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IoT Open-Source and AI based Automatic Door Lock Access Control Solution

  • Yoon, Sung Hoon (Department of Energy grid, Graduate School, Sangmyung University) ;
  • Lee, Kil Soo (KOGEN Co., Ltd) ;
  • Cha, Jae Sang (VTASK Co., Ltd) ;
  • Mariappan, Vinayagam (Graduate School of NID Fusion, Seoul National Univ. of Sci. & Tech.) ;
  • Young, Ko Eun (Graduate School of NID Fusion, Seoul National Univ. of Sci. & Tech.) ;
  • Woo, Deok Gun (IoT Convergence Research Technology Lab, Seoul National Univ. of Sci. & Tech.) ;
  • Kim, Jeong Uk (Department of Electrical Engineering, Sangmyung University)
  • Received : 2020.02.07
  • Accepted : 2020.02.17
  • Published : 2020.05.31

Abstract

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.

Keywords

References

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