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Scalable architecture for an automated surveillance system using edge computing

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Abstract

Over the past few years, the Internet of Things has gone from theoretical concept to our everyday living experience. The explosive growth of sensor streams also leads to a new paradigm of edge computing. In the surveillance system, edge-based automation is crucial to get fast response for fast data analytics among connected devices. In this paper, we propose an automated surveillance system to improve robustness and intelligence. Our scalable architecture is an alternative way of reducing the server resource and wireless network limitation.

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Acknowledgments

This work was supported by the ICT R&D program of MSIP/IITP [R0126-15-1067, Development of Hierarchical Data Stream Analysis SW Technology for Improving the Realtime Reaction on a CoT (Cloud of Things) Environment].

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Authors and Affiliations

  1. Big Data Intelligence Research Department, Software and Contents Research Laboratory, Electronics and Telecommunications Research Institute, Daejeon, Korea

    Hwin Dol Park, Ok-Gee Min & Yong-Ju Lee

  2. Department of Computer Software, University of Science and Technology, Daejeon, Korea

    Hwin Dol Park & Yong-Ju Lee

Authors
  1. Hwin Dol Park
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  2. Ok-Gee Min
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  3. Yong-Ju Lee
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Correspondence to Yong-Ju Lee.

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Park, H.D., Min, OG. & Lee, YJ. Scalable architecture for an automated surveillance system using edge computing. J Supercomput 73, 926–939 (2017). https://doi.org/10.1007/s11227-016-1750-7

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  • DOI: https://doi.org/10.1007/s11227-016-1750-7

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