| Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01066 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/e3sconf/202343001066 | |
| Published online | 06 October 2023 | |
Secure Information System for Visitor Access Recognition using Machine Learning
1 Department of Computer Science and Engineering, GokarajuRangaraju Institute of Engineering and Technology, Hyderabad India
2 Uttaranchal Institute of Management, Uttaranchal University, Dehradun, 248007, India
* Corresponding author: bmadhaviranjan@yahoo.com
Typical visitor access apps are usually passive/manual. The security guards in highly populated communities have to verify the identity of the visitors every single time, be it the residents or new people. This process is also time-consuming. Availability of the resident is also essential to approve the entry. VISITOR ACCESS is a better substitute for the regular visitor access systems. The process starts with choosing the house number and the name initially. When there is a known person, the visitor is verified, recognized, and approved to enter. If the visitor is unknown, he or she is asked to enter a few more details, which are sent to the resident’s mobile. A message is sent to the visitor’s mobile regarding the approval status to deal with the case of multiple visitors. Open CV is used to verify the identity of the visitors using face recognition, and the app acts as an interface between the users and the 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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.