Development of an AI and IOT based system that detects the exact quantity of eggs laid on a poultry farm
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This project report constitutes of the introduction, literature review, the project plan which comprises of the methodology, the references and the appendix that has the budge and tools used. Keeping poultry makes a substantial contribution to household food security and nutritional development and also help diversify income returns as its waste is a fertilizer source for crop growth and it’s the most popular type of livestock in East Africa. For Uganda, there has been significant presence of egg count inefficiency on several poultry farms leading to loses which has affected the steady progress of most poultry farms. This project focused on addressing the challenge of inefficiencies in egg count on most farms. The objective was to design and develop a low cost IoT and AI based system to detect any egg laid by a poultry bird on a farm. The project involved the design and implementation of a prototype that consists of two systems that is the raspberry pi 4 with components connected to it and the cloud server control system. The raspberry pi 4 system has connected a pi camera to capture frames of eggs laid and sends it in form of bytes to the cloud server for processing and Liquid Crystal display (LCD) display to show the count of any egg laid from the data sent from the cloud to display the eggs in the captured frame. The cloud server system carries out the processing of data received from the raspberry pi 4 for the AI model trained that was exported there in the virtual environment developed and process it and sends feedback. The project emphasised the importance of the AI and IoT technologies in proper farm output products management remotely providing real-time results and accurate information which help reduce on the inefficiencies in the farm results. Future work includes; be able to monitor other poultry bird parameters such as temperature to check the health of each birds improving their welfare, further integration of this system with inventory management systems to provide a more comprehensive view of egg production and also scale up to work up to larger farms maintaining same level of accuracy. The project outcomes aimed at enhancing the farm’s resilience, manage egg production inefficiencies, reduce on resources wastage and improve the profitability due to accurate monitoring.