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Artificial Intelligence Laboratory

Data Warehousing - Coplink*/BorderSafe/RISC

* The COPLINK system was initially developed by the University of Arizona Artificial Intelligence Lab with funding from the National Institute of Justice and the National Science Foundation since 1997. With additional venture funding and product development, Knowledge Computing Corporation (KCC) currently distributes, maintains, and updates the commercially available COPLINK Solution Suite.

Demo: COPLINK BorderSafe

Introduction

The BorderSafe project (funded by the Department of Homeland Security) is a collaborative research effort involving the University of Arizona's AI Lab, law enforcement agencies including the Tucson Police Department (TPD), Phoenix Police Department (PPD), Pima County Sheriff's Department (PCSD), and Tucson Customs and Border Protection (CBP) as well as San Diego’s ARJIS (Automated Regional Justice Information Systems) and the San Diego Super Computer Center (SDSC). The BorderSafe project includes several cross-jurisdictional data sharing initiatives.

The project aims to leverage data from participating agencies to develop a testbed for research and analysis on cross-jurisdictional data. Progress has been made in this direction by experimenting with advanced network analysis and visualization techniques. Records from Tucson Police Department, Pima County Sheriff’s Department and Tucson Customs and Border Patrol have been integrated to extract criminal activity networks of drug traffickers and border crossing vehicles. Further research is being pursued in the area of intelligent network analysis to support law enforcement, border patrol, and homeland security.

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Screenshots

Figure 1
Figure 1: Circles represent individuals
Red Rectangles represent border crossing vehicles
Lines between nodes represent links found in law enforcement records

The above network is a typical example of a criminal activity network involving records from multiple agencies. In this case the network may be used identify vehicles associated with a homicide suspect.

Figure 2
  Figure 2:
The use of network visualizations to identify border crossing vehicles potentially involved in criminal activity in local jurisdictions.

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