Smart Water Quality Management System: A Case Study of Tharparkar Region
DOI:
https://doi.org/10.21015/vtse.v13i1.2084Abstract
In this paper, we present the design and implementation of a smart water quality monitoring system for the Tharparkar region of Pakistan, where access to clean water is limited. The system utilizes Internet of Things (IoT) sensors and machine learning algorithms to assess and predict water quality. Parameters such as pH, turbidity, and total dissolved solids were continuously monitored using IoT sensors deployed in three strategically selected groundwater wells in Tharparkar. The collected data was transmitted wirelessly to a central server, where a Support Vector Regression model was applied to analyze water quality trends and classify samples as polluted or unpolluted. The results demonstrate the system's effectiveness in providing accurate, timely, and location-specific information, enabling early detection of contamination, and supporting proactive water resource management. This work highlights the potential of integrating IoT and artificial intelligence to address water scarcity and quality challenges in an underdeveloped region.
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