Mr. Yan Qi Profile

Yan Qi

at Wuhan University of Technology(Wut)

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Proceedings Article | 27 November 2019 Paper

Surveillance of abnormal behavior in elevators based on edge computing

Yan Qi, Ping Lou, Junwei Yan, Jiwei Hu

Proceedings Volume 11321, 1132114 (2019) https://doi.org/10.1117/12.2541397

KEYWORDS: Video, Clouds, Video surveillance, Target detection, Video processing, Detection and tracking algorithms, Computing systems, Sensors, Surveillance

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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.

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