Track&Know will research, develop and exploit a new software framework that aims at increasing the efficiency of Big Data applications in the transport, mobility, motor insurance and health sectors. Stemming from industrial cases, Track&Know will develop user friendly toolboxes that will be readily applicable in the addressed markets, and will be also investigated in additional domains through liaison activities with running ICT-15 Lighthouse projects. Track&Know integrates multidisciplinary research teams from Mobility Data management, Complex Event Recognition, Geospatial Modelling, Complex Network Analysis, Transportation Engineering and Visual Analytics to develop new models and applications. Track&Know recognizes that Big Data penetration is not adequately developed in niche markets outside the traditional verticals (e.g. Finance) and so the Track&Know Toolboxes will be demonstrated in three real-world Pilots using datasets from niche market scenarios to validate efficiency improvements. Performance and impact benchmarks are elaborated and will be documented during pilots deployment. The Track&Know consortium is composed by complementary partners, coming from addressed research, technological and commercial domains, that have a proven track record of high quality research capacity. Thus, the carefully structured workplan, embodies a holistic approach towards meeting the Track&Know objectives and delivering market-relevant outcomes of significant exploitation potential.
Nikolaos Koutroumanis, Georgios Santipantakis, Apostolos Glenis, Christos Doulkeridis and George Vouros “Integration of Mobility Data with Weather Information†published pages: , ISSN: , DOI:
EDBT/ICDT workshops 2019
2020-02-18
2019
Nikola Markovic, Przemylaw Sekula, Zachary Vander Laan, Gennady Andrienko, Natalia Andrienko Applications of Trajectory Data From the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study published pages: 1858-1869, ISSN: 1524-9050, DOI: 10.1109/tits.2018.2843298
IEEE Transactions on Intelligent Transportation Systems 20/5
2020-02-18
2019
Natalia Andrienko, Gennady Andrienko, Jose Manuel Cordero Garcia, David Scarlatti Analysis of Flight Variability: a Systematic Approach published pages: 54-64, ISSN: 1077-2626, DOI: 10.1109/tvcg.2018.2864811
IEEE Transactions on Visualization and Computer Graphics 25/1
2020-02-18
2018
Jie Li, Siming Chen, Kang Zhang, Gennady Andrienko, Natalia Andrienko COPE: Interactive Exploration of Co-occurrence Patterns in Spatial Time Series published pages: 1-1, ISSN: 1077-2626, DOI: 10.1109/tvcg.2018.2851227
IEEE Transactions on Visualization and Computer Graphics
2020-02-18
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