AI-IoT based Water Quality Forecasting and Pollution Trend Analysis

Access to clean water is essential for healthy communities and thriving ecosystems worldwide. However, water pollution is becoming an increasingly urgent challenge, with consequences for both people and the environment. Traditionally, checking water quality has been a slow, manual, and costly process that often fails to provide ongoing insight. In this study, we introduce an IoT-driven water quality monitoring system that uses artificial Intelligence to deliver timely and actionable information. To evaluate water quality, the system continuously monitors acidity, transparency, and mineral content using sensor units, and the gathered readings are sent to the cloud where they are processed and interpreted. AI models then interpret the information, identify any irregularities, and forecast possible pollution events. The findings are presented through an intuitive dashboard that shares real-time alerts and visual summaries, making the system accessible and practical for decision-makers. By moving beyond conventional laboratory-based testing, this solution scales easily and enables a faster response to pollution risks. Integrating IoT monitoring with AI-powered analytics helps communities manage water resources sustainably and respond quickly to contamination threats.