Development of a Raw Water Quality Detection System Prior for Municipal Drinking Water Treatment and Sustainable Environmental Management

Abstract

Variations in raw water quality can reduce the effectiveness of municipal drinking water treatment processes, making early-stage monitoring prior to treatment essential for sustainable environmental management. This study aims to develop and validate a raw water quality detection system based on an ESP32 microcontroller for real-time measurement of pH, temperature, and turbidity. The research employed an engineering Research and Development (R&D) approach, including system design, sensor calibration, laboratory testing, and field validation. The study was conducted from January to March 2025 in Indramayu Regency, Indonesia, with field testing carried out on river water, seawater, rainwater, and groundwater sources. Measurement accuracy was evaluated by comparing sensor readings with laboratory reference instruments, and accuracy values were calculated based on percentage error and correlation analysis. The results show that the system achieved accuracy levels between 96% and 98%, with correlation coefficients (R²) greater than 0.9, indicating strong agreement with reference measurements. River water exhibited the highest turbidity value (86.4 NTU), while rainwater showed the lowest pH value (6.3), reflecting distinct environmental characteristics of each water source. Overall, the developed system demonstrated stable performance under real environmental conditions and can function as a low-cost and reliable early detection tool for raw water quality prior to treatment, with potential to support sustainable water resource management.