Monitoring Industrial Protection Gear Using Intelligent System

In this article, the problem of using an intelligent system to ensure the use of personal protective equipment (PPE) in industrial safety is discussed. The real-time solution provides fast feedback and easy-to-use monitoring to safety managers and users alike by combining sensors and machine learning algorithms. The analysis shows how it can improve industrial safety regulations and assesses its efficacy. Strategically placed sensors gather copious amounts of data about PPE compliance, and the system integrates wearable, vision-based, and environmental technologies. Novel techniques such as Computer vision algorithm is used object detection and recognition. SSD single-shot multi-box detectors and (YOLO) enable efficient object detection and quick PPE item identification. Furthermore, it has been observed that Region-based Convolution Neural Network(R-CNNs) increase workplace safety standards by improving the system's adaptability to variations in the usage of safety gear over time.