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Fighting Crime 24-7

The East Orange
Community Safety
Information Grid

Jose Cordero
By Jose Cordero, Chief
East Orange Police Department


The East Orange Police Department (EOPD) continues to make history with its unique policing methods. The rate of criminal activity fell again in 2009, marking the sixth consecutive yearly drop. With all major crime categories falling by over one half, East Orange now enjoys a lower level of crime than it did as far back as 1967. More importantly, a sense of community wellness and safety has now become a consistent theme in every corner of our city.

As early adopters of technology-enabled crime prevention strategies and after posting a 76 percent drop in overall crime between 2003 and 2009, the EOPD has become the de facto laboratory for what works in policing. Several hundred law enforcement agencies spanning all regions of the U.S. and a growing number of countries across the globe have taken great interest in EOPD’s unique crime prevention approach.

For several years the EOPD has been using and refining a unique policing strategy that focuses first and foremost on preventing, rather than merely reacting to, criminal activity. After all, our citizens benefit most from policing activities that spare them the agony and trauma often associated with criminal victimization.

Our crime prevention strategy combines a plurality of strategies, namely intelligence-led and real time policing, into a single policing paradigm. A key ingredient of the strategy has been the effective use of timely and reliable information to stay ahead of criminal activity.

laptop computer with had coming out of the screen holdeing US Marshal badge

The principle aim of intelligence-led policing (ILP) is to prevent criminal activity by leveraging the power of information. Unfortunately, gathering and having more access to criminal information, alone, still leaves law enforcement one step behind the criminals. Raw data must be quickly transformed into relevant, manageable criminal intelligence and communicated to field units so that police officers can perform their jobs better, faster, and more cost effectively. The key is using information not just to solve crime and for long-term crime prevention planning, but also to anticipate the future.

Two of the biggest challenges faced crime prevention effectiveness and efficiency are lack of adequate police information systems for quickly translating information into useful criminal intelligence and methods for acting upon time sensitive intelligence. Part of the problem is police information and business intelligence systems lack the capacity to help close the agility gap between reactive and intelligence-led policing. Most were designed to support reactive policing methods or case-by-case investigations. Successful application of intelligence-led policing methods must be supported by decision support systems that synergistically identify, quantify, qualify, and translate raw data into actionable intelligence in real-time. From a practical standpoint, decision makers need the right information at the right time to make informed decisions about resource allocation and crime prevention activities.

To overcome these complex challenges, the EOPD developed the Community Safety Information Grid (CGIG). The CSIG is a configurable police technology platform that delivers a controlled 360-degree crime prevention solution ranging from problem identification and assessment all the way through to police response in real-time. By using a combination of data integration, business intelligence, predictive analytics, electronic visualization, and force multiplier systems, the CSIG provides police departments, for the first time, with the ability to identify and defuse threats to public safety before they occur. This unique approach dramatically decreases time spent collecting, assembling, and analyzing information, which allows for more time for decision making to prevent crime. For example, producing daily data displayed by our crime management dashboard requires about 64,000 complex queries of conventional police databases and about 110 crime analysts to sort through the information.

The CSIG is comprised of carefully selected police technology systems. Although some are unique or locally produced, the majority are common systems which many police departments already have and use. But what makes the CSIG different is how those single-purpose police information systems have been integrated into a system architecture that is interconnected and interdependent so that each product is enhanced by other systems to exponentially improve the quality and value of information.

The CSIG is housed in EOPD’s Real-Time Crime Prevention Center (RT-CPC). RT-CPC personnel operate and monitor a chain of interconnected and networked digital, virtual, and image sensory devices which enable them to proactively collect, correlate, fuse, and analyze every reported criminal incident in real time. For example, within minutes of a reported criminal incident, patrol officers wirelessly transmit incident information to the records management system from the field. The crime management dashboard scans each reported incident and automatically identifies and warns of criminal anomalies, trends or increases in overall or specific crimes. Next, an integrated automated pattern identification and correlation system qualifies criminal incident data by identifying and associating similarities. Identified criminal patterns are subsequently analyzed by a predictive analytics system to help identify when and where the next criminal incident is most likely to occur. System features enable electronic formulation and transmission of corresponding crime prevention plans to police patrols, virtual patrollers, and image sensory agents to prevent, not just react to criminal activity and other public safety hazards. Finally, crime prevention response plans can be electronically viewed and modified in real-time.

This systems integration has produced a number of significant breakthroughs in public safety. One example is the Alarm-Based Automated emergency Dispatch (ABAD) system, which now serves as a framework for bridging lags in police responses to emergency 911 calls—a police performance area that often draws widespread criticism and public concern.

ABAD starts with a smart image sensor detection (smart sensors that perform behavioral analytics) of a matter of possible police interest. Sensor alerts are accompanied by streaming video allowing RT-CPC operators to instantly determine if an event warrants an ABAD response (usually a crime in progress or about to occur). Upon activation of ABAD, smart sensors transmit coordinates of the occurrence to the Tactical Vehicle Locator (TAC-AVL) and pan conventional surveillance cameras to form a virtual surveillance ring around the incident location. TAC-AVL displays event locations on a map and identifies and transmits the locations of available police units nearest the location of the alarm to the Computer Aided Dispatch (CAD) system. CAD electronically transmits emergency dispatch instructions to the two closest available police units. This entire fully automated police dispatch sequence takes about ONE second to complete as compared to our average emergency police dispatch time of about 2 minutes, 29 seconds. Since ABAD uses GPS technology to locate the actual closest units to an event, police emergency response times are slashed by over one half.

The EOPD has moved information-led and real-time policing concepts beyond theoretical constructs and into implementation with great success. This policing paradigm has significantly improved not only the effectiveness of policing but also its efficiency and productivity. The CSIG has not only proven to help close the performance gap between strategy development and benefit realization, but also to be an effective method for sustainable improvements in public safety. Many agencies across the U.S. and several countries have expressed interest in and excitement about duplicating EOPD’s methods and concepts to improve public safety in their jurisdictions.


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