Optimizing UAV-assisted IoT sensor networks: A multi-objective approach to data collection and routing

被引：0

作者：

Mohammed, Yasir I. ^{[1
]}

Hassan, Rosilah ^{[1
]}

Hasan, Mohammad Kamrul ^{[1
]}

Abbas, Huda Saleh ^{[2
]}

Khan, Muhammad Attique ^{[3
,6
]}

Baili, Jamel ^{[4
]}

Gupta, Deepak ^{[5
,7
]}

机构：

[1] Univ Kebangsaan Malaysia, Fac informat Sci & Technol, Ctr Cyber Secur, Bangi 43600, Malaysia

[2] Taibah Univ, Coll Comp Sci & Engn, Dept Comp Sci, Medina, Saudi Arabia

[3] Korea Univ, Coll Informat, Dept Comp Sci & Engn, 145 Anam Ro, Seoul 02841, South Korea

[4] King Khalid Univ, Coll Comp Sci, Dept Comp Engn, Abha 61413, Saudi Arabia

[5] Maharaja Agrasen Inst Technol, Delhi, India

[6] Prince Mohammad Bin Fahd Univ, Coll Comp Engn & Sci, Dept AI, Dhahran, Saudi Arabia

[7] Chitkara Univ, Chitkara Univ Inst Engn & Technol, Ctr Res Impact & Outcome, Rajpura, Punjab, India

来源：

ALEXANDRIA ENGINEERING JOURNAL | 2025年 / 115卷

关键词：

Data gathering; Q; -learning; UAVs; FANET; Reinforcement learning; OPTIMIZATION;

D O I：

10.1016/j.aej.2024.12.018

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Unmanned Aerial Vehicles (UAVs) are powerful tools for data gathering in IoT sensor networks, enhancing efficiency in challenging environments. This research proposes an optimized UAV deployment and data routing approach, addressing energy use, coverage, and communication delays. The study guarantees comprehensive coverage and effective data management by employing sophisticated optimisation methodologies. The solution achieves significant energy savings, reduced latency, and improved performance, offering a robust framework for large-scale IoT applications like agriculture, disaster response, and environmental monitoring.

引用

页码：47 / 56

页数：10

共 30 条

[1] Unmanned Aerial Vehicle detection and Tracking using Image Segmentation and Bayesian Filtering
Alshehri, Mohammed S.
Yusuf, Muhammad Ovais
Hanzla, Muhammad
[J]. 4TH INTERDISCIPLINARY CONFERENCE ON ELECTRICS AND COMPUTER, INTCEC 2024, 2024,
[2] Drone Deep Reinforcement Learning: A Review
Azar, Ahmad Taher
Koubaa, Anis
Ali Mohamed, Nada
Ibrahim, Habiba A.
Ibrahim, Zahra Fathy
Kazim, Muhammad
Ammar, Adel
Benjdira, Bilel
Khamis, Alaa M.
Hameed, Ibrahim A.
Casalino, Gabriella
[J]. ELECTRONICS, 2021, 10 (09)
[3] Azzawi M.A., 2016, Int. J. Appl. Eng. Res, V11, P10216
[4] UAV Path Planning for Data Gathering in Wireless Sensor Networks: Spatial and Temporal Substate-Based Q-Learning
Beishenalieva, Aliia
Yoo, Sang-Jo
[J]. IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (06) : 9572 - 9586
[5] Joint Position and Travel Path Optimization for Energy Efficient Wireless Data Gathering Using Unmanned Aerial Vehicles
Ben Ghorbel, Mahdi
Rodriguez-Duarte, David
Ghazzai, Hakim
Hossain, Md. Jahangir
Menouar, Hamid
[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (03) : 2165 - 2175
[6] Bilal Muhammad, 2019, 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T). Proceedings, P350, DOI 10.1109/PICST47496.2019.9061518
[7] Metaverse for Healthcare: A Survey on Potential Applications, Challenges and Future Directions
Chengoden, Rajeswari
Victor, Nancy
Huynh-The, Thien
Yenduri, Gokul
Jhaveri, Rutvij H.
Alazab, Mamoun
Bhattacharya, Sweta
Hegde, Pawan
Maddikunta, Praveen Kumar Reddy
Gadekallu, Thippa Reddy
[J]. IEEE ACCESS, 2023, 11 : 12764 - 12794
[8] A Hybrid Task Offloading and Resource Allocation Approach for Digital Twin-Empowered UAV-Assisted MEC Network Using Federated Reinforcement Learning for Future Wireless Network
Consul, Prakhar
Budhiraja, Ishan
Garg, Deepak
Kumar, Neeraj
Singh, Ramendra
Almogren, Ahmad S.
[J]. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2024, 70 (01) : 3120 - 3130
[9] Data collection using unmanned aerial vehicles for Internet of Things platforms
Goudarzi, Shidrokh
Kama, Nazri
Anisi, Mohammad Hossein
Zeadally, Sherali
Mumtaz, Shahid
[J]. COMPUTERS & ELECTRICAL ENGINEERING, 2019, 75 : 1 - 15
[10] A review of multi-objective optimization: Methods and its applications
Gunantara, Nyoman
[J]. COGENT ENGINEERING, 2018, 5 (01): : 1 - 16

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