Private automated licence plate recognition networks are photographing vehicles across the United States and compiling databases that now hold billions of timestamped sightings, with the information sold or made available to insurers, lenders, repossession companies and law enforcement. The scale and commercial reach of these systems have drawn far less public attention than police-operated cameras, even as the latter face mounting controversy.
One of the largest operators 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, the company described the business as providing vehicle-location data to public-safety and commercial customers through fixed and mobile licence plate reader cameras.
The volume of data involved is substantial. A California appeals court recently noted that, as of May 2024, DRN’s system contained more than nine billion historical licence plate images. Those records include images of plates and vehicles along with the date, time and location where each image was captured. DRN sells the hardware, including fixed cameras and mobile systems that can be mounted on 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 licence 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, neighbourhoods, apartment complexes and schools that can choose to share vehicle data with law enforcement.
The commercial applications are already well established. A 2015 federal appeals court decision involving DRN described how cameras mounted on tow trucks and other vehicles automatically photographed vehicles they encountered, recorded GPS coordinates, dates and times, and how DRN sold the resulting licence plate data to customers including automobile finance and insurance companies. DRN still advertises insurance products built around that information.
One product, Garage Aware, is designed to determine whether a vehicle is actually kept where the policyholder told the insurer it is. This matters because insurance rates can vary significantly based on where a car is garaged. The system can be granular, with DRN’s developer documentation describing «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. It can even incorporate the difference in insurance premiums between postcodes.
Another product, Radius Response, uses licence plate sightings to determine whether commercial vehicles are regularly operating beyond their declared geographic area. A third, 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 a personally insured vehicle is being used commercially, while historical images can help determine whether damage existed before a claim.
There are legitimate applications. Someone claiming their car lives in a rural area when it is actually parked every night in a city centre 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 can establish patterns. A vehicle consistently photographed at one location overnight can potentially reveal where its owner lives, while a vehicle seen regularly at another address may indicate a workplace, a relationship or other personal details. Because private networks face far less public scrutiny than police-operated systems, the question of who is looking at the data, and why, can be considerably more difficult to answer.