# Smart Detection System of Safety Hazards in Industry 5.0
## 1 Introduction  
Over the years, numerous industrial revolutions took place, transforming the industrial scene. These evolutionary phases introduce the progressive integration of novel technologies into manufacturing procedures, aiming to enhance efficiency, productivity, and economic growth. Nowadays, Industry 5.0 is emerging, placing humans at the center of production. Specifically, the human-centered Industry 5.0 emphasizes the integration of smart technologies, automation, and data exchange in manufacturing. Beyond the human-centric focus of the Fifth Revolution, it also induces increased resilience and an improved emphasis on sustainability. The human-centric Industry 5.0 places a high priority on employee safety in manufacturing, emphasizing a knowledge-driven approach to human-machine-environmental safety. Intelligent safety management that goes beyond conventional measures becomes necessary to deal with complex human-machine-environment interactions. Moreover, based on the capabilities and opportunities of Industry 5.0, it becomes pivotal to design and develop safety management strategies that not only address the unique challenges of each manufacturing setting but are also robust enough to be adapted across varying operational landscapes. By leveraging advanced technologies, an efficient, flexible, and adaptable monitoring system can be established. Specifically, object detection algorithms can be integrated into video surveillance systems to analyze the footage in real-time and identify potential hazards within an industrial environment. However, the accuracy of such a complex process, based on AI methods, is strongly dependent on datasets. The acquisition of real data poses significant challenges both in terms of cost and safety, specifically in cases where human participation is required. Especially in hazardous environments, such as manufacturing, obtaining real data involves significant risks, mainly concerning the safety of personnel involved in data collection. Those challenges can be addressed by utilizing game development platforms, such as Unity, to generate high-quality synthetic data via virtual reality (VR). This not only diminishes the time spent on data collection and annotation but also substantially reduces the requisite human effort and cost. Moreover, synthetic datasets can be created to accommodate the specifics of various industrial scenarios. VR acts as an immersive simulation tool, offering safe and controlled environments that mimic real-world scenarios. VR is utilized in various fields, such as education, healthcare, engineering, etc., with potential enhancements through sensors available in VR systems [1]. One of the fundamental methods to protect workers is to monitor and control their exposure to hazards, as well as to detect and identify potential risks in the workplace. According to the National Institute for Occupational Safety and Health (NIOSH) in the U.S., the sequence of control measures begins with the utilization of personal protective equipment (PPE), which refers to specialized gear or clothing intended to protect individuals from potential hazards in the workplace. PPE is used to minimize the risk of injury or exposure to various physical or other types of hazards. Some examples of PPE include safety helmets, vests and other protective clothing, safety goggles, etc. In this research paper, we delve into the importance of a flexible and adjustable detection system of safety hazards for Industry 5.0. Initially, we analyze the five industrial revolutions. More focus is given to Industries 4.0 and 5.0, presenting the benefits of them as well as the needs that pushed the advent of the fifth revolution. Additionally, considering the human-centric nature of Industry 5.0, we examine the necessity of flexible and adaptable safety management methods in manufacturing, leveraging advanced technologies, and highly respecting human-machine-environment interactions.