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

Aliyu Abubakar, Mutari Hajara Ali, Tijjani Hassan Darma

Abstract


This paper presents an advanced state feedback controller designed to optimize various parameters in a poultry production environment, including temperature, CO2 concentration, humidity, light intensity, feeding, watering, and health monitoring. Poultry production systems are increasingly using digital twin technology and IoT automation to enhance productivity and ensure optimal conditions within modular cage systems. The challenge lies in maintaining ideal environmental and operational conditions for poultry growth within modular cages. These conditions are affected by multiple variables that need to be precisely controlled and monitored to ensure maximum production efficiency and animal welfare. A state feedback controller is implemented to manage and control key parameters in the poultry production system. The system's dynamics are modeled, and the state feedback controller is designed to adjust inputs based on the observed state of the system. MATLAB simulations are used to validate the controller’s effectiveness in maintaining desired conditions. The implementation of the state feedback controller demonstrates significant improvements in managing temperature, CO2 levels, humidity, light intensity, feeding, watering, and health of poultry. The results indicate a high degree of stability and performance in achieving the set points for each parameter, providing the set point values of temperature as 25℃, humidity 60%, CO2 500ppm, light intensity 800lux, feeding level 30kg, watering level 50 liters, and health status of poultry at 90%. The state feedback controller provides a robust solution for maintaining optimal conditions in poultry production, leading to enhanced productivity, better animal welfare, and efficient management of resources.


Full Text:

PDF

References


Bhardwaj, U. (2024). IOT Based Framework for Poultry Farm Monitoring and its Benefits. International Journal of Research Publication and Reviews 5(3), 2680–2684.

Corkery, G., Ward, S., Kenny, C., & Hemmingway, P. (2013). Monitoring environmental parameters in poultry production facilities. In Computer Aided Process Engineering, CAPE Forum 2013, Graz University of Technology, Austria, 7-10 April 2013. Institute for Process and Particle Engineering, Graz University of Technology, Austria.

Dinrifo, R. R., & Abatan, E. O. (2023). Smart Poultry Farming using Internet of Things (IoT). Laspotech Journal of Scientific, Engineering and Technology Research, 2(February), 10–17. www.laspotechjsetr.com.

Europe, A. (2021). Using Digital Twin for Decision Support in RAS Feeding Processes. 818036.

Gbadamosi, A. S. (2020). Cloud-Based IoT Monitoring System for Poultry Farming In Nigeria. Arid Zone Journal of Engineering, Technology & Environment, 16(March), 100–108.

Goud, K. S., & Sudharson, A. (2015). Internet based smart poultry farm. Indian Journal of Science and Technology, 8(19), 1–5. https://doi.org/10.17485/ijst/2015/v8i19/76227

Hailegebreal, G., Molla Tanga, B., Woldegiorgis, W., Sulayeman, M., & Sori, T. (2022). Epidemiological investigation of morbidity and mortality of improved breeds of chickens in small holder poultry farms in selected districts of Sidama Region, Ethiopia. Heliyon, 8(8), e10074. https://doi.org/10.1016/j.heliyon.2022.e10074

Kocaman, B., Esenbuga, N., Yildiz, A., Laçin, E., & Macit, M. (2006). Effect of environmental conditions in poultry houses on the performance of laying hens. International Journal of Poultry Science, 5(1), 26–30. https://doi.org/10.3923/ijps.2006.26.30

Petri, I., Rezgui, Y., Ghoroghi, A., & Alzahrani, A. (2023). Journal of Industrial Information Integration Digital twins for performance management in the built environment. Journal of Industrial Information Integration, 33(February), 100445. https://doi.org/10.1016/j.jii.2023.100445

Zhu, X., Li, D., He, D., Wang, J., Ma, D., & Li, F. (2010). A remote wireless system for water quality online monitoring in intensive fish culture. Computers and Electronics in Agriculture, 71, S3-S9.

https://doi.org/10.1016/j.compag.2009.10.004


Refbacks

  • There are currently no refbacks.