AeroShield

Hyperlocal environmental intelligence platform fusing satellite, radar & bioacoustic data to map urban heat islands, safeguard outdoor workers, and deliver street-level disaster warnings.

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Inspiration

Standard citywide weather apps give one generic average temperature for a whole city, but that doesn't show what's happening on the ground. A concrete-heavy market road can easily hit 8–12 degree higher than a nearby park. On top of that, satellite data and environmental metrics are usually buried in heavy academic jargon that regular citizens or outdoor workers can't quickly use. I built AeroShield to fix this. It brings satellite imagery, weather radar, and ground-level signals together into a simple hexagonal grid map that gives real-time heat alerts, worker safeguards, and early disaster warnings in plain language.

What it does

  • Space-to-Ground Data Fusion: Combines satellite telemetry, Doppler radar, air quality, and ground bioacoustics into a live spatial grid.
  • Locality Health & Canopy Index: Tracks ward-level temperature stress and uses Sentinel-2 vegetation trends to highlight urban heat islands.
  • Worker Heat Safeguard: Calculates real-time heat strain for outdoor workers like delivery riders and street vendors, complete with countdown rest timers.
  • Bioacoustic Early Warning Mesh: Listens to regional bird activity data to catch sudden biodiversity silences that often signal incoming severe storms.
  • Green Eco-Shield Routing: Shows nearby cooling sanctuaries like parks with estimated temperature drops and navigation routes.

How we built it

  • Frontend & Map UI: Built with React, TypeScript, Tailwind CSS, and Leaflet.js to handle the custom hexagonal locality overlay smoothly.
  • Data Pipelines: Integrated API feeds from ISRO Bhuvan, Copernicus Sentinel-2, IMD Doppler Weather Radar, CPCB SAFAR-India, and eBird.
  • Engine & Logic: Formulated custom heat index calculations and real-time processing to convert raw environmental metrics into simple risk statuses.

Challenges we ran into

  • Handling Mixed Data Feeds: Pulling data from satellites and ground sensors meant dealing with totally different update frequencies and spatial scales.
  • Translating Complex Metrics: Raw vegetation indices like NDVI don't mean much to everyday users, so turning those into simple actionable alerts took a lot of UI fine-tuning.
  • Map Performance: Rendering dynamic spatial hexagonal layers on top of real-time map controls without making the app feel laggy.

Accomplishments that we're proud of

  • Successfully unifying satellite, radar, air quality, and bioacoustic signals into one functional dashboard.
  • Building a practical tool focused directly on protecting vulnerable outdoor workforces from heatstroke.
  • Creating a clean, readable UI that turns complex spatial telemetry into actionable alerts.

What we learned

  • How to process multi-source Earth observation feeds and display them effectively on a web map.
    • How bioacoustic patterns like sudden bird silences can act as early physical indicators for micro-climate shifts.
    • How crucial it is to design environmental tools around human-centric workflows rather than just raw numbers.

What's next for AeroShield

  • IoT Ground Array: Setting up low-cost micro-environmental sensors in high-risk pilot wards.
  • Model Calibration: Using real physical ground data to refine satellite heat island predictions.
  • City-Level Integration: Expanding the platform for municipal teams to help target urban re-greening and micro-flood management.

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