NIYIBIZIJoseph/TerraNexus-Rwanda

this project is the green based conservation in rwanda and it include the detection and reforestation 🌿 TERRANEXUS RWANDA AI-Driven Environmental Monitoring & Reforestation Platform 📌 1. PROJECT OVERVIEW TerraNexus Rwanda is a distributed environmental intelligence system designed to monitor, analyze, and respond to ecological threats across Rwanda. The system integrates: .Ground-based IoT sensor nodes .Long-range LoRa communication .AI-based risk analysis .Drone orthomosaic mapping .Cloud storage and database infrastructure .Web-based visualization dashboard Its purpose is to provide early detection of floods, landslides, soil degradation, and deforestation while supporting data-driven reforestation and environmental restoration initiatives. 🎯 2. OBJECTIVES The main objectives of TerraNexus Rwanda are: .Detect early signs of landslides using soil tilt and vibration data. .Monitor river water levels to predict flood risks. .Analyze drone imagery to detect vegetation loss and degraded land. .Provide real-time environmental risk scoring. .Deliver SMS-based alerts to communities during emergencies. .Enable coordinate-based reforestation planning. .Provide subscription-based environmental intelligence reports. .Support public offices in identifying critical intervention zones. 🛠 3. TECHNOLOGY The system is built using a multi-layer architecture: .Embedded Systems .ESP32 microcontroller .C++ (Arduino framework) .RadioLib for LoRa communication .AI & Data Processing .Python .OpenCV for image analysis .Risk scoring algorithms .Predictive flood modeling .Communication .LoRa (Long Range, low power) .GSM module for SMS alerts 💻 4. FRONTEND The web interface is developed using: .React.js .Leaflet.js for map visualization .Coordinate-based area selection .Interactive dashboard .Risk-level color coding .User subscription system The frontend communicates with backend APIs via REST endpoints and displays: .Environmental risk reports .Drone orthomosaic imagery .Real-time monitoring data .Historical analysis results 🧠 5. BACKEND The …