Conference Paper

#32 

@inproceedings{Razip2014, title={A Mobile Visual Analytics Approach for Law Enforcement Situation Awareness}, author={Ahmad M. M. Razip and Shehzad Afzak and Matthew Potrawski and Ross Maciejewski and Yun Jang and Niklas Elmqvist and David S. Ebert}, url={http://www.umiacs.umd.edu/~elm/projects/iVALET/iVALET.pdf}, year={2014}, date={2014-01-01}, journal={Proceedings of the IEEE Pacific Symposium on Visualization}, booktitle={Proceedings of the IEEE Pacific Symposium on Visualization}, pages={1235--1244}, abstract={The advent of modern smartphones and handheld devices has given analysts, decision-makers, and even the general public the ability to rapidly ingest data and translate it into actionable information on-the-go. In this paper, we explore the design and use of a mobile visual analytics toolkit for public safety data that equips law enforcement agencies with effective situation awareness and risk assessment tools. Our system provides users with a suite of interactive tools that allow them to perform analysis and detect trends, patterns and anomalies among criminal, traffic and civil (CTC) incidents. The system also provides interactive risk assessment tools that allow users to identify regions of potential high risk and determine the risk at any user-specified location and time. Our system has been designed for the iPhone/iPad environment and is currently being used and evaluated by a consortium of law enforcement agencies. We report their use of the system and some initial feedback.}, keywords={}, }