Advanced Multi Location IoT Enabled Smart Car Parking System with Intelligent Face Recognition

Authors

  • Sumit Das Masters Student, School of Computing, SRM Institute of Science and Technology, Chennai, India
  • R. Kayalvihzi Assistant Professor, Department of Networks and Communication, SRM Institute of Science and Technology, Chennai, India

Keywords:

smart city, face recognition, smart car parking

Abstract

Smart city applications are increasingly being used in many countries because of the positive effects they have on citizens' quality of life and the environment through more efficient use of resources. Parking garages in smart cities typically have better access management and space distribution to cut down on congestion and wait times in high-density commercial zones. The human face is crucial in communication because it reveals a person's individuality. Biometric facial recognition technology, which uses a person's appearance as a means of identification, has gained a lot of popularity. In recent years, face recognition technology has become increasingly common because the user does not need to make any kind of physical touch with the device. The authentication process involves scanning the user's face and cross-referencing it with a database for verification. Additionally, it is easy to set up and doesn't necessitate any costly hardware. The usage of facial recognition technology is widespread across many different types of security systems, such as those used to manage physical access or computer user accounts. It is essential to monitor and manage the access of automobiles to parking places in order to improve the safety and security measures that are in place around the world. This article presents a study of face recognition-based access control system for vehicles entering the park, which can be conveniently deployed at the parking lot entrance.

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Published

09-01-2024

Issue

Section

Articles

How to Cite

[1]
S. Das and R. Kayalvihzi, “Advanced Multi Location IoT Enabled Smart Car Parking System with Intelligent Face Recognition”, IJRESM, vol. 7, no. 1, pp. 5–10, Jan. 2024, Accessed: Nov. 21, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/2910