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 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.