Water Quality Monitoring System for Temperature, pH, Turbidity, DO, BOD, and COD Parameters Based on Internet of Things in Garang Watershed

• Published in: Ecological Engineering & Environmental Technology Vol. 25; no. 2; pp. 1 - 16
• Main Authors: Syafrudin, Syafrudin, Sarminingsih, Anik, Juliani, Henny, Budihardjo, Mochamad Arief, Puspita, Annisa Sila, Auliya Arlin Mirhan, Shafa
• Format: Journal Article
• Language: English
• Published: Polish Society of Ecological Engineering (PTIE) 2024
• Subjects: internet of things; monitoring system; swmm; water quality index
• ISSN: 2719-7050; 2719-7050
• DOI: 10.12912/27197050/174412

Water has recently become a final disposal site for wastewater. Land use has evolved with the global population growth and is generally transformed into settlements and industrial areas. These land use changes could potentially increase wastewater generation from both domestic and non-domestic activities. The Garang watershed, one of the watersheds in Central Java, flows through the Semarang Regency, Kendal Regency, and Semarang City. This study analyzed the water quality conditions in the Garang watershed and designed a real-time water quality monitoring system. The methods used in this study included SWMM modeling, the National Sanitation Foundation Water Quality Index (NSF-WQI), and the Internet of Things. Samples were collected from 10 points in the Garang Watershed, with a sampling frequency of five times at each point. The results of the data analysis demonstrated that the differences in land use resulted in different water parameter levels. The results of the SWMM modeling demonstrated an acceptable model value (NOF between 0 and 1). On the other hand, the WQI analysis results demonstrated that the quality status at the Garang watershed is "medium" at nearly all location points. The designed real-time water quality sensor tool successfully transmitted water quality data online and in real-time, particularly for temperature, pH, turbidity, and DO. This water quality monitoring system offers a variable percentage error value, with the pH sensor ranging between 0.16% and 9.86% and the temperature sensor ranging between 0.64% and 1.72%.