IoT and AI-Based Water Quality Monitoring System

This project develops an intelligent water quality monitoring system using a turbidity sensor to measure suspended particle levels in water. The system integrates with an IoT platform to provide real-time monitoring and remote access to turbidity data.

AI algorithms analyze the collected data to detect trends, identify anomalies like sudden increases in turbidity, and provide predictive insights into water quality changes. This system is ideal for applications in environmental monitoring, wastewater management, and industrial processes. A mobile app allows users to visualize real-time turbidity levels, receive alerts, and generate reports for effective decision-making.

Key Features:

• Accurate measurement of water turbidity levels with IoT-based monitoring.
• AI-powered anomaly detection and predictive water quality analysis.
• Cloud integration for long-term data storage and trend visualization.
• Mobile app for live data access, alerts, and detailed reporting.

This project includes source code, complete hardware setup, detailed analysis, and a comprehensive 200-page project report in soft copy, making it an excellent choice for students working on IoT and AI in environmental and industrial monitoring.