Edge-AI-Powered IoT System for Real-Time Water Quality Monitoring and Intelligent Aquatic Environment Assessments

This project presents an Edge AI–powered IoT system for real-time water quality monitoring and intelligent aquatic environment assessment. The proposed system integrates an Arduino-based control unit with multiple sensors, including a pH sensor for acidity/alkalinity detection, a TDS sensor for measuring dissolved solids, a turbidity sensor for evaluating water clarity, and a DHT11 sensor for temperature monitoring. An LCD module is used to display real-time sensor readings locally, while IoT connectivity enables continuous data transmission to a cloud platform for remote monitoring and storage. Edge AI techniques are incorporated to process sensor data locally and apply machine learning models for predictive analysis, enabling early detection of water quality degradation and potential contamination. The system reduces latency, enhances decision-making, and minimizes dependence on cloud-only processing. This intelligent framework supports applications in aquaculture, environmental monitoring, and smart water management systems by providing accurate, real-time insights into aquatic conditions.