What are the current computer vision applications being utilized in the construction industry for safety purposes?
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Computer vision applications in the construction industry for safety purposes include object recognition models for worker presence, fall risk assessment, and safety gear compliance . Additionally, computer vision technologies like Computer Vision (CV), Internet of Things (IoT), and Convolutional Neural Networks (CNN) are employed for safety monitoring, productivity improvement, progress tracking, infrastructure inspection, and robotic applications on construction sites . Novel approaches like Multi-Domain Convolutional Neural Networks (MD-CNN) are developed to track objects accurately in dynamic construction environments, aiding in hazard prevention and worker monitoring . These technologies offer benefits such as real-time data monitoring, accurate prediction, and model development for on-site health and safety analytics, enhancing overall safety management in the construction sector.
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| Papers (5) | Insight |
|---|---|
| Computer vision applications like Convolutional Neural Networks and VGG16 are used in the construction industry to detect workers on-site and recognize safety equipment, enhancing safety management and instruction. | |
| Computer vision applications in construction safety include object recognition models for worker presence, fall risk assessment, and PPE compliance using image data from construction sites and virtual environments. | |
| Computer vision is extensively used in construction for safety by detecting hazards, enhancing prediction accuracy, real-time monitoring, and developing safety analytics models on-site, ensuring better health and safety management. | |
| Computer vision applications in construction for safety include object detection, object tracking, and image processing to monitor and enhance safety measures on project sites. | |
| Computer vision-based tracking, specifically MDNet, is utilized in construction sites for worker monitoring, hazard prevention, and safety enhancement, as demonstrated in the research. |
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