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IoT-Based Real-Time Monitoring and Control of Well Water Filtration

Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro · Vol. 9 No. 2 (2025) · hlm. 179–187

DOI
10.22373/dqdhmc22
ISSN
2549-3701, 2549-3698
Terbit
2025-08-18
Penerbit
PTE FTK UIN Ar-Raniry
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Controlling a well water filtration system via the internet is a modern solution in the industry 4.0 era to ensure optimal filter performance. This study aims to develop an IoT-based system to monitor and control well water filtration by measuring inlet and outlet pressures. The system uses two pressure sensors, one turbidity sensor, and five solenoid valves to regulate the filtration, backwashing, and rinsing processes. All components are integrated with a NodeMCU ESP32 microcontroller. The IoT user interface was developed using the Blynk application on an Android smartphone, which allows real-time monitoring and automatic notification when filter performance decreases. Experimental trials were conducted by gradually injecting turbid water with varying turbidity levels (low, medium, high) into the filter. The results showed that filter clogging caused an increase in inlet pressure and a decrease in outlet pressure. The backwashing and rinsing processes can be activated via a smartphone when the inlet pressure increases by 24%–45% and the outlet pressure decreases by 37%–72%. The turbidity of the filtered water remained within the range of 0.14–0.19 NTU, which is still below environmental health standards. This demonstrates that the developed IoT-based filtration system is effective for real-time monitoring and control of well water quality.

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Sumber metadata: OAI-PMH (metadata jurnal) https://jurnal.ar-raniry.ac.id/index.php/circuit/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">IoT-Based Real-Time Monitoring and Control of Well Water Filtration</dc:title>
	<dc:creator xml:lang="en">Fitriady, Fitriady</dc:creator>
	<dc:creator xml:lang="en">Fakhruddin, Fakhruddin</dc:creator>
	<dc:creator xml:lang="en">Safwan, Safwan</dc:creator>
	<dc:creator xml:lang="en">Effendi, Effendi</dc:creator>
	<dc:subject xml:lang="en">IoT Control</dc:subject>
	<dc:subject xml:lang="en">Water Filtration System</dc:subject>
	<dc:subject xml:lang="en">Real-time Pressure Monitoring</dc:subject>
	<dc:subject xml:lang="en">Backwash and Rinse</dc:subject>
	<dc:subject xml:lang="en">Turbidity Sensor</dc:subject>
	<dc:subject xml:lang="en">Instrumentation and Control</dc:subject>
	<dc:description xml:lang="en">Controlling a well water filtration system via the internet is a modern solution in the industry 4.0 era to ensure optimal filter performance. This study aims to develop an IoT-based system to monitor and control well water filtration by measuring inlet and outlet pressures. The system uses two pressure sensors, one turbidity sensor, and five solenoid valves to regulate the filtration, backwashing, and rinsing processes. All components are integrated with a NodeMCU ESP32 microcontroller. The IoT user interface was developed using the Blynk application on an Android smartphone, which allows real-time monitoring and automatic notification when filter performance decreases. Experimental trials were conducted by gradually injecting turbid water with varying turbidity levels (low, medium, high) into the filter. The results showed that filter clogging caused an increase in inlet pressure and a decrease in outlet pressure. The backwashing and rinsing processes can be activated via a smartphone when the inlet pressure increases by 24%–45% and the outlet pressure decreases by 37%–72%. The turbidity of the filtered water remained within the range of 0.14–0.19 NTU, which is still below environmental health standards. This demonstrates that the developed IoT-based filtration system is effective for real-time monitoring and control of well water quality.  </dc:description>
	<dc:publisher xml:lang="en">PTE FTK UIN Ar-Raniry</dc:publisher>
	<dc:date>2025-08-18</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.ar-raniry.ac.id/index.php/circuit/article/view/29894</dc:identifier>
	<dc:identifier>10.22373/dqdhmc22</dc:identifier>
	<dc:source xml:lang="en">Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro; Vol. 9 No. 2 (2025); 179-187</dc:source>
	<dc:source>2549-3701</dc:source>
	<dc:source>2549-3698</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jurnal.ar-raniry.ac.id/index.php/circuit/article/view/29894/11910</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Fitriady, Fakhruddin, Safwan, Effendi</dc:rights>
	<dc:rights xml:lang="en">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>