Task offloading and trajectory control techniques in unmanned aerial vehicles with Internet of Things – An exhaustive review

Published

29-12-2023

DOI:

https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.4.43

Keywords:

Unmanned Aerial Vehicles, Task offloading, Trajectory control, Internet of Things

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Issue

Section

SECTION C: ARTIFICIAL INTELLIGENCE, ENGINEERING, TECHNOLOGY

Authors

  • D. Prabakar Department of Computer Science and Engineering, Karpagam College of Engineering, Othakkalmandam, Coimbatore, Tamil Nadu, India
  • Santhosh Kumar D.R. Department of Electronics and Instrumentation Engineering, University BDT College of Engineering, Davangere, Constituent College of VTU, Belagavi, Karnataka, India
  • R.S. Kumar Department of Aeronautical Engineering, Er. Perumal Manimekalai College of Engineering (Autonomous), Hosur, Krishnagiri, Tamil Nadu, India
  • Chitra M. Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, Tamil Nadu, India
  • Somasundaram K. Department of Mehanical Engineering Theni Kammavar Sangam College of Technology, Theni, TamilNadu, India
  • S.D.P. Ragavendiran Department of Computer Science and Engineering, Builders Engineering College, EBET knowledge park, Nathakadaiyur, Tirupur, Tamil Nadu, India
  • Narayan K. Vyas Department of Electronics & Communication Engineering, Government Engineering College, Jhalawar, Sunil road, Tehsil, Jhalarapatan District, Jhalawar Rajasthan, India.

Abstract

Objectives: This article reviews and provides an exhaustive examination of task offloading and trajectory control techniques in unmanned aerial vehicles (UAVs) integrated with Internet of Things (IoT), highlighting their significance and impact on the UAV ecosystem. The paper begins by introducing the fundamental concepts of UAVs, IoT, and their integration, emphasizing the potential benefits and challenges of this union. Subsequently, it delves into an extensive exploration of task offloading, a critical aspect that optimizes UAV operations by distributing tasks between the UAV and edge/cloud computing resources. Various task offloading strategies, including computation offloading, data offloading, and control offloading, is discussed in detail, elucidating their role in optimizing resource utilization, energy efficiency, and real-time decision-making in UAVs.
Methods: The review comprehensively covers trajectory control techniques, which are essential for ensuring UAVs can navigate through dynamic environments safely and efficiently. This study outlines the use of IoT technologies, such as GPS, sensors, and communication networks, to enable precise trajectory planning, obstacle avoidance, and adaptive path adjustments. It also discusses the integration of machine learning and AI algorithms for autonomous UAV navigation, taking into account environmental factors, mission objectives, and real-time data from IoT sources. The paper further discusses the challenges and potential security concerns associated with IoT integration in UAVs, as well as the emerging trends and future prospects of this dynamic field. It emphasizes the need for standardized protocols and robust cybersecurity measures to ensure the reliability and safety of UAV-IoT systems.
Findings: This exhaustive review offers a comprehensive understanding of the synergistic relationship between UAVs and IoT, shedding light on the task offloading and trajectory control techniques that empower these autonomous aerial vehicles. By leveraging IoT technologies, UAVs are poised to continue transforming industries and driving innovation in ways previously unimaginable, making this interdisciplinary field an area of great promise and significance.

How to Cite

Prabakar, D., Kumar D.R., S., Kumar, R., M., C., K., S., Ragavendiran, S., & Vyas, N. K. (2023). Task offloading and trajectory control techniques in unmanned aerial vehicles with Internet of Things – An exhaustive review. The Scientific Temper, 14(04), 1352–1359. https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.4.43

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