A-WEAR : A network for dynamic WEarable Applications with pRivacy constraints
Activity: MSCA-ITN-EJD H2020
The emerging market for wearables is expected to grow exponentially in the near future, driven by the sales increase of smart clothes, watches, and eyeglasses. The future wearables are likely to be heterogeneous, operating on batteries, solar power or human motion, and endowed with smart functions. They will co-operate in a decentralized manner with each other and will be able to reach various interconnected software and applications. The mainstream wearable-based architecture has been applied so far in wellbeing industries, such as eHealth or ambient assisted living, which might also reduce the costs for care and guarantee a healthy independent life in the forthcoming older society. As the digitalisation and data-based economy are growing, the exploitation potential of the wearables can easily be expected to increase. Key wearables stakeholder groups in the future are also smart cities, comprising intelligent building industry and infrastructure, energy-efficient smart grid sector, public e-Services, and smart transport.
Motivated by the opportunities that next-generation wearable intelligence is expected to provide, the mission of A-WEAR action is to cross-disciplinarily create new architectures, open-source software and frameworks for dynamic wearable ecosystems, with distributed localization and privacy constraints. We aim at building new joint/double European doctoral programmes to train a new generation of young researchers in order to be aware of, to cope with, and to disseminate to a large audience the vulnerabilities and the corresponding solutions of the communication and positioning through wearables. The impact of A-WEAR will be to enhance the future social well-being, to contribute to an easy living, effective and enjoyable work, and to offer new solutions to the challenges of violation of privacy by communication and positioning through wearables and to the need of applying the right of the ownership to one’s data.