Project description
Safety and health intelligence at work
Today’s companies face major financial, reputational and productivity losses due to lack of understanding and suboptimal management of safety and health risks for workers and the working environment. Advances in artificial intelligence (AI) can make it easier for companies to find a balance between ensuring safety and health standards and improving productivity. With the goal to prevent all physical and psychological harm at work, the EU-funded WearHealth project is developing smart wearables that can map hidden human risks in real time using AI and the Internet of things (IoT). Its portfolio of validated wearables and IoT devices includes smartwatches, smart shirts and 3D cameras. This new platform is interoperable and can be used in a variety of market verticals.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencesinternetinternet of things
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- social scienceseconomics and businessbusiness and managementemployment
- medical and health scienceshealth sciencespublic healthoccupational health
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
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Programme(s)
Call for proposal
(opens in new window) H2020-EIC-SMEInst-2018-2020
See other projects for this callSub call
H2020-SMEInst-2018-2020-1
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
28359 BREMEN
Germany
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.