Clustering-Based Water Quality Exploration and Visualization in Municipal Water Supply

Monitoring water quality is paramount in the mission to guarantee the provision of safe and high-quality municipal water supply. This study shows an exploration of water quality data collected from municipal water supply systems using sensors. The main objective of this research is to employment cluster analysis, precisely the Elbow Method, to decide the optimal number of clusters (k) for alignment water quality data. The dataset comprises records of Total Dissolved Solids (TDS), pH levels (Potential of Hydrogen), and temperature over a period of time. Our target is to gain visions into the heterogeneity of water quality in municipal supply systems by exploring these clusters, which will eventually inform water treatment strategies and public health policies. This paper provides a foundation for the imagining of water quality patterns within municipal water supplies. It also contributes to the understanding of water quality dynamics.