Optimizing Construction Project Management with Deep Learning-Based Image Classification for Site Monitoring
Keywords:
Deep Learning, Image ClassificationAbstract
The construction industry has long faced challenges related to project management, including monitoring worksite conditions, tracking project progress, and ensuring safety compliance. Traditional methods often rely on manual inspections and periodic reporting, which can be time-consuming and prone to errors. This paper examines the potential of deep learning-based image classification models to enhance construction project management through automated site monitoring. By employing advanced computer vision techniques, construction managers can gain real-time insights into worksite conditions, track project milestones more efficiently, and improve compliance with safety regulations. The study explores various deep learning models, discusses their applications in construction site monitoring, and presents case studies demonstrating their effectiveness. The findings suggest that integrating deep learning image classification into construction management practices can lead to significant improvements in productivity, safety, and project outcomes.
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References
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