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All Journal Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Widi Aribowo
Department of Electrical Engineering, Faculty of Vocational Studies, Universitas Negeri Surabaya, Surabaya, Indonesia
Computer Science & IT Engineering Mechanical Engineering Transportation

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Control of DC Motor in Laundry Liquid Waste Treatment based on ESP32-S3 and Thingsboard Platform Benediktus Arisona Bao; Widi Aribowo; Ayusta Lukita Wardani; Aditya Chandra Hermawan
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.41371

Abstract

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.
The Conceptual Understanding of Metaheuristic Algorithms: A Brief Reviews Widi Aribowo
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 1 (2026)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i1.46163

Abstract

Metaheuristic algorithms have garnered significant attention in the field of optimization due to their ability to address complex, nonlinear, and combinatorial problems where conventional exact methods are often impractical. Inspired by natural phenomena, social behaviors, and physical processes, these algorithms provide near-optimal solutions within reasonable computational time by balancing exploration and exploitation. This paper presents a comprehensive review of metaheuristic algorithms, categorizing them into single-solution-based and population-based approaches. It further discusses hybrid and adaptive variants designed to overcome limitations such as premature convergence and parameter sensitivity. The study highlights the advantages, disadvantages, and practical applications of various metaheuristics across diverse domains including engineering, logistics, artificial intelligence, energy systems, and bioinformatics offering researchers a structured guide for selecting appropriate algorithms based on problem characteristics.
Co-Authors Aditya Chandra Hermawan Ayusta Lukita Wardani Benediktus Arisona Bao