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Evolution and significance of unmanned aerial vehicles

  • Authors Details :  
  • S. Jayanthi ,  
  • H. Shaheen,  
  • U. Balashivudu,  
  • Meesala Shobha Rani

Journal title : Unmanned Aerial Vehicle Cellular Communications

Publisher : Springer International Publishing

Online ISSN : 2523-3742

Page Number : 287-311

541 Views Other

Unmanned aerial vehicles (UAVs) are aerial systems controlled remotely or autonomously by astronauts. Massive advancements in electronics and information technology have prompted the popularity and growth of UAVs. As a result of the huge advances made in electronics and information technology, civilian tasks can now be accomplished with UAV in a more effective, efficient, and secure way. Known as a drone, UAVs are developed and operated using a variety of technologies such as machine learning, computer vision, artificial intelligence, and collision avoidance. Having become more affordable and accessible, drone technology has become more popular among civilians. Therefore, this technology is constantly evolving and can be used across a variety of fields. The application of drones makes a huge difference in the most demanding and complex industrial environments such as those in the mining industry, maritime, oil, gas, and seaports. The usage of drones is increasing among industrialists to improve and optimize processes, as well as to enhance operational efficiency in industrial process. This chapter discusses UAVs on a wide range of topics, including evolution and historical perspectives of UAV, taxonomy of UAV, significance of UAV to society and industry, and industrial and academic perspectives on UAV.

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DOI : https://doi.org/10.1007/978-3-031-08395-2_12

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  • (1). Earls, A. R. (2019). Tech target, IoT agenda. Drone (UAV). https://internetofthingsagenda.techtarget.com/definition/drone
  • (2). Drones and aerial observation: New technologies for property rights, human rights, and global development—A primer, New America, July 2015.
  • (3). Euler, S., Maattanen, H.-L., Lin, X., Zou, Z., Bergström, M., & Sedin, J. (2018, April). Mobility support for cellular connected unmanned aerial vehicles: Performance and analysis. [Online]. Available: https://arxiv.org/abs/1804.04523
  • (4). Evolved Universal Terrestrial Radio Access (E-UTRA); Physical Layer Procedures (Release 9), document 3GPP 136.213, June 2010.
  • (5). Castellanos, C. U., et al. (2008, May). Performance of uplink fractional power control in Utran LTE. In Proc. IEEE VTC (pp. 2517–2521).
  • (6). Unmanned Aircraft System (UAS) service demand 2015–2035: Literature review & projections of future usage. U.S. Dept. Transp., Washington, DC, USA, Tech. Rep. DOT-VNTSC-DoD-13-01, September 2013.
  • (7). Mozaffari, M., Saad, W., Bennis, M., Nam, Y.-H., & Debbah, M. (2018, March). A tutorial on UAVs for wireless networks: Applications, challenges, and open problems. [Online]. Available: https://arxiv.org/abs/1803.00680
  • (8). Bera, B., Saha, S., Das, A. K., Kumar, N., Lorenz, P., & Alazab, M. (2020, August). Blockchain-envisioned secure data delivery and collection scheme for 5G-based IoT-enabled internet of drones environment. IEEE Transactions on Vehicular Technology, 69(8), 9097–9111. https://doi.org/10.1109/TVT.2020.3000576
  • (9). Chandhar, P., & Larsson, E. G. (2017, November). Massive MIMO for drone communications: Applications, case studies and future directions. [Online]. Available: https://arxiv.org/abs/1711.07668
  • (10). Hayat, S., Yanmaz, E., & Muzaffar, R. (2016, 4th Quarter). Survey on unmanned aerial vehicle networks for civil applications: A communications viewpoint. IEEE Communications Surveys & Tutorials, 18(4), 2624–2661.
  • (11). Tahir, A., Böling, J., Haghbayan, M.-H., Toivonen, H. T., & Plosila, J. (2019). Swarms of unmanned aerial vehicles — A survey. Journal of Industrial Information Integration, 16, 100106, ISSN 2452-414X.
  • (12). Zeng, Y., Lyu, J., & Zhang, R. (2018, April). Cellular-connected UAV: Potentials, challenges and promising technologies. [Online]. Available: https://arxiv.org/abs/1804.02217
  • (13). Geraci, G., Garcia-Rodriguez, A., Galati Giordano, L., López-Pérez, D., & Björnson, E. (2018, May). Supporting UAV cellular communications through massive MIMO. In Proc. IEEE ICC workshops (pp. 1–6).
  • (14). Zhang, S., & Cheng, W. (2019). Statistical QoS provisioning for UAV-enabled emergency communication networks. In 2019 IEEE Globecom workshops (GC Wkshps) (pp. 1–6).
  • (15). Garcia-Rodriguez, A, Geraci, G, López-Pérez, D, Giordano, L. G., Ding, M., & Bjornson, E. (2018, May). The essential guide to realizing 5G-connected UAVs with massive MIMO. [Online]. Available: https://arxiv.org/abs/1805.05654
  • (16). Study on channel model for frequencies from 0.5 to 100 GHz (Release 14), document 3GPP 38.901, May 2017.
  • (17). Valavanis, K. P., & Vachtsevanos, G. J. (Eds.). (2005). Handbook of unmanned aerial vehicles. Springer.
  • (18). Stanczak, J., Kovacs, I. Z., Koziol, D., Wigard, J., Amorim, R., & Nguyen, H. (2018, June). Mobility challenges for unmanned aerial vehicles connected to cellular LTE networks. In Proc. IEEE VTC (pp. 1–5).
  • (19). Liu, X., Lai, B., Lin, B., & Leung, V. C. M. Joint communication and trajectory optimization for multi-UAV enabled mobile internet of vehicles. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2022.3140357
  • (20). Taylor, J. W. R., & Guilmartin, J. F. Military aircraft. Encyclopedia Britannica. Invalid Date. https://www.britannica.com/technology/military-aircraft. Accessed 13 Oct 2021.
  • (21). Kammoun, H., Khanfir, Z., Altman, M. D., & Kamoun, M. (2014, June). Preliminary results on 3D channel modeling: From theory to standardization. IEEE Journal on Selected Areas in Communications, 32(6), 1219–1229.
  • (22). Further Advancements for E-UTRA Physical Layer Aspects (Release 9), document 3GPP 36.814, March 2013.
  • (23). Fattah, H., & Leung, C. (2002, October). An overview of scheduling algorithms in wireless multimedia networks. IEEE Wireless Communications, 9(5), 76–83.
  • (24). Price, H. (2018, February). Federal Aviation Administration (FAA) forecast fiscal years 2017–2038. [online] Available: https://www.faa.gov/news/fact_sheets/news_story.cfm?newsId=22594/
  • (25). Nokia and EE trial mobile base stations floating on drones to revolutionise rural 4G coverage. (2016). [online] Available: http://www.ibtimes.co.uk/ nokia-ee-trial-mobilebase-stations-floating-drones-revolutionise-rural-4g-coverage-1575795
  • (26). Technical specification group radio access network; Study on enhanced LTE support for aerial vehicles (release 15), December 2017.
  • (27). Connected Aerial Vehicle Live. (2018, May). [online] Available: http://www.huawei.com/en/industry-insights/innovation/xlabs/use-cases/mbbf2017-connected-aerial-vehicle-live
  • (28). Fotouhi, M. D., & Hassan, M. (2018). Flying drone base stations for macro hotspots. IEEE Access, 6, 19530–19539.
  • (29). Sekander, S., Tabassum, H., & Hossain, E. (2018, March). Multi-tier drone architecture for 5G/B5G cellular networks: Challenges trends and prospects. IEEE Communications Magazine, 56(3), 96–103.
  • (30). https://www.airforce-technology.com/projects/predator-uav/
  • (31). Kapoor, R., Shukla, A., & Goyal, V. (2022). Analysis of multiple antenna techniques for unmanned aerial vehicle (UAV) communication. In T. Senjyu, P. Mahalle, T. Perumal, & A. Joshi (Eds.), IOT with smart systems. Smart innovation, systems and technologies (Vol. 251). Springer. https://doi.org/10.1007/978-981-16-3945-6_34
  • (32). Alamu, O., Gbenga-Ilori, A., Adelabu, M., Imoize, A., & Ladipo, O. (2020). Energy efficiency techniques in ultra-dense wireless heterogeneous networks: An overview and outlook. Engineering Science and Technology, an International Journal, 23(6), 1308–1326., ISSN 2215-0986. https://doi.org/10.1016/j.jestch.2020.05.00
  • (33). Kapoor, R., Shukla, A., & Goyal, V. (2022). Unmanned aerial vehicle (UAV) communications using multiple antennas. In T. K. Gandhi, D. Konar, B. Sen, & K. Sharma (Eds.), Advanced computational paradigms and hybrid intelligent computing. Advances in intelligent systems and computing (Vol. 1373). Springer. https://doi.org/10.1007/978-981-16-4369-9_27
  • (34). Imoize, A. L., Ibhaze, A. E., Atayero, A. A., & Kavitha, K. V. N. (2021). Standard propagation channel models for MIMO communication systems. Wireless Communications and Mobile Computing, 2021, Article ID 8838792, 36 pages.
  • (35). Imoize, A. L., Adedeji, O., Tandiya, N., & Shetty, S. (2021). 6G enabled smart infrastructure for sustainable society: Opportunities, challenges, and research roadmap. Sensors, 21, 1709. https://doi.org/10.3390/s21051709
  • (36). Lim, W. Y. B., et al. (2021, September/October). UAV-assisted communication efficient federated learning in the era of the artificial intelligence of things. IEEE Network, 35(5), 188–195. https://doi.org/10.1109/MNET.002.2000334
  • (37). Shakoor, S., Kaleem, Z., Baig, M. I., Chughtai, O., Duong, T. Q., & Nguyen, L. D. (2019). Role of UAVs in public safety communications: Energy efficiency perspective. IEEE Access, 7, 140665–140679. https://doi.org/10.1109/ACCESS.2019.2942206
  • (38). Yang, Z., et al. (2021, October). AI-driven UAV-NOMA-MEC in next generation wireless networks. IEEE Wireless Communications, 28(5), 66–73. https://doi.org/10.1109/MWC.121.2100058
  • (39). Zhao, J., Yu, L., Cai, K., Zhu, Y., & Han, Z. RIS-aided ground-aerial NOMA communications: A distributionally Robust DRL approach. IEEE Journal on Selected Areas in Communications. https://doi.org/10.1109/JSAC.2022.3143230
  • (40). Aloqaily, M., Hussain, R., Khalaf, D., Hani, D., & Oracevic, A. On the role of futuristic technologies in securing UAV-supported autonomous vehicles. IEEE Consumer Electronics Magazine. https://doi.org/10.1109/MCE.2022.3141065



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