DRONE TABANLI TARIMSAL OPERASYONLARDA HIZ VE YÜKSEKLİĞİN ENERJİ TÜKETİMİNE ETKISİ

Mevlüt İnan; Ali Karci

doi:10.17780/ksujes.1596380

EN TR

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

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

DRONE TABANLI TARIMSAL OPERASYONLARDA HIZ VE YÜKSEKLİĞİN ENERJİ TÜKETİMİNE ETKISİ

Öz

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.

Anahtar Kelimeler

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

Details

Primary Language

Turkish

Subjects

Energy-Efficient Computing , Computer Software

Journal Section

Research Article

Authors

Mevlüt İnan ^*
0000-0002-9840-8404
Türkiye

Ali Karci
0000-0002-8489-8617
Türkiye

Publication Date

June 3, 2025

Submission Date

December 4, 2024

Acceptance Date

April 22, 2025

Published in Issue

Year 1970 Volume: 28 Number: 2

DOI

https://doi.org/10.17780/ksujes.1596380

IZ

https://izlik.org/JA48JX92HR

Cite

RIS / Bibtex

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. https://doi.org/10.17780/ksujes.1596380