The use of License Plate Reader (LPR) technology by law-enforcement agencies has increased heavily in recent years, thanks primarily to significant enhancements in the technology’s underlying hardware and software. Weatherized digital cameras can now quickly capture high-resolution images of passing vehicles, and the mobile computers to which they are connected have the processing power needed to analyze a fast-moving stream of license-plate images. This capability enables law-enforcement officers to quickly canvass a parking lot by simply driving through all of the lanes in the lot while the cameras and computer in the police vehicle automatically check for stolen cars, stolen license plates, and/or wanted persons registered to those vehicles. Previously, officers would be forced to enter each license plate number individually into their mobile computer query systems. Although touch screens and voice-recognition technology can simplify human input to some degree, the capability of LPRs to quickly scan and check a large number of license plates in a very short time makes any form of human input pale by comparison. The operational process used is also much safer than attempting to type license-plate numbers into a mobile computer while driving.
The next technological leap for LPR technology lies in bringing its impressive optical and processing capabilities into the realm of real-time “connected law enforcement” information sharing. Today, most LPR systems compare the results of their scans to a local database, stored on their mobile computers, of vehicles on a current “wanted” list. The database is typically downloaded to the mobile computer by way of “thumb” drive, WiFi, or office LAN and is usually as much as a day old (and sometimes older). If a vehicle is reported stolen after the database has been downloaded, the LPR would ignore license plates not in the locally stored database because they would not be listed there.
However, current LPR software does provide an interface for officers to manually add a license plate to the local database – if alerted by radio dispatch, for example, of a recently stolen vehicle. This process, though, is not yet automated and therefore depends on the availability of an officer both to hear the alert, and then to take the time to enter the newly received information into the mobile computer.
Instant Updates and Immediate Implications
Today, fortunately, the existing communications capabilities already integrated into most mobile computers provide a way, using LPR technology, to enable the real-time transfer of extremely recent law-enforcement data. In fact, some LPR systems, if properly networked, can use wireless broadband networks – e.g., Verizon and AT&T 3G – to transmit updates to field cameras.
The implications for improving law-enforcement responses are significant. For example, vehicles identified as stolen (or registered to newly wanted persons) could be automatically “pushed” to LPRs in police vehicles and/or mounted at fixed locations. In either case, the LPR systems could immediately return a “hit” if the vehicle is scanned at any time from that point forward.
Another significant added value provided by LPR technology is that the newer systems also can store the scans made during a given shift or time period. This means that a large amount of potentially critical information, including the time and GPS (global positioning system) location for each license plate recently stored, is recorded and therefore can be quickly cross-referenced with updated information. For example, if a subject vehicle had been scanned only minutes prior to the receipt of an electronic BOLO (“Be on the Lookout”) message, the system could instantly inform an officer in the field not only that the vehicle had been recently scanned but also where and when the scan took place. The combining of a number of recent scans from several LPR systems could therefore quickly paint a picture of a vehicle’s immediately previous locations and possibly identify a direction of travel or provide other helpful information.
The same technology may prove extremely beneficial to lookout alerts encompassing a relatively large geographical area. For example, in October 2002 the greater Washington, D.C., area was terrorized by the infamous sniper attacks, which stretched from Washington, D.C., and its Maryland suburbs 90 miles south into Virginia. Making the situation more complicated was the fact that early eyewitness reports wrongly identified the vehicle used in the sniper shootings as a “white box van,” a description that led law-enforcement personnel to focus their attention on the wrong type of vehicle.
Erroneous Information Results in a Fruitless Search
A system of “connected” mobile and fixed LPRs might have helped in that investigation by focusing on the identification of vehicles that had been scanned near the times and locations of two or more of the attacks. The systems would not be specifically looking for a white box van. Instead, they would be looking for license plates of vehicles that were known to have been in the proximity of at least two of the several crime scenes at about the same time of two or more of the sniper attacks.
Of course, to create a regional system of connected LPRs would require the standardization of several LPR technologies and the exchange of data across two or more political jurisdictions (usually, though, within the same geographical area). In addition, a regional system of electronic BOLOs would be needed to provide real-time dissemination of information across several LPR networks.
Fortunately, new regional data-sharing systems are already operational in many jurisdictions and could be used for just that purpose. By marrying the technologies and capabilities now in place, newly available features could be further exploited – by the issuance of alerts triggered by what is known as “Geo-Fencing.” One example: If the vehicle owned by a registered sex offender is scanned by an LPR system while that vehicle is physically located in a school zone, the system can alert an officer in the same general vicinity (but no alert would occur if the scan occurred outside of the zone). Finally, the wealth of data being captured by LPRs could be easily exported into a standard XML (extensible markup language) format, thereby making integration with new and robust analytic tools possible across a wide regional area. Such an upgrade could quickly add a new and powerful information layer – and operational capability – to emergency managers and homeland-security officials at all levels of government.
In short, all of the components are already in place to better leverage LPR technology and capabilities to improve law-enforcement operations. What is needed now are strategic coordination, multiagency cooperation, and the political will necessary to make better use of technologies already developed and in the field.
Rodrigo (Roddy) Moscoso
Rodrigo (Roddy) Moscoso is the executive director of the Capital Wireless Information Net (CapWIN) Program at the University of Maryland, which provides software and mission-critical data access services to first responders in and across dozens of jurisdictions, disciplines, and levels of government. Formerly with IBM Business Consulting Services, he has more than 20 years of experience supporting large-scale implementation projects for information technology, and extensive experience in several related fields such as change management, business process reengineering, human resources, and communications.
