvedic hospitals, diet charts are prescribed manually by doctors in handwritten form, tailored to each patient’s needs. Existing software solutions primarily focus on macro- and micro-nutrient tracking but fail to align with Ayurvedic nutritional concepts. This gap creates inefficiencies, reduces accuracy, and makes it harder for practitioners to deliver holistic dietary care rooted in Ayurveda.\n\nDetailed Description\n\nThe problem envisages the development of a dedicated Ayurvedic Diet Management Software designed to efficiently create, manage, and organize patient-specific diet charts with both accuracy and ease. Unlike conventional nutrition tools, the platform will integrate modern nutritional metrics with Ayurvedic dietary principles—such as caloric value, food properties (Hot/Cold, Easy/Difficult to digest), and the six tastes (Rasa).",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "The proposed solution should provide an intuitive platform tailored for Ayurvedic dietitians, enabling quick food input, comprehensive nutrient tracking, and Ayurvedic dietary categorization.\n\nKey Features:\n• Scientifically calculated nutrient data for diverse food categories, customized for men, women, and children across all age groups.\n• A dynamic food database of 8,000+ items covering Indian, multicultural, and international cuisines for wide applicability.\n• Automated diet chart generation with nutritionally balanced, Ayurveda-compliant plans in a clear, organized format.\n• Comprehensive patient management module, including profiles with age, gender, dietary habits, meal frequency, bowel movements, water intake, and other critical health parameters.\n• Recipe-based diet charts with automated nutrient analysis to provide detailed, actionable guidance for patients.\n\nAdditional Features:\n• Security & Compliance: Ensure patient data privacy, adhering to health data regulations (e.g., HIPAA or local laws).\n• User Experience (UX): A clean, user-friendly interface with customization to match Ayurvedic practitioners’ workflows.\n• Integration Potential: Capability to integrate with hospital information systems (HIS) or electronic health records (EHR).\n• Mobile Support: Compatibility with mobile and tablet devices for on-the-go usage by doctors and patients.\n• Reporting Tools: Ability to generate printable diet charts and reports for patient handouts.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
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"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
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"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Ayush",
"problem_description": "Background\n\nCurrently, in Ayurvedic hospitals, diet charts are prescribed manually by doctors in handwritten form, tailored to each patient’s needs. Existing software solutions primarily focus on macro- and micro-nutrient tracking but fail to align with Ayurvedic nutritional concepts. This gap creates inefficiencies, reduces accuracy, and makes it harder for practitioners to deliver holistic dietary care rooted in Ayurveda.\n\nDetailed Description\n\nThe problem envisages the development of a dedicated Ayurvedic Diet Management Software designed to efficiently create, manage, and organize patient-specific diet charts with both accuracy and ease. Unlike conventional nutrition tools, the platform will integrate modern nutritional metrics with Ayurvedic dietary principles—such as caloric value, food properties (Hot/Cold, Easy/Difficult to digest), and the six tastes (Rasa).\n\nExpected Solution\n\nThe proposed solution should provide an intuitive platform tailored for Ayurvedic dietitians, enabling quick food input, comprehensive nutrient tracking, and Ayurvedic dietary categorization.\n\nKey Features:\n• Scientifically calculated nutrient data for diverse food categories, customized for men, women, and children across all age groups.\n• A dynamic food database of 8,000+ items covering Indian, multicultural, and international cuisines for wide applicability.\n• Automated diet chart generation with nutritionally balanced, Ayurveda-compliant plans in a clear, organized format.\n• Comprehensive patient management module, including profiles with age, gender, dietary habits, meal frequency, bowel movements, water intake, and other critical health parameters.\n• Recipe-based diet charts with automated nutrient analysis to provide detailed, actionable guidance for patients.\n\nAdditional Features:\n• Security & Compliance: Ensure patient data privacy, adhering to health data regulations (e.g., HIPAA or local laws).\n• User Experience (UX): A clean, user-friendly interface with customization to match Ayurvedic practitioners’ workflows.\n• Integration Potential: Capability to integrate with hospital information systems (HIS) or electronic health records (EHR).\n• Mobile Support: Compatibility with mobile and tablet devices for on-the-go usage by doctors and patients.\n• Reporting Tools: Ability to generate printable diet charts and reports for patient handouts.",
"ps_number": "SIH25024",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "MedTech / BioTech / HealthTech",
"title": "Comprehensive Cloud-Based Practice Management & Nutrient Analysis Software for Ayurvedic Dietitians Tailored for Ayurveda-Focused Diet Plans"
}
|
{
"category": "Hardware",
"details": {
"ai-based_anomaly_detection": null,
"background": "In Ayurveda and other traditional medicine systems, Rasa (taste) is a fundamental criterion for identifying, classifying, and determining the therapeutic value of medicinal herbs. While this taste-based assessment has been effective for centuries, it is inherently subjective, relying on human perception and expert experience, which often leads to variability and inconsistency.\n\nIn the modern context, ensuring the authenticity, quality, and standardization of herbal raw materials is a critical challenge due to widespread adulteration, batch-to-batch phytochemical variations, and the global demand for reliable herbal products.\n\nRecent advances in sensor science and analytical technologies provide innovative solutions to these challenges. Electronic tongue (e-tongue) systems can mimic human gustatory mechanisms by detecting complex chemical signatures, while spectroscopic techniques such as Near-Infrared (NIR), Raman, and UV-Visible spectroscopy offer rapid, non-destructive chemical profiling of herbal samples.\n\nWhen integrated with Artificial Intelligence (AI) and Machine Learning (ML)—such as chemometric modelling, neural networks, and pattern recognition—large datasets can be analyzed to classify herbs based on taste profiles, threshold levels, and phytochemical composition with high precision. This AI-enabled, sensor-integrated approach ensures faster, objective, and cost-effective quality assurance, bridging traditional Ayurvedic principles with modern scientific validation.\n\nDetailed Description\n\nThe problem statement aims to design and develop a sensor-integrated AI-enabled device for objective quality assessment of marketed herbal samples. The device will incorporate:\n\n• A multi-sensor e-tongue array to detect basic taste modalities (sweet, sour, salty, bitter, pungent, astringent).\n• A threshold detection module for quantifying the minimum perceptible concentration of each taste-related compound.\n• Analytical integration with phytochemical profiling techniques (e.g., HPTLC, FTIR, LC-MS) for correlating taste signatures with chemical constituents.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "• A portable hardware prototype incorporating an electronic tongue (e-tongue) sensor array.\n• Calibration using authenticated herb samples and machine learning models trained on large datasets of taste and phytochemical fingerprints.\n• Smart alerts and decision support for detecting adulteration or substandard quality.\n• A centralized or cloud-compatible database that updates continuously with new samples and learning outputs.\n• Applicability across industries including Ayurvedic pharmacopeia standardization, herbal industry quality control, academic research, and regulatory bodies.",
"impact": null,
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"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
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"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
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"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Ayush",
"problem_description": "Background\n\nIn Ayurveda and other traditional medicine systems, Rasa (taste) is a fundamental criterion for identifying, classifying, and determining the therapeutic value of medicinal herbs. While this taste-based assessment has been effective for centuries, it is inherently subjective, relying on human perception and expert experience, which often leads to variability and inconsistency.\n\nIn the modern context, ensuring the authenticity, quality, and standardization of herbal raw materials is a critical challenge due to widespread adulteration, batch-to-batch phytochemical variations, and the global demand for reliable herbal products.\n\nRecent advances in sensor science and analytical technologies provide innovative solutions to these challenges. Electronic tongue (e-tongue) systems can mimic human gustatory mechanisms by detecting complex chemical signatures, while spectroscopic techniques such as Near-Infrared (NIR), Raman, and UV-Visible spectroscopy offer rapid, non-destructive chemical profiling of herbal samples.\n\nWhen integrated with Artificial Intelligence (AI) and Machine Learning (ML)—such as chemometric modelling, neural networks, and pattern recognition—large datasets can be analyzed to classify herbs based on taste profiles, threshold levels, and phytochemical composition with high precision. This AI-enabled, sensor-integrated approach ensures faster, objective, and cost-effective quality assurance, bridging traditional Ayurvedic principles with modern scientific validation.\n\nDetailed Description\n\nThe problem statement aims to design and develop a sensor-integrated AI-enabled device for objective quality assessment of marketed herbal samples. The device will incorporate:\n\n• A multi-sensor e-tongue array to detect basic taste modalities (sweet, sour, salty, bitter, pungent, astringent).\n• A threshold detection module for quantifying the minimum perceptible concentration of each taste-related compound.\n• Analytical integration with phytochemical profiling techniques (e.g., HPTLC, FTIR, LC-MS) for correlating taste signatures with chemical constituents.\n\nExpected Solution\n\n• A portable hardware prototype incorporating an electronic tongue (e-tongue) sensor array.\n• Calibration using authenticated herb samples and machine learning models trained on large datasets of taste and phytochemical fingerprints.\n• Smart alerts and decision support for detecting adulteration or substandard quality.\n• A centralized or cloud-compatible database that updates continuously with new samples and learning outputs.\n• Applicability across industries including Ayurvedic pharmacopeia standardization, herbal industry quality control, academic research, and regulatory bodies.",
"ps_number": "SIH25025",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "MedTech / BioTech / HealthTech",
"title": "E tongue for Dravya identification"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "India’s Ayush sector is rapidly transitioning from paper-based records to interoperable digital health systems. Central to this transformation are two key coding systems: the National AYUSH Morbidity & Standardized Terminologies Electronic (NAMASTE) codes, which provide over 4,500 standardized terms for Ayurveda, Siddha and Unani disorders, WHO Standardised International Terminologies for Ayurveda and the WHO’s ICD-11, Chapter – 26, Traditional Medicine Module 2 (TM2), which integrates 529 disorder categories and 196 pattern codes into the global ICD framework. Harmonising these vocabularies within Electronic Medical Record (EMR) platforms not only enables accurate clinical documentation and decision support but also ensures compliance with India’s 2016 EHR Standards—mandating FHIR R4 APIs, SNOMED CT and LOINC semantics, ISO 22600 access control, ABHA-linked OAuth 2.0 authentication, and robust audit trails for consent and versioning.\n\nTo operationalize this dual-coding approach, EMR vendors must implement a lightweight terminology micro-service that ingests NAMASTE CSV and synchronises with the WHO-11 ICD-API (Including Biomedicine and TM2). Within the EMR user interface, diagnosis entries should support auto-complete widgets that return both NAMASTE and ICD-11 (TM2 and Biomedicine) codes, comply with the Coding rules of ICD-11 framework and store them together in the patient’s Problem List resource. This integration empowers clinicians to combine traditional and biomedical insights, facilitates Ayush insurance claims under global ICD-11 coding rules, and provides the Ministry of Ayush with real-time morbidity analytics aligned with national and international reporting standards.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": "Design and prototype an API integration that brings India’s NAMASTE terminologies, WHO Standardised International terminology and the WHO ICD-11 (Traditional Medicine Module 2 (TM2) & Biomedicine) into a FHIR-compliant Electronic Medical Record (EMR) system. Your goal is to enable clinicians to record traditional medicine diagnoses (Ayurveda, Siddha, Unani) using NAMASTE codes, then automatically map them to global ICD-11 (TM2 and Biomedicine) identifiers—supporting dual/double-coding (One code denoting Ayurveda/Siddha/Unani (TM) and another denoting Biomedicine) for interoperability, analytics and insurance claims.\n\nYour deliverable is a lightweight micro-service or FHIR terminology plugin offering:\n• A FHIR compliant resource for NAMASTE codes linking to WHO International Terminologies of Ayurveda, ICD-11 (TM2 and Biomedicine) and compliant with ICD-11 Coding rules.\n• A REST endpoint for auto-complete value-set lookup.\n• A translation operation converting NAMASTE ↔ TM2 codes.\n• An encounter upload endpoint that ingests FHIR Bundles with both code systems.\n• OAuth 2.0–secured access using ABHA tokens and audit-ready metadata.\n\nTeams should demonstrate\n\n1. Ingesting the NAMASTE CSV export and generating FHIR CodeSystem + ConceptMap.\n2. Fetching TM2, Biomedicine updates from the WHO ICD-API and merging into your service.\n3. A simple web or CLI interface to search NAMASTE terms, WHO International Terminologies of Ayurveda, see mapped TM2 codes, and construct a FHIR ProblemList entry.\n4. Version tracking and consent metadata to satisfy India’s 2016 EHR Standards (FHIR R4, ISO 22600, SNOMED-CT/LOINC semantics).",
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "A lightweight, FHIR R4–compliant terminology micro-service—built to India’s 2016 EHR Standards—that exposes a NAMASTE CodeSystem, WHO International Terminologies of Ayurveda, an ICD-11 TM2, Biomedicine ConceptMap, an auto-complete value-set lookup endpoint, a NAMASTE↔TM2 translate operation; ICD-11 Biomedicine look up and a secure FHIR Bundle upload interface (for enabling double coding).",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
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"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
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},
"organization": "Ministry of Ayush",
"problem_description": "Background\n\nIndia’s Ayush sector is rapidly transitioning from paper-based records to interoperable digital health systems. Central to this transformation are two key coding systems: the National AYUSH Morbidity & Standardized Terminologies Electronic (NAMASTE) codes, which provide over 4,500 standardized terms for Ayurveda, Siddha and Unani disorders, WHO Standardised International Terminologies for Ayurveda and the WHO’s ICD-11, Chapter – 26, Traditional Medicine Module 2 (TM2), which integrates 529 disorder categories and 196 pattern codes into the global ICD framework. Harmonising these vocabularies within Electronic Medical Record (EMR) platforms not only enables accurate clinical documentation and decision support but also ensures compliance with India’s 2016 EHR Standards—mandating FHIR R4 APIs, SNOMED CT and LOINC semantics, ISO 22600 access control, ABHA-linked OAuth 2.0 authentication, and robust audit trails for consent and versioning.\n\nTo operationalize this dual-coding approach, EMR vendors must implement a lightweight terminology micro-service that ingests NAMASTE CSV and synchronises with the WHO-11 ICD-API (Including Biomedicine and TM2). Within the EMR user interface, diagnosis entries should support auto-complete widgets that return both NAMASTE and ICD-11 (TM2 and Biomedicine) codes, comply with the Coding rules of ICD-11 framework and store them together in the patient’s Problem List resource. This integration empowers clinicians to combine traditional and biomedical insights, facilitates Ayush insurance claims under global ICD-11 coding rules, and provides the Ministry of Ayush with real-time morbidity analytics aligned with national and international reporting standards.\n\nDescription\n\nDesign and prototype an API integration that brings India’s NAMASTE terminologies, WHO Standardised International terminology and the WHO ICD-11 (Traditional Medicine Module 2 (TM2) & Biomedicine) into a FHIR-compliant Electronic Medical Record (EMR) system. Your goal is to enable clinicians to record traditional medicine diagnoses (Ayurveda, Siddha, Unani) using NAMASTE codes, then automatically map them to global ICD-11 (TM2 and Biomedicine) identifiers—supporting dual/double-coding (One code denoting Ayurveda/Siddha/Unani (TM) and another denoting Biomedicine) for interoperability, analytics and insurance claims.\n\nYour deliverable is a lightweight micro-service or FHIR terminology plugin offering:\n• A FHIR compliant resource for NAMASTE codes linking to WHO International Terminologies of Ayurveda, ICD-11 (TM2 and Biomedicine) and compliant with ICD-11 Coding rules.\n• A REST endpoint for auto-complete value-set lookup.\n• A translation operation converting NAMASTE ↔ TM2 codes.\n• An encounter upload endpoint that ingests FHIR Bundles with both code systems.\n• OAuth 2.0–secured access using ABHA tokens and audit-ready metadata.\n\nTeams should demonstrate\n\n1. Ingesting the NAMASTE CSV export and generating FHIR CodeSystem + ConceptMap.\n2. Fetching TM2, Biomedicine updates from the WHO ICD-API and merging into your service.\n3. A simple web or CLI interface to search NAMASTE terms, WHO International Terminologies of Ayurveda, see mapped TM2 codes, and construct a FHIR ProblemList entry.\n4. Version tracking and consent metadata to satisfy India’s 2016 EHR Standards (FHIR R4, ISO 22600, SNOMED-CT/LOINC semantics).\n\nExpected Solution\n\nA lightweight, FHIR R4–compliant terminology micro-service—built to India’s 2016 EHR Standards—that exposes a NAMASTE CodeSystem, WHO International Terminologies of Ayurveda, an ICD-11 TM2, Biomedicine ConceptMap, an auto-complete value-set lookup endpoint, a NAMASTE↔TM2 translate operation; ICD-11 Biomedicine look up and a secure FHIR Bundle upload interface (for enabling double coding).",
"ps_number": "SIH25026",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "MedTech / BioTech / HealthTech",
"title": "Develop API code to integrate NAMASTE and or the International Classification of Diseases (ICD-11) via the Traditional Medicine Module 2 (TM2) into existing EMR systems that comply with Electronic Health Record (EHR) Standards for India"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "The Ayurvedic herbal supply chain in India is characterised by fragmented networks of smallholder farmers, wild collectors and multiple intermediaries, leading to challenges in ensuring consistent quality, authenticity and sustainable sourcing of medicinal plants. Variations in harvesting practices, environmental conditions and manual record-keeping introduce risks of mislabeling, adulteration and over-harvesting of vulnerable species, undermining consumer trust and compliance with regulatory standards. Geographic provenance is often undocumented or opaque, making it difficult for manufacturers and regulators to verify that herbs originate from approved regions or follow sustainable collection guidelines.\n\nA blockchain-based traceability system, augmented with geo-tagging technology, can address these gaps by creating an immutable, decentralised ledger that records every step of the herb's journey—from on-site GPS-tagged collection events through processing, testing and formulation. Smart contracts on a permissioned network (e.g., Hyperledger Fabric) can enforce sustainability criteria and automate quality validations, while IoT-enabled devices capture real-time location and environmental data at remote collection points, even via SMS-over-blockchain gateways where connectivity is sparse. By integrating FHIR-style metadata bundles (e.g., \"CollectionEvent,\" \"QualityTest,\" \"ProcessingStep\") and QR-code scanning at aggregation nodes, stakeholders gain end-to-end visibility, enabling rapid verification of provenance, streamlined certification for export and robust audit trails to support both biodiversity conservation and supply-chain efficiency. When herbs are formulated into finished products, unique, serialised QR codes generated by the blockchain platform could be affixed to each package. End customers scan these codes with a mobile app or web portal—powered by the same blockchain ledger—to retrieve a FHIR-style provenance bundle detailing each upstream event: farm of origin, harvest conditions, intermediary custody, laboratory certificates and batch formulation parameters. This consumer-facing transparency not only verifies authenticity and builds trust, but also supports ethical marketing, enables rapid recall management and fosters incentives for sustainable collection practices by linking premium pricing to verified harvest data. Over time, analytics on consumer scans can feed back into demand forecasting, closing the loop between consumer assurance and supply-chain optimisation.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": "A permissioned blockchain network will immutably record every stage of an Ayurvedic herb's journey—from geo-tagged harvest events by farmers or wild collectors, through multi-stage processing and laboratory testing, to the finished product on retail shelves. At the point of collection, GPS-enabled mobile or IoT devices capture precise location, timestamp, collector identity, species identification and initial quality metrics as a \"Collection Event.\" Subsequent \"Processing Step\" and \"Quality Test\" events—each embedding standardised metadata bundles—are added by processing facilities and testing laboratories. Smart contracts enforce National Medicinal Plants Board sustainability guidelines and Good Agricultural and Collection Practices by automatically validating geo-fencing rules, seasonal restrictions and quality thresholds before committing each transaction to the ledger.\n\nWhen formulation is complete, unique QR codes generated on-chain are affixed to product packaging. End customers scan these codes via a lightweight web or mobile portal (no specialised app required) to retrieve the full provenance record: farm coordinates and harvest conditions; chain-of-custody handoffs; lab certificates for moisture, pesticide and DNA-barcode tests; and sustainability and fair-trade compliance proofs. This consumer-facing transparency assures authenticity and safety, enables rapid recall notifications for affected batches and tells the story of each product—complete with interactive maps and farmer or community profiles. By combining tamper-proof audit trails, geo-tagged traceability and automated compliance enforcement, the system delivers a replicable model for ethical, sustainable and trust-driven Ayurvedic herb sourcing.",
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "Participants will deliver a proof-of-concept blockchain-based botanical traceability system addressing end-to-end provenance of Ayurvedic herbs. The solution should include the following core components and capabilities:\n\n1. Permissioned Blockchain Network\n• A lightweight, permissioned ledger (e.g., Hyperledger Fabric or Corda) that records every supply-chain transaction.\n• Network nodes representing farmers' cooperatives, wild-collector groups, testing laboratories, processing facilities and manufacturers.\n• Smart contracts enforcing:\n- Geo-fencing rules based on collectors' GPS coordinates and approved harvesting zones.\n- Seasonal-harvest restrictions and species-specific conservation limits per National Medicinal Plants Board guidelines.\n- Quality-gate validations (e.g., moisture thresholds, pesticide limits, DNA barcoding checks).\n\n2. Geo-Tagged Data Capture\n• IoT/GPS-enabled mobile DApp (or SMS-over-blockchain gateway) for collectors to record \"CollectionEvent\" metadata: latitude/longitude, timestamp, collector ID, species and initial quality metrics.\n• Sensor integrations or manual interfaces for \"QualityTest\" events (lab results) and \"ProcessingStep\" events (drying, grinding, storage conditions).\n\n3. Smart Labeling & Consumer Portal\n• On-chain generation of unique QR codes for each finished product batch.\n• A lightweight web/mobile portal (no specialised install required) allowing end customers to scan QR codes and retrieve a complete FHIR-style provenance bundle:\n- Collection location map and harvest details\n- Chain-of-custody handoffs through each supply-chain node\n- Laboratory certificates for moisture, pesticide analysis, DNA authentication\n- Sustainability compliance proofs and fair-trade verifications\n- Interactive farmer/community profiles and conservation credentials\n\n4. Integration & Interoperability\n• RESTful APIs for supply-chain managers to query real-time dashboards of harvest volumes, batch statuses, QA results and sustainability metrics.\n• Plugins or connectors to existing ERP/quality-management systems for seamless data exchange.\n• Use of FHIR-style resource models (CollectionEvent, QualityTest, ProcessingStep, Provenance) for standardized metadata exchange.\n\n5. User Interfaces & Reporting\n• A mobile DApp interface optimized for low-bandwidth rural environments, with offline data capture and SMS synchronization.\n• A web dashboard for stakeholders to monitor network health, query provenance records and generate compliance reports aligned with AYUSH Ministry export and sustainability requirements.\n• Automated reporting modules that compile environmental-impact metrics and conservation compliance data for certification bodies.\n\n6. Demonstration & Evaluation\n• A live pilot using one botanical species (e.g., Ashwagandha) across a small farming cooperative and a collaborating processor.\n• End-to-end demonstration: geo-tagging harvest, adding lab results, processing events, QR code scanning by simulated consumers and recall simulation.\n• Metrics collection on data-capture latency, transaction throughput, offline sync reliability and consumer-scan engagement.\n\nBy delivering these elements, participants will showcase a replicable, transparent and sustainable model for botanical traceability that bridges traditional Ayurvedic sourcing with modern blockchain technology and consumer empowerment.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Ayush",
"problem_description": "Background\n\nThe Ayurvedic herbal supply chain in India is characterised by fragmented networks of smallholder farmers, wild collectors and multiple intermediaries, leading to challenges in ensuring consistent quality, authenticity and sustainable sourcing of medicinal plants. Variations in harvesting practices, environmental conditions and manual record-keeping introduce risks of mislabeling, adulteration and over-harvesting of vulnerable species, undermining consumer trust and compliance with regulatory standards. Geographic provenance is often undocumented or opaque, making it difficult for manufacturers and regulators to verify that herbs originate from approved regions or follow sustainable collection guidelines.\n\nA blockchain-based traceability system, augmented with geo-tagging technology, can address these gaps by creating an immutable, decentralised ledger that records every step of the herb's journey—from on-site GPS-tagged collection events through processing, testing and formulation. Smart contracts on a permissioned network (e.g., Hyperledger Fabric) can enforce sustainability criteria and automate quality validations, while IoT-enabled devices capture real-time location and environmental data at remote collection points, even via SMS-over-blockchain gateways where connectivity is sparse. By integrating FHIR-style metadata bundles (e.g., \"CollectionEvent,\" \"QualityTest,\" \"ProcessingStep\") and QR-code scanning at aggregation nodes, stakeholders gain end-to-end visibility, enabling rapid verification of provenance, streamlined certification for export and robust audit trails to support both biodiversity conservation and supply-chain efficiency. When herbs are formulated into finished products, unique, serialised QR codes generated by the blockchain platform could be affixed to each package. End customers scan these codes with a mobile app or web portal—powered by the same blockchain ledger—to retrieve a FHIR-style provenance bundle detailing each upstream event: farm of origin, harvest conditions, intermediary custody, laboratory certificates and batch formulation parameters. This consumer-facing transparency not only verifies authenticity and builds trust, but also supports ethical marketing, enables rapid recall management and fosters incentives for sustainable collection practices by linking premium pricing to verified harvest data. Over time, analytics on consumer scans can feed back into demand forecasting, closing the loop between consumer assurance and supply-chain optimisation.\n\nDescription\n\nA permissioned blockchain network will immutably record every stage of an Ayurvedic herb's journey—from geo-tagged harvest events by farmers or wild collectors, through multi-stage processing and laboratory testing, to the finished product on retail shelves. At the point of collection, GPS-enabled mobile or IoT devices capture precise location, timestamp, collector identity, species identification and initial quality metrics as a \"Collection Event.\" Subsequent \"Processing Step\" and \"Quality Test\" events—each embedding standardised metadata bundles—are added by processing facilities and testing laboratories. Smart contracts enforce National Medicinal Plants Board sustainability guidelines and Good Agricultural and Collection Practices by automatically validating geo-fencing rules, seasonal restrictions and quality thresholds before committing each transaction to the ledger.\n\nWhen formulation is complete, unique QR codes generated on-chain are affixed to product packaging. End customers scan these codes via a lightweight web or mobile portal (no specialised app required) to retrieve the full provenance record: farm coordinates and harvest conditions; chain-of-custody handoffs; lab certificates for moisture, pesticide and DNA-barcode tests; and sustainability and fair-trade compliance proofs. This consumer-facing transparency assures authenticity and safety, enables rapid recall notifications for affected batches and tells the story of each product—complete with interactive maps and farmer or community profiles. By combining tamper-proof audit trails, geo-tagged traceability and automated compliance enforcement, the system delivers a replicable model for ethical, sustainable and trust-driven Ayurvedic herb sourcing.\n\nExpected Solution\n\nParticipants will deliver a proof-of-concept blockchain-based botanical traceability system addressing end-to-end provenance of Ayurvedic herbs. The solution should include the following core components and capabilities:\n\n1. Permissioned Blockchain Network\n• A lightweight, permissioned ledger (e.g., Hyperledger Fabric or Corda) that records every supply-chain transaction.\n• Network nodes representing farmers' cooperatives, wild-collector groups, testing laboratories, processing facilities and manufacturers.\n• Smart contracts enforcing:\n- Geo-fencing rules based on collectors' GPS coordinates and approved harvesting zones.\n- Seasonal-harvest restrictions and species-specific conservation limits per National Medicinal Plants Board guidelines.\n- Quality-gate validations (e.g., moisture thresholds, pesticide limits, DNA barcoding checks).\n\n2. Geo-Tagged Data Capture\n• IoT/GPS-enabled mobile DApp (or SMS-over-blockchain gateway) for collectors to record \"CollectionEvent\" metadata: latitude/longitude, timestamp, collector ID, species and initial quality metrics.\n• Sensor integrations or manual interfaces for \"QualityTest\" events (lab results) and \"ProcessingStep\" events (drying, grinding, storage conditions).\n\n3. Smart Labeling & Consumer Portal\n• On-chain generation of unique QR codes for each finished product batch.\n• A lightweight web/mobile portal (no specialised install required) allowing end customers to scan QR codes and retrieve a complete FHIR-style provenance bundle:\n- Collection location map and harvest details\n- Chain-of-custody handoffs through each supply-chain node\n- Laboratory certificates for moisture, pesticide analysis, DNA authentication\n- Sustainability compliance proofs and fair-trade verifications\n- Interactive farmer/community profiles and conservation credentials\n\n4. Integration & Interoperability\n• RESTful APIs for supply-chain managers to query real-time dashboards of harvest volumes, batch statuses, QA results and sustainability metrics.\n• Plugins or connectors to existing ERP/quality-management systems for seamless data exchange.\n• Use of FHIR-style resource models (CollectionEvent, QualityTest, ProcessingStep, Provenance) for standardized metadata exchange.\n\n5. User Interfaces & Reporting\n• A mobile DApp interface optimized for low-bandwidth rural environments, with offline data capture and SMS synchronization.\n• A web dashboard for stakeholders to monitor network health, query provenance records and generate compliance reports aligned with AYUSH Ministry export and sustainability requirements.\n• Automated reporting modules that compile environmental-impact metrics and conservation compliance data for certification bodies.\n\n6. Demonstration & Evaluation\n• A live pilot using one botanical species (e.g., Ashwagandha) across a small farming cooperative and a collaborating processor.\n• End-to-end demonstration: geo-tagging harvest, adding lab results, processing events, QR code scanning by simulated consumers and recall simulation.\n• Metrics collection on data-capture latency, transaction throughput, offline sync reliability and consumer-scan engagement.\n\nBy delivering these elements, participants will showcase a replicable, transparent and sustainable model for botanical traceability that bridges traditional Ayurvedic sourcing with modern blockchain technology and consumer empowerment.",
"ps_number": "SIH25027",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Blockchain & Cybersecurity",
"title": "Develop a blockchain-based system for botanical traceability of Ayurvedic herbs including geo-tagging from the point of collection (farmers/wild collectors) to the final Ayurvedic formulation label"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Higher Education institutions often face challenges in efficient class scheduling due to limited infrastructure, faculty constraints, elective courses, and overlapping departmental requirements. Manual timetable preparation leads to frequent clashes in classes, underutilized classrooms, uneven workload distribution, and dissatisfied students and faculty members. With the increasing adoption of multidisciplinary curricula and flexible learning under NEP 2020, the class scheduling process has become more complex and dynamic, requiring intelligent and adaptive solutions.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": "The current scheduling mechanism in most higher education institutes/colleges relies on manual input via spreadsheets or basic tools. These fail to account for real-time availability of faculty, room capacity, teaching load norms, subject combinations, and student preferences. A solution is required that will accommodate the various parameters required for scheduling classes for UG and PG students and return an optimized timetable ensuring:\n• Maximized utilization of classrooms and laboratories\n• Minimized workload on faculty members and students\n• Achievement of required learning outcomes\n\nKey Parameters\n\nThe following parameters can be taken into account as variables for creating optimized timetables:\n- Number of classrooms available\n- Number of batches of students\n- Number of subjects to be taught in a particular semester\n- Names of subjects\n- Maximum number of classes per day\n- Number of classes to be conducted for a subject per week / per day\n- Number of faculties available for different subjects\n- Average number of leaves a faculty member takes in a month\n- Special classes that have fixed slots in timetable\n\nStudents may also consider additional variables that may help in effective timetable preparation.",
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "A web-based platform that can be linked to the college website. Authorized personnel will be able to login and input data against the listed variables to generate fully optimized timetables.\n\nThe platform should include:\n• Login facility for authorized personnel to create and manage timetables\n• Multiple options of optimized timetables to choose from\n• Review and approval workflow for competent authorities\n• Suggestions for suitable rearrangements when optimal solutions are not available\n• Support for multi-department and multi-shift scheduling",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Jharkhand",
"problem_description": "Background\n\nHigher Education institutions often face challenges in efficient class scheduling due to limited infrastructure, faculty constraints, elective courses, and overlapping departmental requirements. Manual timetable preparation leads to frequent clashes in classes, underutilized classrooms, uneven workload distribution, and dissatisfied students and faculty members. With the increasing adoption of multidisciplinary curricula and flexible learning under NEP 2020, the class scheduling process has become more complex and dynamic, requiring intelligent and adaptive solutions.\n\nDescription\n\nThe current scheduling mechanism in most higher education institutes/colleges relies on manual input via spreadsheets or basic tools. These fail to account for real-time availability of faculty, room capacity, teaching load norms, subject combinations, and student preferences. A solution is required that will accommodate the various parameters required for scheduling classes for UG and PG students and return an optimized timetable ensuring:\n• Maximized utilization of classrooms and laboratories\n• Minimized workload on faculty members and students\n• Achievement of required learning outcomes\n\nKey Parameters\n\nThe following parameters can be taken into account as variables for creating optimized timetables:\n- Number of classrooms available\n- Number of batches of students\n- Number of subjects to be taught in a particular semester\n- Names of subjects\n- Maximum number of classes per day\n- Number of classes to be conducted for a subject per week / per day\n- Number of faculties available for different subjects\n- Average number of leaves a faculty member takes in a month\n- Special classes that have fixed slots in timetable\n\nStudents may also consider additional variables that may help in effective timetable preparation.\n\nExpected Solution\n\nA web-based platform that can be linked to the college website. Authorized personnel will be able to login and input data against the listed variables to generate fully optimized timetables.\n\nThe platform should include:\n• Login facility for authorized personnel to create and manage timetables\n• Multiple options of optimized timetables to choose from\n• Review and approval workflow for competent authorities\n• Suggestions for suitable rearrangements when optimal solutions are not available\n• Support for multi-department and multi-shift scheduling",
"ps_number": "SIH25028",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "Smart Classroom & Timetable Scheduler"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "With increasing digitization, the problem of fake degrees and forged academic certificates has become a major concern for higher education institutions, employers, and government bodies. Cases of fraudulent documents being used for jobs, admissions, or government schemes have highlighted the absence of a robust mechanism to verify the authenticity of educational credentials issued by colleges and universities.\n\nAt present, verification is often manual, relying on physical inspection, emails to institutions, or outdated databases. This creates delays, inconsistency, and susceptibility to corruption or manipulation. To preserve academic integrity and public trust, there is a pressing need for an efficient, secure, and scalable digital system to detect and prevent the use of fake degrees.\n\nDetailed Description\n\nThe challenge is to create a digital platform that can authenticate and detect fake degrees or certificates issued by higher education institutions across Jharkhand. The system should be able to cross-verify uploaded documents (PDFs, scans, etc.) with institutional databases or credential registries, using metadata, QR codes, signatures, or embedded hashes.\n\nSuch a platform must work with both legacy certificates (issued before digitization) and new ones generated under university ERP systems. It should detect anomalies such as:\n- Tampered grades or photos\n- Forged seals or signatures\n- Invalid certificate numbers\n- Non-existent institutions or courses\n- Duplicate or cloned documents\n\nIncorporating AI, OCR (Optical Character Recognition), and blockchain or cryptographic validation, the platform should enable seamless certificate verification by employers, admission offices, scholarship agencies, and government departments. The goal is to create a trustable and publicly accessible system that protects institutions’ reputation and safeguards student achievements.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "A smart, scalable, and secure Fake Degree/Certificate Recognition system that includes:\n• Upload interface for verifying entities (employers, institutions, agencies) to upload or input certificate details\n• Certificate authenticity checker that:\n – Uses OCR to extract key details (name, roll number, marks, certificate ID)\n – Matches it against a verified database (centralized or decentralized)\n – Flags mismatches or formatting inconsistencies\n• Digital watermark or blockchain verification support for newly issued certificates\n• Institution integration module for universities/colleges to upload their certificate records in bulk or in real-time\n• Admin dashboard for authorized bodies (e.g., Higher Education Department) to monitor verification activity, detect forgery trends, and blacklist offenders\n• Alert system for invalid or forged entries\n• Data privacy and access control measures to ensure secure handling of student information\n\nThis solution must be adaptable across different institutions, work with both physical and digital certificates, and be affordable for state-wide rollout.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Jharkhand",
"problem_description": "Background\n\nWith increasing digitization, the problem of fake degrees and forged academic certificates has become a major concern for higher education institutions, employers, and government bodies. Cases of fraudulent documents being used for jobs, admissions, or government schemes have highlighted the absence of a robust mechanism to verify the authenticity of educational credentials issued by colleges and universities.\n\nAt present, verification is often manual, relying on physical inspection, emails to institutions, or outdated databases. This creates delays, inconsistency, and susceptibility to corruption or manipulation. To preserve academic integrity and public trust, there is a pressing need for an efficient, secure, and scalable digital system to detect and prevent the use of fake degrees.\n\nDetailed Description\n\nThe challenge is to create a digital platform that can authenticate and detect fake degrees or certificates issued by higher education institutions across Jharkhand. The system should be able to cross-verify uploaded documents (PDFs, scans, etc.) with institutional databases or credential registries, using metadata, QR codes, signatures, or embedded hashes.\n\nSuch a platform must work with both legacy certificates (issued before digitization) and new ones generated under university ERP systems. It should detect anomalies such as:\n- Tampered grades or photos\n- Forged seals or signatures\n- Invalid certificate numbers\n- Non-existent institutions or courses\n- Duplicate or cloned documents\n\nIncorporating AI, OCR (Optical Character Recognition), and blockchain or cryptographic validation, the platform should enable seamless certificate verification by employers, admission offices, scholarship agencies, and government departments. The goal is to create a trustable and publicly accessible system that protects institutions’ reputation and safeguards student achievements.\n\nExpected Solution\n\nA smart, scalable, and secure Fake Degree/Certificate Recognition system that includes:\n• Upload interface for verifying entities (employers, institutions, agencies) to upload or input certificate details\n• Certificate authenticity checker that:\n – Uses OCR to extract key details (name, roll number, marks, certificate ID)\n – Matches it against a verified database (centralized or decentralized)\n – Flags mismatches or formatting inconsistencies\n• Digital watermark or blockchain verification support for newly issued certificates\n• Institution integration module for universities/colleges to upload their certificate records in bulk or in real-time\n• Admin dashboard for authorized bodies (e.g., Higher Education Department) to monitor verification activity, detect forgery trends, and blacklist offenders\n• Alert system for invalid or forged entries\n• Data privacy and access control measures to ensure secure handling of student information\n\nThis solution must be adaptable across different institutions, work with both physical and digital certificates, and be affordable for state-wide rollout.",
"ps_number": "SIH25029",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "Authenticity Validator for Academia"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Farmers often face challenges in accessing timely, personalized, and accurate agricultural support. Language barriers, lack of technical knowledge, and limited reach of conventional advisory services reduce the effectiveness of existing solutions. Emerging generative AI technologies present an opportunity to deliver hyper-localized guidance in natural language, paired with visual understanding to assist with field-level problems like crop disease detection.\n\nDetailed Description\n\nThe objective is to create an AI-driven decision support system that determines real-time soil properties (pH, moisture, nutrient content) based on satellite data (e.g., Soil Grids, Bhuvan APIs) or IoT sensors. The system must also account for localized weather forecasts, past crop rotation data to preserve soil fertility, and existing market demand and price trends obtained through APIs or scraping agri-market websites.\n\nA machine learning model will provide the most appropriate crops for specified conditions, forecasting yield, profit margins, and sustainability scores. The solution should comprise a mobile application with a simple multilingual interface where farmers can enter or retrieve relevant data, see recommendations, and operate offline in low-connectivity regions.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "A mobile-based prototype offering farmers customized, science-guided crop advice, increasing income, making resources more efficient, and facilitating sustainable agriculture.\nThe solution should deliver an AI-powered platform that integrates text and image-based interactions tailored for agricultural use. It must support voice and chat interfaces in local languages, enabling farmers to ask questions and receive actionable responses.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Jharkhand",
"problem_description": "Background\n\nFarmers often face challenges in accessing timely, personalized, and accurate agricultural support. Language barriers, lack of technical knowledge, and limited reach of conventional advisory services reduce the effectiveness of existing solutions. Emerging generative AI technologies present an opportunity to deliver hyper-localized guidance in natural language, paired with visual understanding to assist with field-level problems like crop disease detection.\n\nDetailed Description\n\nThe objective is to create an AI-driven decision support system that determines real-time soil properties (pH, moisture, nutrient content) based on satellite data (e.g., Soil Grids, Bhuvan APIs) or IoT sensors. The system must also account for localized weather forecasts, past crop rotation data to preserve soil fertility, and existing market demand and price trends obtained through APIs or scraping agri-market websites.\n\nA machine learning model will provide the most appropriate crops for specified conditions, forecasting yield, profit margins, and sustainability scores. The solution should comprise a mobile application with a simple multilingual interface where farmers can enter or retrieve relevant data, see recommendations, and operate offline in low-connectivity regions.\n\nExpected Solution\n\nA mobile-based prototype offering farmers customized, science-guided crop advice, increasing income, making resources more efficient, and facilitating sustainable agriculture.\nThe solution should deliver an AI-powered platform that integrates text and image-based interactions tailored for agricultural use. It must support voice and chat interfaces in local languages, enabling farmers to ask questions and receive actionable responses.",
"ps_number": "SIH25030",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Agriculture FoodTech & Rural Development",
"title": "AI-Based Crop Recommendation for Farmers"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Local governments often face challenges in promptly identifying, prioritizing, and resolving everyday civic issues like potholes, malfunctioning streetlights, or overflowing trash bins. While citizens may encounter these issues daily, a lack of effective reporting and tracking mechanisms limits municipal responsiveness. A streamlined, mobile-first solution can bridge this gap by empowering community members to submit real-world reports that municipalities can systematically address.\n\nDetailed Description\n\nThe system revolves around an easy-to-use mobile interface that allows users to submit reports in real-time. Each report can contain a photo, automatic location tagging, and a short text or voice explanation, providing sufficient context. These submissions populate a centralized dashboard featuring a live, interactive map of the city's reported issues. The system highlights priority areas based on volume of submissions, urgency inferred from user inputs, or other configurable criteria.\n\nOn the administrative side, staff access a powerful dashboard where they can view, filter, and categorize incoming reports. Automated routing directs each report to the relevant department such as sanitation or public works based on the issue type and location. System architecture accommodates spikes in reporting, ensuring quick image uploads, responsive performance across devices, and near real-time updates on both mobile and desktop clients.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "The final deliverable should include a mobile platform that supports cross-device functionality and seamless user experience. Citizens must be able to capture issues effortlessly, track the progress of their reports, and receive notifications through each stage — confirmation, acknowledgment, and resolution.\nOn the back end, a web-based administrative portal should enable municipal staff to filter issues by category, location, or priority, assign tasks, update statuses, and communicate progress. The platform should integrate an automated routing engine that leverages report metadata to correctly allocate tasks to departments.\nA scalable, resilient backend must manage high volumes of multimedia content, support concurrent users, and provide APIs for future integrations or extensions. Lastly, the solution should deliver analytics and reporting features that offer insights into reporting trends, departmental response times, and overall system effectiveness — ultimately driving better civic engagement and government accountability.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Jharkhand",
"problem_description": "Background\n\nLocal governments often face challenges in promptly identifying, prioritizing, and resolving everyday civic issues like potholes, malfunctioning streetlights, or overflowing trash bins. While citizens may encounter these issues daily, a lack of effective reporting and tracking mechanisms limits municipal responsiveness. A streamlined, mobile-first solution can bridge this gap by empowering community members to submit real-world reports that municipalities can systematically address.\n\nDetailed Description\n\nThe system revolves around an easy-to-use mobile interface that allows users to submit reports in real-time. Each report can contain a photo, automatic location tagging, and a short text or voice explanation, providing sufficient context. These submissions populate a centralized dashboard featuring a live, interactive map of the city's reported issues. The system highlights priority areas based on volume of submissions, urgency inferred from user inputs, or other configurable criteria.\n\nOn the administrative side, staff access a powerful dashboard where they can view, filter, and categorize incoming reports. Automated routing directs each report to the relevant department such as sanitation or public works based on the issue type and location. System architecture accommodates spikes in reporting, ensuring quick image uploads, responsive performance across devices, and near real-time updates on both mobile and desktop clients.\n\nExpected Solution\n\nThe final deliverable should include a mobile platform that supports cross-device functionality and seamless user experience. Citizens must be able to capture issues effortlessly, track the progress of their reports, and receive notifications through each stage — confirmation, acknowledgment, and resolution.\nOn the back end, a web-based administrative portal should enable municipal staff to filter issues by category, location, or priority, assign tasks, update statuses, and communicate progress. The platform should integrate an automated routing engine that leverages report metadata to correctly allocate tasks to departments.\nA scalable, resilient backend must manage high volumes of multimedia content, support concurrent users, and provide APIs for future integrations or extensions. Lastly, the solution should deliver analytics and reporting features that offer insights into reporting trends, departmental response times, and overall system effectiveness — ultimately driving better civic engagement and government accountability.",
"ps_number": "SIH25031",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Clean & Green Technology",
"title": "Crowdsourced Civic Issue Reporting and Resolution System"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "Jharkhand is blessed with natural beauty, tribal culture, historical landmarks, and eco-tourism hotspots like Netarhat, Patratu, Betla National Park, Hundru Falls, and Deoghar. However, despite its vast potential, the state's tourism industry remains underdeveloped due to a lack of digital infrastructure, limited promotional outreach, low tourist awareness, and unorganized travel and hospitality services.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": "Tourists often find it difficult to access reliable information about destinations, local transportation, accommodations, cultural activities, and guides. Additionally, local artisans, tribal communities, and small-scale service providers who could benefit greatly from tourism remain largely excluded from the digital ecosystem. There is a strong need for a centralized digital platform that not only improves the tourist experience through authentic and accessible information but also connects and empowers local communities, making tourism in Jharkhand more inclusive, organized, and sustainable.",
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "Design and develop an AI-powered digital tourism platform (mobile app and/or website) for Jharkhand that offers:\n• AI-based personalized itinerary planning and multilingual chatbot assistance for tourists.\n• Blockchain-enabled secure transactions, guide verification, and digital certification for local service providers.\n• Interactive maps and AR/VR previews of major tourist and cultural sites.\n• Real-time transport and location info using geo-location.\n• Integrated local marketplace for tribal handicrafts, events, homestays, and ecotourism.\n• AI-driven feedback and sentiment analysis for continuous improvement.\n• Analytics dashboard for tourism officials to monitor trends and impact.",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Government of Jharkhand",
"problem_description": "Background\n\nJharkhand is blessed with natural beauty, tribal culture, historical landmarks, and eco-tourism hotspots like Netarhat, Patratu, Betla National Park, Hundru Falls, and Deoghar. However, despite its vast potential, the state's tourism industry remains underdeveloped due to a lack of digital infrastructure, limited promotional outreach, low tourist awareness, and unorganized travel and hospitality services.\n\nDescription\n\nTourists often find it difficult to access reliable information about destinations, local transportation, accommodations, cultural activities, and guides. Additionally, local artisans, tribal communities, and small-scale service providers who could benefit greatly from tourism remain largely excluded from the digital ecosystem. There is a strong need for a centralized digital platform that not only improves the tourist experience through authentic and accessible information but also connects and empowers local communities, making tourism in Jharkhand more inclusive, organized, and sustainable.\n\nExpected Solution\n\nDesign and develop an AI-powered digital tourism platform (mobile app and/or website) for Jharkhand that offers:\n• AI-based personalized itinerary planning and multilingual chatbot assistance for tourists.\n• Blockchain-enabled secure transactions, guide verification, and digital certification for local service providers.\n• Interactive maps and AR/VR previews of major tourist and cultural sites.\n• Real-time transport and location info using geo-location.\n• Integrated local marketplace for tribal handicrafts, events, homestays, and ecotourism.\n• AI-driven feedback and sentiment analysis for continuous improvement.\n• Analytics dashboard for tourism officials to monitor trends and impact.",
"ps_number": "SIH25032",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Travel & Tourism",
"title": "Development of a Smart Digital Platform to Promote Eco & Cultural Tourism in Jharkhand"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "The PM Internship Scheme enables students to gain industry exposure through structured internships. However, matching thousands of applicants with the most suitable opportunities remains a challenge, often leading to suboptimal selections and delays.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": "The problem envisages a smart, automated system that uses AI/ML algorithms to match candidates with internship opportunities based on skills, qualifications, location preferences, and sector interests. The system should also account for affirmative action (e.g., representation from rural/aspirational districts, different social categories), past participation, and internship capacity of industries.",
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "A functional prototype with:\n• AI-based matchmaking engine for internship placement\n• A prototype of the front end demonstrating how this engine will work",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Corporate Affairs",
"problem_description": "Background\n\nThe PM Internship Scheme enables students to gain industry exposure through structured internships. However, matching thousands of applicants with the most suitable opportunities remains a challenge, often leading to suboptimal selections and delays.\n\nDescription\n\nThe problem envisages a smart, automated system that uses AI/ML algorithms to match candidates with internship opportunities based on skills, qualifications, location preferences, and sector interests. The system should also account for affirmative action (e.g., representation from rural/aspirational districts, different social categories), past participation, and internship capacity of industries.\n\nExpected Solution\n\nA functional prototype with:\n• AI-based matchmaking engine for internship placement\n• A prototype of the front end demonstrating how this engine will work",
"ps_number": "SIH25033",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Automation",
"title": "AI-Based Smart Allocation Engine for PM Internship Scheme"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "The PM Internship Scheme receives applications from youth across India, including rural areas, tribal districts, urban slums, and remote colleges. Many of these candidates are first-generation learners with limited digital exposure and no prior internship experience. With hundreds of internships listed on the portal, it becomes difficult for such candidates to identify which ones match their skills, interests, or aspirations. This leads to misaligned applications and missed opportunities.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": "The problem seeks to build a simple, lightweight AI-based recommendation engine that suggests the most relevant internships to each candidate based on their profile, academic background, interests, and location preferences. The system should be user-friendly, mobile-compatible, and work well even for users with low digital literacy. It should offer 3-5 personalized suggestions, instead of a long list, and help candidates make informed choices. The tool must be simple enough to be integrated with the existing PM Internship Scheme portal and must avoid complex or resource-intensive deployment.",
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": "A functional prototype that:\n• Captures basic candidate inputs (education, skills, sector interests, location)\n• Uses a rule-based or ML-light model to suggest 3-5 top internships\n• Has a simple, intuitive UI with minimal text and visual cues\n• Can be accessed on mobile devices and adapted to regional language use\n• Outputs recommendations in a clear, user-friendly format (e.g., cards or simple list)",
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Corporate Affairs",
"problem_description": "Background\n\nThe PM Internship Scheme receives applications from youth across India, including rural areas, tribal districts, urban slums, and remote colleges. Many of these candidates are first-generation learners with limited digital exposure and no prior internship experience. With hundreds of internships listed on the portal, it becomes difficult for such candidates to identify which ones match their skills, interests, or aspirations. This leads to misaligned applications and missed opportunities.\n\nDescription\n\nThe problem seeks to build a simple, lightweight AI-based recommendation engine that suggests the most relevant internships to each candidate based on their profile, academic background, interests, and location preferences. The system should be user-friendly, mobile-compatible, and work well even for users with low digital literacy. It should offer 3-5 personalized suggestions, instead of a long list, and help candidates make informed choices. The tool must be simple enough to be integrated with the existing PM Internship Scheme portal and must avoid complex or resource-intensive deployment.\n\nExpected Solution\n\nA functional prototype that:\n• Captures basic candidate inputs (education, skills, sector interests, location)\n• Uses a rule-based or ML-light model to suggest 3-5 top internships\n• Has a simple, intuitive UI with minimal text and visual cues\n• Can be accessed on mobile devices and adapted to regional language use\n• Outputs recommendations in a clear, user-friendly format (e.g., cards or simple list)",
"ps_number": "SIH25034",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Smart Education",
"title": "AI-Based Internship Recommendation Engine for PM Internship Scheme"
}
|
{
"category": "Software",
"details": {
"ai-based_anomaly_detection": null,
"background": "eConsultation module is an online platform wherein proposed amendments/draft legislations are posted on MCA's website for external users to submit their comments and suggestions pertaining to the same through the MCA21 portal. The comments are captured in a structured format for due consideration with respect to amending the draft legislation, based on the suggestions or observations received.\n\nProblem Statement\n\nThe draft document soliciting comments is made available for a specified period, during which any stakeholder may submit their observations either on the overall amendment or on specific provisions of the draft legislation. In instances where a substantial volume of comments is received on draft legislation, there exists a risk of certain observations being inadvertently overlooked or inadequately analysed. In order to review each individual submission, leveraging AI-assisted tools will help ensure that all remarks are duly considered and systematically analysed. Requirement is the development of an AI model aimed at predicting the sentiments of the suggestions provided by stakeholders in the eConsultation module. It should also generate a visual representation in the form of a word cloud, highlighting the keywords utilised by the stakeholders within their suggestions.\n\nExpected Outcome\n\nThe intention is to discern the feedback received from the stakeholders through the following:\n• Sentiment analysis\n• Summary generation\n• Word cloud\n\nThe solution should considerably reduce the effort of the end user in analysing a high volume of comments. It should be able to clearly identify the sentiments of comments individually as well as broadly overall. The summary generation should be accurate and convey the meaning of the comment properly, in a precise manner. The word cloud feature should showcase the density of the words used by all users.",
"conclusion": null,
"data_privacy_&_security": null,
"deliverables": null,
"description": null,
"digital_tourist_id_generation_platform": null,
"eligibility": null,
"evaluation_criteria": null,
"expected_outcomes": null,
"expected_solution": null,
"impact": null,
"impact___why_this_problem_needs_to_be_solved": null,
"innovative_features": null,
"introduction": null,
"iot_integration_optional": null,
"key_features": null,
"key_performance_parameters": null,
"mobile_application_for_tourists": null,
"multilingual_support": null,
"objective": null,
"problem_description": null,
"relevant_stakeholders___beneficiaries": null,
"supporting_data": null,
"technical_scope": null,
"tourism_department_&_police_dashboard": null
},
"organization": "Ministry of Corporate Affairs",
"problem_description": "Background\n\neConsultation module is an online platform wherein proposed amendments/draft legislations are posted on MCA's website for external users to submit their comments and suggestions pertaining to the same through the MCA21 portal. The comments are captured in a structured format for due consideration with respect to amending the draft legislation, based on the suggestions or observations received.\n\nProblem Statement\n\nThe draft document soliciting comments is made available for a specified period, during which any stakeholder may submit their observations either on the overall amendment or on specific provisions of the draft legislation. In instances where a substantial volume of comments is received on draft legislation, there exists a risk of certain observations being inadvertently overlooked or inadequately analysed. In order to review each individual submission, leveraging AI-assisted tools will help ensure that all remarks are duly considered and systematically analysed. Requirement is the development of an AI model aimed at predicting the sentiments of the suggestions provided by stakeholders in the eConsultation module. It should also generate a visual representation in the form of a word cloud, highlighting the keywords utilised by the stakeholders within their suggestions.\n\nExpected Outcome\n\nThe intention is to discern the feedback received from the stakeholders through the following:\n• Sentiment analysis\n• Summary generation\n• Word cloud\n\nThe solution should considerably reduce the effort of the end user in analysing a high volume of comments. It should be able to clearly identify the sentiments of comments individually as well as broadly overall. The summary generation should be accurate and convey the meaning of the comment properly, in a precise manner. The word cloud feature should showcase the density of the words used by all users.",
"ps_number": "SIH25035",
"s_no": 0,
"submitted_ideas_count": 0,
"theme": "Miscellaneous",
"title": "Sentiment analysis of comments received through E-consultation module"
}
|
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