Article, PLC Application in Smart Livestock: Design and Operation of Automatic Control Systems
PLC Application in Smart Livestock: Design and Operation of Automatic Control Systems
DOI:
https://doi.org/10.65273/hhit.jna.2025.1.011Keywords:
Agricultural IoT, Environmental sensors, High-tech livestock, Livestock automation, Programmable Logic Controller, Smart controlAbstract
In the context of digital transformation in agriculture, this study proposes a novel PLC-based smart livestock management system that integrates multi-gas environmental sensing, automatic control, and cloud-based remote monitoring into a unified architecture. Unlike existing approaches that focus mainly on single-parameter monitoring or manual intervention, the proposed system incorporates a wireless sensor network capable of simultaneously measuring temperature, humidity, light intensity, wind speed, and critical gases (oxygen (O₂), carbon monoxide (CO), carbon dioxide (CO₂), and ammonia (NH₃)) to comprehensively assess barn microclimate conditions. Based on real-time sensor data, a Programmable Logic Controller (PLC) executes automatic and semi-automatic control strategies to regulate ventilation, cooling, lighting, and roof mechanisms, ensuring stable and safe environmental conditions for livestock. Furthermore, a cloud-connected platform enables remote supervision, data storage, scenario-based operation, and real-time alerts via web and mobile applications, enhancing operational flexibility and management efficiency. The system was deployed and evaluated in a commercial poultry farm in Hung Yen, Vietnam, where experimental results demonstrated improved microclimate stability, reduced labor costs, and increased poultry survival rates compared to traditional farming practices. These findings confirm the novelty, feasibility, and scalability of integrating PLC-based automation with multi-gas sensing and cloud technologies, offering a cost-effective and practical solution for modern smart livestock farming..
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[1] A. Fernandes, J. Dorea, G. M. Rosa (2020) Image Analysis and Computer Vision Applications in Animal Sciences: An Overview. Froniers in Veterinary Science. 7:551269. Doi: 10.3389/fvets.2020.551269
[2] J. J. Valletta, C. Torney, M. King, A. Thornton, J Madden (2017) Applications of machine learning in animal behaviour studies. Animal Behaviour, 16-00718. Doi: 10.1016/j.anbehav.2016.12.005
[3] P. Vardhan, A. Badavath, P. Srivalli (2025) Artificial intelligence and its applications in agriculture: A review. Environment Conservation Journal, 26(1):274-280. Doi:10.36953/ECJ.28802904
[4] B. Jiang, W. Tang, L. Cui, X. Deng (2023) Precision Livestock Farming Research: A Global Scientometric Review. Animals, 13(13):2096. Doi: 10.3390/ani13132096
[5] S. R. P. D. (2016). "PLC-based automated control system for poultry farms."International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 5(11), 8440–8446.
[6] Nguyen Duc Duong, Nguyen Thi Hien, (2022), Building a SCADA control and monitoring system for a product sorting line by color based on PLC S7-1200 applying IoT technology”. Vietnam Journal of Agricultural Science, 20, 6, 803–812.
[7] Nguyen Duc Dien, Nguyen Cao Cuong, Tran Ngoc Son (2018) Building a SCADA control and monitoring system for a production line via the internet based on PLC S7-1200”. Vietnam Journal of Science and Technology, 49, 66-70.
[8] Pham Trong Nguyen, Nguyen Ngoc Chau, Nguyen Thi Thuy Hong, Huynh Pham Bao Ngoc, Nguyen Nhu Tuong An and Do Vinh Quang, (2023), Building and controlling and monitoring an automatic plant milk cooking system. Journal of Can Tho University, Vietnam. 1A, 59, 39-46.
[9] A. Sagheer, M. Mohammed, K. Riad, M. Alhajhoj (2020) A Cloud-Based IoT Platform for Precision Control of Soilless Greenhouse Cultivation. Sensors, 21(1), 223. Doi: 10.3390/s21010223
[10] D. Oliveira, L. Pereira , T. Bresolin, R. Ferreira, J. Dorea (2021) A Review of Deep Learning Algorithms for Computer 2 Vision Systems in Livestock. Livestock Science. 253, 104700. Doi: 10.1016/j.livsci.2021.104700
[11] B. İ. Yıldız (2024) Intelligent Approaches in Livestock Farming: Using Deep Learning Models. Turkish Journal of Agriculture-Food Science and Technology, 12(11): 1959-1967. Doi: 10.24925/turjaf.v12i11.1959-1967.6861.
[12] R. Dallaev, T. Pisarenko, Ş. Ţălu, D. Sobola, J. Majzner, N. Papež (2023) Current applications and challenges of the Internet of Things. New Trends In Computer Sciences, 1(1), 51–61. Doi: 10.3846/ntcs.2023.17891
[13] M. Țălu (2025) Security and privacy in the IIoT: threats, possible security countermeasures, and future challenges. Computing & AI Connect, 2: 1–12, article ID: 0011. Doi: 10.69709/CAIC.2025.139199
[14] P. Faverdin, C. Allain, R. Guatteo (2020) Precision Livestock Farming: New information to help decision-making? INRAE Prod. Anim, 33 (4), 223e-234e. Doi: 10.20870/productions-animales.2020.33.4.4585
[15] G. Putra, E. Dewi, W. Amaliah, G. Side (2025) Development of IoT-based Smart System for Environmental Control and Water Quality Monitoring in Plant Factory. Jurnal Teknotan 19(2): 115-122. Doi: 10.24198/jt.vol19n2.6
[16] R. Muttha, S. Deshpande, M. A. Chaudhari, N. Wagh (2012) PLC Based Poultry Automation System. International Journal of Scicentific System, 3(6):149-152. Doi: 10.15373/22778179/June2014/52
[17] A. Sagheer, M. Mohammed, K. Riad, M. Alhajhoj (2021) A Cloud-Based IoT Platform for Precision Control of Soilless Greenhouse Cultivation. Sensors, 21(1), 223. Doi: 10.3390/s21010223
[18] G. Abbas, M. Iqbal, S. Jaffery, M. Arshad (2024) IoT and cloud computing solutions for next-generation agriculture and animal husbandry. Pakistan Joural of Science, 76(02):314-345. Doi: 10.57041/pjs.v76i02.1168.
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The data that support the findings of this study are available from the corresponding authors upon reasonable request
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Copyright (c) 2025 Umut (Translator); Vu Minh Thoai, Dang Ngoc Truong, Ştefan Ţălu (Author)
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