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000827061 019__ $$a1033649582
000827061 020__ $$a9783319756080$$q(electronic book)
000827061 020__ $$a3319756087$$q(electronic book)
000827061 020__ $$z9783319756073
000827061 0247_ $$a10.1007/978-3-319-75608-0$$2doi
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000827061 035__ $$aSP(OCoLC)1029352353$$z(OCoLC)1033649582
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000827061 050_4 $$aQA76.9.D343
000827061 08204 $$a006.3/12$$223
000827061 1112_ $$aItalian Conference for the Traffic Police$$n(1st :$$d2017 :$$cRome, Italy)
000827061 24510 $$aTraffic mining applied to police activities :$$bproceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017) /$$cFabio Leuzzi, Stefano Ferilli, editors.
000827061 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2018]
000827061 264_4 $$c©2018
000827061 300__ $$a1 online resource.
000827061 336__ $$atext$$btxt$$2rdacontent
000827061 337__ $$acomputer$$bc$$2rdamedia
000827061 338__ $$aonline resource$$bcr$$2rdacarrier
000827061 347__ $$atext file$$bPDF$$2rda
000827061 4901_ $$aAdvances in intelligent systems and computing,$$x2194-5357 ;$$vvolume 728
000827061 504__ $$aIncludes bibliographical references and index.
000827061 5050_ $$aIntro; 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
000827061 5058_ $$a2 Collective Mobility Data Analysis3 Individual Mobility Data Analysis; 4 Mobility Data-Driven Applications and Services; 5 Conclusions; References; Part II Technical Contributions; Towards a Pervasive and Predictive Traffic Police; 1 Introduction; 2 Research Fields: Background and Challenges; 2.1 Mining Traffic Data; 2.2 Hints of Vehicle Forensics and Analytics; 2.3 Mining Patrolling Data; 2.4 Mining Information Exchange Among Control Rooms; 3 An Integrated Approach to Road Understanding and Event Management; 4 Conclusions; References
000827061 5058_ $$aA 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
000827061 5058_ $$a4.2 Second Profile5 Conclusions and Future Work; References; Efficient and Accurate Traffic Flow Prediction via Fast Dynamic Tensor Completion; 1 Introduction; 2 Related Works; 3 Proposed Method; 3.1 Dynamic Tensor Model for Traffic Flow; 3.2 Fast Dynamic Tensor Completion; 4 Experimental Evaluation; 4.1 Experiment Settings; 4.2 Experiment Results; 5 Conclusion; References; Reducing the Risk of Accidents with Not Insured British Vehicles in Southern Spain; 1 Introduction; 2 Methodology; 2.1 Collecting the Samples; 2.2 Weakness; 3 Results and Discussion
000827061 5058_ $$a3.1 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
000827061 506__ $$aAccess limited to authorized users.
000827061 520__ $$aThis 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.
000827061 588__ $$aOnline resource; title from PDF title page (viewed March 26, 2018).
000827061 650_0 $$aData mining in law enforcement$$vCongresses.
000827061 650_0 $$aSocial sciences$$xMethodology$$vCongresses.
000827061 7001_ $$aLeuzzi, Fabio,$$eeditor.
000827061 7001_ $$aFerilli, Stefano,$$eeditor.
000827061 77608 $$iPrint version: $$z9783319756073
000827061 830_0 $$aAdvances in intelligent systems and computing ;$$v728.
000827061 852__ $$bebk
000827061 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-75608-0$$zOnline Access$$91397441.1
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