Personal Protective Equipment Detector Using Computer Vision

In an era of enormous global health issues, appropriate personal protective equipment (PPE) use is critical. This study presents a revolutionary solution for PPE identification that makes use of powerful computer vision algorithms. Deep learning models are used in our system to detect and recognize...

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Veröffentlicht in:2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE) S. 38 - 41
Hauptverfasser: M, Prabha, M, Karuppasamy, P, Saraswathi, K, Poorani, S, Aswin Kumar
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 22.11.2024
Schlagworte:
Computational modeling
Computer vision
Computer vision algorithms
Deep learning
Deep learning models
Detectors
Face recognition
Neural networks
Object detection
Object detection algorithms
Personal protective equipment
PPE
Real-time systems
Safety
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Zusammenfassung:In an era of enormous global health issues, appropriate personal protective equipment (PPE) use is critical. This study presents a revolutionary solution for PPE identification that makes use of powerful computer vision algorithms. Deep learning models are used in our system to detect and recognize important PPE components such as masks, gloves, and face shields in real-time video feeds or photos. Our application detects the presence of PPE and assesses its right usage and adherence to safety requirements by combining cutting-edge object detection algorithms and neural networks. This technology has enormous promise in a variety of areas, including healthcare, manufacturing, and public spaces, ensuring people's safety and well-being. The proposed PPE detector is an important step towards improving safety measures and lowering the danger of infection, thus contributing to a safer and healthier society.
DOI:10.1109/AECE62803.2024.10911791