The Development of a Water Quality Control System for Tilapia Farming Using IoT-LoRa

Cage-based tilapia farming is highly affected by rapid variations in water quality, particularly variations in dissolved oxygen (DO), which can lead to mass fish mortality and significant economic losses. To address this challenge, in this study, an internet of things (IoT)- and LoRa-based water quality monitoring and control system is proposed, designed for real-time aquaculture management. The developed prototype enables peer-to-peer communication among distributed control nodes for continuous monitoring of dissolved oxygen, pH, and water temperature. Measured data are transmitted remotely and integrated with automated oxygen pump control through a mobile application, allowing timely intervention without continuous on-site supervision. To mitigate sensor degradation caused by prolonged submersion, an automatic probe lifting mechanism was incorporated into the system, significantly reducing biofouling and sensor drift. The experimental results show that this mechanism improves measurement accuracy, achieving a dissolved oxygen RMSE of 0.186, which is substantially lower than that of a continuously submerged sensor. Evaluation of communication performance confirms reliable LoRa transmission with a 100% packet delivery rate over distances up to 1,600 m, maintaining positive signal-to-noise ratios and RSSI values above receiver sensitivity. Detection latency analysis demonstrates sub-second response times for both single- and multi-hop configurations, sufficient for timely aeration control. Evaluation by five specialists yielded a high average performance score of 4.11, while post-implementation satisfaction assessments involving 20 tilapia farmers indicated an average score of 4.48, confirming the system’s effectiveness, reliability, and suitability for practical deployment in cage-based tilapia farming.