A Survey on Applications of Unmanned Aerial Vehicles Using Machine Learning

被引:11
|
作者
Teixeira, Karolayne [1 ]
Miguel, Geovane [1 ]
Silva, Hugerles S. [2 ,3 ,4 ]
Madeiro, Francisco [1 ]
机构
[1] Univ Catol Pernambuco Unicap, Escola Unicap ICAM TECH, BR-50050900 Recife, Brazil
[2] Univ Aveiro, Inst Telecomunicacoes, Campus Univ Santiago, P-3810193 Aveiro, Portugal
[3] Univ Aveiro, Dept Eletron Telecomunicacoes & Informat, Campus Univ Santiago, P-3810193 Aveiro, Portugal
[4] Univ Brasilia UnB, Dept Elect Engn, BR-70910900 Brasilia, Brazil
关键词
Unmanned aerial vehicle; machine learning; literature review; UAV applications; neural networks; HIGH-RESOLUTION IMAGERY; ARTIFICIAL-INTELLIGENCE; CHLOROPHYLL CONTENT; VEGETATION INDEXES; TRAFFIC-CONGESTION; TARGET DETECTION; YIELD ESTIMATION; DATA-COLLECTION; RANDOM FOREST; DATA FUSION;
D O I
10.1109/ACCESS.2023.3326101
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Unmanned Aerial Vehicles (UAVs) play an important role in many applications, including health, transport, telecommunications and safe and rescue operations. Their adoption can improve the speed and precision of applications when compared to traditional solutions based on handwork. The use of UAVs brings scientific and technological challenges. In this context, Machine Learning (ML) techniques provide solutions to several problems concerning the use of UAVs in civil and military applications. An increasing number of scientific papers on the use of ML in UAVs context have been published in academic journals. In this work, we present a literature review on the use of ML techniques in UAVs, outlining the most recurrent areas and the most commonly used ML techniques in UAV applications. The results reveal that applications in the areas of environment, communication and security are among the main research topics.
引用
收藏
页码:117582 / 117621
页数:40
相关论文
共 50 条
  • [41] Machine Learning-Based Beamforming for Unmanned Aerial Vehicles Equipped with Reconfigurable Intelligent Surfaces
    Ahmad, Ishtiaq
    Narmeen, Ramsha
    Becvar, Zdenek
    Guvenc, Ismail
    IEEE WIRELESS COMMUNICATIONS, 2022, 29 (04) : 32 - 38
  • [42] Intrusion Detection Systems for Networked Unmanned Aerial Vehicles: A Survey
    Choudhary, Gaurav
    Sharma, Vishal
    You, Ilsun
    Yim, Kangbin
    Chen, Ing-Ray
    Cho, Jin-Hee
    2018 14TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC), 2018, : 560 - 565
  • [43] A Study on the Applicability of Unmanned Aerial Vehicles to the Sounding Survey of Tidelands
    Jeong, Sae-Han
    Kwon, Jay Hyoun
    Kim, Jung Uk
    JOURNAL OF COASTAL RESEARCH, 2019, : 436 - 440
  • [44] Survey On Applications Of Internet Of Things Using Machine Learning
    Majumdar, Namrata
    Shukla, Shipra
    Bhatnagar, Anisha
    2019 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2019), 2019, : 562 - 566
  • [45] Machine Learning, Unmanned Vehicles, and Energy: A Review
    Santiago, Brian L. Reyes
    Ortiz-Rivera, Eduardo
    2023 IEEE 50TH PHOTOVOLTAIC SPECIALISTS CONFERENCE, PVSC, 2023,
  • [46] TECHNICAL ANALYSIS OF UNMANNED AERIAL VEHICLES (DRONES) FOR AGRICULTURAL APPLICATIONS
    Marinello, Francesco
    Pezzuolo, Andrea
    Chiumenti, Alessandro
    Sartori, Luigi
    15TH INTERNATIONAL SCIENTIFIC CONFERENCE: ENGINEERING FOR RURAL DEVELOPMENT, 2016, : 870 - 875
  • [47] Detection of Unauthorized Unmanned Aerial Vehicles Using YOLOv5 and Transfer Learning
    Al-Qubaydhi, Nader
    Alenezi, Abdulrahman
    Alanazi, Turki
    Senyor, Abdulrahman
    Alanezi, Naif
    Alotaibi, Bandar
    Alotaibi, Munif
    Razaque, Abdul
    Abdelhamid, Abdelaziz A.
    Alotaibi, Aziz
    ELECTRONICS, 2022, 11 (17)
  • [48] Improving Unmanned Aerial Vehicle Remote Sensing-Based Rice Nitrogen Nutrition Index Prediction with Machine Learning
    Zha, Hainie
    Miao, Yuxin
    Wang, Tiantian
    Li, Yue
    Zhang, Jing
    Sun, Weichao
    Feng, Zhengqi
    Kusnierek, Krzysztof
    REMOTE SENSING, 2020, 12 (02)
  • [49] Optimal coverage of borders using unmanned aerial vehicles
    Etezadi, Mohammad
    Ashrafi, Siamak
    Ghasemi, Mostafa
    COMMUNICATIONS IN COMBINATORICS AND OPTIMIZATION, 2024, 9 (03) : 467 - 484
  • [50] Cooperative fire detection using unmanned aerial vehicles
    Merino, L
    Caballero, F
    Martínez-De Dios, JR
    Ollero, A
    2005 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-4, 2005, : 1884 - 1889