System design of video surveillance

Authors

  • Mohanad Abdulhamid The Department of Electrical Engineering of AL-Hikma University, Baghdad, Iraq
  • Mwongeera Murungi The Department of Electrical Engineering of Nairobi University, Nairobi, Kenya

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2019.4.05

Keywords:

system design, video surveillance, CCTV

Abstract

This paper describes the steps involved in designing of a video surveillance system. It discusses the theory of video surveillance types, components involved, selection of the best equipment, and also a detailed virtual design. An introduction of the concept of video surveillance systems is followed by the detailed discussion of design considerations and the design verification. The system is designed to monitor a bank floor where the monitor displays the desired output from a simulated implementation of the system.

Author Biographies

Mohanad Abdulhamid, The Department of Electrical Engineering of AL-Hikma University, Baghdad

Mohanad Abdulhamid,

Ph.D. in electrical engineering, an assistant professor at the Department of Electrical Engineering of AL-Hikma University, Baghdad, Iraq.

Mwongeera Murungi, The Department of Electrical Engineering of Nairobi University, Nairobi

Mwongeera Murungi,

B.Sc. in electrical engineering, an assistant lecturer at the Department of Electrical Engineering of Nairobi University, Nairobi, Kenya.

References

Banu V. Intelligent video surveillance system /V. Banu, I. Costea, F. Nemtanu, B. Iulian // IEEE 23rd International Symposium for Design and Technology in Electronic Packaging. — Romania, 2017.

Raghunandan A. Object detection algorithms for video surveillance applications / A. Raghunandan, P. Raghav, H. Aradhya // IEEE International Conference on Communication and Signal Processing. — India, 2018.

Zhang D. Application of robust face recognition in video surveillance systems / D. Zhang, A. Peng, H. Zhang // Optoelectronics Letters. — 2018. — Vol. 14, Issue 2. — P. 152–155.

Sreenu G. Intelligent video surveillance: a review through deep learning techniques for crowd analysis / G. Sreenu, M. Durai // Journal of Big Data. — 2019. — Vol. 6, Issue 1. — P. 1–27.

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Published

2019-12-23

Issue

No. 4 (2019)

Section

Decision making and control in economic, technical, ecological and social systems

License

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