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Targeted intervention method for unsafe behavior based on pan-scene data of subway construction.
Bingqian Fan1, Ninghao Sun2, Ruipeng Tong2
1Department of Aviation Safety and Emergency Management, Civil Aviation Management Institute of China, China.
Summary
This study introduces a targeted intervention method using pan-scene data to control unsafe behavior in subway construction. The approach effectively identifies and manages risks, improving overall work safety.
Area of Science:
- Construction Safety
- Data Mining
- Behavioral Science
Background:
- Unsafe behavior in subway construction poses significant risks.
- Effective control of these behaviors is crucial for worker safety and project success.
- Existing safety data often remains underutilized.
Purpose of the Study:
- To propose a targeted intervention method for unsafe behavior in subway construction.
- To leverage pan-scene data for improved safety intervention.
- To enhance the value derived from work safety data.
Main Methods:
- Utilized pan-scene data theory to analyze 393 samples of unsafe behavior across six dimensions.
- Applied association rule data mining to identify intervention nodes.
- Developed 16 specific targeted intervention measures.
Main Results:
- The targeted intervention method demonstrated improvements in system construction, safety culture, and safety management.
- Association rule mining successfully located key intervention nodes.
- The method facilitated accurate identification and management of unsafe behaviors.
Conclusions:
- The proposed targeted intervention method offers novel strategies for modifying unsafe behavior.
- This approach enables precise identification, intervention, and management of workplace risks.
- Effective utilization of safety data can significantly enhance construction site safety.
