With the objective of improving life and workplace balance, prevention Occupational Service Health schemes are permanently being developed in various multi-businesses industry parks covering the multiple aspects of the Citizen wellbeing at home and workplace, physiotherapist, GP on demand including the adoption of Wearables, smart textiles, training and fitness data, home training.

In the context of the DIH4CPS project, the partners Uninova, KnowledgeBiz, and Produtech will conduct an application experiment which will establish a platform that collects data from workers and provides advice to the worker and to the enterprise’s human resources about the best strategies to keep the worker safe and fit at work and at home, with the purpose of  promoting worker’s safety and wellbeing.

The Problem

Workers suffer from different types of physiological and posture related problems due to work execution without advice and corrective measures. Such problems include: bad posture, risk of injury, long standing hours, trunk flexion, load lifting/pushing pulling, body vibration, tension of shoulders and back muscles, and so on. After work, older workers usually arrive home tired and just want to relax by being seated watching tv or reading a book. This consecutive routine will slowly deteriorate the person’s body and mind, and the situation is drastically increased by the lack of physical and mental exercises that can oppose the usual after work sedentary behaviour. Another problem is the place where persons usually sit or the mattress where they sleep may not be the most appropriate and can continue to deteriorate their health.

The Solution

The objective is to trigger real-time corrective notifications to older workers through the conversational interface, in order to reduce the risk of injury, but at the same time, to notify the worker and the human resources department, about causes affecting physical conditions of workers, so that preventive measures can be taken within the working environment.  In order to address problems of older workers that could occur at their home after work, older workers continue to be accompanied by the devices that they are wearing or that exist in their living environment.

The experiment will consist in establishing different modalities for data collection that will enable the reasoning and advice to workers improvement of posture, wellbeing and lifestyle. The implementation of the experiment is comprised of the following tasks:

• Design and implementation of Information gathering platform
• Design and implementation of user’s data collection systems (hardware and software)
• Machine learning Analytics – A.I. for improving systems efficiency and prediction methods
• System implementation, testing and training on a real world environment

Source

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