Project Summary and Main Technological Topics
The project focuses on the integration of digital twins and artificial intelligence (AI) to improve worker safety in the manufacturing sector. Thanks to real-time data collected from IoT sensors, accurate virtual representations of work environments are created, used to monitor, analyze, and predict physical risks. This proactive approach enables the implementation of preventive measures and improves productivity and operational efficiency.
Main Project Phases:
- Analysis and Planning: study of needs and initial design.
- Digital Twin Creation: development of virtual representations of the work environment.
- AI Model Development: implementation and training of predictive algorithms.
- Monitoring System Implementation: integration of IoT sensors with the digital twin.
- Pilot Phase: testing and validation in a real industrial context.
- Digital Twin: creation of dynamic virtual models to simulate scenarios and identify risks in real time.
- Artificial Intelligence: use of advanced algorithms for predictive analysis and accident prevention.
- IoT (Internet of Things): real-time data collection through sensors and connected devices.
- Human Digital Twin (HDT): monitoring the physical, mental, and emotional state of workers.
- Predictive Maintenance: simulation and analysis to prevent failures and optimize production processes.
- Human Digital Twin (HDT) in Industry 5.0: use of AI to analyze stress, anxiety, and other factors affecting worker safety.
- Fujitsu’s Actlyzer: technology to map movements and machinery in a three-dimensional space, optimizing the layout of work environments.
- AI for Worker Safety: implementation of monitoring systems that provide early warnings and suggest preventive measures.
- Improvement of worker safety and well-being.
- Reduction of production costs and downtime.
- Optimization of workplace design.
- Increase in competitiveness through the adoption of innovative technologies.
