AI-Powered Multi-Hazard Early Warning, Human Detection and Environmental Intelligence System

AI-Powered IoT Digital Twin for Multi-Hazard Prediction, Early Warning, Human Detection and Rescue Support.This project proposes an AI-Powered IoT Digital Twin for Multi-Hazard Prediction, Early Warning, Human Detection and Rescue Support, integrating IoT sensors, LoRa-based wireless communication, AI/ML, sensor fusion, cloud computing and Digital Twin technology. Distributed sensors monitor rainfall, water level, temperature, smoke/gas, soil moisture and ground movement. Sensor data is transmitted through LoRa to a gateway, where AI-based sensor fusion estimates hazard probability and predicts the progression of floods, fires and landslides. Cloud computing enables centralized data storage, historical analysis, remote monitoring and access to the Digital Twin from anywhere. A dynamic Digital Twin visualizes hazard intensity and spatial risk zones while generating risk scores and early warnings. mmWave/radar sensors support human-presence detection and approximate localization during emergencies. The system also incorporates what-if simulation, explainable AI, sensor-fault detection and rescue prioritization. Local processing can support essential monitoring and alerts during internet outages, improving system reliability and emergency response.