IoT and ML in Liquid Waste Water Management

Rapid urbanization, industrial discharge, and erratic water usage patterns, managing liquid wastewater is a major environmental and public health challenge. Real-time changes in water quality and flow conditions are frequently too rapid for the manual observation, laboratory testing, and operator skill that form the basis of traditional wastewater systems. This study demonstrates how wastewater monitoring, treatment effectiveness, and reuse planning can be enhanced by combining machine learning (ML) with the Internet of Things (IoT). While machine learning algorithms help with overflow prevention, prediction, and anomaly detection, IoT sensors provide continuous monitoring including pH, turbidity, dissolved oxygen, nutrients, pollutants. A clever system that combines wireless communication, cloud/edge processing, sensor networks, and machine learning algorithms for automated decision-making is also covered in the article. Furthermore, for scalable and sustainable liquid waste management systems, innovative techniques like edge AI, federated learning, biodegradable sensors, and circular water economy integration are prioritized.