dc.contributor.author | Nelson, Wilson Ayyanthole | |
dc.date.accessioned | 2024-08-28T08:09:38Z | |
dc.date.available | 2024-08-28T08:09:38Z | |
dc.date.created | 2024-08-20T14:10:20Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Wilson, A. N. (2024). Smart Sensing and Communications for UAVs/Drones [Doctoral dissertation]. University of Agder. | en_US |
dc.identifier.isbn | 978-82-8427-202-3 | |
dc.identifier.uri | https://hdl.handle.net/11250/3148763 | |
dc.description.abstract | Reliable sensing and energy-efficient communication are an integral part of unmanned aerial vehicle (UAV)-based applications. However, it is challenging to ensure reliable sensing under all weather conditions. Furthermore, enabling robust and energy-efficient communication of this sensed data for seamless autonomous operations is equally demanding. Low-complexity and lightweight algorithms play a vital role in this regard. As a result, the goal of this Ph.D. research project is to design, develop, and implement reliable sensing and energy-efficient communication techniques to provide seamless autonomous operations for UAVs and ground control stations. To achieve the intended goal, one of the objectives is directed toward developing novel lightweight low-complexity smart sensing algorithms that attain improved detection performance in adverse weather and lighting conditions too. In this regard, this research focuses on utilizing thermal, acoustic, and mmWave frequency-modulated continuous wave (FMCW) radar sensors with lightweight machine learning algorithms to obtain improved detection and localization performance. The sensed information along with telemetry data is required to be transmitted to other UAVs or ground control stations to facilitate efficient and secure coordination of autonomous UAVs. Hence, the secondary objective of this research addresses the challenge of achieving energy-efficient data transmission for a UAV-assisted wireless network. The research for attaining energy-efficient data transmission focuses on the design of a dynamic and adaptively optimized switching algorithm that leverages the distinct features of the various onboard communication modules. This thesis is a compendium of seven publications that are organized into five chapters. Overall the primary objective is to develop reliable smart sensing algorithms along with energy-efficient communication schemes to enable seamless autonomous UAV operations. The first chapter briefly introduces the various challenges dealt in the thesis and provides an overview of the thesis structure. Chapter 2 provides the necessary literary material to navigate the subsequent chapters. Chapter 3 discusses three sensing approaches using thermal, acoustic, and mmWave FMCW radar sensors to achieve improved detection and localization performance. In chapter 4, the notion of an adaptively optimized switching algorithm for energyefficient communication is conceived. Two approaches to form the hybrid communication switching network are discussed. Finally, chapter 5 concludes the Ph.D. dissertation by summarizing the proposed approaches and providing avenues for future research. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | University of Agder | en_US |
dc.relation.ispartofseries | Doctoral dissertations at University of Agder; no 485 | |
dc.relation.haspart | Paper I: Wilson, A. N., Kumar, A., Jha, A., & Cenkeramaddi, L. R. (2022). Embedded sensors, communication technologies, computing platforms and machine learning for UAVs: A review. IEEE Sensors Journal, 22(3), 1807-1826. Accepted manuscript. Full-text is not available in AURA as a separate file. | en_US |
dc.relation.haspart | Paper II: Wilson, A. N., Gupta, K. A., Koduru, B. H., Kumar, A., Jha, A., & Cenkeramaddi, L. R. (2023). Recent advances in thermal imaging and its applications using machine learning: A review. IEEE Sensors Journal, 23(4), 3395-3407. Accepted manuscript. Full-text is not available in AURA as a separate file. | en_US |
dc.relation.haspart | Paper III: W. A. N., Jha, A., Kumar, A., & Cenkeramaddi, L. R. (2023). Estimation of UAV count using thermal imaging and lightweight CNN. In Proceedings of the International Conference on Control, Mechatronics and Automation (ICCMA) (pp. 92-96). Grimstad, Norway. Accepted manuscript. Full-text is not available in AURA as a separate file. | en_US |
dc.relation.haspart | Paper IV: Wilson, A. N., Jha, A., Kumar, A., & Cenkeramaddi, L. R. (2023). Estimation of number of unmanned aerial vehicles in a scene utilizing acoustic signatures and machine learning. Journal of the Acoustical Society of America, 154(1), 533–546. Accepted version. Full-text is available in AURA as a separate file: https://hdl.handle.net/11250/3148752. | en_US |
dc.relation.haspart | Paper V: Wilson, A. N., Kumar, A., Jha, A., & Cenkeramaddi, L. R. (2023). Multitarget angle of arrival estimation using rotating mmWave FMCW radar and Yolov3. IEEE Sensors Journal, 23(3), 3173-3182. Accepted manuscript. Full-text is not available in AURA as a separate file. | en_US |
dc.relation.haspart | Paper VI: W. A. N., Reddy, Y. S., Jha, A., Kumar, A., & Cenkeramaddi, L. R. (2021). Hybrid BLE/LTE/Wi-Fi/LoRa switching scheme for UAV-assisted wireless networks. In Proceedings of the IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (pp. 78-83). Hyderabad, India. Accepted manuscript. Full-text is not available in AURA as a separate file. | en_US |
dc.relation.haspart | Paper VII: Nelson, W. A., Yeduri, S. R., Jha, A., Kumar, A., & Cenkeramaddi, L. R. (2024). RL-based energy-efficient data transmission over hybrid BLE/LTE/Wi-Fi/LoRa UAV-assisted wireless network. IEEE/ACM Transactions on Networking, 32(3), 1951-1966. Accepted manuscript. Full-text is not available in AURA as a separate file. | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Smart Sensing and Communications for UAVs/Drones | en_US |
dc.type | Doctoral thesis | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | © 2024 Wilson Ayyanthole Nelson | en_US |
dc.subject.nsi | VDP::Technology: 500::Information and communication technology: 550::Telecommunication: 552 | en_US |
dc.source.pagenumber | 318 | en_US |
dc.source.issue | 485 | en_US |
dc.identifier.cristin | 2287966 | |