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Pattern extraction for high-risk accidents in the construction industry: a data-mining approach
Mehran Amiri1, Abdollah Ardeshir1, Mohammad Hossein Fazel Zarandi2
1a Civil and Environmental Engineering Department , Amirkabir University of Technology , Tehran , Iran.
Construction accidents, including falls and falling objects, were analyzed. Findings reveal key accident factors like time, location, and affected body parts, with higher risks during evening/night shifts and weekends for severe incidents.
Area of Science:
- Occupational Safety and Health
- Construction Industry Safety
- Accident Analysis and Prevention
Background:
- Falls and falling objects are frequent construction accidents (Group I).
- Vehicle collisions, electrocution, excavation collapses, fires, and explosions are less frequent but severe (Group II).
- Understanding accident patterns is crucial for improving safety in the construction sector.
Purpose of the Study:
- To analyze a comprehensive database of construction accidents in Iran (2007-2011).
- To identify significant correlations between accident characteristics and outcomes.
- To provide data-driven insights for enhancing construction safety protocols.
Main Methods:
- Utilized multiple correspondence analysis, decision tree, ensembles of decision trees, and association rules.
- Analyzed a national database of construction accidents spanning five years.
- Investigated relationships between accident variables such as time, location, body part affected, and consequences.
Main Results:
- Group I: Significant links found between accident time, location, affected body part, consequence, and lost workdays.
- Group I: Night shifts showed fewer accidents; head, back, spine, and limb injuries were more frequent.
- Group II: Accident time and body part affected were strongly related; married, older workers had higher accident frequency, especially during evening/night shifts and weekends.
Conclusions:
- The study identified critical factors contributing to both frequent (falls) and severe (vehicle, fire) construction accidents.
- Results align with previous research, reinforcing the importance of shift timing, worker demographics, and accident circumstances.
- Findings can inform targeted safety interventions to reduce accident rates and severity in the construction industry.
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