🌡️ TooHot2Handle

Inspiration

As an EMT, I’ve witnessed people collapse from heat exhaustion before help arrived. Those moments inspired us to build TooHot2Handle — an AI-powered platform designed to prevent heat-related deaths before they happen.


What It Does

TooHot2Handle uses real-time satellite and weather data to detect dangerously hot zones, predict who’s most at risk, and guide users to safety.
It provides:

  • Personalized heat risk alerts
  • Shaded route recommendations using AI-analyzed satellite maps
  • Locations of nearby cooling centers and hydration stations
  • Voice-guided safety updates through ElevenLabs

How We Built It

  • Frontend: JavaScript + Next.js for a smooth, responsive UI
  • Backend: Node.js connected to a local database for managing user profiles and alerts
  • AI & Data Integration:
    • Gemini API — analyzes live weather, health, and risk data
    • ElevenLabs API — converts AI insights into real-time spoken alerts
    • Satellite data — used to identify shaded vs. sun-exposed walking routes through AI image analysis

Challenges We Ran Into

  • Integrating multiple APIs (Gemini, ElevenLabs, satellite mapping) while keeping latency low
  • Maintaining real-time accuracy for route and heat-risk prediction
  • Balancing user privacy, limited hardware resources, and fast response times

Accomplishments We’re Proud Of

  • Built a working prototype that merges emergency awareness, live data, and AI navigation
  • Achieved accurate shade-route prediction using satellite image models
  • Created a fully accessible experience through voice-guided instructions

What We Learned

  • Learned how AI and public health can intersect to save lives
  • Improved our API integration, data handling, and machine learning skills
  • Understood the importance of accessibility and speed in emergency technology

What’s Next for TooHot2Handle

  • Collaborate with EMS departments and city agencies for pilot testing
  • Scale our model using national heat, air quality, and population density datasets
  • Introduce humidity and AQI-based risk prediction
  • Deploy mobile and web apps for real-world emergency use

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