INtelligent Synthesis and Real-tIme Response using Massive StreaminG of HeTerogeneous Data -




The instrumentation of the world with diverse sensors, smart phones, and social networks acquires exascale data that offer the potential of enhanced science and services. In particular, a better societal management of the overall cycle of disaster monitoring and response becomes possible, citizens may now become involved in decision making and data acquisition (crowd-sourcing), and advanced planning can conserve resources. Current systems are limited in three important elements: (i) lack of methods for handling heterogeneous data streams in real-time,(ii) absence of social computing integrated with big data analysis, (iii) real-time prediction and alarm capabilities have not yet been incorporated into the infrastructure for intelligent management. The goal of the INSIGHT project is to radically advance our ability of coping with emergency situations in Smartcities by developing innovative technologies, methodologies and systems that will put new capabilities in the hands of disaster planners and city personnel to improve emergency planning and response.



Staff Members:

Liebig, Thomas
Morik, Katharina




Artikis/etal/2014a Alexander Artikis and Matthias Weidlich and Francois Schnitzler and Ioannis Boutsis and Thomas Liebig and Nico Piatkowski and Christian Bockermann and Katharina Morik and Vana Kalogeraki and Jakub Marecek and Avigdor Gal and Shie Mannor and Dimitrios Gunopulos and Dermot Kinane. Heterogeneous Stream Processing and Crowdsourcing for Urban Traffic Management. In Proceedings of the 17th International Conference on Extending Database Technology, 2014.
Kinane/etal/2014a Dermot Kinane and François Schnitzler and Shie Mannor and Thomas Liebig and Katharina Morik and Jakub Marecek and Bernard Gorman and Nikolaos Zygouras and Yannis Katakis and Vana Kalogeraki and Dimitrios Gunopulos. Intelligent Synthesis and Real-time Response using Massive Streaming of Heterogeneous Data (INSIGHT) and its anticipated effect on Intelligent Transport Systems (ITS) in Dublin City, Ireland. In Proceedings of the 10th ITS European Congress, Helsinki, pages (to appear), 2014.
Liebig/etal/2014b Liebig, Thomas and Andrienko, Gennady and Andrienko, Natalia. Methods for Analysis of Spatio-Temporal Bluetooth Tracking Data. In Journal of Urban Technology, Vol. 21, No. 2, pages 27--37, Taylor and Francis, 2014.
Liebig/etal/2014d Thomas Liebig and Nico Piatkowski and Christian Bockermann and Katharina Morik. Route Planning with Real-Time Traffic Predictions. In Proceedings of the LWA 2014 Workshops: KDML, IR, FGWM, pages 83-94, 2014.
Schnitzler/etal/2014b Schnitzler, Francois and Artikis, Alexander and Weidlich, Matthias and Boutsis, Ioannis and Liebig, Thomas and Piatkowski, Nico and Bockermann, Christian and Morik, Katharina and Kalogeraki, Vana and Marecek, Jakub and Gal, Avigdor and Mannor, Shie and Kinane, Dermot and Gunopulos, Dimitrios. Heterogeneous Stream Processing and Crowdsourcing for Traffic Monitoring: Highlights. In Proceedings of the European Conference on Machine Learning (ECML), Nectar Track, pages 520-523, Springer, 2014.
Schnitzler/etal/2014c Francois Schnitzler and Thomas Liebig and Shie Mannor and Gustavo Souto and Sebastian Bothe and Hendrik Stange. Heterogeneous Stream Processing for Disaster Detection and Alarming. In IEEE International Conference on Big Data, pages 914-923, IEEE Press, 2014.
Liebig/etal/2013a T. Liebig and Z. Xu and M. May. Incorporating Mobility Patterns in Pedestrian Quantity Estimation and Sensor Placement. In J. Nin and D. Villatoro (editors), Proceedings of the First International Workshop on Citizen Sensor Networks CitiSens 2012, LNAI 7685, pages 67--80, Springer, 2013.
Roesler/Liebig/2013a Rösler, Roberto and Liebig, Thomas. Using Data from Location Based Social Networks for Urban Activity Clustering. In Vandenbroucke, Danny and Bucher, Bénédicte and Crompvoets, Joep (editors), Geographic Information Science at the Heart of Europe, pages 55--72, Springer, 2013.