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Publication

Multiple Safety Equipment’s Detection at Active Construction sites Using Effective Deep Learning Techniques

Author/Presenter: Tyagi, Rashu; Thomas, K.T.
Abstract:

The safety of human labour is the most important thing in this era no matter where the labour force works. Governments and various NGOs focus on ensuring the delivery of the top safety to the labor class of the country. One such example is the working of the labour force at huge construction sites. For them a lot of work includes a huge amount of risks hence following full safety is the need of the hour for the workers working at construction sites. In order to deal with proper monitoring of the safety being followed at Construction sites. In order to make use of the latest technologies in this field also some of the good object detection models can be used for detecting the safety equipment of the workers which include things like Hard Hats, Masks, Vest, Boots. A lot of research is going on in improving the detection speed and accuracy of objects using state-of-the-art techniques in Computer Vision and this could lead to providing better results. Based on the available research and compute resources future work can be done to improve the results in this specific domain also.

Source: 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI)
Publication Date: 2022
Source URL: Link to URL
Publication Types: Books, Reports, Papers, and Research Articles
Topics: Computer Vision; Construction Sites; Detection and Identification; Machine Learning; Protective Clothing; Worker Safety

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