Law enforcement agencies across the country are facing a staffing crisis. According to a recent survey by the Police Executive Research Forum, 63% of police departments reported a decrease in applications for sworn positions in the past five years, while 29% reported an increase in resignations and retirements. The reasons for this decline are complex and multifaceted, ranging from low pay and morale to negative public perception and increased scrutiny. The consequences, however, are clear: reduced capacity, increased workload and compromised public safety.
The potential of automated license plate recognition systems
ALPR systems are computer-controlled camera systems that can automatically capture and analyze license plate images from vehicles that pass within their view. The images are then converted into alphanumeric characters using optical character recognition, and compared to databases of vehicles of interest, such as stolen cars, wanted suspects or missing persons. If a match is found, the system can alert the officers in real time, providing them with relevant information and actionable intelligence, such as the location, direction and speed of the vehicle, the identity and criminal history of the owner or driver, and any outstanding warrants or alerts associated with them. This can help the officers to quickly locate and apprehend the suspects, prevent or solve crimes, and recover stolen property.
ALPR systems can also utilize archived data from the real time crime center (RTCC) databases to provide insights for investigators on cold cases. RTCCs are centralized locations that gather, analyze, and share data from various sources, such as security cameras, gunshot detection systems, automated license plate readers, social media monitoring, computer-aided dispatch systems and criminal databases. By accessing the RTCC databases, ALPR systems can help investigators to track the movements and associations of vehicles and suspects over time, identify patterns and trends and generate leads and evidence for solving crimes. This can improve the clearance rates and case solvability of law enforcement agencies, as well as enhance their accountability and transparency.
The role of civilian data analysts
ALPR systems are powerful tools for law enforcement, but they are not perfect. They can sometimes produce errors, such as misreading a license plate, failing to detect a plate, or matching a plate to the wrong vehicle. They can also raise ethical and legal concerns, such as privacy violations, data breaches or misuse of data. Therefore, ALPR systems need human oversight, maintenance and analysis to ensure their accuracy, reliability and compliance with laws and policies.
This is where civilian data analysts come in. Civilian data analysts are non-sworn personnel who have specialized skills in data collection, processing and interpretation. They can play a dual role in the ALPR ecosystem: driving equipped ALPR cars to gather data on the field and verifying and analyzing the data in the Real Time Crime Center (RTCC).
By using machine learning (ML) techniques, such as clustering, classification and anomaly detection, civilian data analysts can also enhance the data insights and optimize the ALPR performance. ML techniques can help the analysts to identify patterns and trends, detect outliers and anomalies and improve the accuracy and speed of the ALPR system. By doing so, they can effectively multiply the agency’s ability with minimal staff, reducing the workload and pressure on the sworn officers.
By providing timely and accurate information to sworn officers, civilian data analysts can support the law enforcement mission and enhance public safety and security. They can help the officers to quickly locate and apprehend suspects, prevent or solve crimes and recover stolen property. They can also help the officers to comply with the legal and ethical standards of using ALPR data, such as obtaining warrants, deleting irrelevant data and protecting data from unauthorized access.
Case studies and considerations
ALPR systems have become more advanced and ubiquitous, thanks to the rapid development of artificial intelligence and computer vision. ALPR systems can now capture and analyze license plates in various conditions, such as low light, rain, snow or fog. They can also recognize license plates from different countries, regions and formats, as well as distinguish between similar-looking characters, such as O and 0, or I and 1. ALPR systems can also integrate with other sources of data such as facial recognition, biometric identification, vehicle registration, criminal records and social media profiles to provide a comprehensive picture of the vehicle and its occupants.
Imagine how a law enforcement agency that has implemented ALPR systems and hired a team of civilian data analysts to support them are likely to see positive results, such as increased recovery of stolen vehicles, identification of suspects and clearance of cases. The civilian analysts are able to drive around the city in ALPR cars, scanning license plates and collecting GPS locations and time stamps. They also monitor and validate the ALPR alerts in the Real Time Crime Center (RTCC), filtering out false positives and identifying patterns and trends. Further they use ML algorithms to group vehicles by similarity, classify vehicles by risk level and detect anomalies or outliers. For example, the advances indicate they can use clustering algorithms to find vehicles that frequently travel together, indicating possible criminal associations. They can use classification algorithms to assign a risk score to each vehicle, based on factors such as previous offenses, outstanding warrants, or suspicious behavior. They can use anomaly detection algorithms to identify vehicles that deviate from their normal routes, locations, or times, indicating possible threats or emergencies.
They also provide training and technical assistance to officers on how to use ALPR systems effectively. For example, they can teach officers how to interpret the ALPR data, how to access additional information sources and how to use the ALPR system as an investigative tool.
However, the agency also faces some challenges in integrating civilian data analysts into its ALPR workflows. The agency needs to ensure that civilian analysts have the necessary qualifications, background checks and security clearances to handle sensitive data. This may require the agency to adopt stricter standards and protocols for hiring, training, and certifying civilian analysts, as well as for protecting, storing and sharing the ALPR data. It also needs to provide them with adequate training, supervision and feedback to ensure quality and consistency. This may involve establishing clear roles and responsibilities, performance indicators and evaluation methods to monitor and improve the civilian analysts’ work. The data analysts must be able to convey to officers the effectivity of ALPR systems, how the data is interpreted, how the information sources are accessed and any technical questions which may arise for court testimony.
One way to do this is to have regular sessions where civilian analysts and sworn officers exchange knowledge and best practices on using ALPR systems and ML techniques. This can also foster a culture of collaboration and trust between the two groups, as well as address any potential issues of role ambiguity, conflict or resentment. For example, the civilian analysts can share their insights and suggestions on how to improve the ALPR system, while the sworn officers can provide feedback and guidance on how to use the ALPR data effectively and ethically. This can also create a sense of mutual respect and appreciation, as well as enhance the communication and coordination between the two groups.
Leverage the power of technology
ALPR systems are a powerful tool for law enforcement. Civilian data analysts can complement the skills of sworn officers, providing them with valuable insights and intelligence that can enhance their operations and efficiency. The integration of ALPR systems and civilian data analysts into law enforcement agencies can provide a powerful solution to the current staffing crisis. By utilizing advanced technology and the expertise of civilian analysts, law enforcement agencies can enhance their operations, increase efficiency and improve public safety. However, careful consideration must be given to the ethical implications of using AI in law enforcement, including issues of privacy, accountability and bias. Consideration must also be given to the processing of digital evidence, court testimony and best practices. It is crucial for law enforcement agencies to establish clear protocols and guidelines for the use of ALPR systems and the integration of civilian analysts into their workflows. By doing so, law enforcement agencies can effectively leverage the power of technology while maintaining the trust and confidence of the communities they serve. In the upcoming articles of this series, we will explore some ethical issues, such as privacy, accountability, and bias as well as evidence and data integrity.
