Muhammad Saqib Bukhair, Syed Muhammad Tufail, Sikander Sultan, Mubashir Zafar Ansari
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Development of Cloud-based Water Quality Monitoring System
Water quality is paramount for sustaining life and maintaining ecological balance. However, traditional monitoring methods often must improve by providing real-time and comprehensive information. The developed systems show a cloud-based water quality monitoring system that overcomes the drawbacks of conventional approaches. The system allows numerous users to collect, store, and retrieve real-time data by combining sensors, an ESP32 microcontroller, Google Firebase Cloud, and a mobile application. The prototype illustrates the viability of using cloud computing to monitor water quality accurately and thoroughly. This effort advances the field by highlighting water quality is importance to supporting ecosystems and life. It highlights the system's contribution to allowing proactive decision-making and quick solutions to water quality challenges while outlining potential directions for future advancements in sensor calibration, testing in various water bodies, and cutting-edge data analytics methods. The cloud-based system for monitoring water quality has uses in various fields, such as environmental management, public health, and water resource conservation. It makes it easier to make educated decisions and take preventative action to preserve water quality and sustainability.
期刊介绍:
Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.