Herramienta digital para el procesamiento de imágenes mediante un algoritmo de aprendizaje supervisado para la identificación de patrones de levantamiento de cargas y emisión de alertas tempranas de riesgo ergonómico.

Abstract

Digital tool for image processing using a supervised learning algorithm to identify lifting patterns and issue early warnings of ergonomic risk. The system uses a webcam to capture images in real time and a supervised learning algorithm that analyzes the biomechanics of postures in a controlled environment. When inadequate postures are identified, alerts are generated that allow immediate correction, improving safety and reducing occupational risks. A problem in Occupational Safety and Health (OSH) lies in the difficulty of simultaneously supervising several employees in physical activities, especially where space is limited. Traditional observation methods are often biased and inefficient. This automated system optimizes supervision and facilitates the detection of risks in an objective manner. The proposed solution integrates technological devices, communication networks and programming based on supervised learning for the review of postures during lifting. As a result, it facilitates real-time decision making in controlled work environments. The implementation of this system represents an advance in the prevention of musculoskeletal disorders, optimizing occupational health and safety surveillance processes and enabling more efficient occupational risk management.