Evaluating the Feasibility of Personalized Health Status Feedback to Enhance Worker Safety and Well-Being at Construction Jobsites
Publication: Construction Research Congress 2024
ABSTRACT
Advancements in wearable sensor technology and AI provide an excellent opportunity to monitor the health status of construction workers on-site. However, there is still a lack of efficient means of promptly communicating this information to workers without violating their privacy. This study evaluates the feasibility of providing personal feedback to construction workers regarding their health status while carrying out routine tasks. The proposed mechanism employs machine learning models and a decision tree to provide workers with timely private feedback and corresponding recommendations or risk mitigation strategies. As such, an experiment was conducted to evaluate the performance of the proposed feedback system as well as users’ perception of its usability. The findings revealed that the proposed feedback system could provide the workers with accurate and effective feedback regarding their health status, indicating the great potential to enhance worker safety and well-being at construction jobsites.
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Information & Authors
Information
Published In
Construction Research Congress 2024
Pages: 575 - 585
History
Published online: Mar 18, 2024
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Business management
- Computer programming
- Computing in civil engineering
- Ecosystems
- Employment
- Engineering fundamentals
- Environmental engineering
- Feasibility studies
- Labor
- Measurement (by type)
- Methodology (by type)
- Mitigation and remediation
- Occupational safety
- Personnel management
- Practice and Profession
- Public administration
- Public health and safety
- Research methods (by type)
- Safety
- Sensors and sensing
- Trees
- Vegetation
Authors
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