A real-time control approach based on intelligent video surveillance for violations by construction workers

    Shengyu Guo Affiliation
    ; Chaohua Xiong Affiliation
    ; Peisong Gong Affiliation


The unsafe behavior of workers is the main object of construction safety management, in which violations require increased attention due to their pernicious consequences. However, existing studies have merely discussed violations separately from unsafe behaviors. To respond quickly to workers’ violations on site, this study proposes a real-time control approach based on intelligent video surveillance. First, scenes reflecting unsafe behaviors are automatically acquired through camera-based behavior analysis technology. Meanwhile, the time corresponding to the construction phase is recorded. Second, the temporal association rule model of worker’s unsafe behavior is constructed, and the rule “construction phase→unsafe behavior” is determined by the Apriori algorithm to identify target behaviors necessary for critical control in different construction phases. Finally, statistical process control is used to find the trends of violations with frequency and mass characteristics through the dynamic monitoring of target behavior. In addition, real-time alerts of these unsafe acts are produced simultaneously. A pilot study is conducted on the cross-river tunnel project in Wuhan city, Hubei, China, and the violations related to construction machineries is proven to be controllable. Thus, the proposed approach promotes behavioral safety management on construction since it effectively controls workers’ violations by real-time monitoring and analysis.

Keyword : unsafe behavior, violation, association rule, statistical process control, intelligent video surveillance

How to Cite
Guo, S., Xiong, C., & Gong, P. (2018). A real-time control approach based on intelligent video surveillance for violations by construction workers. Journal of Civil Engineering and Management, 24(1), 67-78.
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Mar 9, 2018
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This work is licensed under a Creative Commons Attribution 4.0 International License.


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