Vol. 3 No. 2 (2023): Journal of AI-Assisted Scientific Discovery
Articles

Ethical Considerations in Deploying IoT Sensors for Anomaly Detection in Autonomous Vehicles

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  • Dr. João Madeira
Dr. João Madeira
Professor of Informatics, Instituto Superior Técnico (IST), Portugal
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Published 02-06-2023

Keywords

  • IoT,
  • Learning Methods
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. João Madeira, “Ethical Considerations in Deploying IoT Sensors for Anomaly Detection in Autonomous Vehicles”, Journal of AI-Assisted Scientific Discovery, vol. 3, no. 2, pp. 1–13, Jun. 2023, Accessed: Sep. 19, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/31

Abstract

In an effort to detect as many anomalies as possible, the transportation industry uses all kinds of sensors on different forms of transportation. Various types of sensors, ranging from simple and inexpensive wear sensors to the more expensive and complex temperature, smoke, fire, toxic gas, and liquid and chemical sensors, are used to monitor the health condition of the vehicle. To expand the detection of anomalies, deep learning methods have been successfully employed in an unsupervised fashion to analyze sensing data. These learned models will prompt the human or system operator about a problem in the vehicle operation. While current IoT sensors promise to provide never-ending streams of information regarding the health and status of vehicle transportation systems, caution needs to be taken to not interfere personally with the traveling passengers or the vehicle operator.

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