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DRONE TABANLI TARIMSAL OPERASYONLARDA HIZ VE YÜKSEKLİĞİN ENERJİ TÜKETİMİNE ETKISİ

Year 2025, Volume: 28 Issue: 2, 674 - 689, 03.06.2025

Mevlüt İnan , Ali Karci

Abstract

Bu çalışma, tarımsal ve endüstriyel uygulamalarda operasyonel verimliliği optimize etme amacıyla, 5 litrelik yük taşıyan bir drone'nun enerji tüketimi üzerinde hız ve uçuş yüksekliğinin etkisini araştırmaktadır. Kontrollü çevre koşulları altında 1 hektarlık bir tarım arazisinde yürütülen çalışmada, farklı hız (2, 5, 8 m/s) ve yükseklik (5, 10, 15 m) parametrelerini birleştiren dokuz senaryoyu simüle etmek için bir dört pervaneli drone (quadcopter drone) kullanılmıştır. Kalibre edilmiş sensörler kullanılarak 600 veri noktasında enerji tüketimi verileri toplanmıştır. Sonuçlar, hız, yükseklik ve enerji tüketimi arasında net bir ilişki olduğunu ortaya koymuştur. Daha yüksek hızlar enerji tüketimini önemli ölçüde artırmış, değerler 2 m/s'de 66,67 W'tan 8 m/s'de 121,90 W'a yükselmiştir. Yükseklik değişimlerinin enerji tüketimi üzerindeki etkisi, hızın etkisine kıyasla daha sınırlı olmasına rağmen, yine de dikkate değer bir katkı sağlamıştır. Özellikle yükseklik 5 metreden 15 metreye çıkarıldığında, enerji tüketiminde %10 ila %15 arasında bir artış gözlemlenmiştir. Bu da hızın enerji tüketimi üzerinde yükseklikten daha baskın bir etkiye sahip olduğunu göstermektedir. Bu bulgular, enerji verimliliği elde etmek için hız ve yükseklik parametrelerini dikkatlice optimize etme ihtiyacını vurgulamaktadır. Bu çalışma, uzun süreli operasyonlar için düşük hız(2 m/s) ve orta yükseklik kombinasyonlarını ve yalnızca zamana duyarlı görevler için yüksek hız ayarlarını önererek, droneların tasarımı ve işletimi için uygulanabilir iç görüler sunmaktadır.

Keywords

iha tarım enerji tüketimi hız ve yükseklik enerji verimliliği

References

  • Ahmed, S., Mohamed, A., Harras, K., Kholief, M., & Mesbah, S. (2016). Energy efficient path planning techniques for UAV-based systems with space discretization. In 2016 IEEE Wireless Communications and Networking Conference (pp. 1–6). IEEE.
  • Ali, M. F. M., Jamaludin, J., Ahmedy, I., & Awalin, L. J. (2023). Energy performance review of battery-powered drones for search and rescue (SAR) operations. IOP Conference Series: Earth and Environmental Science, 1261(1), 012021. https://doi.org/10.1088/1755-1315/1261/1/012021
  • Almutairi, A., Baroom, A., Alsubey, R., & Elhag, S. (2024). Sensory system for swarm drone: A systematic review. International Journal of Computers and Informatics, 3(6), 72–108. https://doi.org/10.59992/ijci.2024.v3n6p3
  • Askarzadeh, T., Bridgelall, R., & Tolliver, D. (2024). Monitoring nodal transportation assets with uncrewed aerial vehicles: A comprehensive review. Drones, 8(6), 233. https://doi.org/10.3390/drones8060233
  • Beigi, P., Rajabi, M. S., & Aghakhani, S. (2023). An overview of drone energy consumption factors and models. In Proceedings of the International Conference on Advances in Computing. https://doi.org/10.1007/978-3-030-97940-9_200
  • Borikar, G. P., Gharat, C., & Deshmukh, S. R. (2022). Application of drone systems for spraying pesticides in advanced agriculture: A review. IOP Conference Series: Materials Science and Engineering, 1259(1), 012015. https://doi.org/10.1088/1757-899x/1259/1/012015
  • Çabuk, U. C., Tosun, M., Dağdeviren, O., & Öztürk, Y. (2024). Modeling energy consumption of small drones for swarm missions. IEEE Transactions on Intelligent Transportation Systems, 25(8), 10176–10189. https://doi.org/10.1109/TITS.2024.3350042
  • Czachórski, T., Gelenbe, E., Kuaban, G. S., & Marek, D. (2022). Optimizing energy usage for an electric drone. Communications in Computer and Information Science, 61–75. https://doi.org/10.1007/978-3-031-09357-9_6
  • Diller, J., & Han, Q. (2023). Energy-aware drone path finding with a fixed-trajectory ground vehicle. Research Square. https://doi.org/10.21203/rs.3.rs-3793699/v1
  • Dorling, K., Heinrichs, J., Messier, G. G., & Magierowski, S. (2016). Vehicle routing problems for drone delivery. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(1), 70–85. https://doi.org/10.1109/TSMC.2016.2582745
  • Dutta, S., Singh, A., Mondal, B. P., Paul, D., & Patra, K. (2023). Perspective chapter: Digital inclusion of the farming sector using drone technology. In Human-Robot Interaction - Perspectives and Applications. https://doi.org/10.5772/intechopen.108740
  • Figliozzi, M. A. (2017). Lifecycle modeling and assessment of unmanned aerial vehicles (drones) CO2e emissions. Transportation Research Part D: Transport and Environment, 57, 251–261. https://doi.org/10.1016/j.trd.2017.09.011
  • Goh, C., Leow, C. Y., & Nordin, R. (2023). Energy efficiency of unmanned aerial vehicle with reconfigurable intelligent surfaces: A comparative study. Drones, 7(2), 98. https://doi.org/10.3390/drones7020098
  • Gong, H., Huang, B., Jia, B., & Dai, H. (2023). Modeling power consumptions for multirotor UAVs. IEEE Transactions on Aerospace and Electronic Systems, 1–14. https://doi.org/10.1109/TAES.2023.3288846
  • Huang, C., Hu, K., Cheng, H., & Lin, Y. S. (2023). A mission-oriented flight path and charging mechanism for internet of drones. Sensors, 23(9), 4269. https://doi.org/10.3390/s23094269
  • Jacewicz, M., Żugaj, M., Głębocki, R., & Bibik, P. (2022). Quadrotor model for energy consumption analysis. Energies, 15(19), 7136. https://doi.org/10.3390/en15197136
  • LibreTexts. (n.d.). Electric power summary. LibreTexts Physics. Retrieved December 3, 2024, from https://physics.info/electric-power/summary.shtml
  • Liu, Z., Sengupta, R., & Kurzhanskiy, A. (2017). A power consumption model for multi-rotor small unmanned aircraft systems. In Proceedings of ICUAS 2017 (pp. 310–315). https://doi.org/10.1109/ICUAS.2017.7991310
  • MATACHE, M. (2023). Development of a tricopter-hexarotor agricultural UAV destined for the realization of precision spraying works. Inmateh Agricultural Engineering, 11–20. https://doi.org/10.35633/inmateh-70-01
  • McCarthy, C., Nyoni, Y., Kachamba, D. J., Banda, L. B., Moyo, B., Chisambi, C., & Hoshino, B. (2023). Can drones help smallholder farmers improve agriculture efficiencies and reduce food insecurity in sub-Saharan Africa Local perceptions from Malawi. Agriculture, 13(5), 1075. https://doi.org/10.3390/agriculture13051075
  • Merkert, R., & Bushell, J. (2020). Managing the drone revolution: A systematic literature review into the current use of airborne drones and future strategic directions for their effective control. Journal of Air Transport Management, 89, 101929. https://doi.org/10.1016/j.jairtraman.2020.101929
  • Mohsan, S. A. H., Othman, N. Q. H., Khan, M. A., Hussain, A., & Żywiołek, J. (2022). A comprehensive review of micro UAV charging techniques. Micromachines, 13(6), 977. https://doi.org/10.3390/mi13060977
  • Mourgelas, C., Micha, E., Chatzistavrakis, E., & Voyiatzis, I. (2023). Meteorolojide insansız hava araçlarının sınıflandırılması: Bir araştırma. 16. Uluslararası Meteoroloji, Klimatoloji ve Atmosfer Fiziği Konferansı COMECAP 2023, 135. https://doi.org/10.3390/environsciproc2023026135
  • Muli, C., Park, S., & Liu, M. (2022). A comparative study on energy consumption models for drones. In A. González-Vidal, A. M. Abdelgawad, E. Sabir, S. Ziegler, & L. Ladid (Eds.), Internet of Things. GIoTS 2022 (Lecture Notes in Computer Science, Vol. 13533). Springer, Cham. https://doi.org/10.1007/978-3-031-20936-9_16
  • Özgüven, M. M., Altaş, Z., Güven, D., & Çam, A. (2022). Tarımda drone kullanımı ve geleceği. Ordu Üniversitesi Bilim ve Teknoloji Dergisi, 12(1), 64–83. https://doi.org/10.54370/ordubtd.1097519
  • Paiva, D. Z., & Reis, T. (2023). The use of drones in agriculture: A literature review between 2012 and 2022. Journal of Agricultural Sciences Research, 3(7), 2–14. https://doi.org/10.22533/at.ed.973372330051
  • Panjaitan, S., Dewi, Y., Hendri, M., Wicaksono, R., & Priyatman, H. (2022). A drone technology implementation approach to conventional paddy fields application. IEEE Access, 10, 120650–120658. https://doi.org/10.1109/access.2022.3221188
  • Qu, Z., & Willig, A. (2022). Sensorless and coordination-free lane switching on a drone road segment—a simulation study. Drones, 6(12), 411. https://doi.org/10.3390/drones6120411
  • Singh, N., Gupta, D., Joshi, M., Yadav, K., Nayak, S., Kumar, M., & Rajpoot, A. S. (2024). Application of drone technology in agriculture: A modern approach. Journal of Scientific Research and Reports, 30(7), 142–152. https://doi.org/10.9734/jsrr/2024/v30i72131
  • Stolaroff, J. K., Samaras, C., O’Neill, E. R., Lubers, A., Mitchell, A. S., & Ceperley, D. (2018). Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery. Nature Communications, 9(1), 409. https://doi.org/10.1038/s41467-018-07015-5
  • Thibbotuwawa, A., Nielsen, P., Zbigniew, B., & Bocewicz, G. (2019). Energy consumption in unmanned aerial vehicles: A review of energy consumption models and their relation to UAV routing. In J. Świątek, L. Borzemski, & Z. Wilimowska (Eds.), Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology (pp. 853–865). Springer, Cham. https://doi.org/10.1007/978-3-319-99996-8_16
  • Wu, K., Lu, S., Chen, H., Feng, M., & Lu, Z. (2024). An energy-efficient logistic drone routing method considering dynamic drone speed and payload. Sustainability, 16(12), 4995. https://doi.org/10.3390/su16124995
  • Wu, Q., Zeng, Y., & Zhang, R. (2018). Joint trajectory and communication design for multi-UAV enabled wireless networks. IEEE Transactions on Wireless Communications, 17(3), 2109–2121. https://doi.org/10.1109/twc.2017.2789293
  • Xu, L., Yang, Z., Huang, Z., Ding, W., & Buck-Sorlin, G. (2023). Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach. International Journal of Agricultural and Biological Engineering, 16(1), 66–72. https://doi.org/10.25165/j.ijabe.20231601.6581
  • Yu, S. (2023). Comparison of the spray effects of air induction nozzles and flat fan nozzles installed on agricultural drones. Applied Sciences, 13(20), 11552. https://doi.org/10.3390/app132011552
  • Zailani, M. A. H., Sabudin, R. Z. A. R., Rahman, R. A., Saiboon, I. M., Ismail, A., & Mahdy, Z. A. (2020). Drone for medical products transportation in maternal healthcare. Medicine, 99(36), e21967. https://doi.org/10.1097/md.0000000000021967
  • Zhang, J., Campbell, J. F., Sweeney II, D. C., & Hupman, A. C. (2021). Energy consumption models for delivery drones: A comparison and assessment. Transportation Research Part D: Transport and Environment, 90, 102668. https://doi.org/10.1016/j.trd.2020.102668
  • Zorbas, D., Pugliese, L. D. P., Razafindralambo, T., & Guerriero, F. (2016). Optimal drone placement and cost-efficient target coverage. Journal of Network and Computer Applications, 75, 16–31. https://doi.org/10.1016/j.jnca.2016.08.009

THE IMPACT OF SPEED AND ALTITUDE ON ENERGY CONSUMPTION IN DRONE-BASED AGRICULTURAL OPERATIONS

Year 2025, Volume: 28 Issue: 2, 674 - 689, 03.06.2025

Mevlüt İnan , Ali Karci

Abstract

This study investigates the impact of speed and flight altitude on the energy consumption of a drone carrying a 5-liter payload, with the aim of optimizing operational efficiency in agricultural and industrial applications. Conducted on a 1-hectare agricultural field under controlled environmental conditions, the study utilized a quadcopter drone to simulate nine scenarios combining different speed(2, 5, 8 m/s) and altitude(5, 10, 15 m) parameters. Energy consumption data were collected at 600 data points using calibrated sensors. The results revealed a clear relationship between speed, altitude, and energy consumption. Higher speeds significantly increased energy consumption, rising from 66.67 W at 2 m/s to 121.90 W at 8 m/s. Although the effect of altitude variations on energy consumption was less pronounced compared to speed, it still contributed notably; raising the altitude from 5 meters to 15 meters resulted in a 10% to 15% increase in energy consumption. This indicates that speed has a more dominant influence on energy consumption than altitude. The findings highlight the need to carefully optimize speed and altitude parameters to achieve energy efficiency. The study provides actionable insights for drone design and operation, recommending low-speed and mid-altitude combinations for long-duration operations and high-speed settings for time-sensitive tasks.

Keywords

uav agriculture energy consumption altitude and speed energy efficiency

References

  • Ahmed, S., Mohamed, A., Harras, K., Kholief, M., & Mesbah, S. (2016). Energy efficient path planning techniques for UAV-based systems with space discretization. In 2016 IEEE Wireless Communications and Networking Conference (pp. 1–6). IEEE.
  • Ali, M. F. M., Jamaludin, J., Ahmedy, I., & Awalin, L. J. (2023). Energy performance review of battery-powered drones for search and rescue (SAR) operations. IOP Conference Series: Earth and Environmental Science, 1261(1), 012021. https://doi.org/10.1088/1755-1315/1261/1/012021
  • Almutairi, A., Baroom, A., Alsubey, R., & Elhag, S. (2024). Sensory system for swarm drone: A systematic review. International Journal of Computers and Informatics, 3(6), 72–108. https://doi.org/10.59992/ijci.2024.v3n6p3
  • Askarzadeh, T., Bridgelall, R., & Tolliver, D. (2024). Monitoring nodal transportation assets with uncrewed aerial vehicles: A comprehensive review. Drones, 8(6), 233. https://doi.org/10.3390/drones8060233
  • Beigi, P., Rajabi, M. S., & Aghakhani, S. (2023). An overview of drone energy consumption factors and models. In Proceedings of the International Conference on Advances in Computing. https://doi.org/10.1007/978-3-030-97940-9_200
  • Borikar, G. P., Gharat, C., & Deshmukh, S. R. (2022). Application of drone systems for spraying pesticides in advanced agriculture: A review. IOP Conference Series: Materials Science and Engineering, 1259(1), 012015. https://doi.org/10.1088/1757-899x/1259/1/012015
  • Çabuk, U. C., Tosun, M., Dağdeviren, O., & Öztürk, Y. (2024). Modeling energy consumption of small drones for swarm missions. IEEE Transactions on Intelligent Transportation Systems, 25(8), 10176–10189. https://doi.org/10.1109/TITS.2024.3350042
  • Czachórski, T., Gelenbe, E., Kuaban, G. S., & Marek, D. (2022). Optimizing energy usage for an electric drone. Communications in Computer and Information Science, 61–75. https://doi.org/10.1007/978-3-031-09357-9_6
  • Diller, J., & Han, Q. (2023). Energy-aware drone path finding with a fixed-trajectory ground vehicle. Research Square. https://doi.org/10.21203/rs.3.rs-3793699/v1
  • Dorling, K., Heinrichs, J., Messier, G. G., & Magierowski, S. (2016). Vehicle routing problems for drone delivery. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(1), 70–85. https://doi.org/10.1109/TSMC.2016.2582745
  • Dutta, S., Singh, A., Mondal, B. P., Paul, D., & Patra, K. (2023). Perspective chapter: Digital inclusion of the farming sector using drone technology. In Human-Robot Interaction - Perspectives and Applications. https://doi.org/10.5772/intechopen.108740
  • Figliozzi, M. A. (2017). Lifecycle modeling and assessment of unmanned aerial vehicles (drones) CO2e emissions. Transportation Research Part D: Transport and Environment, 57, 251–261. https://doi.org/10.1016/j.trd.2017.09.011
  • Goh, C., Leow, C. Y., & Nordin, R. (2023). Energy efficiency of unmanned aerial vehicle with reconfigurable intelligent surfaces: A comparative study. Drones, 7(2), 98. https://doi.org/10.3390/drones7020098
  • Gong, H., Huang, B., Jia, B., & Dai, H. (2023). Modeling power consumptions for multirotor UAVs. IEEE Transactions on Aerospace and Electronic Systems, 1–14. https://doi.org/10.1109/TAES.2023.3288846
  • Huang, C., Hu, K., Cheng, H., & Lin, Y. S. (2023). A mission-oriented flight path and charging mechanism for internet of drones. Sensors, 23(9), 4269. https://doi.org/10.3390/s23094269
  • Jacewicz, M., Żugaj, M., Głębocki, R., & Bibik, P. (2022). Quadrotor model for energy consumption analysis. Energies, 15(19), 7136. https://doi.org/10.3390/en15197136
  • LibreTexts. (n.d.). Electric power summary. LibreTexts Physics. Retrieved December 3, 2024, from https://physics.info/electric-power/summary.shtml
  • Liu, Z., Sengupta, R., & Kurzhanskiy, A. (2017). A power consumption model for multi-rotor small unmanned aircraft systems. In Proceedings of ICUAS 2017 (pp. 310–315). https://doi.org/10.1109/ICUAS.2017.7991310
  • MATACHE, M. (2023). Development of a tricopter-hexarotor agricultural UAV destined for the realization of precision spraying works. Inmateh Agricultural Engineering, 11–20. https://doi.org/10.35633/inmateh-70-01
  • McCarthy, C., Nyoni, Y., Kachamba, D. J., Banda, L. B., Moyo, B., Chisambi, C., & Hoshino, B. (2023). Can drones help smallholder farmers improve agriculture efficiencies and reduce food insecurity in sub-Saharan Africa Local perceptions from Malawi. Agriculture, 13(5), 1075. https://doi.org/10.3390/agriculture13051075
  • Merkert, R., & Bushell, J. (2020). Managing the drone revolution: A systematic literature review into the current use of airborne drones and future strategic directions for their effective control. Journal of Air Transport Management, 89, 101929. https://doi.org/10.1016/j.jairtraman.2020.101929
  • Mohsan, S. A. H., Othman, N. Q. H., Khan, M. A., Hussain, A., & Żywiołek, J. (2022). A comprehensive review of micro UAV charging techniques. Micromachines, 13(6), 977. https://doi.org/10.3390/mi13060977
  • Mourgelas, C., Micha, E., Chatzistavrakis, E., & Voyiatzis, I. (2023). Meteorolojide insansız hava araçlarının sınıflandırılması: Bir araştırma. 16. Uluslararası Meteoroloji, Klimatoloji ve Atmosfer Fiziği Konferansı COMECAP 2023, 135. https://doi.org/10.3390/environsciproc2023026135
  • Muli, C., Park, S., & Liu, M. (2022). A comparative study on energy consumption models for drones. In A. González-Vidal, A. M. Abdelgawad, E. Sabir, S. Ziegler, & L. Ladid (Eds.), Internet of Things. GIoTS 2022 (Lecture Notes in Computer Science, Vol. 13533). Springer, Cham. https://doi.org/10.1007/978-3-031-20936-9_16
  • Özgüven, M. M., Altaş, Z., Güven, D., & Çam, A. (2022). Tarımda drone kullanımı ve geleceği. Ordu Üniversitesi Bilim ve Teknoloji Dergisi, 12(1), 64–83. https://doi.org/10.54370/ordubtd.1097519
  • Paiva, D. Z., & Reis, T. (2023). The use of drones in agriculture: A literature review between 2012 and 2022. Journal of Agricultural Sciences Research, 3(7), 2–14. https://doi.org/10.22533/at.ed.973372330051
  • Panjaitan, S., Dewi, Y., Hendri, M., Wicaksono, R., & Priyatman, H. (2022). A drone technology implementation approach to conventional paddy fields application. IEEE Access, 10, 120650–120658. https://doi.org/10.1109/access.2022.3221188
  • Qu, Z., & Willig, A. (2022). Sensorless and coordination-free lane switching on a drone road segment—a simulation study. Drones, 6(12), 411. https://doi.org/10.3390/drones6120411
  • Singh, N., Gupta, D., Joshi, M., Yadav, K., Nayak, S., Kumar, M., & Rajpoot, A. S. (2024). Application of drone technology in agriculture: A modern approach. Journal of Scientific Research and Reports, 30(7), 142–152. https://doi.org/10.9734/jsrr/2024/v30i72131
  • Stolaroff, J. K., Samaras, C., O’Neill, E. R., Lubers, A., Mitchell, A. S., & Ceperley, D. (2018). Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery. Nature Communications, 9(1), 409. https://doi.org/10.1038/s41467-018-07015-5
  • Thibbotuwawa, A., Nielsen, P., Zbigniew, B., & Bocewicz, G. (2019). Energy consumption in unmanned aerial vehicles: A review of energy consumption models and their relation to UAV routing. In J. Świątek, L. Borzemski, & Z. Wilimowska (Eds.), Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology (pp. 853–865). Springer, Cham. https://doi.org/10.1007/978-3-319-99996-8_16
  • Wu, K., Lu, S., Chen, H., Feng, M., & Lu, Z. (2024). An energy-efficient logistic drone routing method considering dynamic drone speed and payload. Sustainability, 16(12), 4995. https://doi.org/10.3390/su16124995
  • Wu, Q., Zeng, Y., & Zhang, R. (2018). Joint trajectory and communication design for multi-UAV enabled wireless networks. IEEE Transactions on Wireless Communications, 17(3), 2109–2121. https://doi.org/10.1109/twc.2017.2789293
  • Xu, L., Yang, Z., Huang, Z., Ding, W., & Buck-Sorlin, G. (2023). Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach. International Journal of Agricultural and Biological Engineering, 16(1), 66–72. https://doi.org/10.25165/j.ijabe.20231601.6581
  • Yu, S. (2023). Comparison of the spray effects of air induction nozzles and flat fan nozzles installed on agricultural drones. Applied Sciences, 13(20), 11552. https://doi.org/10.3390/app132011552
  • Zailani, M. A. H., Sabudin, R. Z. A. R., Rahman, R. A., Saiboon, I. M., Ismail, A., & Mahdy, Z. A. (2020). Drone for medical products transportation in maternal healthcare. Medicine, 99(36), e21967. https://doi.org/10.1097/md.0000000000021967
  • Zhang, J., Campbell, J. F., Sweeney II, D. C., & Hupman, A. C. (2021). Energy consumption models for delivery drones: A comparison and assessment. Transportation Research Part D: Transport and Environment, 90, 102668. https://doi.org/10.1016/j.trd.2020.102668
  • Zorbas, D., Pugliese, L. D. P., Razafindralambo, T., & Guerriero, F. (2016). Optimal drone placement and cost-efficient target coverage. Journal of Network and Computer Applications, 75, 16–31. https://doi.org/10.1016/j.jnca.2016.08.009
There are 38 citations in total.

Details

Primary Language Turkish
Subjects Energy-Efficient Computing, Computer Software
Journal Section Mechanical Engineering
Authors

Mevlüt İnan 0000-0002-9840-8404

Ali Karci 0000-0002-8489-8617

Publication Date June 3, 2025
Submission Date December 4, 2024
Acceptance Date April 22, 2025
Published in Issue Year 2025Volume: 28 Issue: 2

Cite

APA İnan, M., & Karci, A. (2025). DRONE TABANLI TARIMSAL OPERASYONLARDA HIZ VE YÜKSEKLİĞİN ENERJİ TÜKETİMİNE ETKISİ. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(2), 674-689.
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