Real-Time Access Control System Method Using Face Recognition

2020 ◽  
pp. 101-108
Author(s):  
Mohammed Abdulhakim Al-Absi ◽  
Gabit Tolendiyev ◽  
Hoon Jae Lee ◽  
Ahmed Abdulhakim Al-Absi
Keyword(s):  
Control System ◽  
Face Recognition ◽  
Access Control ◽  
Real Time ◽  
System Method ◽  
Access Control System

Personal access control system using speech and face recognition

1988 ◽  
Vol 83 (3) ◽  
pp. 1211-1211
Author(s):  
Wolfgang H. Feix ◽  
Hartwig E. Ruell
Keyword(s):  
Control System ◽  
Face Recognition ◽  
Access Control ◽  
Access Control System

scholarly journals Access control system using beacon-based indoor location data pattern analysis

2018 ◽  
Vol 7 (2.12) ◽  
pp. 325
Author(s):  
Jae Gwang Lee ◽  
Jae Pil Lee ◽  
Eun Su Mo ◽  
Jun Hyeon Lee ◽  
Ki Su Yoon ◽  
...  
Keyword(s):  
Control System ◽  
Access Control ◽  
Real Time ◽  
Pattern Analysis ◽  
Behavior Pattern ◽  
Abnormal Behavior ◽  
Location Information ◽  
Indoor Location ◽  
Location Data ◽  
Access Control System

Background/Objectives: With the development of IT, accidents of industrial secret leakage have occurred more than before. Such acci-dents are mostly caused by insiders. Methods/Statistical analysis: An existing access control system uses RFID and NFC tag. The system saves only the final location in-formation in DB. For the reason, it is hard to track a user’s location data in real time. However, a beacon-based access control system saves a user’s location information in DB in real time. By analyzing the location information of DB, it is possible to track a user. Findings: Beacons are used for determining a user’s location. The determined location information is converted into location data which is saved into DB. The location data is converted into coordinates. The converted coordinate data is analyzed for understanding a user’s behavior pattern. In the pattern analysis, if a user takes an abnormal behavior, policy-based response is performed. The user behavior pattern analysis system proposed in this study is able to respond to an accident in real time. Therefore, it is expected to contribute to reducing the number of industrial secret leakage accidents caused by insiders. Improvements/Applications: This study designs a model that analyzes behavior pattern by using the indoor location data of a user based on beacon. 

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