https://github.com/mihiraggarwal/smokescreen
Personal air and fire awareness dashboard
https://github.com/mihiraggarwal/smokescreen
aqi fire
Last synced: 3 months ago
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Personal air and fire awareness dashboard
- Host: GitHub
- URL: https://github.com/mihiraggarwal/smokescreen
- Owner: mihiraggarwal
- Created: 2025-06-25T18:32:03.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-06-30T14:02:37.000Z (4 months ago)
- Last Synced: 2025-06-30T14:47:17.240Z (4 months ago)
- Topics: aqi, fire
- Language: TypeScript
- Homepage: https://smokescreen-live.vercel.app
- Size: 2.83 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# SmokeScreen
SmokeScreen is a personal air and fire awareness dashboard. It shows you where fires are burning nearby, how they might affect your air quality, and what precautions you should take — all in real time.
## Why It Matters
Fires are one of the biggest contributors to air pollution — especially during harvest seasons in South Asia. But while AQI numbers are everywhere, fire data has remained hidden — locked behind satellite systems and technical dashboards most people never see.
SmokeScreen changes that. It makes real-time fire data visible, understandable, and personal. You can finally see where fires are burning near you, how far they are, and whether you need to take precautions today.
## Who This Is For
This platform is designed for everyday citizens, students, commuters, and health-conscious users who want to know: "What's burning near me?" and "Should I go outside today?"
## What It Does
- Shows active fire locations on a live map using NASA VIIRS satellite data
- Fetches real-time AQI and displays localized air quality levels
- Predicts fire risk in your area using a machine learning model trained on weather and satellite data
- Explains the causes behind high AQI, such as wind direction or nearby fires
- Gives actionable daily advice: whether to mask up, stay indoors, or enjoy clean air
- Includes a conversational assistant to answer any further questions## Where The Data Comes From
- Fires: VIIRS satellite data from NASA FIRMS
- AQI: Sourced from API Ninjas
- Weather: Wind, rainfall, and temperature from Open-Meteo
- Predictions: Trained XGBoost model using satellite + weather data## Tech Stack
- Frontend: Next.js, Typescript, Tailwind, Leaflet.js
- Backend: FastAPI
- ML Model: XGBoost
- Feature Extraction: Google Earth Enging
- LLM Integration: Google Generative AI API
- Hosting: Vercel + Render