Untreated laundry wastewater contributes to environmental pollution, with TSS levels reaching 600 mg/L, far above the 100 mg/L limit set by East Java Governor Regulation No. 72 of 2013. This research develops an IoT-enabled automated wastewater treatment systemutilizing the ESP32-S3 microcontroller, integrated with pH, TSS, and temperature sensors, and featuring real-time monitoring via theThingsBoard platform. A DC motor serves as an actuator for chemical dosing and mixing, controlled by sensor feedback. The system serves small-scale laundry businesses with limited access to centralized treatment. Testing showed 100% effectiveness in reducing TSS and 95% in stabilizing pH. Data transmission delays averaged 4 seconds for turbidity and 5 seconds for pH. Processing effectiveness was evaluated based on regulatory compliance, with 71% classified as Feasible, 5% as Very Feasible, and 19% as Less Feasible. Whilecalibration and reliability improvements are necessary, the system demonstrates potential to assist local laundries in meetingenvironmental standards. Future work will focus on enhancing sensor accuracy and implementing fault-tolerant control.
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