Development of smart water quality monitoring system using ESP32 based sensors for sustainable environmental management

Wong, Jia Heng (2023) Development of smart water quality monitoring system using ESP32 based sensors for sustainable environmental management. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Water quality is paramount for environmental sustainability and human well-being, serving as a cornerstone for healthy ecosystems, sustainable development, and public health protection. However, this critical resource faces escalating threats from pollution, population expansion, and climate fluctuations. Conventional water quality monitoring systems are often prohibitively expensive, complex, and limited in scope, impeding their widespread adoption and accessibility. To confront these challenges head-on, this study endeavors to design and implement a smart water quality monitoring system utilizing the ESP32 microcontroller. This system will possess the capability to accurately measure crucial parameters such as pH, temperature, and turbidity. Additionally, a centralized data management infrastructure will be established to efficiently store, process, and analyze the gathered data, facilitating the identification of trends, patterns, and anomalies in water quality. Moreover, the system will integrate a monitoring mechanism to promptly alert users to abnormal readings, thereby enhancing responsiveness and proactive management. Methodologically, the research will draw upon reputable sources, such as the IEEE website, and employ pH, temperature, and turbidity sensors in conjunction with the ESP32 microcontroller. Real-time observation and monitoring will be facilitated through the utilization of the Blynk.io platform. This study aspires to make significant contributions toward the development of effective and accessible water quality monitoring systems, addressing the urgent need for sustainable water resource management and the protection of public health. Furthermore, the analysis of the table reveals distinct characteristics of various water samples. Sample 4 has the lowest pH and highest turbidity, closely followed by Sample 3. In contrast, Sample 1 has the lowest turbidity and a safe pH level of 7.25. The presence of acidic and cloudy water near residential areas poses dangers like infrastructure corrosion and environmental harm, necessitating actions like drainage improvements and intensified monitoring. Sample 3, from a stream for human waste, raises concerns due to acidity and potential contaminants. Similarly, Sample 4, from the Malacca River, shows unsafe pH and turbidity levels likely due to pollution. Sample 5, from Lake Ayer Keroh, also has acidity and cloudiness, impacting the ecosystem and aesthetics. All samples maintain a consistent temperature of around 27°C. Overall, the project has achieved its objectives successfully, but it could be further enhanced by incorporating additional sensors to augment water quality measurement capabilities.

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