Overview
- Gathers the proceedings of the 1st Italian Conference for the Traffic Police, Rome, Italy, October 25-26, 2017
- Aimed at researchers as well as practitioners, standard developers and policymakers
- Presents high-quality peer-reviewed papers covering various aspects of data traffic analysis for police activities
Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 728)
Included in the following conference series:
Conference proceedings info: TRAP 2017.
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Table of contents (11 papers)
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Front Matter
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Technical Contributions
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Front Matter
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Back Matter
Other volumes
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Traffic Mining Applied to Police Activities
Keywords
About this book
This book presents high-quality original contributions on the development of automatic traffic analysis systems that are able to not only anticipate traffic scenarios, but also understand the behavior of road users (vehicles, bikes, trucks, etc.) in order to provide better traffic management, prevent accidents and, potentially, identify criminal behaviors. Topics also include traffic surveillance and vehicle accident analysis using formal concept analysis, convolutional and recurrent neural networks, unsupervised learning and process mining. The content is based on papers presented at the 1st Italian Conference for the Traffic Police (TRAP), which was held in Rome in October 2017. This conference represents a targeted response to the challenges facing the police in connection with managing massive traffic data, finding patterns from historical datasets, and analyzing complex traffic phenomena in order to anticipate potential criminal behaviors. The book will appeal to researchers, practitioners and decision makers interested in traffic monitoring and analysis, traffic modeling and simulation, mobility and social data mining, as well as members of the police.
Editors and Affiliations
Bibliographic Information
Book Title: Traffic Mining Applied to Police Activities
Book Subtitle: Proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017)
Editors: Fabio Leuzzi, Stefano Ferilli
Series Title: Advances in Intelligent Systems and Computing
DOI: https://doi.org/10.1007/978-3-319-75608-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Softcover ISBN: 978-3-319-75607-3Published: 22 March 2018
eBook ISBN: 978-3-319-75608-0Published: 21 March 2018
Series ISSN: 2194-5357
Series E-ISSN: 2194-5365
Edition Number: 1
Number of Pages: XII, 155
Number of Illustrations: 6 b/w illustrations, 33 illustrations in colour
Topics: Computer Communication Networks, Transportation Technology and Traffic Engineering, Data Mining and Knowledge Discovery, Operations Research, Management Science