Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
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Article Number | 01289 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/e3sconf/202343001289 | |
Published online | 06 October 2023 |
Study on different types of sensors and Machine Learning Algorithms used for Surveillance Automobile System
School of Mechanical Engineering, KIIT deemed to be University, Bhubneswar, Odisha 751024, India
* Corresponding author: rubymishrafme@kiit.ac.in
A broad range of modern technologies is used for surveillance as well as security of passengers in automobiles. These technologies include face identification, fingerprint identification, Iris identification, and speaker recognition. Among these face recognition and fingerprint recognition are most commonly used for the surveillance of the vehicle. The demand for face identification in automobiles is increasing as it serves better than that fingerprint technology. The face identification system involves both face recognition and face detection. Researchers have tried to implement a face recognition system in automobiles to detect facial features from a captured image using different machine learning algorithms. This will prevent an unauthorized person to enter the car and will lock the ignition system until and unless the person is recognized. This paper gives a brief review on different types of sensors combined with processing unit and different types of machine learning algorithms used for the vehicle security and tracking system using different technologies.
Key words: surveillance / face recognition / machine learning algorithm / ignition / vehicle tracking system
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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