Development of a Low-Cost TDS Sensor Using an Electric Plug with The Curve Fitting Method Approaches

Suwandi, Bondan; Istianto, Yuki; Nugroho, Budi; Taufik, Nashrullah; Azhari, Siswayudi; Astawa, I Made; Marianto, Fajar Adi; Ma'arif, Riky Alam; Hanifa, Rizky

doi:10.1109/icramet56917.2022.9991206

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…Through real-time monitoring and alerts, coupled with Wi-Fi-enabled control via the ESP822 module, the system promises enhanced management capabilities, ensuring the health and productivity of the aquaponic setup. Research for managing water quality in treatment plants has intensified due to its substantial potential to enhance operational efficiency, ensure regulatory compliance, and improve overall water treatment effectiveness [16][17][18]. Simultaneously, research efforts [19][20][21][22][23][24][25][26][27][28][29][30] have concentrated on refining water management control.…”

Section: Introductionmentioning

confidence: 99%

Smart Aquaponics: An Automated Water Quality Management System for Sustainable Urban Agriculture

Kok,

Kusuma,

Koh

et al. 2024

Electronics

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As the demand for high-quality food rises, especially amidst the COVID-19 pandemic and the continuous development of society meaning that people demand to eat well, ensuring food security has become increasingly urgent. Agricultural technology is evolving, with aquaponic systems emerging as a promising solution to urban food needs. However, these systems present challenges, such as maintaining optimal water quality and minimizing environmental control errors. In this study, we propose a comprehensive approach combining a literature review and controlled experiments. Through the literature review, the recent findings on water management and sustainability in food production were analyzed, providing crucial insights for enhancing aquaponic system performance. Building on this, a series of experiments were conducted to develop and test a water quality management system using PID control. The integration of PID control showed good performance and reduced errors in SIMULINK, and we applied three controls to manage the stability and responsiveness of the aquaponic system. The optimal values obtained from the controller of the vegetable tank system were 4,706,691,503 and −174.418; for the fish tank, they were 36,167, 0.00126, and −174.418; and for the heater system, they were 4.761, 0.0488, and −31.88. This solution is expected to be responsive and provide stable control over various variables.

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