Prototype Monitoring and Controlling of Wastewater Treatment Plant (WWTP) on IoT-Free Output Channels
Prototype Monitoring dan Controlling Instalasi Pengolahan Air Limbah (IPAL) pada Saluran Output Berbasis IoT
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(1) * Iswanto Iswanto
Widyagama University Malang
Indonesia
(2) Fachrudin Hunaini Widyagama University Malang
Indonesia
(3) Dedi Usman Effendy Widyagama University Malang
Indonesia
(*) Corresponding Author
Abstract
The largest water pollution occurs due to the disposal of waste from the industrial sector, while some of it comes from the household sector. In the labor-intensive industrial sector and the household sector, domestic liquid waste is generated. The high level of liquid waste pollution can be overcome by using a wastewater treatment plant (WWTP). Wastewater parameters according to research that has been done, namely pH, Turbidity, and Ammonia are very important parameters and the main priority for the quality of wastewater discharged into the environment. In this study, a prototype monitoring and controlling WWTP on the output channel was designed by measuring wastewater parameters and an Internet of Things (IoT) based pump output control system. This prototype is programmed with 2 mode options, namely auto mode where the controlling system works based on program commands with target limits, namely pH 6 – 9, Turbidity < 300 NTU, and Ammonia < 20 PPM, if the wastewater measurement value is on target, the system activates the outgoing pump. for direct disposal to the environment. Meanwhile, if it does not meet the target, the system activates the treatment pump to return the wastewater back to the WWTP. Then the manual mode, which is the controlling system, works by operating the operator directly to activate the outgoing or treatment pump on a smartphone using the Blynk application. In Auto and Manual mode, wastewater parameters can be monitored on a smartphone using the Blynk application. All sensors used have been calibrated with 2 calibrator solutions. The calibration results show an error value of 0.115 for the pH sensor, an error value of 0.075 for the Turbidity sensor, and an error value of 0.115 for the Ammonia sensor.
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Copyright (c) 2023 Iswanto Iswanto, Fachrudin Hunaini, Dedi Usman Effendy
This work is licensed under a Creative Commons Attribution 4.0 International License.
