Building Control Box Attached Monitor based Color Grid Recognition Methods for User Access Authentication



The secure access the lighting, Heating, ventilation, and air conditioning (HVAC), fire safety, and security control boxes of building facilities is the primary objective of future smart buildings. This paper proposes an authorized user access to the electrical, lighting, fire safety, and security control boxes in the smart building, by using color grid coded optical camera communication (OCC) with face recognition Technologies. The existing CCTV subsystem can be used as the face recognition security subsystem for the proposed approach. At the same time a smart device attached camera can used as an OCC receiver of color grid code for user access authentication data sent by the control boxes to proceed authorization. This proposed approach allows increasing an authorization control reliability and highly secured authentication on accessing building facility infrastructure. The result of color grid code sequence received by the unauthorized person and his face identification allows getting good results in security and gaining effectiveness of accessing building facility infrastructure. The proposed concept uses the encoded user access authentication information through control box monitor and the smart device application which detect and decode the color grid coded informations combinations and then send user through the smart building network to building management system for authentication verification in combination with the facial features that gives a high protection level. The proposed concept is implemented on testbed model and experiment results verified for the secured user authentication in real-time.


1. Introduction
2. Proposed Building Facility Control Box Access Authentication Approach
3. Building Facility Control Box User Access Authentication Algorithm
4. Experimental Result and Analysis
5. Conclusion


  • Sung Hoon Yoon Ph.D Candidate, Department of Energy grid, Graduate School, Sangmyung University, KOGEN Co., Ltd, Korea
  • Kil Soo Lee KOGEN Co., Ltd, Korea
  • Jae Sang Cha VTASK Co., Ltd, Korea
  • Timur Khudaybergenov PhD Course, Graduate School of NID Fusion, Seoul National Univ. of Sci. & Tech., Korea
  • Min Soo Kim PhD Course, Graduate School of NID Fusion, Seoul National Univ. of Sci. & Tech., Korea
  • Deok Gun Woo IoT Convergence Research Technology Lab, Seoul National Univ. of Sci. & Tech., Korea
  • Jeong Uk Kim Professor, Department of Electrical Engineering, Sangmyung University, Seoul, Korea


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