Abstract

Tailgating is the one where an employee holds the office door for others to enter into the building with one access. This leads to insecure where in the unknown person can also enters into the building with the access of the original employee. To overcome this, introducing security system that prevents tailgating that provides authentication, accuracy, flexibility and gives more convenience to the security guards. It is an embedded based system and built under the Linux environment. First the faces of all the people is captured and trained using OpenCV python package for the purpose of further experimentation in the future. In this Raspberry pi is used as a main controller along with camera which enables to access image processing with any portable embedded system. When the person enters near to the gate, the ultrasonic sensor starts to sense and triggers the camera which detects the person face and checks with the trained dataset using the Haar Cascading algorithm, if it matches the gate gets opened. If suppose the person enters the gate with other person with one access control, then again, the camera gets triggered to capture the unauthorized person face and sends the mail of the detected person to the concerned authority through firebase cloud database.

Keywords

Face recognition, Face detection, open CV, Haar Cascading, Ultrasonic sensor, Raspberry pi,

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References

  1. T.W. Chan, V.V. Yap, C.S. Soh, (2012) Embedded Based Tailgating / Piggybacking Detection Security System, IEEE Colloquium on Humanities, Science & Engineering Research (CHUSER 2012), IEEE, 277-282.
  2. D. Nikhil Reddy, B. Mahadev, K.V. Achyuth, Sharmila Nagesawaran, (2018) Development of Security System to Prevent Tail-Gating, In2018 International Conference on Communication and Signal Processing (ICCSP), IEEE.
  3. R. Nandhini, NDuraimurugan, S.P. Chokkalingam, Facial Recognition Based Attendance System, International Journal of Engineering and Advanced Technology (IJEAT) 8 (2019) 574-577.
  4. R. Kannammaet al. / International Research Journal of Multidisciplinary Technovation2020; 2(5): 20-25
  5. N.S. Tummala, P.C.Sekar,(2017) Face Recognition Using PCA and Geometric Approach, In2017 International Conference on Computing Methodologies and Communication (ICCMC), IEEE, 562-565.
  6. M. Sahani, C. Nanda, A.K. Sahu, B. Pattnaik, Online Embedded Door Access Control and Home Security System Based on Face Recognition, International Conference on Circuit, Power and Computing Technologies [ICCPCT], IEEE, 1-6.