IoT-Based Smart Water Quality Monitoring and Analysis System: Analysis Using AI Algorithms with Field Data
$ 42.5
Description
Water is essential for human survival. Most infectious diseases are transmitted through contaminated water, resulting in millions of deaths annually. Thus, it is necessary to establish a monitoring system to assess if the water quality is adequate for the intended purposes. This study describes the design and development of a portable real-time water quality monitoring system based on Machine Learning and the Internet of Things (IoT). Moreover, the system consists of multiple sensors for detecting physical and chemical properties of water, including pH, Total Dissolved Solids (TDS), Turbidity, Electric Conductivity (EC), and Temperature. The ESP32 microcontroller processes the measured values from the sensors, and it interacts with the cloud-based interface. In this regard, this system was formed through supervised machine learning while utilizing a binary classification method. Consequently, the data set was split into two categories with one thousand data points.