Vol. 1 No. 1 (2021): African Journal of Artificial Intelligence and Sustainable Development
Articles

Enhancing AV Fleet Management through IoT-enabled Predictive Maintenance and Cybersecurity Measures: Discusses how IoT-enabled predictive maintenance and cybersecurity measures can improve AV fleet management

Dr. Peter Ivanov
Professor of Artificial Intelligence, Lomonosov Moscow State University, Russia
Cover

Published 30-05-2021

Keywords

  • Autonomous Vehicles,
  • Fleet Management,
  • IoT

How to Cite

[1]
Dr. Peter Ivanov, “Enhancing AV Fleet Management through IoT-enabled Predictive Maintenance and Cybersecurity Measures: Discusses how IoT-enabled predictive maintenance and cybersecurity measures can improve AV fleet management”, African J. of Artificial Int. and Sust. Dev., vol. 1, no. 1, pp. 45–51, May 2021, Accessed: Nov. 24, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/35

Abstract

The advent of Autonomous Vehicles (AVs) has ushered in a new era of transportation, promising increased safety, efficiency, and convenience. However, managing and maintaining a fleet of AVs present unique challenges, particularly in terms of predictive maintenance and cybersecurity. This paper explores how IoT-enabled predictive maintenance and cybersecurity measures can enhance AV fleet management.

IoT-enabled predictive maintenance involves the use of sensors and data analytics to monitor the health of AVs in real-time, allowing for proactive maintenance to prevent breakdowns and optimize performance. Similarly, cybersecurity measures are crucial to protect AVs from cyber threats that could compromise their safety and functionality.

This paper first provides an overview of AV fleet management, highlighting the challenges faced in maintenance and cybersecurity. It then delves into IoT-enabled predictive maintenance, discussing its benefits and implementation strategies. Next, it explores cybersecurity measures for AVs, including encryption, authentication, and intrusion detection systems.

The paper also discusses the integration of predictive maintenance and cybersecurity, emphasizing the importance of a holistic approach to AV fleet management. Finally, it concludes with a discussion on the future prospects of IoT-enabled predictive maintenance and cybersecurity in enhancing AV fleet management.

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References

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  2. Tatineni, Sumanth. "An Integrated Approach to Predictive Maintenance Using IoT and Machine Learning in Manufacturing." International Journal of Electrical Engineering and Technology (IJEET) 11.8 (2020).
  3. Vemori, Vamsi. "Evolutionary Landscape of Battery Technology and its Impact on Smart Traffic Management Systems for Electric Vehicles in Urban Environments: A Critical Analysis." Advances in Deep Learning Techniques 1.1 (2021): 23-57.