Year: 2024
Type: article
Study design: Systematic Review
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.
DOI: 10.56294/mr2024.129
Authors: Leidy Laura Castellón Simancas, Naywin Olascoaga Tous, Lorena Mischell Carriazo Mendoza, Camila Castrillon Ramirez, Carlos Alberto Severiche Sierra
Institution: University of Cartagena
Language: English
Subfield: Radiological and Ultrasound Technology
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409278225