Title: Big data meeting Cloud and IoT for empowering the citizen clout in smart cities
BigClouT project will in particular make use of today’s three key technologic enablers, Internet of Things (IoT), cloud computing and big data, for the objective of increasing the efficiency in using urban infrastructure, economic and natural resources shared by the increasing population.
BigClouT will leverage the results of the EU-Japan ClouT project and will bring them beyond, by adding for instance distributed intelligence with edge computing principles, big data analytics capability, in addition to self-awareness and dependability properties towards a programmable smart city platform.
Resources and knowledge from prestigious European and Japanese institutions are now together to keep on creating a long-lasting synergy between EU and Japan for tackling future city challenges.
The overall objectives of the BigClouT project can be listed as follows:
Build an interoperable architecture enabling data-driven IoT applications
Enable self-awareness in smart city platform with programmability and dependability properties
Provide libraries and tools for scalable knowledge extraction from distributed information sources in urban areas
Design and assess, with citizens and end-user involvement, attractive smart city services and applications taking into account personal data protection concerns
Propose sustainable dissemination and exploitation plans and create an ecosystem of innovators (SMEs, startups, citizens, etc.) with realistic win-win business models
The main outcome will be an integrated smart city platform, which will be deployed and validated in 4 pilot cities within the project, Grenoble, Bristol, Tsukuba and Fujisawa, targeting applications in several domains such as: Business tourism, Tokyo Olympics 2020 tourism, Smart transportation, and Smart energy management.
DKMS Role: Scientific and technical coordinator
As the technical coordinator, DKMS (ICCS) leads the user requirements task of the project, and mainly participates in the analysis of existing assets, the definition of the platform architecture and the integration process. Apart from that, ICCS leads the WP3 with particular effort on the tasks related with smart analytics, data-adaptive machine learning techniques, the incorporation of techniques inspired by the social media and CEP and event detection. ICCS also contributes to the programming models for elastic deployments, which will be exploited by the reconfigurable platform. Finally, as an academic institution, ICCS will participate in the activities related with the dissemination of the project to conferences and workshops.
Contact points: Dr Antonis Litke (firstname.lastname@example.org)
Start/End Date: 7/2016 – 6/2019