Private automated license plate recognition networks are photographing vehicles across the United States and compiling billions of timestamped sightings into databases that are sold to insurers, lenders, repossession companies, and law enforcement. While police-operated ALPR systems have drawn widespread controversy, the private networks that operate largely out of public view may pose a broader challenge to oversight and transparency.
One of the largest players is Digital Recognition Network, known as DRN, which is now part of Motorola Solutions. Motorola acquired DRN and its law-enforcement-focused sibling Vigilant Solutions when it bought VaaS International Holdings for $445 million in 2019. At the time, Motorola described the business as providing vehicle-location data to both public-safety and commercial customers through fixed and mobile license plate reader cameras.
The scale of the operation is substantial. A California appeals court recently noted that, as of May 2024, DRN's system contained more than 9 billion historical license plate images. Those records include images of plates and vehicles along with the date, time, and location where each image was captured. DRN sells ALPR hardware, including fixed cameras and mobile systems that can be mounted to vehicles such as tow trucks.
DRN is not alone. MVTRAC, which primarily serves auto lenders and the repossession industry, says its network collects more than 500 million new license plate recognition data points every month through a nationwide network of more than 600 recovery affiliates. Flock Safety represents another model, with cameras used by private businesses, neighborhoods, apartment complexes, schools, and other organizations that have the option of sharing vehicle data with law enforcement.
The business models differ, but the broader pattern is consistent: privately operated cameras are already collecting enormous amounts of data about where vehicles are seen. That information can then be sold or made available to customers ranging from lenders and repossession companies to insurance companies and law enforcement.
The insurance applications are particularly detailed. DRN openly advertises insurance products built around its data. One called Garage Aware is designed to determine whether a vehicle is actually kept where the policyholder told the insurance company it is. That matters because insurance rates can vary significantly based on where a car is garaged. DRN's developer documentation describes «sleep hour sightings» and the ability to compare those observations with both the address provided by a customer and another location discovered through its data. The system can even incorporate the difference in insurance premiums between ZIP codes.
Another product, Radius Response, uses license plate sightings to determine whether commercial vehicles are regularly operating beyond their declared geographic area. Vehicle Sighting Search is advertised to insurers as a way to «map vehicle movements» to investigate claims, identify suspicious patterns, and enforce policy compliance. Images can also be examined for company signage, toolboxes, ladder racks, and trailers that might indicate someone is using a personally insured vehicle commercially. Historical images can help determine whether damage existed before an insurance claim.
There are legitimate applications for this technology. Someone claiming their car lives in rural Iowa when it is actually parked every night in downtown Chicago is withholding information an insurer legitimately uses to calculate risk. The same applies to someone insuring a work truck as a personal vehicle.
The concern is that the technology capable of discovering those deceptions is also capable of revealing much more. Repeated sightings could establish patterns that go beyond insurance verification. A vehicle consistently photographed at one location overnight can potentially reveal where its owner lives, and the aggregation of billions of records creates a detailed picture of movement that individual photographs would not.
Private ALPR networks face far less public scrutiny than police-operated systems. With police systems, the public can at least identify the government agency involved and seek information through public records processes. With private networks, determining exactly who is looking at the data, and why, can be considerably more difficult. The result is a growing repository of vehicle location information that operates largely outside the debates that have surrounded law enforcement use of the same technology.