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Proceedings Paper

Surveillance of abnormal behavior in elevators based on edge computing
Author(s): Yan Qi; Ping Lou; Junwei Yan; Jiwei Hu
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Paper Abstract

Edge computing is an extension of the cloud computing paradigm that shifts part of computing data, applications and services from the cloud server to the network edge, providing low-latency, mobility and location-aware support for delaysensitive applications. The elevators in the high-rise buildings are geographically distributed and movable. Safety and reliability of elevators have attracted people’s attention. Security problem in the elevator is a key issue, especially in emergencies requiring fast response and low latency. In this paper, an elevator abnormal behavior video surveillance system is designed and developed using edge computing paradigm. The recognition of abnormal image sequences and the evaluation of abnormal behavior are realized. Collecting, processing, and analyzing video images are completed at the network edge in real time. The Edge computing nodes are distributed and deployed according to the geographic location of the elevator. The edge nodes are based on mobile embedded devices, and use the computing resources of the embedded devices to implement edge computing at the network edge. Through the edge network, there are several edge nodes based clusters being built to perform distributed computation tasks.

Paper Details

Date Published: 27 November 2019
PDF: 6 pages
Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 1132114 (27 November 2019); doi: 10.1117/12.2541397
Show Author Affiliations
Yan Qi, Wuhan Univ. of Technology (China)
Ping Lou, Wuhan Univ. of Technology (China)
Junwei Yan, Wuhan Univ. of Technology (China)
Jiwei Hu, Wuhan Univ. of Technology (China)


Published in SPIE Proceedings Vol. 11321:
2019 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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