AI-Powered Multi-Agent Urban Flash Flood Detection & Emergency Response System
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Updated
Jul 25, 2026 - TypeScript
AI-Powered Multi-Agent Urban Flash Flood Detection & Emergency Response System
This project uses SENTINEL-1/2 machine learning for flood extent and depth estimation, with cross-scene generalisation and explainable AI, to detect extent and depth of flooding in South Yorkshire (Fishlake and Bentley/Toll Bar), during flood events of 2019 and 2021.
This Arduino project deploys two servos, a moisture sensor, and a buzzer for flood detection. Upon surpassing a set moisture threshold, the system raises a bridge, triggering a buzzer. The bridge lowers when the flood subsides, enhancing flood response capabilities.
This project is to test a simple and a diverse approch to make use of clusters for identify or detect water level in an image using unsupervised learning(K-Mean clustering) instead of object detection model or masking model, which by the way were tested but the result optained was not good enough.
Real-time IoT flood monitor with dashboard using ESP8266.
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