AI-Driven Predictive Analytics for Autonomous Vehicle Component Health Monitoring

Authors

  • Dr. Theophilus Akinbami Professor of Electrical Engineering, Federal University of Technology Akure (FUTA), Nigeria Author

Abstract

 Artificial Intelligence (AI) is making the high expense of oil a less significant factor in car development. AI enables such developments. Maintenance and repair costs can therefore be optimized. The enormous increase in the software and electronics content of cars enhances the efficiency of the automobile amongst other ways through the continued development of drive systems and AI-based driver assistance systems; it’s alleged that road accidents could be reduced in number by up to 90% by the deployment of self-driving cars. Since the use of self-driving cars at the moment is still highly restricted, our great hope and the technologies of the future surround the use of AI.[2] The enhancements in the vehicle performance obtained through faster performance of road and traffic automation can be appreciably limited under certain conditions by ominous developments in the automobile. Such limitations include the greatest safety risk currently occurring with self-driving cars.

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References

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Published

14-06-2023

How to Cite

[1]
Dr. Theophilus Akinbami, “AI-Driven Predictive Analytics for Autonomous Vehicle Component Health Monitoring”, Distrib Learn Broad Appl Sci Res, vol. 9, pp. 164–188, Jun. 2023, Accessed: Nov. 07, 2024. [Online]. Available: https://dlabi.org/index.php/journal/article/view/40