A Machine Learning-Based Safety Assessment Framework for Roadway Construction Projects in Flood-Prone Regions
Publication: Computing in Civil Engineering 2023
ABSTRACT
Transportation construction sites generally encompass unsecured materials, temporary facilities, various equipment, and structures that are incomplete which result in an unsafe area, especially during or after the occurrence of environmental disaster events such as floods or hurricanes. Improper and insufficient safety pre-assessment and measures planned before a project begins can cause not only physical and financial losses but also additional costs and delays, especially for a construction project in a disaster-prone area. To address the existing challenge, this study aims to predict potential safety hazards according to a jobsite condition and expected severe weather in roadway construction projects. The proposed framework adopts machine learning for safety assessment that is conducted based on a project schedule, occupational safety database, and flood zone areas. With the scope of flood disasters and roadway construction, the framework is expected to evaluate the impact of severe weather on roadway construction safety, identify the possible sources of work events, and predict the class of events for a project team to promote safe and resilient work environment against flood disasters.
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Information & Authors
Information
Published In
Computing in Civil Engineering 2023
Pages: 426 - 433
History
Published online: Jan 25, 2024
ASCE Technical Topics:
- Business management
- Construction engineering
- Construction equipment
- Construction industry
- Construction management
- Construction materials
- Construction sites
- Engineering fundamentals
- Engineering materials (by type)
- Equipment and machinery
- Floods
- Infrastructure
- Infrastructure construction
- Materials engineering
- Occupational safety
- Practice and Profession
- Project management
- Public administration
- Public health and safety
- Safety
- Traffic engineering
- Traffic management
- Traffic safety
- Transportation engineering
- Water and water resources
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