Artificial intelligence tools for safety and health systems at work

Abstract

A systematic review of the literature was carried out, key technologies such as machine learning, computer vision, wearable devices and intelligent monitoring systems are identified. These tools are applied in accident prevention, continuous monitoring of workers’ health, automation of surveillance and improvement of safety training. The implementation of predictive AI makes it possible to identify risks and prevent accidents, reducing the incident rate and improving safety. Wearable devices and biometric sensors are effective in the early detection of occupational diseases and musculoskeletal disorders. Additionally, automating surveillance with computer vision optimizes compliance with safety standards, such as the use of personal protective equipment (PPE), easing the operational burden on security managers. Despite its benefits, the implementation faces ethical and technical challenges, such as data privacy, algorithm transparency, and worker training. The need to develop clear regulations and an ethical approach in the adoption of AI is highlighted. In conclusion, AI tools have great potential to transform occupational health and safety systems, but it is essential to address ethical challenges and technicians to guarantee its responsible and effective implementation.