Yapay Zekâ Tabanlı Otomatik Ahır İklim Yönetimi

Year 2025, Volume: 20 Issue: 2, 371 - 388, 30.09.2025

Asilhan Mehmet Nacar , Haydar Safa Kılıç , Ali Günlü , Zeynep Özpolat

https://doi.org/10.55525/tjst.1615709

https://izlik.org/JA32MW93CZ

Abstract

İklim değişikliğinin sebep olduğu yüksek hava sıcaklığı günlük yaşam rutinleri içerisinde birçok alanı etkilemektedir. Hayvancılık alanı için örnek vermek gerekirse süt sığırlarında ısı stresi durumunu ortaya çıkarmaktadır. Isı stresi hayvanların sağlığını ve süt verimliliğini düşürdüğü için bu işletmeler ahırlarda çeşitli serinletme ve iklimlendirme sistemleri kullanmaktadır. Ancak bu sistemler geleneksel olup akıllı kararlar alan bir mekanizmaya sahip değildir. Bu çalışmada işletmelerin verimliliklerini arttırmak ve sürdürülebilir bir yapı oluşturabilmek adına serinletme sistemlerine yapay zekâ destekli görüntü ve veri işleme modeli entegrasyonu üzerinde durulmaktadır. Yapay zekâ modeli sayesinde kurulu olan serinletme sistemleri daha duyarlı ve etkili hale geleceğinden, değişen ortam koşullarında daha doğru çalışan ve kaynak kullanımını azaltan bir serinletme sistemi sağlanması hedeflenmektedir. Serinletme sistemlerinin hayvanların verimlilikleri üzerindeki etkileri araştırılmakta ve bu sistemlerin daha etkili verimli kullanılabilmesi adına geliştirmeler yapılmaktadır. Sistemin yapay zekâ ve görüntü işleme modeli ile çalışması verimlilik açısından değerlendirilmektedir. Akıllı sistemlerin entegrasyonu sonucunda kaynak kullanımının azaltılması üzerinde durulmaktadır. Hayvan refahı ve sağlığının daha etkili ve az kaynak kullanımıyla sağlanması, serinletme sistemlerinin otomatize ve akıllı karar mekanizmalarıyla çalışması ve sonuç olarak işletme maliyetlerinin minimize edilerek kararlılıklarının arttırılması hedeflenmektedir. Bunun yanında gerçek zamanlı çalışan bir sistemin işletme üzerinde ne gibi avantajlara sahip olabileceği tartışılmaktadır. Hayvan sağlığı üzerinde gerçek zamanlı takibin hayvan davranışlarını inceleyerek anlık sistem tepkileri üretilmesinin faydaları araştırılmaktadır. Gerçekleştirilen testler sonucunda, sistemin ortalama 1.8 saniyelik tepki süresi ile çalıştığı, geleneksel sistemlere kıyasla %28 oranında su tasarrufu sağladığı ve inek tespitinde %91,2 mAP doğruluğu elde ettiği belirlenmiştir.

Keywords

Yapay zekâ , görüntü işleme , akıllı sistemler , hayvancılık , süt verimliliği

Artificial Intelligence-Based Automated Barn Climate Management

https://izlik.org/JA32MW93CZ

Abstract

High air temperatures caused by climate change affect various aspects of daily life, including the livestock sector. In dairy farming, heat stress in cows emerges as a major issue, reducing both animal health and milk productivity. To mitigate these effects, farmers commonly use barn cooling and climate control systems. However, these traditional systems lack intelligent decision-making mechanisms. This study focuses on the integration of an AI-powered image and data processing model into existing cooling systems to improve efficiency and establish a sustainable infrastructure. Through the use of artificial intelligence, the cooling systems are expected to operate more sensitively and efficiently, adapting to changing environmental conditions while minimizing resource usage. The impact of cooling systems on livestock productivity is analyzed, and improvements are proposed for more effective use. The integration of image processing and AI-based models is evaluated in terms of operational efficiency. Reducing resource usage through smart systems is emphasized as a key advantage. The system aims to ensure animal welfare and health with minimal resource consumption, by automating climate control systems and enabling intelligent decision-making processes. As a result, operational costs are expected to decrease and system stability to increase. Additionally, the study discusses the potential benefits of a real-time system for operational management. Real-time monitoring of animal behavior and automated system responses are explored for their potential to improve farm management. Experimental results showed that the proposed system achieved an average response time of 1.8 seconds, a 28% reduction in water consumption compared to traditional systems, and a cow detection accuracy of 91.2% mAP, confirming its effectiveness in real-time barn environments.

Keywords

Artificial intelligence , image processing , smart systems , livestock farming , milk productivity

Supporting Institution

KAZANCI HOLDİNG

Thanks

Ahmet Vefa Erdem, Çağrı Ata

References

• Leliveld LMC, Lovarelli D, Riva E, Provolo G. Dairy cow behaviour and physical activity as indicators of heat stress. Ital J Anim Sci 2025; 24(1): 772-778.
• Mbuthia JM, Mayer M, Reinsch N. Modeling heat stress effects on dairy cattle milk production in a tropical environment using test-day records and random regression models. Anim 2021; 15(8): 100222.
• Liu E, Liu L, Zhang Z, Qu M, Xue F. An automated sprinkler cooling system effectively alleviates heat stress in dairy cows. Animals 2024; 14(17): 2586.
• Cattaneo L, Piccioli-Cappelli F, Minuti A, Trevisi E. Metabolic and physiological adaptations to first and second lactation in Holstein dairy cows. J Dairy Sci 2023; 106(5): 3559-3575.
• O’Connor C, Webster J. Welfare of dairy cows in pasture-based systems. In: Cattle Welfare in Dairy and Beef Systems: A New Approach to Global Issues. Cham: Springer Int Publ., pp. 105-124, 2023.
• Tresoldi G, Schütz K E, Tucker C B. Cooling cows with sprinklers: Effects of soaker flow rate and timing on behavioral and physiological responses to heat load and production. J Dairy Sci 2019; 102(1): 528-538.
• Liu E, Liu L, Zhang Z, Qu M, Xue F. An automated sprinkler cooling system effectively alleviates heat stress in dairy cows. Animals 2024; 14(17): 2586.
• Yavaş V. Havacılıkta dijitalleşme ve verimlilik ilişkisi üzerine bir içerik analizi. Verimlilik Dergisi pp. 225-237, 2022.
• Janke D, Caiazzo A, Ahmed N, Alia N, Knoth O, Moreau B, John V. On the feasibility of using open source solvers for the simulation of a turbulent air flow in a dairy barn. Comput Electron Agric 2020; 175: 105546.
• Kaixuan Z, Dongjian H. Target detection method for moving cows based on background subtraction. Int J Agric Biol Eng 2015; 8(1): 42-49.
• Işık AH, Alakuş F, Eskicioğlu ÖC. Hayvancılıkta robotik sistemler ve yapay zekâ uygulamaları. Düzce Univ Bilim Teknol Derg 2021; 9(6): 370-382.
• Firfiris VK, Martzopoulou AG, Kotsopoulos TA. Passive cooling systems in livestock buildings towards energy saving: A critical review. Energy Build 2019; 202: 109368.
• Zhang W, Yang R, Choi CY, Rong L, Zhang G, Wang K, Wang X. Recent research and development of individual precision cooling systems for dairy cows – A review. Comput Electron Agric 2024; 225: 109248.
• Liberati P. An active drying sensor to drive dairy cow sprinkling cooling systems. Sustainability 2023; 15(12): 9384.
• Cao M, Yang R, Choi CY, Rong L, Zhang G, Wang K, Wang X. Effects of discharge angle of jet from a slot orifice on cooling performance for a perforated air ducting system in dairy cattle barn. Comput Electron Agric 2023; 210: 107890.
• Garcia PR, Silveira RMF, Lensink J, da Silva IJO. Thermal performance of a low-profile cross-ventilated freestall dairy barn with evaporative cooling pads in a hot and humid climate. Int J Biometeorol 2023; 67(10): 1651-1658.
• Rebez EB, Sejian V, Silpa MV, Kalaignazhal G, Thirunavukkarasu D, Devaraj C, Dunshea F R. Applications of artificial intelligence for heat stress management in ruminant livestock. Sensors 2024; 24(18): 5890.
• Hall R, Schumacher S, Bildstein A. Systematic analysis of Industrie 4.0 design principles. Procedia CIRP 2022; 107: 440-445.
• Mirzaei A, Carter SR, Patanwala AE, Schneider CR. Missing data in surveys: Key concepts, approaches, and applications. Res Social Adm Pharm 2022; 18(2): 2308-2316.
• Jagatheesaperumal SK, Rahouti M, Ahmad K, Al-Fuqaha A, Guizani M. The duo of artificial intelligence and big data for industry 4.0: Applications, techniques, challenges, and future research directions. IEEE Internet Things J 2021; 9(15): 12861-12885.
• Logeswaran T, Johinth P, KVMP, Manivashagan A, Prem S, Suresh M. Smart cow care: IoT-driven automatic feeding and temperature control. In: 4th Int Conf Sustainable Expert Systems (ICSES). IEEE, pp. 231-235, 2024.
• Irmak E, Erkek İ. Endüstriyel kontrol sistemleri ve SCADA uygulamalarının siber güvenliği: Modbus TCP protokolü örneği. Gazi Univ J Sci Part C: Design Technol 2018; 6(1): 1-16.
• Wang Q, Wang G, Xie X, Zhou L. Design and simulation for temperature measurement and control system based on PT100. In: IEEE 4th Adv Inf Technol Electron Autom Control Conf (IAEAC). IEEE, pp. 2301-2304, 2019.
• Szeliski R. Computer Vision: Algorithms and Applications. Springer Nature, 2022.
• Hennessy JL, Patterson DA. Computer Architecture: A Quantitative Approach. Elsevier, 2011.
• Sozol MS, Islam MM, Rahman MM, Uzzaman MA, Zamshed M, Saki GM. Building an impenetrable vault: Advanced cybersecurity strategies for database servers. Indian Sci J Res Eng Manag 2024; 8(11): 1-7.
• Du Y, Zhou Z, Yang X, Yang X, Wang C, Liu J, Yuan J. Dynamic thermal environment management technologies for data center: A review. Renew Sust Energy Rev 2023; 187: 113761.
• Lopez-Miguel ID, Tournier JC, Adiego BF. PLCverif: Status of a formal verification tool for programmable logic controller. arXiv preprint arXiv:2203.17253, 2022.
• Aggarwal A, Mittal M, Battineni G. Generative adversarial network: An overview of theory and applications. Int J Inf Manag Data Insights 2021; 1(1): 100004.
• Goodfellow I, Bengio Y, Courville A. Deep Learning. MIT Press, 2016.
• Wang A, Chen H, Liu L, Chen K, Lin Z, Han J. YOLOv10: Real-time end-to-end object detection. Adv Neural Inf Process Syst 2024; 37: 107984-108011.
• Asadi F, Eguchi K. Power Electronics Circuit Analysis with PSIM®. Walter de Gruyter GmbH & Co KG, 2021.
• Priyanka S, Shobana N, Alfarhood S, Pankajavalli P B, Sakthivel R, Safran M. Synchronization for industrial internet of things using resilient fault-tolerant control design. IEEE Access 2024; 12: 138816-138826.
• Kumar P, Singhal A, Mehta S, Mittal A. Real-time moving object detection algorithm on high-resolution videos using GPUs. J Real-Time Image Proc 2016; 11(1): 93-109.
• Rebez EB, Sejian V, Silpa MV, Kalaignazhal G, Thirunavukkarasu D, Devaraj C, Dunshea FR. Applications of artificial intelligence for heat stress management in ruminant livestock. Sensors 2024; 24(18): 5890.
• Zulovich JM, Milhollin RK, Horner JL, Harner JP, Lim TT. Air conditioning for naturally ventilated dairy barns. In: 10th Int Livest Environ Symp (ILES X). ASABE, p. 1, 2018.
• Macavoray A, Rashid MA, Rahman H, Shahid MQ. On-farm water use efficiency: Impact of sprinkler cycle and flow rate to cool Holstein cows during semi-arid summer. Sustainability 2023; 15(4): 3774.
• Nguyen-Ky SY, Penttilä K. Indoor climate and energy model calibration with monitored data of a naturally ventilated dairy barn in a cold climate. Appl Eng Agric 2021; 37(5): 851-859.
• Gauly M, Ammer S. Review: Challenges for dairy cow production systems arising from climate changes. Anim 2020; 14(S1): S196-S203.