# Individual Environmental Risk Assessment and Management in Industry 4.0: An IoT-Based Model
## 4 Discussion
In addition, none of the proposals mentioned the analysis of the health history of workers using artificial intelligence techniques. This is a big issue for future works and will be addressed in the next stage of our work. In treating privacy concerns from an employee perspective, according to [51], devices such as wearable wristbands are widely used in workplaces to continuously collect personally sensitive data, such as geolocation. The data are transferred through wireless networks, and the potential threat to the individual's privacy can make the employees unsure about using any wearable devices [52]. Another point that deserves attention is that, despite its important role in health and safety purposes, extending the use of wearable devices from the professional to the private domain can invade employees' privacy and cause psychological pressure. Anyway, the successful use of a solution depends on several factors, such as acceptance of workers and risk variability. It is very important to note that the difficulty of implementing new technologies can vary significantly according to the activity. For example, in construction sites, there are many hazards for workers, and because tasks change as construction progresses, monitoring hazards in these workplaces can be a very complex task [53]. On the other hand, warehouses and storerooms can also present a variety of risks, such as dust, sedentary work, and insufficient lighting, but due to the nature of the activities, which present some regularity, the risks become easier to measure. As mentioned above, in the context of Industry 4.0, new possibilities for risk assessment and mitigation arise. However, new risks emerge from the interaction of humans with machines and robots, while mental illness becomes increasingly common, along with the worsening of conditions such as obesity resulting from sedentary jobs [9, 10]. As discussed in [54], concerning legislation, noting the transformations in the industry over the years, it is possible to note that the approach to OSH changed altogether. Labor unions, laws, regulations, and standards emerged in industrialized countries, and workplace conditions have significantly improved in recent decades. OSH law and regulation play an important role in obliging industries to meet safety standards. Concerning OSHstandards and legislation, updates in response to technological progress are critical because, aside from systems to help with the promotion of safer workplaces, dangerous innovations could be installed in industries as well. Smart PPE and environmental monitoring systems in general should be mandatory in work environments to allow companies to obtain large volumes of data that can direct actions in OSH, especially in activities with higher risk, such as construction and mines. Although costs can be challenging, especially for small and medium-sized companies at first, the popularization of the use of these devices and the emergence of new manufacturers tend to contribute to making costs viable. In the future stages of our project, as mentioned above, the monitoring device will be tested with all its sensors and then integrated with the server-side applications; new settings and graphs will be added to Grafana, and an additional configuration must be performed in Telegraf to write new data in InfluxDB. The list of diseases that can be registered on the server will be populated with the help of at least two physicians to maintain consistency. If they do not agree, a third doctor will be consulted. Regarding the artificial intelligence module, the relationship between possible future diseases and exposure to hazardous agents will be built based on the extensive literature available on the subject and will be validated by the same doctors, using the same criteria for cases of disagreement. Then, usability tests will be performed in a real work context (industrial environment). The criteria for participant recruitment are explained below.