Digital Twin Enabled IoT Automation System for Monitoring and Control of Poultry Production in a Modular Cage System
Poultry production in modular cage systems requires precise control over environmental conditions such as temperature, humidity, and feed levels to ensure optimal growth and health of the birds. However, traditional monitoring and control systems often struggle with the variability and uncertainties inherent in such systems, leading to suboptimal conditions and potential production losses. The primary challenge in poultry production within modular cages is maintaining stable environmental conditions despite fluctuations and disturbances. The aim of this study is to develop an advanced monitoring and control system that integrates a sliding mode observer (SMO) with digital twin and IoT technologies to enhance the stability and accuracy of environmental control in poultry production within modular cage systems. The proposed system employs a digital twin model to simulate and optimize key environmental parameters in the modular cage system. A sliding mode observer is designed to provide robust state estimation, handling uncertainties and disturbances effectively. IoT devices are integrated to collect real-time data, which is then used by the digital twin and SMO to maintain optimal conditions within the cage system. The implementation of the digital twin and SMO-based control system demonstrated significant improvements in maintaining stable environmental conditions. Performance metrics such as state estimation accuracy and system responsiveness were substantially enhanced compared to traditional methods. Real-world testing confirmed that the system could effectively manage environmental variables and improve poultry production efficiency. The integration of SMO with digital twin and IoT technologies offers several benefits, including improved accuracy in state estimation, enhanced system stability, and more effective control of environmental conditions, contributing to better poultry health and productivity while reducing potential losses and improving overall system efficiency.
Download Paper