Paper Title
REAL TIME MONITORING AND DETECTION OF PERSONAL PROTECTIVE EQUIPMENT IN CONSTRUCTION SITES
Article Identifiers
: Authors
Keywords
deep learning , data
Abstract
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. Deep learning models trained on extensive datasets process these inputs to detect the presence or absence of PPE, triggering instant alerts in cases of violations. The presented method uses the CNN algorithm that is based on convolutional neural networks. This system enhances worker safety by providing immediate feedback and streamlining compliance monitoring, reducing the need for manual inspections. Furthermore, the collected data offers valuable insights into safety practices, facilitating data-driven decision-making and continuous improvement in safety management. Despite environmental variability and privacy concerns, the benefits of real-time PPE monitoring systems including improved safety, efficiency, and regulatory compliance underscore their potential as essential tools in modern construction site operations.
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How To Cite (APA)
PRABAVATHI R, Bhuvaneshwari R, Tamilselvi R, & Apinaya P (July-2024). REAL TIME MONITORING AND DETECTION OF PERSONAL PROTECTIVE EQUIPMENT IN CONSTRUCTION SITES. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(7), g315-g318. https://ijnrd.org/papers/IJNRD2407534.pdf
Issue
Volume 9 Issue 7, July-2024
Pages : g315-g318
Other Publication Details
Paper Reg. ID: IJNRD_226048
Published Paper Id: IJNRD2407534
Downloads: 000122255
Research Area: Science & Technology
Author Type: Indian Author
Country: THIRUCHIRAPALLI, Tamil Nadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2407534.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407534
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