Summary
Artificial intelligence is a key priority for the European Union and is a field in which experts are in high demand. US tech giants are paying huge salaries for AI and machine learning talent, creating the potential for an EU brain-drain in the field. European AI research is well funded, but European ‘deep tech’ SMEs are generally less successful than the Americans at leveraging AI R&D into successful commercial ventures.
WearHealth is an intelligent decision support system that can use any 3rd party wearables and IoT devices. 3rd party hardware is integrated into our proprietary cognitive technologies to build an intelligent software platform that can identify markers of workers’ occupational risks, health, workload, and work efficiency. With these insights, businesses will be able to detect and predict worker safety and health risks, thus preventing accidents and managing their workforce to improve productivity and operational efficiency.
WearHealth’s disruptive character is defined by its unparalleled performance, interoperability, and potential utility in a wide variety of market verticals, unlike any competitive commercial solutions. Following 10 years of R&D at the Artificial Intelligence Institute at the University of Bremen, our team has created a self-learning platform that improves as it analyzes new streams of data.
EU industry leaders are already paying to use our version 1.0 platform for worker safety applications in transportation and energy.
The goal of this project is to further segment target user groups and refine our go-to-market strategy for WearHealth version 2.0, guided by feedback from large-scale target user and client interviews and surveys.
We project generating €40M annual revenue by year 3 after market launch, and directly creating 180 jobs over the same time period.
WearHealth is an intelligent decision support system that can use any 3rd party wearables and IoT devices. 3rd party hardware is integrated into our proprietary cognitive technologies to build an intelligent software platform that can identify markers of workers’ occupational risks, health, workload, and work efficiency. With these insights, businesses will be able to detect and predict worker safety and health risks, thus preventing accidents and managing their workforce to improve productivity and operational efficiency.
WearHealth’s disruptive character is defined by its unparalleled performance, interoperability, and potential utility in a wide variety of market verticals, unlike any competitive commercial solutions. Following 10 years of R&D at the Artificial Intelligence Institute at the University of Bremen, our team has created a self-learning platform that improves as it analyzes new streams of data.
EU industry leaders are already paying to use our version 1.0 platform for worker safety applications in transportation and energy.
The goal of this project is to further segment target user groups and refine our go-to-market strategy for WearHealth version 2.0, guided by feedback from large-scale target user and client interviews and surveys.
We project generating €40M annual revenue by year 3 after market launch, and directly creating 180 jobs over the same time period.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/864149 |
| Start date: | 01-05-2019 |
| End date: | 31-08-2019 |
| Total budget - Public funding: | 71 429,00 Euro - 50 000,00 Euro |
Cordis data
Original description
Artificial intelligence is a key priority for the European Union and is a field in which experts are in high demand. US tech giants are paying huge salaries for AI and machine learning talent, creating the potential for an EU brain-drain in the field. European AI research is well funded, but European ‘deep tech’ SMEs are generally less successful than the Americans at leveraging AI R&D into successful commercial ventures.WearHealth is an intelligent decision support system that can use any 3rd party wearables and IoT devices. 3rd party hardware is integrated into our proprietary cognitive technologies to build an intelligent software platform that can identify markers of workers’ occupational risks, health, workload, and work efficiency. With these insights, businesses will be able to detect and predict worker safety and health risks, thus preventing accidents and managing their workforce to improve productivity and operational efficiency.
WearHealth’s disruptive character is defined by its unparalleled performance, interoperability, and potential utility in a wide variety of market verticals, unlike any competitive commercial solutions. Following 10 years of R&D at the Artificial Intelligence Institute at the University of Bremen, our team has created a self-learning platform that improves as it analyzes new streams of data.
EU industry leaders are already paying to use our version 1.0 platform for worker safety applications in transportation and energy.
The goal of this project is to further segment target user groups and refine our go-to-market strategy for WearHealth version 2.0, guided by feedback from large-scale target user and client interviews and surveys.
We project generating €40M annual revenue by year 3 after market launch, and directly creating 180 jobs over the same time period.
Status
CLOSEDCall topic
EIC-SMEInst-2018-2020Update Date
27-10-2022
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