An Intelligent Detection System for Water Safety Identifying Foreign Organisms

This work offers an intelligent detection system for water safety in identifying harmful foreign organisms that exist in water sources, like lizards and insects. It uses a real-time monitoring of the water body through an ESP32-camera module and deep learning algorithms. The embedded unit captures images and uses convolutional neural networks (CNN) to distinguish foreign organisms from debris based on characteristics such as size, shape, and movement. This water level monitoring system supports user-friendly interfaces that show the real-time and access of history while the mechanism to alert is custom to use in different applications. Applications for this system are its uses in household water tanks, public reservoirs, as well as aquaculture systems. It is, therefore, useful in integration with sensors TDS and pH when using in water quality monitoring due to its comprehensive features being able to act proactively on preventing safety threats on water.