Periodic Reporting for period 2 - WorkingAge (Smart Working environments for all Ages)
Período documentado: 2020-08-01 hasta 2022-07-31
WorkingAge seeks to improve the well-being of people over 45 years old, especially in the work environment for office, manufacturing and teleworking workplaces. It also considers the workers daily activities outside work.
With the changing demography and rising of the retirement age, the European workforce is ageing. Older workers have specific conditions that need a specific response to maintain/improve their well-being, supporting motivation to stay working at higher age and enable better productivity.
WorkingAge project aims at making a step forward in technology for new working environment possibilities. The project’s objectives have been structured in different areas:
• Improve quality of life of people
• Provide digitally enabled adaptive services and solutions
• Create a Smart Working Environment
• Develop a user-centred design, with new intuitive ways of human-computer interaction
The WorkingAge team has developed the WAOW tool, which aims at improving the health and well-being of older workers at work and leisure time by supervising their working conditions and providing different types of advice through personalized technologies and friendly & intelligent human interfaces. The tool covers mental, physical, social aspects and the worker’s environment.
The user receives useful tips for a healthier life, and the system considers the user’s activities to give personalized advice. To do this, the worker has a series of tools available, including a mobile application for interaction with the system.
The application integrates a virtual agent who guides the user through questions and advice, many different factors concerning the user's well-being are taken into account as ground for feedback to the user.
These factors are the psychosocial condition of the worker, the physical condition and working environment. All these data are collected in the WAOW Tool where the user is guided through advice, quick exercises and other recommendations.
This tool is customizable by the user, so that it can be adapted to personal preferences offering a rewarding experience. Of course, everything has been designed to guarantee full user privacy.
In this way, the WorkingAge project has created a sustainable and scalable product, the WAOW Tool, that empowers users, increasing their well-being by attenuating the impact of ageing in their autonomy, work conditions and health.
With the changing demography and rising of the retirement age, the European workforce is ageing. Older workers have specific conditions that need a specific response to maintain/improve their well-being, supporting motivation to stay working at higher age and enable better productivity.
WorkingAge project aims at making a step forward in technology for new working environment possibilities. The project’s objectives have been structured in different areas:
• Improve quality of life of people
• Provide digitally enabled adaptive services and solutions
• Create a Smart Working Environment
• Develop a user-centred design, with new intuitive ways of human-computer interaction
The WorkingAge team has developed the WAOW tool, which aims at improving the health and well-being of older workers at work and leisure time by supervising their working conditions and providing different types of advice through personalized technologies and friendly & intelligent human interfaces. The tool covers mental, physical, social aspects and the worker’s environment.
The user receives useful tips for a healthier life, and the system considers the user’s activities to give personalized advice. To do this, the worker has a series of tools available, including a mobile application for interaction with the system.
The application integrates a virtual agent who guides the user through questions and advice, many different factors concerning the user's well-being are taken into account as ground for feedback to the user.
These factors are the psychosocial condition of the worker, the physical condition and working environment. All these data are collected in the WAOW Tool where the user is guided through advice, quick exercises and other recommendations.
This tool is customizable by the user, so that it can be adapted to personal preferences offering a rewarding experience. Of course, everything has been designed to guarantee full user privacy.
In this way, the WorkingAge project has created a sustainable and scalable product, the WAOW Tool, that empowers users, increasing their well-being by attenuating the impact of ageing in their autonomy, work conditions and health.
WorkingAge commenced with a thorough user study. Requirements have been defined building on the theoretical background of the stress-strain concept, by analysing the three different use cases of office, manufacturing and teleworking.
A User Behavioural Model and behavioural goals were developed with the aim of promoting healthy habits and well-being improvements in both work and domestic daily life. This is supported by a very complete WorkingAge ontology. Conditions for launching interventions have been determined; these are dynamically adjusted by the Decision Support System (DSS) to specifically address the user’s needs.
Innovative methods were developed for obtaining mental, emotional, physical, ergonomic and environmental data of workers, inside and outside work. The pilots were drastically influenced and shortened by various consequences of the Covid-19 pandemic, however their results illustrate a positive change in the area of physical working conditions, especially for office and teleworking workplaces. Positive psychosocial changes, on the other hand, are measurable for production workplaces; the same applies to general well-being and the assessment of quality of life.
Particularly noteworthy is the fact that users considered social, ethical and legal implications considerably less after the longer period of use. A very good sign that speaks for transparency and security towards the WAOW tool where not only a lot of effort was put in legal compliance and technical security, but also in explaining the users to create trust.
Most of the resulting innovations are being used in follow-up project or research, and some have been started an exploitation trajectory, like the Internet of Edges used in the network infrastructure and the Synthetic Images Generator for Data Augmentation used for training the deep learning algorithms of the body pose recognition.
A User Behavioural Model and behavioural goals were developed with the aim of promoting healthy habits and well-being improvements in both work and domestic daily life. This is supported by a very complete WorkingAge ontology. Conditions for launching interventions have been determined; these are dynamically adjusted by the Decision Support System (DSS) to specifically address the user’s needs.
Innovative methods were developed for obtaining mental, emotional, physical, ergonomic and environmental data of workers, inside and outside work. The pilots were drastically influenced and shortened by various consequences of the Covid-19 pandemic, however their results illustrate a positive change in the area of physical working conditions, especially for office and teleworking workplaces. Positive psychosocial changes, on the other hand, are measurable for production workplaces; the same applies to general well-being and the assessment of quality of life.
Particularly noteworthy is the fact that users considered social, ethical and legal implications considerably less after the longer period of use. A very good sign that speaks for transparency and security towards the WAOW tool where not only a lot of effort was put in legal compliance and technical security, but also in explaining the users to create trust.
Most of the resulting innovations are being used in follow-up project or research, and some have been started an exploitation trajectory, like the Internet of Edges used in the network infrastructure and the Synthetic Images Generator for Data Augmentation used for training the deep learning algorithms of the body pose recognition.
A comprehensive user and use case study was performed, resulting in important information on user acceptance. Privacy turned out to be a key aspect for user acceptance and was addressed thoroughly; technologically assuring data security and legally with detailed documentation and agreements between participants, hosting companies and consortium partners. Additionally, transparency towards all involved was key to create trust among both employees and employers.
As a base of the decision-making process, a holistic ontology was developed. It represents the data model for the high-level information generated by the data collecting components. Starting from this information, the Decision Support System (DSS) generates personalised advice and interventions for the workers able to adapt to the user’s preferences and profile. It uses a novel probabilistic methodology which eliminates the need for lengthy artificial intelligence training processes.
Very innovative sensors are included in the WAOW tool, like the facial affect analysis going beyond typical standard emotions resulting in far more realistic representations of the user state and valuable new knowledge on AI bias for elderly, or the simple neurometric sensors for emotions and mental state. Apart from these technology-based inputs, also a set of customised questionnaires was developed that enabled e.g. the evaluation of well-being and usability of the tool as a whole and per component.
Although the pilots didn’t provide enough data to deliver proof because of the pandemic, there are promising indications that the concept of the WAOW tool could indeed lead to increased well-being of older workers, of which employing organisations would also benefit. At the time of project end, the most appealing impact lie firstly in the new knowledge and scientific impact, as can be deduced from the high number of relevant publications and continued research in e.g. emotional / mental state measurements. Secondly, the innovative technology that was developed and corresponding exploitation initiatives.
ncome.
As a base of the decision-making process, a holistic ontology was developed. It represents the data model for the high-level information generated by the data collecting components. Starting from this information, the Decision Support System (DSS) generates personalised advice and interventions for the workers able to adapt to the user’s preferences and profile. It uses a novel probabilistic methodology which eliminates the need for lengthy artificial intelligence training processes.
Very innovative sensors are included in the WAOW tool, like the facial affect analysis going beyond typical standard emotions resulting in far more realistic representations of the user state and valuable new knowledge on AI bias for elderly, or the simple neurometric sensors for emotions and mental state. Apart from these technology-based inputs, also a set of customised questionnaires was developed that enabled e.g. the evaluation of well-being and usability of the tool as a whole and per component.
Although the pilots didn’t provide enough data to deliver proof because of the pandemic, there are promising indications that the concept of the WAOW tool could indeed lead to increased well-being of older workers, of which employing organisations would also benefit. At the time of project end, the most appealing impact lie firstly in the new knowledge and scientific impact, as can be deduced from the high number of relevant publications and continued research in e.g. emotional / mental state measurements. Secondly, the innovative technology that was developed and corresponding exploitation initiatives.
ncome.