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Automated license plate reader coverage in the USA

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Built this over the last few days, based on a Rust codebase that parses the latest ALPR reports from OpenStreetMaps, calculates navigation statistics from every tagged residential building to nearby amenities, and tests each route for intersection with those ALPR cameras (Flock being the most widespread).These have gotten more controversial in recent months, due to their indiscriminate large scale data collection, with 404 Media publishing many original pieces (https://www.404media.co/tag/flock/) about their adoption and (ab)use across the country. I wanted to use open source datasets to track the rapid expansion, especially per-county, as this data can be crucial for 'deflock' movements to petition counties and city governments to ban and remove them.In some counties, the tracking becomes so widespread that most people can't go anywhere without being photographed. This includes possibly sensitive areas, like places of worship and medical facilities.The argument for their legality rests upon the notion that these cameras are equivalent to 'mere observation', but the enormous scope and data sharing agreements in place to share and access millions of records without warrants blurs the lines of the fourth amendment.

HN · launched Dec 10, 2025 · 239 upvotes (top 4%) · 0 views

Niche: interactive mapping platforms · 191 launches, 16 in the last 7 days ▲ +7% · Explore this niche →

Category and tags

  • Security
  • Vertical SaaS
  • B2B
  • Not AI
  • Commercial product

Visit website ↗ Source listing ↗

Could you build this?

Partial Calculating routing intersections using Rust and OpenStreetMap data is achievable, but running country-scale routing simulations across every residential building in the US requires significant computational geography and high-performance routing engines.

What it would actually take: The architecture requires ingesting massive OSM extracts (PBF format) into a custom Rust routing engine (or customizing Valhalla/OSRM) to run multi-point isochrones and shortest-path calculations from hundreds of millions of residential nodes to target amenities. The primary technical bottleneck is spatial indexing (using R-trees, H3, or S2) and memory-efficient graph traversal to calculate hundreds of millions of route intersections against camera coordinates without running out of RAM or taking weeks of compute.

Discussion

20 comments analyzed.

Competitors mentioned: Citizens app (crimestopper social media platform), Automated traffic enforcement systems, Repo tracking companies

Concerns raised: Surveillance overreach and privacy risks, Lack of discretion in automated enforcement (same penalty for minor vs. dangerous violations), Video editing makes automated enforcement unreliable, Potential for abuse similar to historical surveillance abuses, Data fatigue without actionable solutions

Feature requests: AI that enforces spirit of law (dangerous driving) instead of letter of law, Broader enforcement beyond speeding (phone use, improper turns, failure to signal), Model daily commute routines rather than straight-shot paths

Competitors

Other products that read as similar to this one : 40 launches clear the similarity bar, closest 8 shown.

Attention rank: #3 of 41 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Looks like the first mover among its competitors.

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