A Review : Office Monitoring and Surveillance System
Facial recognition is a biometric software category that mathematically maps the facial features of a person and stores the data as a face-print. Using machine learning algorithms, the software compares a live capture or digital image to the stored face print to verify an individual's identity and help automate authentication. Facial recognition will increase protection, recognize unauthorized entry and keep a track of visitors. ID passes are yesterday’s technology. A conventional security-guard system is not an easy job and it’s impossible to catch everything. For eg, in a big organization, a security guard might not recognize who is the employee and who the visitor. Likewise, retired workers who hold their old door passes. Every security guard must be informed of all these things. Also, the most professional and attentive security guard would have breaks and get distracted while dealing with some other issues. This allows the intruder to get unapproved access to the building. In our project, an effort has been made to deal with risks from unauthorized entry, fraud, and theft. Our project's main task is to identify if the person is an employee or a visitor by using a face recognition system where in security guards job is to watch over the process and stepping in only when the system says that the person is not an employee or when they see something suspicious. Other features include the admin/managers having a complete report of the incoming and outgoing flow of visitors and employees in the office premises in a statistical format they can directly access the list of the visitors who have visited and who are going to visit the office premises, the most important function of the surveillance system is keeping a track on the frequency of incoming and outgoing employees and visitors. The key role of the employee in this system is to provide relevant information regarding the visitor who will be visiting. In this way, our system will be able to achieve security and surveillance for the office organization
Year of publication: |
2020
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Authors: | Patil, Vishal ; Ashra, Jay ; Gajinkar, Mehul ; Faizee, Sakina |
Publisher: |
[S.l.] : SSRN |
Saved in:
freely available
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