INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data
Abstract
In this demo we present INSIGHT, a system that provides traffic event detection in Dublin by exploiting Big Data and Crowdsourcing techniques. Our system is able to process and analyze input from multiple heterogeneous urban data sources.
Cite
Text
Panagiotou et al. "INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016. doi:10.1007/978-3-319-46131-1_5Markdown
[Panagiotou et al. "INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016.](https://mlanthology.org/ecmlpkdd/2016/panagiotou2016ecmlpkdd-insight/) doi:10.1007/978-3-319-46131-1_5BibTeX
@inproceedings{panagiotou2016ecmlpkdd-insight,
title = {{INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data}},
author = {Panagiotou, Nikolaos and Zygouras, Nikolas and Katakis, Ioannis and Gunopulos, Dimitrios and Zacheilas, Nikos and Boutsis, Ioannis and Kalogeraki, Vana and Lynch, Stephen and O'Brien, Brendan and Kinane, Dermot and Marecek, Jakub and Yu, Jia Yuan and Verago, Rudi and Daly, Elizabeth and Piatkowski, Nico and Liebig, Thomas and Bockermann, Christian and Morik, Katharina and Schnitzler, François and Weidlich, Matthias and Gal, Avigdor and Mannor, Shie and Stange, Hendrik and Halft, Werner and Andrienko, Gennady L.},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2016},
pages = {22-26},
doi = {10.1007/978-3-319-46131-1_5},
url = {https://mlanthology.org/ecmlpkdd/2016/panagiotou2016ecmlpkdd-insight/}
}