عنوان

Traffic mining applied to police activities :

(Number (ISBN

3319756087

(Number (ISBN

9783319756080

Erroneous ISBN

3319756079

Erroneous ISBN

9783319756073

Title Proper

Traffic mining applied to police activities :

General Material Designation

[Book]

Other Title Information

proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017) /

First Statement of Responsibility

Fabio Leuzzi, Stefano Ferilli, editors.

Place of Publication, Distribution, etc.

Cham, Switzerland :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

[2018]

Date of Publication, Distribution, etc.

©2018

Specific Material Designation and Extent of Item

1 online resource

Series Title

Advances in intelligent systems and computing,

Volume Designation

volume 728

ISSN of Series

2194-5357 ;

Text of Note

Includes bibliographical references and index.

Text of Note

Intro; Foreword; Preface; Organization; Executive Committee; Program Committee; Organizing Committee; Sponsoring Institutions; Contents; Part I Invited Talks; Data and Analytics Framework. How Public Sector Can Profit from Its Immense Asset, Data; 1 Introduction; 2 Big Data Analytics for the Public Administration; 3 Big Data and Public Policy; 4 Data and Analytics Framework for the Public Administration; 5 Services Provided by the DAF; 6 Architectural Design Highlights; 7 Conclusions; References; Advancements in Mobility Data Analysis; 1 Big Mobility Data Sources.

Text of Note

2 Collective Mobility Data Analysis3 Individual Mobility Data Analysis; 4 Mobility Data-Driven Applications and Services; 5 Conclusions; References; Part II Technical Contributions; Towards a Pervasive and Predictive Traffic Police; 1 Introduction; 2 Research Fields: Background and Challenges; 2.1 Mining Traffic Data; 2.2 Hints of Vehicle Forensics and Analytics; 2.3 Mining Patrolling Data; 2.4 Mining Information Exchange Among Control Rooms; 3 An Integrated Approach to Road Understanding and Event Management; 4 Conclusions; References.

Text of Note

3.1 A Real Case of Study in Mijas (Spain)3.2 Actual Results; 3.3 Other Results; 4 Practical Applications; 5 Conclusions and Future Work; References; Unsupervised Classification of Routes and Plates from the Trap-2017 Dataset; 1 Introduction; 2 Statistical Analysis; 3 Design of a Plates Behavior Classifier; 3.1 Overview; 3.2 The Tool; 4 Our Findings; 4.1 Tuning the Classifier; 4.2 Classifying Routes; 4.3 Classifying Plates; 5 Related Work; 5.1 Traffic Monitoring and Analysis; 5.2 Pattern Mining and Clusterization; 6 Conclusions and Future Work; References.

Text of Note

4.2 Second Profile5 Conclusions and Future Work; References; Efficient and Accurate Traffic Flow Prediction via Fast Dynamic Tensor Completion; 1 Introduction; 2 Related Works; 3 Proposed Method; 3.1 Dynamic Tensor Model for Traffic Flow; 3.2 Fast Dynamic Tensor Completion; 4 Experimental Evaluation; 4.1 Experiment Settings; 4.2 Experiment Results; 5 Conclusion; References; Reducing the Risk of Accidents with Not Insured British Vehicles in Southern Spain; 1 Introduction; 2 Methodology; 2.1 Collecting the Samples; 2.2 Weakness; 3 Results and Discussion.

Text of Note

A Process Mining Approach to the Identification of Normal and Suspect Traffic Behavior1 Introduction; 2 The WoMan Framework; 2.1 Input Formalism; 2.2 Output Formalism; 3 Workflow Supervision and Prediction; 4 Proposal for Application to Traffic Understanding; 4.1 Setting; 4.2 Motivation; 4.3 Example; 5 Conclusions and Future Work; References; Detecting Criminal Behaviour Patterns in Spain and Italy Using Formal Concept Analysis; 1 Introduction; 2 Formal Concept Analysis; 3 Criminal Behaviour Patterns in Southern Spain; 4 Analysing Datasets of Traffic Cameras; 4.1 First Profile.

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Text of Note

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.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9783319756080

International Standard Book Number

9783319756073

Data mining in law enforcement, Congresses.

Social sciences-- Methodology, Congresses.

COMPUTERS-- Database Management-- Data Mining.

Data mining in law enforcement.

Data mining.

Highway & traffic engineering.

Network hardware.

Operational research.

Social sciences-- Methodology.

COM-- 021030

UKN

Number

Edition

Class number

Ferilli, Stefano

Leuzzi, Fabio

Italian Conference for the Traffic Police(1st :2017 :, Rome, Italy)

Date of Transaction

20200823110121.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y