TerrainSentinel

A smart, drone-based landslide detection and early warning system. Built using HTML, CSS, and JavaScript — this code simulates real-time risk zones, visualizes past data from CSV, python for data analysis and uses data procured by the TerrainSentinel drone[Our hardware].

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TerrainSentinel - Landslide Detection & Early Warning System

TerrainSentinel is a smart, drone-based system designed to detect landslide risks and provide early warnings using aerial survey data, AI/ML analytics, and real-time environmental inputs.

What This Project Does Displays simulated landslide risk zones on a map (India).

Shows real-time alerts based on mock data.

Allows users to simulate safe paths through affected zones.

Visualizes past landslide events from a CSV data file.

Project Structure File Purpose index.html Main page showing live landslide risk simulation past_data.html Table-based view of historical landslide data products.html Information about the drone system, technologies used, and system flow style.css Styling for all pages (modern, minimal UI) script.js Contains simulation logic, risk updates, and path finder landslide_simulation_data.csv Mock CSV with past landslide events

Technologies Used Frontend: HTML, CSS, JavaScript, Python

Visualization: Simulated alerts, path simulator, interactive tables

Backend Logic : Python, AI/ML risk classification, IMD API integration

Tools: Plotly, Folium, Matplotlib (for prototype data processing)

System Workflow (Planned Hardware) Drone flies over terrain collecting LiDAR, camera, and weather data

Data is preprocessed and sent to analysis modules

AI/ML models identify high-risk zones

Alerts and maps are generated and served via this platform

Credits Developed by Team Critical Visual Tech