Digital Twin-Enabled IoT Automation System for Monitoring and Control of Poultry Production in a Modular Cage System using Fuzzy Logic Controller

Aliyu Abubakar, Mutari Hajara Ali, Tijjani Hassan Darma

Abstract


This paper presents the utilization of a digital twin-enabled IoT automation system in conjunction with a fuzzy logic controller to enhance the management of poultry production in a modular cage system. The effective monitoring and control of poultry production systems are vital for optimizing productivity and ensuring the health of the poultry. Traditional control methods often struggle to cope with the complexity and nonlinearity of such systems. Poultry production environments involve multiple variables such as temperature, humidity, light intensity, feeding, watering, and health management, each with complex interdependencies. Traditional control approaches may not adequately address these complexities, leading to suboptimal performance. We implemented a fuzzy logic controller within a digital twin-enabled IoT automation framework to manage and control various parameters of the poultry production system. The fuzzy controller was designed to handle the nonlinear relationships between system inputs and outputs, adapting to changes in environmental conditions and system states. The fuzzy logic controller effectively managed temperature, humidity, light intensity, feeding, watering, and health parameters, improving system performance. Results showed that the controller-maintained parameters within desired ranges more effectively compared to traditional control methods. The proposed system enhances the ability to manage complex poultry production environments, leading to improved productivity and better health outcomes for the poultry. The fuzzy logic controller provides flexibility and adaptability to changing conditions, making it a valuable tool for modern poultry management.


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References


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