Intelligent Water Quality Assessment System For Industrial Regions : Integrating Sensors, IoT and Random Forest Classification

This paper focuses on the development of an intelligent water quality assessment system that integrates sensors, Internet of Things (IoT) technology, and random forest classification. Water quality assessment plays a crucial role in safeguarding public health and environmental sustainability. Traditional methods often suffer from limitations such as time-consuming manual sampling and analysis processes. In response, this project proposes a novel approach leveraging colorimetric paper sensors and IoT connectivity to assess water quality. The collected data are then processed using the random forest classification algorithm to classify water quality levels and identify potability of the water sample. The integration of these technologies enables proactive and automated monitoring, facilitating timely interventions and decision-making for water management authorities. Through the implementation of this intelligent system, it is anticipated that water quality monitoring processes will become more efficient, accurate, and cost-effective, ultimately contributing to the protection of human health and the environment.