Unity 3D Tabanlı Dijital İkiz Prototipi: Gerçek Zamanlı Sera İzleme ve Kontrol

Öz

Artan küresel nüfus, iklim değişikliği ve küresel ısınmanın etkileriyle birleştiğinde, daha düşük maliyetlerle yüksek kaliteli tarım ürünleri üretimi kritik bir gereklilik haline gelmiştir. Bu zorlukların üstesinden gelmek, gelişmekte olan teknolojilerin kullanılmasını gerektirmektedir. Bu çalışma, dijital ikiz teknolojisini sera tarımına entegre eden bir prototip sistem sunmaktadır. Fiziksel bir sera, gerçek zamanlı veri toplamak amacıyla bir Raspberry Pi ve çeşitli çevresel sensörlerle donatılmıştır. Toplanan bu veriler, Unity 3D tabanlı bir dijital ikiz aracılığıyla görselleştirilmekte ve yönetilmektedir; ayrıca, kurala dayalı karar mantığıyla otomatik kontrol sağlanmaktadır. İzlenen parametreler arasında sıcaklık, nem, ışık şiddeti ve toprak nemi yer almakta olup; bu veriler, sulama, havalandırma ve aydınlatma mekanizmalarının dinamik olarak tetiklenmesini sağlamaktadır. Sistem, farklı aydınlatma senaryoları altında yedi günlük bir süre boyunca test edilmiştir. Sonuçlar, sistemin tutarlı bir performans sergilediğini göstermiş ve bu durum, sistemin eğitim amaçlı kullanım ve küçük ölçekli tarım uygulamaları için uygunluğunu ortaya koymuştur. Ayrıca, sistemin esnek mimarisi, gelecekte kestirimsel modelleme ve uyarlanabilir kontrol stratejilerine doğru genişletilebilme potansiyelini de göstermektedir.

Anahtar Kelimeler

• dijital ikiz
• gömülü sistem
• sera izleme
• akıllı tarım
• Unity 3D

Digital Twin Prototype in Unity 3D: Real-Time Greenhouse Monitoring and Control

Abstract

The increasing global population, combined with the impacts of climate change and global warming, has made the production of high-quality agricultural products at lower costs a critical necessity. Addressing these challenges requires leveraging emerging technologies. This study presents a prototype system that integrates digital twin technology into greenhouse farming. A physical greenhouse was equipped with a Raspberry Pi and various environmental sensors to collect real-time data. This data is visualized and managed through a Unity 3D-based digital twin, enabling automated control via rule-based decision logic. Monitored parameters include temperature, humidity, light intensity, and soil moisture, which dynamically trigger irrigation, ventilation, and lighting mechanisms. The system was tested over a seven-day period under different lighting scenarios. Results showed consistent system performance, demonstrating its viability for educational use and small-scale agricultural applications. Furthermore, the flexible architecture of the system suggests potential for future extension toward predictive modeling and adaptive control strategies.

Keywords

• digital twin
• embedded system
• greenhouse monitoring
• smart agriculture
• Unity 3D

References

1. [1] Alves, G., Maia, R., & Lima, F. (2023). Development of a Digital Twin for smart farming: Irrigation management system for water saving. Journal of Cleaner Production, 388, 135920. https://doi.org/10.1016/j.jclepro.2023.135920
2. [2] Attaran, M., & Celik, B. G. (2023). Digital twin: benefits, use cases, challenges, and opportunities. Decision Analysis Journal, 6, 100165.
3. [3] Chamara, N., Islam, M. D., Bai, G., Shi, Y., & Ge, Y. (2022). Ag-IoT for crop and environment monitoring: Past, present, and future. Agricultural Systems, 203, 103497. https://doi.org/10.1016/j.agsy.2022.103497
4. [4] Isied, R., Mengi, E., & Zohdi, T. (2022). A digital-twin framework for genomic-based optimization of an agrophotovoltaic greenhouse system. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 478. https://doi.org/10.1098/rspa.2022.0414
5. [5] Li, L., Aslam, S., Wileman, A., & Perinpanayagam, S. (2022). Digital twin in aerospace industry: a gentle introduction. IEEE Access, 10, 9543–9562.
6. [6] Liu, J., Wang, L., Wang, Y., Xu, S., & Liu, Y. (2023). Research on the Interface of Sustainable Plant Factory Based on Digital Twin. Sustainability, 15, 5010. https://doi.org/10.3390/su15065010
7. [7] Moreno, J. C., Berenguel, M., Donaire, J. G., Rodríguez, F., Sánchez-Molina, J. A., Guzmán, J. L., & Giagnocavo, C. L. (2024). A pending task for the digitalisation of agriculture: A general framework for technologies classification in agriculture. Agricultural Systems, 213, 103794.
8. [8] Pajpach, M., Drahoš, P., Pribiš, R., & Kučera, E. (2022). Educational-development Workplace for Digital Twins using the OPC UA and Unity 3D. 2022 Cybernetics & Informatics (K&I), Visegrád, Hungary, pp. 1-6. https://doi.org/10.1109/KI55792.2022.9925933

9. [9] Paruelo, J. M., Texeira, M., & Tomasel, F. (2024). Hybrid modeling for grassland productivity prediction: A parametric and machine learning technique for grazing management with applicability to digital twin decision systems. Agricultural Systems, 214, 103847. https://doi.org/10.1016/j.agsy.2023.103847
10. [10] Purcell, W., & Neubauer, T. (2022). Digital Twins in Agriculture: A State-of-the-art review. Smart Agricultural Technology, 3, 100094. https://doi.org/10.1016/j.atech.2022.100094
11. [11]Raspberry Pi. Retrieved from https://www.raspberrypi.com/ (accessed 10 March 2024)
12. [12] Silveira, F., Silva, S. L. C., Machado, F. M., Barbedo, J. G. A., & Amaral, F. G. (2023). Farmers' perception of the barriers that hinder the implementation of agriculture 4.0. Agricultural Systems, 208, 103656.
13. [13] Sun, T., He, X., Song, X., Shu, L., & Li, Z. (2022). The digital twin in medicine: a key to the future of healthcare? Frontiers in Medicine, 9, 907066.
14. [14] Unity, Introduction to Digital Twins with Unity. Retrieved from https://learn.unity.com/tutorial/introduction-to-digital-twins-with-unity (accessed 30 March 2024))
15. [15]Verdouw, C., Tekinerdogan, B., Beulens, A., & Wolfert, S. (2021). Digital twins in smart farming. Agricultural Systems, 189, 103046. https://doi.org/10.1016/j.agsy.2020.103046
16. [16] Viana, C. M., Freire, D., Abrantes, P., Rocha, J., & Pereira, P. (2022). Agricultural land systems importance for supporting food security and sustainable development goals: A systematic review. Science of the Total Environment, 806, 150718.
17. [17] Zhang, Z., Zhu, Z., Gao, G., Qu, D., Zhong, J., Jia, D., Du, X., Yang, X., & Pan, S. (2023). Design and research of digital twin system for multi-environmental variable mapping in plant factory. Computers and Electronics in Agriculture, 213, 108243.