The elastic Wireless Networking Experimentation (eWINE) research project will realize elastic networks that can scale to a high number of users in a short timespan through the use of an agile infrastructure (intelligent software and flexible hardware), enabling: (1) dynamic on-demand end-to-end wireless connectivity service provisioning, (2) elastic resource sharing in dense heterogeneous and small cell networks (HetSNets), and (3) intelligent and informed configuration of the physical layer. eWINE will develop and validate algorithms for advanced Cognitive Networking (context determination & sensing, optimization & negotiation techniques, and online learning algorithms) through experimentally-driven research on top of existing FIRE/FIRE+ facilities (CREW, WiSHFUL, FLEX). Several partners are involved in these facility projects. The consortium includes both academic researchers and industrial developers (3 SMEs + 1 multinational company). The uptake of the project results will be promoted by making openly available the Intelligence Toolbox and organizing the eWINE Grand Challenge; through Open Calls of WiSHFUL; and by educating the wireless community via FORGE, VideoLectures.net and YouTube. To cope with the increasing density of wireless devices, eWINE will primarily address the EU’s need for intelligent solutions to mitigate the spectrum scarcity and network configuration problems and strengthen the competitiveness of European companies (reducing development costs, speeding product validation and shortening time-to-market) in developing innovative products able to increase wireless capacity and energy efficiency, and lower electromagnetic exposure. The project results will lead to improved European innovation in several domains (secured & robust communication, IoT, 5G, etc.). eWINE will leverage research to exploit the full potential of the coordinated use of heterogeneous wireless networks, and as such will contribute significantly to regulatory policies and standardization.

Degradation of a cultural artefact depends on the environmental stress over time, especially during fluctuating environmental conditions, and the reactive behaviours of the materials of its composition. For an effective preventive conservation (PC) it is key to consider the historic environmental stress and degradation kinetics of the different materials (and their synergies) and monitor the artefact at all times. However, due to the heterogeneity of the material nature of the artefacts, this requires expensive monitoring as well as specialized personnel, out of reach for most, small to medium sized museums. CollectionCare will develop an innovative PC decision support system targeting the needs of small-medium sized museums. It will integrate IoT monitoring of the microclimatology of each artefact at any place, either at display, storage, handling or transport, integrated with multi-scale modelling for the different artefact materials while complying with current PC norms and recommendations. We will integrate latest advances in sensoring electronics, LPWAN wireless communication, multi-scale and multi-material degradation knowledge, big data and cloud computing into a single affordable system, adapted to the specific needs and resources of small museums and collections. The solution will built on the knowledge of different renown research groups and companies in the fields of PC (KADK, TU/e, LSIWC, UW, URO1, JHI and UPV), cloud computing and big data (ATOS), IoT connectivity (SGF), wireless sensoring (UPV, URO1), artefact transport (CBC, HvK), collection management (PS) as well as a large number of museums to guarantee future market acceptance (DFA-Spain, KMKG-Belgium, IVC-Spain, OAML-Latvia, IEEE-Greece, RDC-Denmark). The project will also count on a strong International Cooperation by an external Advisory Board of experts with prominent professional background from prestigious institutions and enterprises like: GCI, CCI, ICCROM, ICOMOS, Hispania Nostra and AXA ART.