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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Chafsah, Anis Mahmuda
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Computer Science & IT Engineering

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Greywater treatment system based on fuzzy logic control Pratama, I Putu Eka Widya; Ridha, Muhammad Rasyid; Chafsah, Anis Mahmuda; Hija, Akhmad Ibnu; Zaine, Siti Nur Azella
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i6.pp4643-4651

Abstract

Greywater from households and public facilities represents a major source of untreated wastewater, carrying high microbial loads and variable chemical composition that threaten environmental and public health. Conventional treatment systems often lack adaptive control mechanisms capable of handling the dynamic fluctuations of greywater quality. This study presents the design and validation of an intelligent greywater treatment system that integrates real–time sensing with a Sugeno fuzzy logic controller to regulate pump and solenoid valve operation. The system continuously monitors pH, total dissolved solids (TDS), dissolved oxygen (DO), and ammonia (NH3), and dynamically adjusts treatment cycles based on sensor feedback. Experimental deployment demonstrated significant improvements in effluent quality, with pH reduced from 9.04 to 8.08, TDS from 611.04 ppm to 393.96 ppm, and NH₃ from 0.52 ppm to 0.19 ppm, while DO increase from 2.52 mg/L to 6.07 mg/L. These results confirm that fuzzy logic–based control enhances system responsiveness and ensures effluent compliance under variable influent conditions. The proposed framework provides a scalable, cost-effective solution for decentralized wastewater management, advancing the development of intelligent treatment technologies for sustainable urban water systems.
Co-Authors Hija, Akhmad Ibnu Muhammad Rasyid Ridha Pratama, I Putu Eka Widya Zaine, Siti Nur Azella