Last week, BetaBoston provided a glimpse into how a handful of private data brokers have compiled massive databases of vehicle location records. By mounting high-speed license plate readers on tow trucks and repo “spotter” cars in nationwide networks, these brokers claim to have compiled scans for a majority of vehicles registered in the United States.
There has been some debate over law enforcement use of license plate scanners, including the technology’s deployment by Boston police and more than 60 other agencies across the Commonwealth. But widespread commercial use has gone largely unnoticed, even though private scanners target residential areas, employee lots, and commercial parking facilities at malls and shopping centers, in particular.
The largest such company, Digital Recognition Network of Fort Worth, Tex., commands a cache of 1.8 billion license plate scans, each a GPS-tagged snapshot of where a particular vehicle was at a particular point in time. At a hearing last week, CEO Chris Metaxas argued before Massachusetts legislators that DRN has a constitutional right to photograph license plates in plain view, and that his network’s servers store plate scans “just like people store pictures on Instagram.”
Much of what BetaBoston has uncovered about commercial license plate scanners — particularly regarding how and where the private networks collect data — comes from marketing materials from DRN’s parent company, Vigilant Solutions (previously Vigilant Video), and in particular from pitches to law enforcement subscribers.
In a June 2011 presentation for the International Association of Chiefs of Police, DRN gave a glimpse into just where its 400 affiliates collect data.
Two and a half years later, DRN’s data volume has quadrupled to 1.8 billion vehicle scan records (VSRs in the graphic above), and currently grows at 70 million scans per month, according to Vigilant’s website. The 2011 map indicates that scanning hotspots center around major metropolitan areas and more densely populated states, including much of the East Coast.
Within these states, DRN’s network of 400 repo affiliates collect data with license plate readers mounted on tow trucks and dedicated “spotter” cars. Each scanner is capable of collecting thousands of plates each day as repo agents drive around.
DRN pitches its data based on where its affiliates collect data. While vehicles scanned in transit offer some indication of driving patterns, a parked vehicle indicates its driver’s destination. Per the presentation, DRN affiliates prioritize “dependable locations,” like residential and business lots.
Data from high-density residential areas, such as apartment complexes, is part of makes DRN’s data “so valuable” to its wide clientele.
A white paper from 2010 provides further insight into the mechanics. DRN affiliates “gather vehicle license plate data in locations where vehicles are reasonably expected to remain or re-appear for an extended period of time,” such as “residential areas, apartment complexes, and business office complexes with large employee parking areas. ”
Such routes are organized based on type of site, it seems. A “typical” residential route might have “up to 50 apartment complexes or residential areas” for scanning “during hours when the locations would be most fully populated with resident vehicles (e.g., in the middle of the night).” By contrast, commercial or workplace locations are scanned “during daytime working hours.”
When asked about the above documents for last week’s article, DRN’s Metaxas insisted that his company did not direct its affiliates to collect data on private property.
“DRN provides a wide range of tools that help its authorized users do their jobs more effectively,” he said in an emailed statement. “In no instance does DRN tell agents where to go or how to do their jobs. Authorized users of DRN technology are responsible for following all relevant federal, state and local ordinances in the course of their work.”
At last week’s hearing, DRN’s Metaxas indicated that his company provides “heat maps” to its affiliates, but did not go into further detail about the network’s role in guiding data collection.