INTERNET OF THINGS ENABLED PRECISION FARMING FOR OPTIMUM CATFISH PRODUCTION: A CASE STUDY OF UNCLE B’S FARM, ONDO STATE

Abstract

Internet of Things (IoT) is an evolving paradigm concentrating on linking devices to each other and to the users. This technology is aimed at bringing convenience, security, and efficiency into day-to-day activities, including farming. Fish has been identified as a great source of animal protein for a large percentage of the world population. Huge amount of money is spent on catfish production to meet daily needs. Its production processes are hindered due to some factors such as stocking density, feeding rate, feed quality, time of feeding, and water quality. In other to achieve optimum production of catfish, a solution through the use of wireless sensors network was deployed to monitor the production processes. Information retrieved from the wireless sensors were used to track optimal feeding temperature (26℃−28℃) for the fish and feed were administered to the fish at that particular temperature of the day. Other parameters of the fish pond such as pH, turbidity, and conductivity were also monitored on timely basis through the developed mobile application. The final mean weights of the fish cultured in both control and experimental pond are 42g and 45g respectively, while the corresponding values of specific growth rate of both ponds were 65.1 and 69.72 respectively for the culture period. An optimal average temperatures range of 27.000℃− 32.589℃ were recorded during the culture period. A lower Feed Conversion Ratio (FCR) of 0.62 indicating that a good feed to flesh conversion was recorded in the experimental pond aided with the IoT-based precision farming system. The study further showed that the deployed system supports the farmers in designing a feeding pattern that supports optimum growth of catfish, it also provides a platform through which farmers can have access to the status of the pond anywhere in the world. The study revealed strong correlation between water quality parameters of the pond and weekly mean weight gain of fish, and confirmed that temperature and pH are the largest contributing water parameters to weekly fish weight gain.