Intelligent Access Control for Valid Vehicles Using RFID and Helmet Detection for Bikes

Ghorpade Nayan Sanjay *, Kankariya Trupti Anil **, Kobarne Priyanka Babasaheb ***, S. N. Jadhav ****, Sharifa*****
*-***** Padmashri Dr. Vitthalrao Vikhe Patil Institute of Technology & Engineering Polytechnic Loni, Maharashtra, India.
Periodicity:January - June'2021
DOI : https://doi.org/10.26634/jic.9.1.18445

Abstract

This study describes an intelligent access control system for valid vehicles that uses RFID and bike helmet detection. The RFID and automatic licence plate recognition (ALPR) technologies are combined in this paper to create a hybrid system for vehicle access control. RFID technology has been shown to be a viable solution to a variety of tracking and location issues. The system, on the other hand, has flaws when it comes to tracking objects/users without a tag. As a result, we propose that this technology be supplemented with ALPR to control the access of various types of vehicles to the Mecca (Saudi Arabia) area during pilgrimage seasons. With so many vehicles seeking to enter, this little location can quickly become clogged. Vehicles authorised to enter the territory are given passive RFID tags that identify their allowed entry schedule before the season begins. ALPR is used to detect and identify violating automobiles that do not have RFID tags. Over the course of two pilgrimage seasons, the devised method was put to test. The ALPR system achieved 94 percent recognition accuracy of vehicles not equipped with RFID tags, whereas the designed RFID system was able to recognise all passing vehicles with speeds up to 100 km/h.This system stores all valid vehicle numbers, and when those vehicles pass through the gate, the gate will automatically open. If an unknown vehicle passes through, the gate will be closed and the alarm will sound as a warning. Another prerequisite for the bike is that the helmet must be worn. If the bike number is genuine but the helmet is not detected, the gate cannot be opened. A smart helmet is a sort of protective headgear worn by the rider that makes biking safer than it was previously. The main goal of this smart helmet is to keep the rider safe. This is accomplished by incorporating advanced features such as alcohol detection, resulting in not just a smart helmet but also a smart bike. A RF Module is a wireless interface that allows the transmitter and receiver to communicate.

Keywords

Access Control, Vehicles, RFID, Helmet Detection, Automatic License Plate Recognition (ACPR).

How to Cite this Article?

Sanjay, G. N., Anil, K. T., Babasaheb, K. P., Jadhav, S. N., and Lavhate, S. B. (2021). Intelligent Access Control for Valid Vehicles Using RFID and Helmet Detection for Bikes. i-manager's Journal on Instrumentation and Control Engineering, 9(1), 1-9. https://doi.org/10.26634/jic.9.1.18445

References

[1]. Divyasudha, N., Arulmozhivarman, P., & Rajkumar, E. R. (2019, April). Analysis of smart helmets and designing an IoT based smart helmet: A cost effective solution for Riders. In 2019, 1st International Conference on Innovations in Information and Communication Technology (ICIICT) (pp. 1-4). IEEE. https://doi.org/10.1109/ICIICT1.2019.8741415
[2]. Goudar, R. H., & Megha, H. N. (2017, August). Next generation intelligent traffic management system and analysis for smart cities. In 2017, International Conference On Smart Technologies for Smart Nation (SmartTechCon) (pp. 999-1003). IEEE. https://doi.org/10.1109/SmartTech Con.2017.8358521
[3]. Gudavalli, D. K. P., Rani, B. S., & Sagar, C. V. (2017, March). Helmet operated smart E-bike. In 2017, IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS) (pp. 1-5). IEEE. https://doi.org/10.1109/ITCOSP.2017.8303138
[4]. Gupta, S., Sharma, K., Salvekar, N., & Gajra, A. (2019, January). Implementation of alcohol and collision sensors in a smart helmet. In 2019, International Conference on Nascent Technologies in Engineering (ICNTE) (pp. 1-5). IEEE. https://doi.org/10.1109/ICNTE44896.2019.8945979
[5]. Jesudoss, A., Vybhavi, R., & Anusha, B. (2019, April). Design of smart helmet for accident avoidance. In 2019, International Conference on Communication and Signal Processing (ICCSP) (pp. 0774-0778). IEEE. https://doi.org/ 10.1109/ICCSP.2019.8698000
[6]. Karthikeyan, S., Singh, S., Jain, H. M., Kumar, M. S., & Priya, V. (2018, October). Smart and assistive driving headgear. In 2018, 3rd International Conference on Communication and Electronics Systems (ICCES) (pp. 335- 339). IEEE. https://doi.org/10.1109/CESYS.2018.8723943
[7]. Katsigiannis, S., Willis, R., & Ramzan, N. (2018). A QoE and simulator sickness evaluation of a smart-exercise-bike virtual reality system via user feedback and physiological signals. IEEE Transactions on Consumer Electronics, 65(1), 119-127. https://doi.org/10.1109/TCE.2018.2879065
[8]. Nanda, S., Joshi, H., & Khairnar, S. (2018, August). An IOT based smart system for accident prevention and detection. In 2018, Fourth International Conference on Computing Communication Control and Automation (ICCUBEA) (pp. 1-6). IEEE. https://doi.org/10.1109/ICCUBEA. 2018.8697663
[9]. Nataraja, N., &Mamatha, K. S. (2018, May). Smart helmet. In 2018, 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 2338-2341). IEEE.
[10]. Padmini, V. L., Kishore, G. K., Durgamalleswarao, P., & Sree, P. T. (2020, September). Real time automatic detection of motorcyclists with and without a safety helmet. In 2020, International Conference on Smart Electronics and Communication (ICOSEC) (pp. 1251-1256). IEEE. https://doi.org/10.1109/ICOSEC49089.2020.9215415
[11]. Preetham, D. A., Rohit, M. S., Ghontale, A. G., & Priyadarsini, M. J. P. (2017, December). Safety helmet with alcohol detection and theft control for bikers. In 2017, International Conference on Intelligent Sustainable Systems (ICISS) (pp. 668-673). IEEE. https://doi.org/10.1109/ ISS1.2017.8389255
[12]. Rahman, M. A., Ahsanuzzaman, S. M., Rahman, I., Ahmed, T., & Ahsan, A. (2020, June). IoT based smart helmet and accident identification system. In 2020, IEEE Region 10 Symposium (TENSYMP) (pp. 14-17). IEEE. https://doi.org/10.1109/TENSYMP50017.2020.9230823
[13]. Saumya, A., Gayathri, V., Venkateswaran, K., Kale, S., & Sridhar, N. (2020, September). Machine Learning based Surveillance System for Detection of Bike Riders without Helmet and Triple Rides. In 2020, International Conference on Smart Electronics and Communication (ICOSEC) (pp. 347-352). IEEE. https://doi.org/10.1109/ICOSEC49089. 2020.9215266
[14]. Singh, D., Vishnu, C., & Mohan, C. K. (2016, December). Visual big data analytics for traffic monitoring in smart city. In 2016, 15th IEEE international conference on machine learning and applications (ICMLA) (pp. 886-891). IEEE. https://doi.org/10.1109/ICMLA.2016.0159
[15]. Swathi, S. J., Raj, S., & Devaraj, D. (2019, April). Microcontroller and sensor based smart biking system for driver's safety. In 2019, IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS) (pp. 1-5). IEEE. https://doi.org/10.1109/ INCOS45849.2019.8951409
[16]. Vashisth, R., Gupta, S., Jain, A., Gupta, S., & Rana, P. (2017, September). Implementation and analysis of smart helmet. In 2017, 4th International Conference on Signal Processing, Computing and Control (ISPCC) (pp. 111-117). IEEE. https://doi.org/10.1109/ISPCC.2017.8269660
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