Voice Controlled EV System and Locking System with Gesture Based Authentication

Mrs A Praveena; Putala Balanarayana; M Ajay; M S HariharaSudhan; P Johndev

doi:10.32628/IJSRST25121193

Authors

Mrs A Praveena Associate Professor , Department of C.S.E, Jansons Institute of Technology, Coimbatore, India Author
Putala Balanarayana UG Student, Department of C.S.E, Jansons Institute of Technology, Coimbatore, India Author
M Ajay UG Student, Department of C.S.E, Jansons Institute of Technology, Coimbatore, India Author
M S HariharaSudhan UG Student, Department of C.S.E, Jansons Institute of Technology, Coimbatore, India Author
P Johndev UG Student, Department of C.S.E, Jansons Institute of Technology, Coimbatore, India Author

DOI:

https://doi.org/10.32628/IJSRST25121193

Keywords:

Voice Recognition, Gesture-Based Authentication, Mel-Frequency Cepstral Coefficients, Computer Vision, Electric Vehicle, Security, Biometric Authentication, Smart Vehicle Access, Signal Processing, Machine Learning, Human-Vehicle Interaction

Abstract

The "Voice Controlled EV System and Locking System with Gesture-Based Authentication" introduces an advanced vehicle security and accessibility solution by integrating voice recognition using Mel-Frequency Cepstral Coefficients (MFCC) and gesture-based authentication via computer vision. This dual-layered system eliminates the need for traditional keys, enhancing both security and convenience by requiring specific voice commands and hand gestures for vehicle access and control.

The primary objective is to develop a robust framework that ensures only registered users can unlock and operate the vehicle through authenticated voice and gesture inputs. By merging these technologies, the project creates an intuitive interface while improving system security and reliability. This aligns with the growing demand for smarter, connected vehicles, making it a timely innovation in the automotive sector.

The methodology combines expertise in electrical engineering, computer science, signal processing, and motor control systems. The voice recognition module leverages MFCC for accurate speech feature extraction, while the gesture authentication system uses image processing and machine learning for reliable hand movement detection. These subsystems are integrated with a microcontroller-driven motor system that executes validated commands.

The project follows a systematic development process, including standalone module creation, integration, and real-world testing to ensure efficiency and reliability. By replacing conventional access mechanisms with voice and gesture controls, this innovation enhances user experience, addresses modern security challenges, and sets a new benchmark for intuitive vehicle interaction.

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References

Dr. ChandraSekhar.P e.tl.,”Vehicle Security system with facial and voice recongnition,” International Journal of Scientific Research and Engineering Development-– Volume 7 Issue 2, Mar-Apr 2024 .

M. Jie Zhang e.tl,.”intelligent user identity authentication in vehicle security system based on wireless signal”, Complex & Intelligent Systems (2022) 8:1243–1257. DOI: https://doi.org/10.1007/s40747-021-00593-6

R. K. Sehgal and M. Sharma, "A secure gesture based vehicle locking system using deep learning," IEEE Access, vol. 8, pp. 51705–51716, April 2020.

V. Nguyen, T. Le, and A. Patra, "Design and implementation of IoTenabled gesture recognition systems in automotive applications," Proceedings of the IEEE International Conference on Internet of Things, pp. 254– 259, Dec. 2019.

A. Zhang and X. Lin, "Security and privacy analysis of modern voice driven systems," Proceedings of the IEEE Conference on Communications and Network Security (CNS), pp. 1–9, Oct. 2018.

S. Kumar and S. S. Solanki, "Voice and touch control home automation," 2016 3rd International Conference on Recent Advances in Information Technology (RAIT), Dhanbad, 2016+, pp. 495-498. DOI: https://doi.org/10.1109/RAIT.2016.7507951

Kumar v, Sundara. (2015). MEMS based Hand Gesture Wheel Chair Movement Control for DisablePersons.5.17741776.10.14741/Ijcet/22774106/5. 3.2015.48. (EECCIS), Malang, 2014, pp. 142-146.

Shashank H, PradyathHehde, ”MEMS based device for physically challenged Proceedings of 10th IRF International Conference, 04th October2014, Bengaluru, India, ISBN: 978-93-84209- 56-8.

N. bt Aripin and M. B. Othman, "Voice control of home appliances using Android," 2014 Electrical Power, Electronics, Communicatons, Control and Informatics Seminar.

N. bt Aripin and M. B. Othman, "Voice control of home appliances using Android," 2014 Electrical Power, Electronics, Communicatons, Control and Informatics Seminar. DOI: https://doi.org/10.1109/EECCIS.2014.7003735

R. piyare, M.Tazil, “Bluetooth based home automation system using cell phone”, 2011 IEEE 15th International symposium on consumer Electronics. DOI: https://doi.org/10.1109/ISCE.2011.5973811

D. Kim, S. Oh, and J. Kim, "Vision based hand gesture recognition for vehicle access control," IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 3, pp. 807–817, Sept. 2011