In Detail:
Automated License Plate Readers (ALPR)
An overview for public safety professionals
Mindy Duong, Statistical Analyst, Office of Research & Statistic (May 2024)
PDF Version- In Detail: Automated License Plate Readers (ALPR)
HTML Version- In Brief: Automated License Plate Readers (ALPR)
PDF Version- In Brief: Automated License Plate Readers (ALPR)
BACKGROUND
Automated license plate readers (ALPR) are high-speed cameras that automatically capture license plates and contextual photos of related vehicles in addition to providing information about the geographic location of where the plates were captured, the date and time the plates were captured, and the specific camera/unit that was used. The data directly captured by the ALPR are anonymous, providing no personally identifiable information (PII) on the occupants of the vehicle, registered owner, nor any description of the vehicle itself. The ALPR simply indicates that a plate was captured by their camera, whether mobile (e.g., mounted on a police car) or stationary (e.g., placed on a roadway or building) at a certain place and time. If a plate is put on a list of known stolen vehicles (i.e., a hotlist), then an alert would be sent, but not every plate captured will be reviewed for further details unless determined to be relevant to an ongoing investigation, necessary to locate a person (e.g., suspect, victim, missing people), or to protect the public or critical infrastructure during special events (IACP, n.d.). span>
Data retention policies vary from state to state, but a Colorado Statute passed in 2014 (§24-72-113, C.R.S.) “requires that video or still images obtained by passive surveillance by governmental entities, such as images from monitoring cameras, must be destroyed within three years after the recording of the images” (NCSL, 2022). Currently, there are no federal laws “that explicitly govern or limit the use of ALPR technology or taking photographs of things that are plainly visible from public spaces by law enforcement agencies;” however, there are state-level policies that restrict ALPR access to authorized and trained law enforcement personnel only, which includes an audit trail that indicates who, when, and what data was accessed and a justification (e.g., ongoing investigation) for the access (IACP, n.d.).
IMPACT ON CRIME & INVESTIGATIONS
Investigators need one of three elements to solve a crime: a witness, physical evidence, or a confession (Klockars & Mastrofski, 1991 as cited in Willis, Koper, & Lum, 2018). These elements may not be as reliable as desired — witness statements may be misrepresented, physical evidence may be unavailable, and suspect confessions may be fabricated. The use of ALPR can help corroborate or disprove these elements by providing objective data on a vehicle’s whereabouts during a specific time and place (Byrne & Marx, 2011 as cited in Willis, et al., 2018). A 2020 survey conducted by the Bureau of Justice Statistics found that 65% of participating local police departments used ALPR (Goodison & Brooks, 2023).
ALPR can be used to assist in locating a person of interest (e.g., suspect, victim, missing person), provide information and assistance to an ongoing investigation, or for crime prevention and public safety strategies. The most notable usage of ALPR is for identifying and locating stolen vehicles. Colorado continues to lead the nation in motor vehicle thefts (MVT) with a rate of 785.7 per 100K residents compared to the U.S. rate of 282.7 in 2022. In 2023, the MVT rate per 100K residents was at 654.8, a 17% decrease from 2022 (see Figure 1 below). The use of ALPR technology has the potential to assist law enforcement in reducing these high rates.
Figure 1. Colorado Motor MVT rate versus U.S. MVT rate per 100K residents, 2014-2023.
Source: Colorado Bureau of Investigation & Federal Bureau of Investigation, Crime Data Explorer (retrieved, 2/16/2024).
In 2022, the majority (79%) of secondary crimes related to MVT were property crimes, most notably destruction and vandalism (33%), theft from motor vehicles (21%), and stolen property (15%) (CBI, 2022). Using ALPR to help reduce MVT has a potential domino effect on reducing crimes as a whole.
ALPR USAGE FOR OFFICERS
- Hotlists automatically identify and track vehicles (and plates) of interest and send alerts when hit.
- Increase arrest rates due to quicker response times using real-time data and alerts.
- Collect millions of vehicle and plate data to investigate current and past crimes.
- Data collected can provide a geographic timeline of vehicle travel patterns. (EFF, n.d.)
CONTROVERSIES & ETHICAL CONCERNS
Support for ALPR usage varies on the circumstance for it being used; for example, people are generally more supportive of ALPRs to detect stolen vehicles, but are less supportive of using ALPRs to scan vehicles that had unpaid tickets or parking violations. Increased support for ALPR correlates with increased trust in law enforcement and whether the data collected were viewed as public information. Lower levels of trust in law enforcement is correlated with decreased support for ALPR, especially in racial and ethnic minority groups (Merola & Lum, 2014 as cited in Shjarback, 2024). In addition, a 2018 survey conducted with 405 non-law enforcement participants found that those with more knowledge of the usage of ALPR had “significantly lower levels of trust in police” (Merola, Lum, & Murphy, 2019).
There are concerns regarding privacy and civil liberties with the use of ALPR. Since ALPR can capture and store vast amounts of license plate data, there is a potential to create a detailed record of an individual's movements over time. The lack of consistent state or federal regulations on data retention and usage raises questions about how this information is stored, shared, and protected. Additionally, there is the risk of misuse or unauthorized access to the collected data, leading to potential violations of individuals' privacy rights (ACLU, 2013). Critics argue that the widespread deployment of ALPRs without adequate safeguards may result in unwarranted surveillance and erosion of personal freedoms, highlighting the need for a thoughtful balance between security and privacy in the implementation of such technologies (Stein, 2023).
CONSIDERATIONS
While ALPR has been used by law enforcement agencies to aid in crime prevention and investigations, the effectiveness of ALPR in reducing crime rates remains a complex and multifaceted issue as it depends on various factors, including their implementation, integration with other law enforcement tools, and adherence to privacy and data protection regulations. Public debate and regulatory oversight are crucial in ensuring a balance between crime prevention and individual rights. It is important to remember some key facts about ALPR:
- ALPR data is anonymous and does not provide information on the vehicle's occupants or the vehicle description itself. It only provides the license plate, contextual photo of the vehicle (e.g., back of the vehicle where the license plate is), when and where it was captured, and by what camera/unit it was captured (IACP, n.d.).
- While data may be stored for up to three years in Colorado, not every license plate is constantly monitored. Those placed on a hotlist will be flagged, and individual queries can be performed on specific plates, but every single individual’s movements are not being actively tracked or reviewed.
- ALPR has been shown as an effective crime deterrent and investigative tool:
- The visible presence of ALPR may act as a deterrent to criminal activity, especially vehicle-related crimes, since the likelihood of being monitored and recorded may discourage opportunistic individuals from engaging in illegal activities involving vehicles (Shults, 2018).
- ALPR data can be analyzed to identify patterns of movement and association between vehicles, potentially providing insight into criminal networks, creating a geographic profile of suspects, and detecting unusual or suspicious behavior (Shults, 2018).
The following is a summary of additional arguments for and against ALPR (Diaz & Levinson-Waldman, 2020; Klawans, 2023; NYLN Youth Leader Blog, 2016; Shashirangana, Padmasiri, Meedeniya, & Perera, 2021; Spinks, 2023.)
| Arguments For ALPR | Arguments Against ALPR |
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Technological Advancements
Technology and artificial intelligence (AI) have been advancing exponentially, contributing to increased ALPR capabilities and functions to assist law enforcement in accurate detections, criminal investigations, and issues related to staffing shortages. The implementation of ALPR technology has eliminated the need for manual labor of collecting and monitoring license plates, allowing law enforcement to do more with less (Lukens, 2024). Methodologies that yield more than 95% efficacy for ALPR have existed for more than 20 years and will continue to improve as technology and AI continue to progress (Heo, Kim, Jung, Lee, & Oh, 2007; Lee, Chen, & Wang, 2004; Luo, Sun, Zhou, & Lou, 2009). According to former police chief, Philip Lukens (2024), advancing ALPR technology can “improve the clearance rates and case solvability of law enforcement agencies, as well as enhance their accountability and transparency.”
Additional Information and Resources
- Major Cities Chiefs Association (MCCA), ALPR Working Group, Recommendations & Considerations (pdf)
- CATPA: Template Guide for Funding an ALPR System - ALPR Standards and Requirements (pdf)
- IACP: License Plate Reader (LPR) Systems: Use Cases (pdf)
- Check if a vehicle is stolen: Colorado Bureau of Investigation (CBI): Motor Vehicle (VIN) Verification System
- Check if a VIN matches the vehicle: National Highway Traffic Safety Administration (NHTSA) VIN Decoder
Grant Programs
In June 2023, Colorado Senate Bill 2023-257 was passed to provide the Colorado Auto Theft Prevention Authority (CATPA) with $5M to address MVT-related concerns, including equipment such as ALPR (CATPA, 2023). In 2022, the Justice Assistance Grant (JAG) funded $2.4M in various law enforcement initiatives; of those, about $120K was specifically spent on ALPR (JAG, 2023). Finally, Colorado’s Crime Prevention through Safer Streets Grant Program has a budget of $3.7M that will invest in preventative measures and proactive initiatives between 2024-2026, including ALPR purchases (DCJ: Safer Streets, 2023).
REFERENCES
ACLU (American Civil Liberties Union). (2013). You Are Being Tracked: How License Plate Readers Are Being Used to Record Americans’ Movements. ACLU.Org. (accessed, 11/15/2024).
Byrne, J. M., & Marx, G. (2011). Technological Innovations in Crime Prevention and Policing: A Review of the Research on Implementation and Impact. Journal of Police Studies, 3(20), 17-40. [Linked to the NCJRS Virtual Library that includes a link to a PDF version of the article.]
CATPA (Colorado Auto Theft Prevention Authority). (2023). Grants: All About CATPA Grant Programs. LockDownYourCar.Org. (accessed, 1/15/2024).
CBI (Colorado Bureau of Investigation). (2022). Colorado Crime Statistics: Motor Vehicle Theft 2022. Colorado Crime Online: ColoradoCrimeStats.State.Co.Us/TOPS. (accessed, 11/15/2023).
Diaz, A. & Levinson-Waldman, R. (2020). Automatic License Plate Readers: Legal Status and Policy Recommendations for Law Enforcement Use. Brennan Center for Justice. (accessed, 11/15/2023).
DCJ: Safer Streets (2023). Crime Prevention through Safer Streets Grant Program. Office of Adult and Juvenile Justice Assistance, Division of Criminal Justice. (accessed, 1/15/2024).
EFF (Electronic Frontier Foundation). (no date). Data Driven: What is ALPR. EFF.Org. (accessed, 1/15/2024).
Goodison, S. E., & Brooks, C. (2023). Local Police Departments, Procedures, Policies, and Technology, 2020 – Statistical Tables (pdf). Bureau of Justice Statistics, Office of Justice Programs, U.S. Department of Justice [NCJ 307405].
Heo, G., Kim, M., Jung, I., Lee, D. -R., & Oh, I. -S. (2007). Extraction of Car License Plate Regions Using Line Grouping and Edge Density Methods. Proceedings of the 2007 International Symposium on Information Technology Convergence, Jeonju, South Korea, pp. 37-42. DOI: 10.1109/ISITC.2007.79.
IACP (International Association of Chiefs of Police) (no date). Automated License Plate Recognition. TheIACP.Org: Projects - ALPR. (accessed, 12/15/2023).
JAG (Justice Assistance Grant). (2024). 2024 Edward Byrne Memorial Justice Assistance Grant Program. Office of Adult and Juvenile Justice Assistance, Division of Criminal Justice. (accessed, 1/15/2024).
Klawans, J. (2023). The Pros and Cons of License-plate Reader Technology. TheWeek.com. (accessed, 1/15/2024).
Klockars, C., & Mastrofski, S. D. (1991). The Police and Serious Crime. In C. Klockars & S. D. Mastrofski (Eds.), Thinking about Police: Contemporary Readings (pp. 131-138). New York, NY: McGraw-Hill.
Lee, H. -J., Chen, S. -Y., & Wang, S. -Z. (2004). Extraction and Recognition of License Plates of Motorcycles and Vehicles on Highways. Proceedings of the 17th International Conference on Pattern Recognition. ICPR, Cambridge, pp. 356-359 Vol.4. DOI: 10.1109/ICPR.2004.1333776.
Luo, L., Sun, H., Zhou, W., & Luo, L. M. (2009). An Efficient Method of License Plate Location. Proceedings of the First International Conference on Information Science and Engineering, Nanjing, China, pp. 770-773. IEEE Xplore-DOI: 10.1109/ICISE.2009.250.
Lukens, P. (2024). Improving Law Enforcement with ALPR Technology. Police1.Com (accessed, 4/2/2024).
Merola, L. M., & Lum, C. (2014). Predicting Public Support for the Use of License Plate Recognition Technology by Police. Police Practice and Research, 15(5), 373-388. DOI:10.1080/15614263.2013.814906.
Merola, L. M., Lum, C., Cave, B., & Hibdon, J. (2014). Community Support for License Plate Recognition. Policing: An International Journal, 37(1), 30-51. DOI: 10.1108/PIJPSM-07-2012-0064
Merola, L. M., Lum, C., & Murphy, R. P. (2019). The Impact of License Plate Recognition Technology (LPR) on Trust in Law Enforcement: A Survey-Experiment. Journal of Experimental Criminology, 15(1), 55-66. DOI: 10.1007/s11292-018-9332-8
NCSL (National Conference of State Legislatures). (2022). Automated License Plate Readers: State Statutes. NCSL.Org: Technology. (accessed, 11/15/2023).
NYLN: Youth Leader Blog. (2016). Automatic Number Plate Recognition Pros and Cons List. NYLN.Org - National Youth Leadership Network. (accessed, 11/15/2023).
Shashirangana, J., Padmasiri, H., Meedeniya, D., & Perera, C. (2021). Automated License Plate Recognition: A Survey on Methods and Techniques. IEEE Access, 9, 11203-11225. DOI: 10.1109/ACCESS.2020.3047929.
Shjarback, J. A. (2024). Examining Police Officers’ Perceptions of Automated License Plate Readers Before Technology Expansion. Criminal Justice Policy Review, 35(1), 3-21. DOI: 10.1177/08874034231220627.
Shults, J. F. (2018). How ALPR Data Drives Intelligence-led Policing. Police1.Com (accessed, 11/15/2023).
Spinks, R. (2023). What You Need to Know About Automatic License Plate Readers. American Police Beat: APBWeb.Com. (accessed, 11/15/2023).
Stein, N. (2023). Automated License Plate Readers: Legal and Policy Evaluation (pdf). Ann Arbor, MI: University of Michigan, Ford School of Public Policy: Science, Technology and Public Policy Program. (See also, Automated License Plate Readers widely used, subject to abuse.)
Willis, J. J., Koper, C., & Lum, C. (2018). The Adaptation of License-Plate Readers for Investigative Purposes: Police Technology and Innovation Re-invention. Justice Quarterly, 35(4), 614-638. DOI: 10.1080/07418825.2017.1329936.
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