Developing an embedded system for aquaculture water quality control for increased yields of Nile tilapia farming in Uganda.

Abstract

Fish farming thrives in Uganda, where artificial systems like ponds, tanks, and aquaria are widespread for commercial fish cultivation. However, manual wastewater management and feeding practices pose challenges. Although some farmers have automated aerations in aquariums, these are often uncontrolled, operating continuously. Maintaining water freshness becomes challenging due to unexpected fluctuations in crucial water quality parameters, impacting fish growth and causing economic losses for farmers. To address these challenges, an Embedded Aquaculture Water Quality Control and Fish Feeding System was developed that simultaneously combated real-time deterioration in water quality and optimized fish feeding. This provided an all-in-one solution, considering real-time monitoring on web applications, automated precise feeding, water quality optimization, and data-driven insights. It is more comprehensive compared to existing uncontrolled aquarium systems, surpassing even semi-automated systems adopted elsewhere that focus solely on automating individual modules. Recognizing poor feeding practices' contribution to increased waste, the system mitigated such effects, preventing water quality decline. Using a sensor network to monitor pH, dissolved oxygen, temperature, and turbidity, the microcontroller activated devices like water pumps, aerators, and heaters to stabilize water quality within 19.125 milliseconds. The water quality sensor unit linked to an automated feeding chamber ensured precise feeding based on scheduled intervals, relevant parameters, fish life stage, and tank fish population. Proven effective for Tilapia fish, the system maintained optimal water conditions with pH ranging from 6-8.5, temperature of 25oC-28°C, Dissolved Oxygen of 3mg/L-7mg/L, and water turbidity of 0-500 NTU. Real-time remote monitoring through a web application reduced the need for constant supervision, enhancing stocking density and production efficiency. Quantitative methods, analysing Feed Conversion Ratios, Growth Rate, and Weight Gained, regulated feeding and minimized errors. Recommendations included implementing industrial sensors for accuracy, and considering solar panels for power backup. This system offered a comprehensive solution for sustainable and efficient fish farming in Uganda.