International Journal of Internet, Broadcasting and Communication

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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An Abnormal Worker Movement Detection System Based on Data Stream Processing and Hierarchical Clustering

  • Duong, Dat Van Anh (Department of Electrical, Electronic and Computer Engineering, University of Ulsan) ;
  • Lan, Doi Thi (Department of Electrical, Electronic and Computer Engineering, University of Ulsan) ;
  • Yoon, Seokhoon (Department of Electrical, Electronic and Computer Engineering, University of Ulsan)
  • Received : 2022.09.07
  • Accepted : 2022.09.14
  • Published : 2022.11.30
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Abstract

Detecting anomalies in human movement is an important task in industrial applications, such as monitoring industrial disasters or accidents and recognizing unauthorized factory intruders. In this paper, we propose an abnormal worker movement detection system based on data stream processing and hierarchical clustering. In the proposed system, Apache Spark is used for streaming the location data of people. A hierarchical clustering-based anomalous trajectory detection algorithm is designed for detecting anomalies in human movement. The algorithm is integrated into Apache Spark for detecting anomalies from location data. Specifically, the location information is streamed to Apache Spark using the message queuing telemetry transport protocol. Then, Apache Spark processes and stores location data in a data frame. When there is a request from a client, the processed data in the data frame is taken and put into the proposed algorithm for detecting anomalies. A real mobility trace of people is used to evaluate the proposed system. The obtained results show that the system has high performance and can be used for a wide range of industrial applications.

Keywords

Acknowledgement

This work was supported in part by the Institute of Information and Communication Technology Planning and Evaluation (IITP) Grant by the Korean Government through MSIT (Development of 5G-Based Shipbuilding and Marine Smart Communication Platform and Convergence Service) under Grant 2020-0-00869, and in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant 2021R1I1A3051364.

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