Surveillance Has No Borders
When we launched Sentinel, it mapped 354,000 cameras. Almost all of them were in the United States. That was a problem.
Surveillance infrastructure doesn’t respect borders. A French journalist investigating organized crime faces speed cameras on every highway. A German activist traveling to a protest encounters ANPR readers at every motorway junction. A South Korean whistleblower walks through a city with more CCTV per capita than almost anywhere on Earth.
If you only map cameras in one country, you’re giving people a false sense of security everywhere else.
21 countries and counting
Today, Sentinel covers 414,000+ cameras across 21 countries. We didn’t just scrape data from one source. We built ingest pipelines for government open data APIs from agencies across three continents:
North America: Caltrans (California’s 3,434 highway cameras across 12 districts), DriveBC (1,058 cameras on BC highways), Ontario 511, Alberta 511, Quebec MTQ, Toronto, Vancouver, Calgary, Austin, Chicago, NYC, and DC.
Europe: France has 60,983 speed cameras. Germany, Spain, Poland, Austria, Switzerland, Sweden, Belgium, Czech Republic, Portugal, Netherlands, Norway, and Denmark all have significant camera networks. The UK alone has 5,637 mapped cameras including TfL JamCams and ANPR readers.
Asia-Pacific: South Korea (3,028), India (4,084), Japan (1,784), Australia (1,548 across multiple states), and New Zealand (895).
Every data point comes from a public source: government open data portals, OpenStreetMap community mapping, EFF research, or public records requests.
Why government data matters
Community-mapped data (like OpenStreetMap) is valuable but inconsistent. A city might have 10,000 cameras but only 200 mapped by volunteers.
Government open data is different. When Caltrans publishes camera locations, that’s the official count. When Ontario 511 exposes an API with 923 cameras, those are real, verified, maintained installations. When TfL shares 883 JamCam locations, that’s London’s traffic surveillance network confirmed by the agency that operates it.
We treat government data as the highest-confidence source in our pipeline, followed by community-verified data, then crowdsourced data.
The scale of what we don’t know
414,000 cameras sounds like a lot. It’s not.
China has an estimated 600 million surveillance cameras. The UK alone has an estimated 5.2 million CCTV cameras, but only about 6,000 appear in public mapping databases. The US has roughly 100 million cameras in operation, but only a fraction appear in any public dataset.
Amazon Ring alone has 20-30 million residential cameras. Clearview AI has indexed 70 billion faces. Retailers deploy facial recognition without disclosure. Police use cell-site simulators that don’t appear in any public record.
Sentinel maps what can be verified from public sources. The true surveillance infrastructure is orders of magnitude larger.
What comes next
We’re actively expanding coverage:
- Italy, Finland, Singapore are in the pipeline (their datasets are large enough to cause our data provider’s servers to time out, so we’re working on batch processing)
- More Australian states (Queensland, Western Australia, South Australia)
- US 511 networks across Georgia, New York, Wisconsin, Idaho, and Minnesota (awaiting API keys)
- UK council data from more local authorities beyond Leicester
- South Korea’s national CCTV registry (1.7 million cameras, requires data.go.kr registration)
The goal is simple: if a camera exists in a public record, it should be on the map. Anywhere in the world.
Why this matters
Surveillance works because it’s invisible. You can’t make informed decisions about your privacy if you don’t know what’s watching you.
Sentinel makes the invisible visible. Open the map and see for yourself.