Presentation Title

Discovering Crime Trends and Patterns Using Three-Dimensional Interactive Visualization Techniques

Format of Presentation

Poster to be presented the Friday of the conference

Presenter Information

Kyle BehielsFollow

Abstract

Law enforcement is under constant pressure to be aware of current criminal activity and must constantly be developing strategies to deal with it. In this regard, analytical reasoning with interactive visual interfaces, a technique called visual analytics, can be a powerful tool, serving to augment the trend and pattern recognition capabilities of experts. This research focuses on creating a framework for the three-dimensional (3D), interactive representation of criminal data. We used an open data set for this study, published by the Vancouver Police Department, that contains information on crimes committed in the area from 2003 to 2019. Two-dimensional models are an effective tool for quickly exploring data; however, they lack the natural interactivity of three-dimensional space. We have thus developed a 3D interactive visualization framework that enables temporal and spatial aspects of crime data to be visualized on a 3D, high-quality model of the City of Vancouver along with other relevant information such as public transportation and pedestrian flow data. This helps us discover trends, recognize patterns in crime and understand why certain types of crimes occur at particular locations at particular times. This framework can be used by police officers and crime analysts for effective police patrol in crime-ridden areas. Our framework, with minimal adaptation, can be altered to represent similar data from other police departments across the world.

Department

Computing Science

Faculty Advisor

Andrew Park

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Discovering Crime Trends and Patterns Using Three-Dimensional Interactive Visualization Techniques

Law enforcement is under constant pressure to be aware of current criminal activity and must constantly be developing strategies to deal with it. In this regard, analytical reasoning with interactive visual interfaces, a technique called visual analytics, can be a powerful tool, serving to augment the trend and pattern recognition capabilities of experts. This research focuses on creating a framework for the three-dimensional (3D), interactive representation of criminal data. We used an open data set for this study, published by the Vancouver Police Department, that contains information on crimes committed in the area from 2003 to 2019. Two-dimensional models are an effective tool for quickly exploring data; however, they lack the natural interactivity of three-dimensional space. We have thus developed a 3D interactive visualization framework that enables temporal and spatial aspects of crime data to be visualized on a 3D, high-quality model of the City of Vancouver along with other relevant information such as public transportation and pedestrian flow data. This helps us discover trends, recognize patterns in crime and understand why certain types of crimes occur at particular locations at particular times. This framework can be used by police officers and crime analysts for effective police patrol in crime-ridden areas. Our framework, with minimal adaptation, can be altered to represent similar data from other police departments across the world.