Vehicle Safety System with Arduino-Based Face Detection Technique

Authors

  • Mira Mira Politeknik Negeri Malang, Indonesia
  • Samsul Hadi Politeknik Negeri Malang, Indonesia
  • Arif R Fachrudin Politeknik Negeri Malang, Indonesia
  • Sugeng Hadi Susilo Politeknik Negeri Malang, Indonesia
  • Rilis Eka Perkasa Politeknik Negeri Malang, Indonesia

DOI:

https://doi.org/10.51278/aj.v3i3.282

Keywords:

Vehicle Safety System,, Face Detection,, Arduino-Based Face Detection

Abstract

Security systems on vehicles with alarms have been widely applied to detect the presence of thieves. But the system cannot tell the difference between a vehicle owner and a thief, so the security level is very low. The aim of this study is to recognize the vehicle owner's face and distinguish it from the thief's face. Face recognition is a technology from a computer that allows us to identify or verify a person's face through a digital image. The trick is to match the texture of our facial curves with facial data stored in the database. The vehicle security system using Face Recognition is a system that is very helpful in securing the vehicle from theft when the owner leaves it. The vehicle can only be started by detecting the owner's face which has been entered in the system database. If the driver's face is not recognized and is not in the system database, this tool will automatically sound an alarm and turn off the ignition of the vehicle so that it cannot be turned on. In this study, four facial samples were included in the database which was identified as the owner of the vehicle. And four samples of faces that were not entered in the database as foreigners or non-owners of the vehicle. The result of the research is that only facial samples registered in the database can start the vehicle. While samples outside the database cannot start the vehicle.

Keywords: Vehicle Safety System, Face Detection, Arduino-Based Face Detection

References

Ambadi P, Joyal Johnson. “Security System Based on Face Detection” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering. 2017
E.Francy Irudaya Rani, R.Vedhapriyavadhana, S.Jeyabala.”Attendance Monitoring Using Face Recognition with Message Allert” Indo Iranian Journal of Scientific Research (IIJSR). 2018
Nethravati B, Sinchana SS, Anil BC . “Advanced Face Recognition Based Door Unlock System using Arduino” International Journal of Recent Technology and Engineering (IJRTE). 2019
Maneesh Ayi, Ajay Kamal Ganti, Maheswari Adimulam “Face Tracking and Recognition Using Matlab and Arduino” International Journal for Research in Applied Science & Engineering Technology (IJRASET). 2017
Bahajathul Fathema, Bandlamudi Ravali. “Real Time Face Detection Using Matlab” International Journal of Engineering Research and Technology (IJERT) 2018
Hsu, Rein-Lien, Mohamed Abdel-Mottaleb, and Anil K. Jain. "Face detection in color images." Pattern Analysis and Machine Intelligence, IEEE Transactions on 24.5 (2002): 696-706L. Daewon, S. Hanbyul, B. Clerckx, E. Hardouin, D. Mazzarese, S. Nagata dan K. Sayana, "Coordinated multipoint transmission and reception in LTE-advanced: deployment scenarios and operational challenges," IEEE Commun. Magazine, vol. 50, no. 2, pp. 148-155, 2012.
MayankChauha and MukeshSakle. ?Study & Analysis of Different Face Detection Techniques.? International Journal of Computer Science and Information Technologies, Vol. 5 (2), 2014, 1615-1618.
Surya Sujarwo, Aswin Wibisurya. “Door Security System for Home Monitoring Based on ESP 32”ICCSI 2019
K. Zhang, Z. Zhang, Z. Li and Y. Qiao, "Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks," in IEEE Signal Processing Letters, vol. 23, no. 10, pp. 1499-1503, Oct. 2016, doi: 10.1109/LSP.2016.2603342.
Marella Nagendra Babu, P Murali Khrisna. “Hand Gesture Based Camera Monitoring System Using Raspberry Pi” IRJET 2019
N. Y. L. Venkata, C. Rupa, B. Dharmika, T. G. Nithin and N. Vineela, "Intelligent Secure Smart Locking System using Face Biometrics," 2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT), 2021, pp. 268-273, doi: 10.1109/RTEICT52294.2021.9573869.

Downloads

Published

2021-11-27

How to Cite

Mira, M., Hadi, S., Fachrudin, A. R., Susilo, S. H., & Perkasa, R. E. (2021). Vehicle Safety System with Arduino-Based Face Detection Technique. Attractive : Innovative Education Journal, 3(3), 196–202. https://doi.org/10.51278/aj.v3i3.282

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.