Machine Learning-Driven Visual Risk Assessments for Safety and Compliance in Project Management
Keywords:
Machine Learning, Visual Risk Assessments, Project Management, Computer Vision, Automation, Construction SafetyAbstract
The integration of machine learning and computer vision into project management represents a significant advancement in safety and compliance efforts. This paper explores how these technologies can automate visual risk assessments, enabling project managers to identify safety issues proactively and ensure compliance with regulations. By analyzing visual data collected from job sites, machine learning algorithms can detect potential hazards and compliance gaps in real time, significantly reducing the likelihood of accidents and costly delays. The research provides insights into various machine learning techniques applicable to visual risk assessments, highlights case studies demonstrating their effectiveness, and discusses the implications for project management practices. The findings suggest that adopting machine learning-driven visual assessments can lead to safer and more efficient project outcomes.
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