SIH26181: A secure, AI-powered Personal Health Companion that delivers real-time, privacy- — SIH 2026 | Wynit

SIH26181: A secure, AI-powered Personal Health Companion that delivers real-time, privacy- — SIH 2026 | Wynit

What they'll ask you

14

Generated from the brief's own wording and the competition's published rules, never from a guess about what this ministry prefers.

Which specific wearable hardware or sensor types must be supported?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
What accuracy thresholds are required for anomaly and fall detection?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Which exact APIs or formats should be used for environmental data integration?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.

11 morethe ones a panel gets to if there is time

Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.
The brief asks for continuous health monitoring. How would you build that?
Decoded from SIH26181 itself: Monitors heart rate, SpO2, body temperature, activity levels, and sleep quality while tracking baseline health patterns. The brief asks for it by name.
The brief asks for ai anomaly detection. How would you build that?
Decoded from SIH26181 itself: Runs on-device AI inference to detect abnormal vital signs, heat stress, dehydration, fatigue, and respiratory issues. The brief asks for it by name.
The brief asks for disaster health alerts. How would you build that?
Decoded from SIH26181 itself: Generates warnings for heat waves, air quality, floods, cyclones, and extreme weather risks. The brief asks for it by name.
The brief asks for edge ai processing. How would you build that?
Decoded from SIH26181 itself: Processes all sensitive health data locally on the device to ensure privacy and offline functionality. The brief asks for it by name.
The brief asks for emergency assistance. How would you build that?
Decoded from SIH26181 itself: Detects falls or medical distress automatically and sends SOS alerts to caregivers or emergency contacts. The brief asks for it by name.
The brief asks for personal wellness dashboard. How would you build that?
Decoded from SIH26181 itself: Displays daily health summaries, risk scores, and personalized recommendations for hydration and rest. The brief asks for it by name.
Where does your data come from: a published source, one you collect, or one you generate?
No dataset is attached to this problem statement, so sourcing it is part of the work and nobody told you that.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: evaluators will check if all data processing happens locally on the device without cloud dependence, whether the app functions entirely offline, and if it correctly identifies specific risks like heat stress and respiratory distress from sensor inputs.
This is the evaluator read for your problem statement, decoded from the brief's own wording.

The government's original description (532 words)

Background India faces recurring public health challenges during and after disasters such as heat waves, floods, cyclones, air pollution events, disease outbreaks, and extreme weather conditions. Heat stress, dehydration, respiratory illnesses, cardiovascular complications, and delayed access to healthcare are common during such events. Rural populations, elderly citizens, outdoor workers, and people with chronic medical conditions are particularly vulnerable. Climate-related hazards are increasing in frequency and intensity, creating a need for continuous, personalized health monitoring that can function even when connectivity and healthcare access are disrupted. Advances in edge AI now enable wearable devices and mobile phones to analyze health data locally, providing real-time insights while preserving user privacy and operating without constant cloud connectivity. Local AI processing can support health monitoring in remote and underserved areas where internet access may be limited. Description Develop a Personal Health Companion, a privacy-preserving wearable or mobile application that continuously monitors an individual's physiological and environmental data and uses on-device AI to detect potential health anomalies in real time.The solution should analyze data from sensors such as heart rate, blood oxygen (SpO?), body temperature, activity levels, sleep patterns, and environmental conditions. The system should identify early indicators of heat stress, dehydration, respiratory distress, abnormal vital signs, fatigue, falls, and other health risks that may be exacerbated during disasters and environmental emergencies.All sensitive health data should be processed locally on the device to maximize privacy, minimize latency, and ensure continuous operation even during network outages. The application should provide actionable alerts, wellness recommendations, and emergency notifications while allowing users to maintain control over their personal health information. Edge AI approaches provide faster responses, improved privacy, and offline functionality. Expected Solution The proposed solution should implement some or all of the following: 1. Continuous Health Monitoring • Monitor heart rate, SpO?, body temperature, activity levels, and sleep quality. • Track changes in baseline health patterns. • Generate personalized wellness indicators. 2. AI-Based Health Anomaly Detection • Detect abnormal heart rate patterns. • Identify indicators of heat stress, dehydration, fatigue, and respiratory issues. • Recognize sudden changes that may require medical attention. • Provide risk assessments using on-device AI inference. 3. Disaster-Specific Health Alerts • Heat-wave exposure warnings. • Air-quality and respiratory-risk alerts. • Flood and cyclone-related health advisories. • High-risk notifications for vulnerable individuals during extreme weather events. 4. Environmental Awareness • Integrate data from local temperature, humidity, and air-quality sensors. • Assess environmental conditions that may affect health. • Generate personalized recommendations based on local risks. 5. Privacy-Preserving Edge AI • Perform all health analysis locally on the device. • Minimize transmission of sensitive personal information. • Operate effectively with intermittent or no internet connectivity. • Maintain user control over data sharing. 6. Emergency Assistance Features • Automatic detection of falls or medical distress. • SOS alerts to caregivers or emergency contacts. • Location-enabled emergency assistance when permitted by the user. 7. Personal Wellness Dashboard • Daily health summaries and trend analysis. • Risk scores for heat, respiratory, and cardiovascular stress. • Personalized recommendations for hydration, rest, activity, and medical consultation. 8. Scalable Deployment • Support smartphones, smartwatches, fitness bands, and specialized healthcare wearables. • Suitable for individual consumers, healthcare providers, disaster-response agencies, and public health programs.