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Akıllı Tarım Uygulamaları İçin Kablosuz İletişim Standardı Tavsiye Sistemi Tasarımı

Year 2025, Volume: 17 Issue: 1, 92 - 104

Abstract

Endüstriyel tarım sistemlerinin yaygınlaşmasının ardından özellikle son on yıllık zaman diliminde akıllı tarım sistemlerinin gelişim süreci ivme kazanmıştır. Bu hızlanma kapsamında kablosuz iletişim sistemleri akıllı tarım alanında lokomotif rollerden birini üstlenmiştir. Nesnelerin İnterneti konseptinin akıllı tarım sistemleri açısından da mümkün kılınabilmesi yeni nesil kablosuz iletişim sistemleri ile beraber gerçekleşmiştir. Özellikle 5. Nesil (5G) hücresel iletişim sistemlerinin standartlaştırılması sırasında akıllı tarım uygulamaları önemli bir ana senaryo olarak karşımıza çıkmıştır. 5G haricinde akıllı tarım sistemlerinde yararlanılabilecek farklı avantajlara sahip kablosuz iletim standartları vardır. Bu çalışmada, akıllı tarım için kullanılmak istenen farklı alt sistemlerin dinamik yapısı göz önünde bulundurularak hangi durumda hangi kablosuz iletişim standardının daha yüksek fayda getireceğine yönelik bir tavsiye karar sistemi geliştirilmiştir. Makine öğrenmesinden yararlanılarak geliştirilen bu yaklaşım kullanılarak akıllı tarım uygulamalarında hangi kablosuz haberleşme standartlarından daha etkin şekilde yararlanılabileceğine karar verdirilebilmektedir.

Ethical Statement

Yapılan çalışmada Etik Kurul Onay Belgesi gerekmemektedir.

Supporting Institution

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

Project Number

122E400

Thanks

Bu çalışma 122E400 no'lu Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK) projesi kapsamında desteklenmiştir.

References

  • Altunan, U., Sazak, H., Yazar, A. 2023. "ML-Based Service Type Priority Decision Method Using Ambient Information for 5GB", International Conference on Smart Applications, Communications and Networking (SmartNets), 1-5.
  • Arık, M., Korkut İ. 2022. "Irrigatıon in Agriculture and Automation Based Irrigation Systems", Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 10(2), 360-367.
  • Ayaz, M., Ammad-Uddin, M., Sharif, Z., Mansour, A., Aggoune, E.H.M. 2019. "Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk", IEEE Access, 7, 129551-129583.
  • Emam, K.E. 2020. "Accelerating AI with Synthetic Data", O’Reilly Media, Inc.
  • Eren, H. A., Adar, N., Yazar, A. 2023. "Vehicle-to-Everything Communications Standard Selection Under Different Intelligent Transportation Scenarios with Artificial Learning", Journal of Intelligent Systems: Theory and Applications, 6(1), 67-74.
  • Fuentealba, D., Flores, C., Soto, I., Zamorano, R., Reid, S. 2022. "Guidelines for Digital Twins in 5G Agriculture", International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), 613-618.
  • Hançer, A., Yazar, A. 2023a. "Waveform Decision Method with Machine Learning for 5G Uplink Communications", International Journal of Engineering Research and Development, 15(2), 820-827.
  • Hançer, A., Yazar, A. 2023b. "Multi-Carrier and Single-Carrier Waveform Decision Method in Non-Terrestrial Networks", Signal Processing and Communications Applications Conference, 1-4.
  • Hossain, M.I., Markendahl, J.I. 2021. "Comparison of LPWAN Technologies: Cost Structure and Scalability", Wireless Pers Commun, 121, 887–903.
  • Jape, S. D., Mungase, K. V., Thite, V. B., Jadhav, D. 2023. "A Comprehensive Analysis on 5G, IoT and Its Impact on Agriculture and Healthcare", International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), 1599-1605.
  • Khan, M. A., Khan, A., Abuibaid, M., Huang, J. S. 2023. "Harnessing 5G Networks for Enhanced Precision Agriculture: Challenges and potential Solutions", International Conference on Smart Applications, Communications and Networking (SmartNets), 1-6.
  • Kihero, A.B., Tusha, A., Arslan, H. 2021. "Wireless Channel and Interference, Wireless Communication Signals: A Laboratory-based Approach", Wiley, 10, 267–324.
  • Liya, M.L., Arjun, D. 2020. "A Survey of LPWAN Technology in Agricultural Field", International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 313-317.
  • Nikolenko, S.I. 2022. "Synthetic Data for Deep Learning", Springer Cham.
  • Ouafiq, E. M., Saadane, R., Chehri, A., Wahbi, M. 2022. "6G Enabled Smart Environments and Sustainable Cities: an Intelligent Big Data Architecture", Vehicular Technology Conference (VTC-Spring), 1-5.
  • Sazak, H., Yazar, A. 2023. "Ambient Aware User-Numerology Association for 5G and Beyond", Signal Processing and Communications Applications Conference (SIU), 1-4.
  • Shwartz-Ziv, R., Armon, A. 2022. "Tabular Data: Deep Learning is Not All You Need", Information Fusion, 81, 84–90.
  • Yang, L., Shami, A. 2020. "On hyperparameter optimization of machine learning algorithms: Theory and practice, Neurocomputing", 415, 295–316.
  • Yarkan, S., Arslan, H. 2008. "Exploiting Location Awareness toward Improved Wireless System Design in Cognitive Radio", IEEE Communications Magazine, 46(1), 128–136.
  • Yazar, A., Dogan-Tusha, S., Arslan, H. 2020. "6G Vision: An Ultra-Flexible Perspective", ITU Journal on Future and Evolving Technologies, 1(1), 1-20.
  • Yazar, A. 2021. "Requirement Analysis and Clustering Study for Possible Service Types in 6G Communications", Signal Processing and Communications Applications Conference (SIU), 1-4.
  • Zhang, J., Zhang, R., Yang, Q., Hu, T., Guo, K., Hong, T. 2021. "Research on Application Technology of 5G Internet of Things and Big Data in Dairy Farm", International Wireless Communications and Mobile Computing (IWCMC), 138-140.

Wireless Communications Standard Recommendation System Design for Smart Agriculture Applications

Year 2025, Volume: 17 Issue: 1, 92 - 104

Abstract

After the widespread adoption of industrial agricultural systems, the development of smart farming systems has gained momentum, especially in the last decade. Within the scope of this acceleration, wireless communication systems have assumed a pivotal role in the field of smart agriculture. The realization of the Internet of Things (IoT) concept in the context of smart farming has become possible in conjunction with next-generation wireless communication systems. Particularly, smart farming applications emerged as a significant use case during the standardization of 5th Generation (5G) cellular communication systems. Apart from 5G, there are different wireless transmission standards with advantages that can be leveraged in smart farming systems. In this study, a recommendation decision system has been developed to determine which wireless communication standard would provide higher benefits under various dynamic scenarios, taking into account the dynamic nature of different subsystems desired for smart farming. This approach, developed using machine learning, enables the decision-making process regarding which wireless communication standards can be utilized more effectively in smart farming applications.

Project Number

122E400

References

  • Altunan, U., Sazak, H., Yazar, A. 2023. "ML-Based Service Type Priority Decision Method Using Ambient Information for 5GB", International Conference on Smart Applications, Communications and Networking (SmartNets), 1-5.
  • Arık, M., Korkut İ. 2022. "Irrigatıon in Agriculture and Automation Based Irrigation Systems", Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 10(2), 360-367.
  • Ayaz, M., Ammad-Uddin, M., Sharif, Z., Mansour, A., Aggoune, E.H.M. 2019. "Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk", IEEE Access, 7, 129551-129583.
  • Emam, K.E. 2020. "Accelerating AI with Synthetic Data", O’Reilly Media, Inc.
  • Eren, H. A., Adar, N., Yazar, A. 2023. "Vehicle-to-Everything Communications Standard Selection Under Different Intelligent Transportation Scenarios with Artificial Learning", Journal of Intelligent Systems: Theory and Applications, 6(1), 67-74.
  • Fuentealba, D., Flores, C., Soto, I., Zamorano, R., Reid, S. 2022. "Guidelines for Digital Twins in 5G Agriculture", International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP), 613-618.
  • Hançer, A., Yazar, A. 2023a. "Waveform Decision Method with Machine Learning for 5G Uplink Communications", International Journal of Engineering Research and Development, 15(2), 820-827.
  • Hançer, A., Yazar, A. 2023b. "Multi-Carrier and Single-Carrier Waveform Decision Method in Non-Terrestrial Networks", Signal Processing and Communications Applications Conference, 1-4.
  • Hossain, M.I., Markendahl, J.I. 2021. "Comparison of LPWAN Technologies: Cost Structure and Scalability", Wireless Pers Commun, 121, 887–903.
  • Jape, S. D., Mungase, K. V., Thite, V. B., Jadhav, D. 2023. "A Comprehensive Analysis on 5G, IoT and Its Impact on Agriculture and Healthcare", International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), 1599-1605.
  • Khan, M. A., Khan, A., Abuibaid, M., Huang, J. S. 2023. "Harnessing 5G Networks for Enhanced Precision Agriculture: Challenges and potential Solutions", International Conference on Smart Applications, Communications and Networking (SmartNets), 1-6.
  • Kihero, A.B., Tusha, A., Arslan, H. 2021. "Wireless Channel and Interference, Wireless Communication Signals: A Laboratory-based Approach", Wiley, 10, 267–324.
  • Liya, M.L., Arjun, D. 2020. "A Survey of LPWAN Technology in Agricultural Field", International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 313-317.
  • Nikolenko, S.I. 2022. "Synthetic Data for Deep Learning", Springer Cham.
  • Ouafiq, E. M., Saadane, R., Chehri, A., Wahbi, M. 2022. "6G Enabled Smart Environments and Sustainable Cities: an Intelligent Big Data Architecture", Vehicular Technology Conference (VTC-Spring), 1-5.
  • Sazak, H., Yazar, A. 2023. "Ambient Aware User-Numerology Association for 5G and Beyond", Signal Processing and Communications Applications Conference (SIU), 1-4.
  • Shwartz-Ziv, R., Armon, A. 2022. "Tabular Data: Deep Learning is Not All You Need", Information Fusion, 81, 84–90.
  • Yang, L., Shami, A. 2020. "On hyperparameter optimization of machine learning algorithms: Theory and practice, Neurocomputing", 415, 295–316.
  • Yarkan, S., Arslan, H. 2008. "Exploiting Location Awareness toward Improved Wireless System Design in Cognitive Radio", IEEE Communications Magazine, 46(1), 128–136.
  • Yazar, A., Dogan-Tusha, S., Arslan, H. 2020. "6G Vision: An Ultra-Flexible Perspective", ITU Journal on Future and Evolving Technologies, 1(1), 1-20.
  • Yazar, A. 2021. "Requirement Analysis and Clustering Study for Possible Service Types in 6G Communications", Signal Processing and Communications Applications Conference (SIU), 1-4.
  • Zhang, J., Zhang, R., Yang, Q., Hu, T., Guo, K., Hong, T. 2021. "Research on Application Technology of 5G Internet of Things and Big Data in Dairy Farm", International Wireless Communications and Mobile Computing (IWCMC), 138-140.
There are 22 citations in total.

Details

Primary Language English
Subjects Decision Support and Group Support Systems
Journal Section Articles
Authors

Ahmet Yazar 0000-0001-9348-9092

Ayşe Rabia Soylu 0009-0001-5778-4163

Orçun Balatlıoğlu 0009-0005-0309-6970

Project Number 122E400
Early Pub Date March 3, 2025
Publication Date
Submission Date April 15, 2024
Acceptance Date October 9, 2024
Published in Issue Year 2025 Volume: 17 Issue: 1

Cite

APA Yazar, A., Soylu, A. R., & Balatlıoğlu, O. (2025). Wireless Communications Standard Recommendation System Design for Smart Agriculture Applications. International Journal of Engineering Research and Development, 17(1), 92-104. https://doi.org/10.29137/umagd.1468766

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