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PS 26181HARDWAREMedTech / BioTech / HealthTechHeavy R&D

A secure, AI-powered Personal Health Companion that delivers real-time, privacy-preserving health monitoring and early warning capabilities, helping individuals recognize health risks before they become emergencies. The solution should improve resilience during heat waves, floods, pollution events, and other disasters common in India while enabling continuous health support through on-device intelligence.

Qualcomm IncQualcomm Inc
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30-Second Plain English Summary

Patients with chronic cardiovascular and metabolic diseases in India suffer sudden fatal cardiac events (arrhythmias, heart attacks) because standard smartwatches only record passive fitness metrics and upload sensitive biometric data to commercial cloud servers with delayed analysis. Build a Secure, Real-Time AI Personal Health Companion for Qualcomm Inc running on Qualcomm Snapdragon Wear platforms that performs on-device ECG arrhythmia classification (Atrial Fibrillation, PVCs), continuous blood pressure estimation, and automated emergency SOS dispatch with zero cloud latency.

5-Dimension Strategic ScorecardOverall Score: 4.3 / 5.0
Innovation
4.6 / 5
36h Feasibility
3.9 / 5
Uniqueness
4.3 / 5
Jury Appeal
4.8 / 5
Tech Depth
4 / 5
Recommended System Architecture Pipeline
Wearable ECG & PPG Sensors -> Motion Artifact Denoising Filter -> Qualcomm Snapdragon Wear NPU (1D-CNN) -> Qualcomm Secure Enclave -> Emergency Haptic & SOS Dispatch
Hardware Bill of Materials (BOM) & Cost BreakdownEstimated component unit economics in Indian Rupee (INR)
Prototype Unit Cost:3,800
ComponentSpecificationQtyEst. Cost
Nordic nRF52840 Ultra-Low-Power BLE 5.3 SoC64MHz ARM Cortex-M4F with hardware cryptographic engine for local private health processing1750
MAX30102 High-Sensitivity PPG Heart Rate & Pulse Oximeter ModuleIntegrated dual-wavelength optical sensor for continuous SpO2 and pulse wave analysis1280
MLX90614 Non-Contact Medical Infrared Skin Temperature SensorFactory calibrated ±0.2°C precision sensor detecting early fever and heat exhaustion onset1850
Bosch BMA400 Ultra-Low Power 3-Axis AccelerometerContinuous activity monitoring, sleep stage tracking, and emergency fall detection (sub-4uA)1260
Sensirion SHT31 Ambient Temperature & Relative Humidity SensorMeasures local environmental heat index to provide proactive dehydration/heat-stroke warnings1420
0.96-inch Sunlight-Readable Monochrome OLED DisplayHigh contrast visual interface for immediate vital readouts and SOS trigger alerts1240
3.7V 350mAh Curved Li-Po Battery with Qi Wireless Charging CoilProvides 5-day continuous biometric tracking per charge cycle1650
Biocompatible Hypoallergenic Silicone Wristband CaseErgonomic water-resistant wearable enclosure with magnetic quick-release strap1350
Power Input: 3.7V DC Rechargeable Li-Po (5-Day Runtime)
Form Factor: Sleek 44x36mm Medical-Grade Wearable Wristband
Architecture & Prototyping Strategy: Two-tier presentation strategy: (1) Hackathon Tabletop MVP (~₹1k–₹1.5k) with ESP32 + MAX30102 + DHT11 displayed on smartphone via BLE; (2) Medical Disaster Health Band (~₹3.8k) with Nordic nRF52840, MLX90614 medical IR temp, BMA400 fall detection, Qi wireless charging, and 5-day battery life.
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Official Government Problem Description
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.
AI & PPT Citation Format

Smart India Hackathon 2026 Problem Statement PS-26181: "A secure, AI-powered Personal Health Companion that delivers real-time, privacy-preserving health monitoring and early warning capabilities, helping individuals recognize health risks before they become emergencies. The solution should improve resilience during heat waves, floods, pollution events, and other disasters common in India while enabling continuous health support through on-device intelligence.", Ministry: Qualcomm Inc. Strategy & Architecture via SIH ONE (https://sihone.pages.dev/ps/26181)

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