IOT Monitoring Systems in Fish Farming Case Study:” University of Rwanda Fish Farming and Research Station (Ur-FFRs)”

Purpose: Fish farming refers to the farming of aquatic organisms such as fish. It involves cultivating freshwater and saltwater populations under controlled conditions. The purpose of this research is to provide a solution to the fish farmer by developing an application that would be easy to monitor water quality during the fish farming process. This will help the fish farmers to intervene timely, and therefore increase their production. The design and implementation of IoT Monitoring Systems in Fish farming helps to observe the farming system remotely by using different sensors for the water parameters. The research focused on developing a system for real time monitoring of culture tank water quality as a proof of concept and testing the basic functionalities of the system. Methodology: The research adopted the Rapid application methodology, which was deemed best due to its iterative approach to applications development as it also delivers systems faster at a lower cost in time-constrained projects. This methodology was suitable for our research given the time constraints in developing the application. Secondary data was used to determine the water quality aspects that require monitoring. Interviewing the operators of the culture tank also provided information on what should be incorporated in the model. by developing an application that would be easy to monitor water quality during the fish farming process. The application dashboard is the graphical user interface that the users shall use to interact with application components. Findings: This research proposes a solution, which is a real-time culture tank (hatchery) water quality-monitoring model, which utilizes a web application that shall be adopted by the staff of the University of Rwanda Fish Farming and Research Station and farmers. The model utilizes the IoT concept, which enables information gathering about water quality through the corresponding sensors. The status of the water quality aspects shall then be relayed on a real-time basis through a cloud platform. The farmer can then act based on the information provided, or the model can act on the farmer's behalf based on predetermined actions. The model's data can be extracted and analysed in a variety of different ways. Recommendations: This research contributed in developing a technological solution for real time monitoring water quality aspects of culture tank (hatchery) that can  be adopted by fish farmers in Rwasave Fish Farming and Research Station by providing them with real time data whenever they are within or away from the culture tank (hatchery) site. This  helps to eliminate or minimize the risk of losing fish and wastages due late interventions.it was validated by supervisors of the project.