Published Paper Details:

Wearing a safety helmet while working is crucial for protecting workers from head injuries, which can range from mild to severe. In construction sites, workers are often exposed to hazardous materials, dangerous machinery, and other potential hazards that can cause head injury. A safety helmet can help to prevent head injuries by absorbing the impact of a falling object or other traumatic force. This paper to develop a deep learning- based system for detecting the presence and proper wear of construction workers safety helmets. The presented method uses the CNN algorithm that is based on Convolutional Neural Networks. The system will be trained on a large dataset of annotated images to accurately recognize and classify various types of safety helmets and their proper wear. This system has the potential to significantly improve the efficiency and accuracy of construction safety inspections, reducing the risk of head injuries and promoting a safer working environment.