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Tarımda Ağaç İlaçlamanın Drone’larla Yapılmasında Yeni bir Yöntemin Geliştirilmesi ve Uygulanması

Year 2021, Volume: 6 Issue: 2, 72 - 89, 01.06.2021

Abstract

Geçmişten günümüze insanların en çok enerji ve emek harcadığı alanlardan biri şüphesiz ki tarım ve çiftçilik olmuştur. Çiftçilerin büyük emekler harcadığı tarım alanlarında, günümüz teknolojilerin kullanılması, bu alanların zaman, enerji, maliyet açısından daha verimli bir hale getirilmesini sağlayacaktır. Drone’lar bu teknolojilerden biri olarak ön plana çıkmaktadır. Tarım üreticilerinin, gıda üretimi, üretkenliğin artırılması ve sürdürülebilirliğin öncelik haline getirilmesi için bu araçları kullanması, daha yüksek üretim ve sistematik tarım için kesin bir yöntem sağlayabilecektir. Tarım alanlarının ve bu alandaki mahsullerin tüm gelişim ve bakım sürecini, drone’ların üzerinde yer alan akıllı sensörler, kullanılan açık kaynak teknolojileri, hızlı entegrasyon, daha fazla uçuş süresi, kullanım kolaylığı gibi parametreler ile daha cazip hale geleceği öngörülmektedir. Otonom drone’lar ise çiftçilik yapma şeklini kökünden değiştirecek -ancak bu düşündüğümüz ötesinde faydalar sağlayacaktır. Araştırmacılar, insan-makine etkileşimine doğru evrilen bu drone teknolojilerinin yapay zekâ, derin öğrenme, makine tanıma, bilgisayarlı görme ve diğer birçok teknolojiyi içereceğini belirtmektedirler. Bu teknolojiler kullanılarak çiftçiler tarım ile ilgili tüm bu operasyonlarını, evlerinde veya iş yerlerinde veya herhangi bir ortamda bir bilgisayar, tablet, akıllı cep telefonu aracılığıyla bu araçları kontrol etmek için ve onu serbest bırakırken ne yaptıklarını izlemek için bu araçlarla arayüz oluşturabileceklerdir. Bu makale drone için geliştirilen etkinlik algoritması ile otonom rota planın çıkarılmasını sağlayan modüler ve genel bir sistemi açıklamaktadır. Sistemin otonom karar verme işlemini gerçekleştirmesine olanak sağlamak için Kmax ağacı ve temel kesme işlemi yaklaşımı uygulanmıştır. Bu otonom drone’lar sayesinde önceden ilaçlanmış bir tarım alanın hiçbir insan müdahalesi olmadan planlanmış bir şekilde drone’lar tarafından otomatik ilaçlanması, gübrelenmesi, sulanması, haritalanması, sağlık durumlarının değerlendirilmesi ve daha birçok şey gelecekte çok daha rahat bir şekilde yapılabilecektir.

Supporting Institution

İnönü Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi

Project Number

FBG-2020-2143

Thanks

Bu çalışmanın gerçekleştirilmesinde FBG-2020-2143 numaralı proje kapsamında, vermiş oldukları maddi ve manevi destekten dolayı, İnönü Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimine teşekkür ederiz.

References

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  • [4] ŞAHİN, G. “Türkiye'de Gübre Kullanım Durumu ve Gübreleme Konusunda Yaşanan Problemler”, Turkish Journal Agricultural Economics, vol. 22, no. 1, pp. 19-32, May 2016
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  • [6] H. Fraser, R., Olthof, I., C. Lantz, T., and Schmitt, C,.”UAV photogrammetry for mapping vegetation in the low-Arctic”, Arctic Science. vol. 2, no. 3, pp. 79-102, June 2016, https://doi.org/10.1139/as-2016-0008
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  • [12] Konert , A., Smereka , J., Szarpak, L., “The Use of Drones in Emergency Medicine: Practical and Legal Aspects”, Emergency Medicine International, vol. 2019, December 2019, https://doi.org/10.1155/2019/3589792
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  • [14] Samaras, S., Magoulianitis, V., Dimou, A., Zarpalas, D., Daras, P., “UAV Classification with Deep Learning Using Surveillance Radar Data”, International Conference on Computer Vision Systems, vol. 10, no. 1, pp. 744-753, November 2019, https://10.1007/978-3-030-34995-0_68
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  • [16] Banić, M., Miltenović, A., Pavlović, M., Ćirić, I., “Intelligent machine vision based railway infrastructure inspection and monitoring using UAV”, Facta Universitatis Ser. Mech. Eng., vol. 17, no. 3, pp. 357-364, 2019, https://doi.org/10.22190/FUME190507041B
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  • [18] Lottes, P., Chebrolu, N., Liebisch, F., Stachniss C., “UAV-based Field Monitoring for Precision Farming” in Proc. 25. Workshop Computerbildanalyse in der Landwirtschaft, 2019
  • [19] Chebrolu , N., Läbe , T.,Stachniss , C., "Robust Long-Term Registration of UAV Images of Crop Fields for Precision Agriculture", IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3097-3104, October 2018, doi: https://10.1109/LRA.2018.2849603
  • [20] Yang, L., Qi, J., Xiao, J., Yong, X., "A literature review of UAV 3D path planning," Proceeding of the 11th World Congress on Intelligent Control and Automation, Shenyang, 2014, pp. 2376-2381, doi: https://10.1109/WCICA.2014.7053093
  • [21] Anand, K., Goutam , R., “An Autonomous UAV for Pesticide Spraying”, International Journal of Trend in Scientific Research and Development, vol. 3, pp. 986-990, 2019, doi: 10.31142/ijtsrd23161
  • [22] Weinstein, B.G., Marconi, S., Bohlman, S., Zare, A., White, E., “Individual Tree-Crown Detection in RGB Imagery Using Semi-Supervised Deep Learning Neural Networks”, Remote Sens, vol. 11, no. 11, pp. 1309, June 2019
  • [23]Karci, A.,“New Algorithms for Minimum Dominating Set in Any Graphs”, Computer Science , vol. 5, no. 2, pp. 62-70, December 2019
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  • [26]AUAV, [Online]. Available: https://www. auav.com.au/articles/drone-types/ [Accessed Feb, 21 2020]
  • [27]Offıce Of Energy Efficiency & Renewable Energy, [Online]. Available: https://www. energy.gov/eere/solar/how-does-solar-work [Accessed Feb, 262021]
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Development and Application of a New Method for Tree Spraying with Drones in Agriculture

Year 2021, Volume: 6 Issue: 2, 72 - 89, 01.06.2021

Abstract

One of the areas where people spent the most energy and effort from the past to the present has undoubtedly been agriculture and farming. Using today’s techonologies in the agricultural areas where farmer spend a lot of effort makes these areas efficent in terms of time, energy and costs. The use of these tools by agricultural producers to produce food, increase productivity and prioritize sustainability could provide a definitive method for higher production and systematic agriculture. It is predicted that the entire development and maintenance process of agricultural areas and crops in this area will become more attractive with parameters such as smart sensors on drones, open source technologies, fast integration, more flight time, ease of use. Autonomous drones, on the other hand, will fundamentally change the way we farm, but this will provide benefits beyond what we think. Researchers state that these drone technologies that evolve towards human-machine interaction will include artificial intelligence, deep learning, machine recognition, computer vision and many other technologies. Using these technologies, farmers will be able to interface with all these farming-related operations in their home or workplace or in any environment to control these tools via a computer, tablet, smart mobile phone and monitor what they do while releasing it. This article describes a modular and general system that provides autonomous route planning with the activity algorithm developed for the drone. In order to allow the system to perform autonomous decision-making, Kmax tree and basic cutting operation approach have been applied. Thanks to these autonomous drones, automatic disinfection, fertilization, irrigation, mapping, evaluation of health conditions and many other things will be done much more comfortably in the future by drones in a pre-sprayed agricultural field without any human intervention.

Project Number

FBG-2020-2143

References

  • [1] Ti̇ryaki̇, B. , Canhi̇lal, R. and Horuz, S., “Tarım ilaçları kullanımı ve riskleri”, Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, vol. 26, no. 2, pp. 154-169, April 2010.
  • [2] Robyn, C. Gilden, Huffling , K., Sattler, B., “Pesticides and Health Risks”, Journal of Obstetric, Gynecologic & Neonatal Nursing, vol. 39, no. 1, pp. 103-110, December 2015, https://doi.org/10.1111/j.1552-6909.2009.01092.
  • [3] Sarwar, M., “The Dangers of Pesticides Associated with Public Health and Preventing of the Risks”, International Journal of Bioinformatics and Biomedical Engineering, vol. 1, no. 2, pp. 130-136, April 2015
  • [4] ŞAHİN, G. “Türkiye'de Gübre Kullanım Durumu ve Gübreleme Konusunda Yaşanan Problemler”, Turkish Journal Agricultural Economics, vol. 22, no. 1, pp. 19-32, May 2016
  • [5] Smith, C. (2016). Shooting photographs with a drone, In The photographers guide to drones (pp. 135-162)
  • [6] H. Fraser, R., Olthof, I., C. Lantz, T., and Schmitt, C,.”UAV photogrammetry for mapping vegetation in the low-Arctic”, Arctic Science. vol. 2, no. 3, pp. 79-102, June 2016, https://doi.org/10.1139/as-2016-0008
  • [7] Siebert, S., Teizer, J. “Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system”, Appl Geomat vol. 6, no. 3, pp. 1-14, May 2014, https://doi.org/10.1016/j.autcon.2014.01.004
  • [8] Nex, F., Remondino, F. “UAV for 3D mapping applications: a review”, Automation in Construction vol. 6, no. 3, pp. 1-15, November 2014, https://10.1007/s12518-013-0120-x
  • [9] North, D., “Private drones: Regulations and insurance”, Layola consumer law review, vol. 27, no. 2, pp. 334-357, May 2015
  • [10] Wall, T., Monahan, T., “Surveillance and violence from afar: The politics of drones and liminal security-scapes”, SAGE Journals, vol. 15, no. 3, pp. 239-254, August 2011, https://doi.org/10.1177/1362480610396650
  • [11] Krishna, V. Vamsi, T., Shastri, S., Kulshrestha, S., Mariajossy, A., “Design Of Drone Ambulance”, International Journal of Pure and Applied Mathematics, vol. 119, no. 15, pp. 1813-1818, 2018
  • [12] Konert , A., Smereka , J., Szarpak, L., “The Use of Drones in Emergency Medicine: Practical and Legal Aspects”, Emergency Medicine International, vol. 2019, December 2019, https://doi.org/10.1155/2019/3589792
  • [13] Frachtenberg, E., “Practical Drone Delivery” in Computer, vol. 52, no. 12, pp. 53-57, Dec. 2019, doi: 10.1109/MC.2019.2942290
  • [14] Samaras, S., Magoulianitis, V., Dimou, A., Zarpalas, D., Daras, P., “UAV Classification with Deep Learning Using Surveillance Radar Data”, International Conference on Computer Vision Systems, vol. 10, no. 1, pp. 744-753, November 2019, https://10.1007/978-3-030-34995-0_68
  • [15] Greenwood, William W., Lynch, Jerome P., Dimitrios.,Z., ”Applications of UAVs in Civil Infrastructure”, Journal of Infrastructure Systems, vol. 25, no. 2, June 2019 https://doi.org/10.1061/(ASCE)IS.1943-555X.0000464
  • [16] Banić, M., Miltenović, A., Pavlović, M., Ćirić, I., “Intelligent machine vision based railway infrastructure inspection and monitoring using UAV”, Facta Universitatis Ser. Mech. Eng., vol. 17, no. 3, pp. 357-364, 2019, https://doi.org/10.22190/FUME190507041B
  • [17] Kato, A., Wakabayashi, H., Hayakawa, Y., Bradford, M., Watanabe, M., Yamaguchi, Y., “Tropical forest disaster monitoring with multi-scale sensors from terrestrial laser, UAV, to satellite radar” 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, 2017, pp. 2883-2886, doi: https://10.1109/IGARSS.2017.8127600
  • [18] Lottes, P., Chebrolu, N., Liebisch, F., Stachniss C., “UAV-based Field Monitoring for Precision Farming” in Proc. 25. Workshop Computerbildanalyse in der Landwirtschaft, 2019
  • [19] Chebrolu , N., Läbe , T.,Stachniss , C., "Robust Long-Term Registration of UAV Images of Crop Fields for Precision Agriculture", IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3097-3104, October 2018, doi: https://10.1109/LRA.2018.2849603
  • [20] Yang, L., Qi, J., Xiao, J., Yong, X., "A literature review of UAV 3D path planning," Proceeding of the 11th World Congress on Intelligent Control and Automation, Shenyang, 2014, pp. 2376-2381, doi: https://10.1109/WCICA.2014.7053093
  • [21] Anand, K., Goutam , R., “An Autonomous UAV for Pesticide Spraying”, International Journal of Trend in Scientific Research and Development, vol. 3, pp. 986-990, 2019, doi: 10.31142/ijtsrd23161
  • [22] Weinstein, B.G., Marconi, S., Bohlman, S., Zare, A., White, E., “Individual Tree-Crown Detection in RGB Imagery Using Semi-Supervised Deep Learning Neural Networks”, Remote Sens, vol. 11, no. 11, pp. 1309, June 2019
  • [23]Karci, A.,“New Algorithms for Minimum Dominating Set in Any Graphs”, Computer Science , vol. 5, no. 2, pp. 62-70, December 2019
  • [24]FarmingMagazine, [Online]. Available: https://www.farmingmagazine.com/bits-and-pieces/tractors/autonomous-vehicles/. [Accessed Feb, 12 2021]
  • [25]DroneLife, [Online]. Available: https:// dronelife.com/2014/10/24/drone-need-gps-connection/ [Accessed Feb, 18 2021]
  • [26]AUAV, [Online]. Available: https://www. auav.com.au/articles/drone-types/ [Accessed Feb, 21 2020]
  • [27]Offıce Of Energy Efficiency & Renewable Energy, [Online]. Available: https://www. energy.gov/eere/solar/how-does-solar-work [Accessed Feb, 262021]
  • [28]Ecogreen Electrical, [Online]. Available: http://www.ecogreenelectrical.com/solar.htm. [Accessed Mar, 082021]
There are 28 citations in total.

Details

Primary Language Turkish
Subjects Artificial Intelligence, Control Engineering, Mechatronics and Robotics
Journal Section PAPERS
Authors

Mevlüt İnan 0000-0002-9840-8404

Ali Karci 0000-0002-8489-8617

Project Number FBG-2020-2143
Publication Date June 1, 2021
Submission Date April 26, 2021
Acceptance Date May 6, 2021
Published in Issue Year 2021 Volume: 6 Issue: 2

Cite

APA İnan, M., & Karci, A. (2021). Tarımda Ağaç İlaçlamanın Drone’larla Yapılmasında Yeni bir Yöntemin Geliştirilmesi ve Uygulanması. Computer Science, 6(2), 72-89.

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