Nobody — not a vendor, not a federal agency, not a single state — publishes a complete, public, up-to-date list of every ALPR camera in the United States. Deployment is too decentralized: thousands of separate police departments, HOAs, and private businesses, each buying cameras on their own schedule from a handful of competing vendors. Into that gap has stepped an unusual volunteer effort: mapping ALPR cameras directly into OpenStreetMap, the crowdsourced, editable map that anyone can contribute to.

What OpenStreetMap is, briefly

OpenStreetMap (OSM) is a free, editable map of the world, built entirely from volunteer contributions and licensed under the Open Database License (ODbL) — the same license FlockScanner’s own camera data draws from. Anyone can add a point to the map and tag it with structured metadata describing what it represents: a coffee shop, a fire hydrant, a traffic signal, or, as it turns out, a surveillance camera.

The tagging scheme

OSM already had a general man_made=surveillance tag for marking camera locations before ALPR-specific mapping took off. Volunteers extended it with a surveillance:type=ALPR sub-tag, documented on the OpenStreetMap Wiki, specifically to mark a camera known to be part of an automatic license plate recognition system, as distinct from a generic CCTV camera.

Contributors are encouraged to add further structured detail where it’s known, including:

  • manufacturer=* — the camera vendor (Flock, Motorola/Vigilant, Genetec, Rekor, and others)
  • camera:direction=* — which way the camera faces, recorded in degrees
  • surveillance:zone=* — what kind of area the camera watches: through-traffic, a parking area, or an entrance/exit point

That last tag matters for interpretation. A camera watching a highway on-ramp serves a different surveillance purpose than one watching the entrance to a single parking garage, even though both might carry the same ALPR type tag.

Who’s behind it: DeFlock

The most visible organizing effort behind this mapping push is DeFlock, an open-source project created by a group going by FoggedLens. DeFlock isn’t a data source of its own — it doesn’t run its own camera registry — it’s a set of tools (a mobile-friendly submission flow and a public map built on the Overpass API and Leaflet) that make it easier for ordinary people to find, verify, and tag ALPR cameras directly into OpenStreetMap using the scheme described above. The live map is published at maps.deflock.org.

By early 2026, reporting on the project put the count of ALPR-tagged nodes in OpenStreetMap at more than 336,000 worldwide, spanning Flock’s cameras alongside a long tail of other vendors. That scale reflects both real growth in ALPR deployment and the project’s growing volunteer base — the Criminal Legal News coverage of the project describes it as a direct, grassroots response to the lack of any official public inventory.

Why crowdsourcing, not an official registry

An official government registry would need cooperation from thousands of independent police departments, HOAs, and private camera owners — many of whom have no obligation, and sometimes an active disincentive, to publish their camera locations. Crowdsourcing sidesteps that by relying instead on what’s directly observable in public: a camera mounted on a pole is visible to anyone walking or driving past it. That’s also its limitation — coverage depends entirely on volunteer attention, so densely populated, privacy-active regions tend to be mapped more thoroughly than rural ones, and any given map is a snapshot, not a guarantee of completeness.

Data quality and verification

Because anyone can edit OpenStreetMap, the community relies on conventions rather than centralized review to keep tagging accurate: requiring a description or photo evidence for surveillance tags, cross-checking against known vendor hardware appearances, and allowing other mappers to review and correct entries. It isn’t perfect, but the same open-editing model that built the rest of OpenStreetMap over two decades has scaled reasonably well for this narrower use case too.

How this connects to FlockScanner

FlockScanner’s own camera map is built directly from this same OpenStreetMap data — specifically, nodes tagged man_made=surveillance with surveillance:type=ALPR — licensed under ODbL, the same license terms described above. We don’t scrape vendor data or deflock.org itself; we read the same open, crowdsourced OSM dataset that volunteers using DeFlock’s tools (and many others, contributing directly through standard OSM editors) have been building up. If you want to see what’s been documented in a specific state, visit a directory page like /cameras/tx or /cameras/ca, or explore the interactive map directly.

If you’re interested in contributing a camera you’ve spotted, OpenStreetMap’s standard editors (iD or JOSM) support adding the tags described above directly, and DeFlock’s own submission tools are built specifically to make that easier for people who aren’t already familiar with OSM editing conventions.