Smart India Hackathon (SIH) Project Demo: ThermoScope
Problem Statement Code: SIH26162
Organization: National Technical Research Organisation (NTRO)
Theme: Disaster Management

Welcome to the walkthrough of ThermoScope — an AI-powered geospatial monitoring platform developed for SIH26162. ThermoScope integrates NASA FIRMS thermal anomaly data, OpenStreetMap (OSM) infrastructure layers, and satellite imagery to automatically detect, classify, and isolate industrial fires and persistent thermal sources from natural forest fires.

Core Features:
• Thermal Anomaly Detection: Real-time ingestion and spatial clustering of thermal hotspot data from NASA FIRMS.
• AI/ML Source Classification: Differentiates industrial heat signatures from forest fires and natural thermal sources.
• Interactive GIS Dashboard: Map-based web interface with layered overlays for monitoring industrial infrastructure risks.
• Spatial Analysis & Risk Scoring: Cross-references hotspot coordinates with OSM facility databases for rapid disaster response.

Tech Stack:
• Core Languages & Analytics: Python, Machine Learning Models (Scikit-Learn / PyTorch)
• Geospatial & Data Science: NASA FIRMS API, GeoPandas, OpenStreetMap (OSM) Data
• Frontend / Dashboard: React / Leaflet GIS Map Visualization
• Backend Services: Python (FastAPI / Flask)

Project Resources:
• Source Code (GitHub Repository): https://github.com/Sammmyyyyyyy/ThermoScope
• Official Problem Statement: SIH26162 (Disaster Management Category)

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