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Digital Twins for Worker Safety

Contact Person: Elias Montini


Technology

The main result of the Digital Twins for Worker Safety is the Fatigue Monitoring System (FaMS). The FaMS takes in input the worker’s physiological data from the devices enriched with static information, to compute physical fatigue exertion. The FaMS predicts the worker’s physical exertion on the Borg CR-10 Scale, and it helps in monitoring the overall safety level on the factory. The FaMS estimates the perceived exertion of workers based on static data (e.g., age, weight, height, hiring date, maximum heart rate, body fat, sex, working experience, grip strength, etc.), and dynamic data (e.g., current heart rate, skin temperature, galvanic skin response, etc.) of the worker.


Organisation

SUPSI offers more than 30 bachelor's and master’s degree courses, characterized by cutting edge education which merges classical theoretical-scientific instruction with practical orientation. Great focus is given to research, carried out in key domains for EU competitiveness, and funded on acquired projects within European or National frameworks. Within SUPSI, the Institute of System and Technologies for Sustainable Production (ISTePS) will participate to the project. The mission of the Institute is the innovation of products, manufacturing processes and business models in order to accompany companies in facing the challenges of globalization under the economic, environmental and social aspects. The fulfilment of the mission is achieved through the development of human capital and the innovation of production systems and technologies by means of education activities at bachelor, master and employment levels, as well as through research, development and technology transfer activities with reference to the life cycle of products and industrial processes, in the fields of design, automation and management of production systems and the relative value chains. Key research areas are: Sustainability and Personalization; Human in the Loop; Simulation Technologies; Automation and Control.

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