article
SPRING | 2026
Policing Technologies: Automated License Plate Readers, Then and Now.
By Dr. Edward Restrepo
Spring | 2026
Today there is a large variety of technologies for law enforcement agencies to employ that enhance their capabilities to serve their communities. Some of these include Real Time Crime Centers (RTCC), drones, sound detection devices, GPS vehicle launching devices, artificial intelligence enabled surveillance cameras, body-worn cameras (BWC) equipped with contemporaneous translating and transcribing features, virtual reality (VR) training, less lethal options such as electronic control weapons (ECW), remote restraint devices, and pepper ball systems are just a few to mention. It is clear public safety innovations are at the forefront and remain a top priority for technological companies. However, one advancement that has been a gamechanger for law enforcement are automated license plate readers (ALPR). This article delves into the technology’s humble beginnings, its progression throughout the years, various challenges, and where ALPR innovation is heading in the larger crime-fighting ecosystem.
History of ALPRs
To better understand the future of ALPR holds it is only sensible to explore its origin and the reasons that led to its creation. Early in 1974, in northern England, a horrific bombing was carried out by members of the Irish Republican Army (IRA) that killed 12 and severely wounded 14 individuals (Pylas, 2020). In the years to follow, bombings tied to the IRA in London and across the United Kingdom, were responsible for hundreds of deaths and injuries. Car bombs were a common approach to deploying these devices. To better investigate the bombers, the London Police assembled a robust closed-circuit television (CCTV) system to monitor and document the license plates of vehicles at critical ingress and egress points of the city. As the program evolved, law enforcement was able to capture images of license plates to identify and detain vehicles associated with IRA terrorist attacks or other significant crimes (Gierlack, et al., 2014). This initiative, named “Project Laser”, was a tremendous achievement that ultimately led to the identification and successful prosecution of thousands of individuals linked to IRA bombings (Roberts & Cassanova, 2012).
By 1997, the United Kingdom had created a data center that enabled law enforcement officers’ access the Automatic Number-Plate Recognition (ANPR) database regardless of their jurisdictional boundaries. Centralizing the data gathered by cameras in the United Kingdom proved to be very successful and garnered the attention of law enforcement in the United States. In 1998, the United States Customs and Border Patrol (CBP) implemented this state-of-the-art technology. Coined as Automated License Plate Readers (ALPR) the technology was received with much optimism to improving overall border security (Harkins, 2011). Similar to the growth of the ANPR technology from London to the entire United Kingdom, CBP’s successful use of ALPR technology to combat human and drug trafficking quickly drew the attention of law enforcement agencies across the United States.
Progression of Technology
If one looks at the various innovations within policing, many will say the invention of the telephone was paramount since it allowed citizens to directly report emergencies to the police. Additionally, it permitted officers to check in at various times during their shift, improved their safety and that of its citizens. By the end of the nineteenth century, the use of patrol cars and subsequently, motorcycles, enabled officers to respond to emergencies much faster. There was a clear hinderance for officers on scene to communicate with the dispatcher, which significantly compromised the officers’ safety. The next major improvement that changed police response times was the creation of the two-way radio that allowed for real-time communication between officers and dispatchers. It facilitated officers’ requests for additional resources, broadcasting important information such as suspect descriptions, and providing their status on calls. These advancements remarkably improved the services police provided and kept them safer.
As the public safety landscape evolved, so too has the next revolution in policing technology, which many law enforcement professionals have touted ALPRs as the next true game-changer (Brayne, 2020). Since its inception, the advancement of the ALPR has broadly aided in identifying vehicles associated with individuals connected to illegal activities. Prior to the implementation of ALPRs officers would have to comb through paper or electronic BOLO (Be On the Lookout) notices and familiarize themselves with all the vehicles with associated wants. Also, while on patrol, they would manually run license plates on their in-car computers. However, this method had its limitations since they could only input license plates one at a time for vehicles that were nearby. Cars moving at higher speeds pose numerous challenges, especially at night, when accurately deciphering the license plates alphanumeric characters was more difficult.
Various Challenges Presented
Whether one is driving through congested interstates or on two-lane roads in rural Georgia, it is hard to miss the presence of ALPRs mounted on intersection poles or hung on an unassuming pole with a medium-sized solar panel. However, this is not how the technology was originally deployed. In the late 1990’s and early 2000’s, large cameras were mounted on the front and rear portions of patrol cars. By 2009, approximately one-third of all U.S. law enforcement agencies with 100 or more officers deployed ALPRs (Lum et al., 2019) and by 2020 the number of agencies that acquired this technology reached nearly 65 percent (Finklea, 2024). Early versions of ALPRs were expensive and had issues with improper camera orientation as well as weather exposure that frequently caused connectivity issues. The license plate data was stored on a local government server, which limited their capacity to identify vehicles from other jurisdictions. Additionally, the ALPRs only operated when the patrol car was in use and limited to the areas patrol cars were travelling.
Soon after the implementation of ALPR technology, civil liberties organizations, watchdog groups, and average citizens expressed their concerns regarding police agencies using this new technology (Steinkraus, 2018). One of the main contentions was the propensity for abuse by members of the law enforcement community. The specific concern was how fast and broad implementation of the technology spread across the nation under the premise that it was effective in decreasing crime. Secondly, the expansion of regional databases, which in their opinion greatly aid in tracking a vehicle’s location. Lastly, there existed frustration with a perceived lack of concern for uniform standards regarding the accessibility of the collected data and retention rates by government officials (Brayne, 2017).
In an effort to quell privacy concerns, states drafted and enacted legislation that provided guidelines on the use of ALPRs, retention schedules, and training requirements. ALPR companies have followed suit by incorporating resilient auditing system which show how often the database was accessed, types of searches performed, and if hotlists were created. In addition, agencies can control the level of accessibility officers are provided. These safeguards go a long way to ensure databases are used appropriately and curtail misuse. In addition, it is critical for agencies to prioritize training in the use of ALPRs to ensure officers are efficient in its use and understand the importance of complying with respective laws and policies.
To mitigate the cost associated with purchasing and operating ALPRs, there are a variety of funding alternatives for agencies. These include state and federal grants, Special Purpose Local Options Sales Tax (SPLOST), unspent American Rescue Plan Act (ARPA) funds, partnering with local Community Improvement District (CIDs), private-public partnerships, school zone camera programs, general-fund or capital improvement allocations, asset-forfeiture funds, and a growing option, is seeking funding through an established law enforcement agency’s foundation (Moulton & Stainbrook, 2025).
ALPRs Space in the Future
ALPR companies and the law enforcement community recognized what tremendous crime-fighting technology these cameras provide and as such made significant improvements. The ALPRs became smaller. Mobile and stationary systems continued to evolve with advanced optics, robust algorithms, operate with an alternative power source such as solar as well as connect via cellular. The ruggedness and solar capabilities of these improved ALPRs facilitated rapid scalability and allowed the cameras to efficiently operate 24 hours a day, and featured a high weatherproof rating (U.S. Department of Homeland Security, 2025). This made the placement of fixed ALPRs more convenient and significantly lowered the installation and associated maintenance costs.
ALPR technology has come a long way since its inception. There now exists Android and iOS applications enable smartphones into an ALPR. Moreover, ALPR data can be used in real-time collaboration with other policing technologies such as with drone deployment. AI enhanced video cameras can also be converted to operate as an ALPR, algorithms that focus on the distinct features of a vehicle in addition to license plate numbers, Computer Aided Dispatch (CAD) and Report Management Systems (RMS) are increasingly integrating ALPR systems to create a seamless mechanism within the larger public safety ecosystem.
So how do these collaborations work in a real-time environment? In the event an ALPR identifies a license plate of interest, the system would immediately create a CAD event for an ALPR detection. The communications officer relays the vehicle’s location, requests the launch of an autonomous police drone, check nearby cameras, and provides its direction of travel. Some software programs provide a predictive path of travel and view cameras along that possible route. These once disparate systems work cohesively, increasing the success of locating, tracking, stopping and detaining its occupants. From an investigative perspective, these collaborative systems allow analysts and detectives to effectively conduct robust searches across various systems and generate credible leads when conducting investigations. Obtaining this information quickly can often be the difference between catching the criminals or them getting away to further victimize others. The future of ALPR technology is boundless so as long as there are talented and dedicated public safety professionals behind the scenes ensuring excellent results.
References
Brayne, S. (2017). Big Data Surveillance: The Case of Policing. American Sociological Review, 82(5), 977–1008. https://doi.org.saintleo.idm.oclc.org/10.1177/0003122417725865
Brayne, S. (2020). Predict and surveil: Data, discretion, and the future of policing. Oxford University Press.
Finklea, K. (2024, August 19). Law enforcement and technology: Use of automated license plate readers (CRS Report R48160). Congressional Research Service. https://crsreports.congress.gov/product/pdf/R/R48160
Gierlack, K., Williams, S., LaTourrette, T., Anderson, J. M., Mayer, L. A., & Zmud, J. (2014). License plate readers for law enforcement: Opportunities and obstacles (RR-467). RAND Corporation. https://www.rand.org/pubs/research_reports/RR467.html
Harkins, G. (2011, May 11). License plate recognition databases—good for cops or invasion of privacy? Medill National Security Zone. http://nationalsecurityzone.org/site/license plate-recognition-databases%E2%80%94good-for-copsor-invasion-of-privacy/
Lum, C., Koper, C. S., Willis, J., Happeny, S., Vovak, H. and Nichols, J. (2019), “The rapid diffusion of license plate readers in US law enforcement agencies,” Policing: An International Journal, 42(3), 376–393. https://doi.org/10.1108/PIJPSM-04 2018-0054
Pylas, P. (2020, November 18). UK police arrest man over IRA bombings in pubs in 1974. Associated Press. https://apnews.com/article/england-arrests-bombings-birmingham belfast-93706d448ff929a551ff75dca598b082
Roberts, D. J., & Casanova, M. (2012). Automated license plate recognition systems: Policy and operational guidance for law enforcement. Washington, DC: National Institute of Justice.
Moulton, M., & Stainbrook, M. (2025, August 27). Enhancing public safety through technology adoption: A call to action for police leaders. Police Chief Online. https:/www.policechief magazine.org/enhancing-public-safety-tech/
Steinkraus, R. (2018). Automatic License Plate Readers: The Answer to Preemptive Crime Prevention. U. Cent. Fla. Dep’t Legal Stud. LJ, 1, 25.
U.S. Department of Homeland Security, Science and Technology Directorate, National Urban Security Technology Laboratory. (2025, June 10). Automated license plate readers: Market survey report. https://www.dhs.gov/sites/default/files/2025-06/25_0606_st_lprmsr .pdf
Dr. Edward Restrepo
Dr. Edward Restrepo is a law enforcement executive with more than 29 years of experience. He was a Major with the second‑largest police department in Georgia, conducting and overseeing major felony investigations retiring as Commander of the Special Operations Division after nearly a decade volunteering as a SWAT crisis negotiator. In October 2024 he earned a Doctor of Criminal Justice (D.C.J.) with a Specialization in Education from Saint Leo University, where he has been adjunct faculty since 2019. He currently serves as the Chief for the newly formed Peachtree Corners Marshal’s Office since 2023.












