The solution
Stanford Rivers, a small village near Ongar in Essex, sits on the A113, where the national speed limit drops to 30mph on entering — clearly signposted, routinely ignored. Drivers have been detected at up to 60mph. The parish council had no realistic way to police it.
One resident — identity hidden — built the answer from spare parts: a small camera that derives each car's speed from the distance travelled between two frames, an AI layer that counts everything into a live dashboard, and an automatic social-media feed that shames the worst offender every hour on the 'Wall of Shame'. Friday's count was 1,377 vehicles; the creator estimates 80% come from the London direction. He says he was inspired by a similar bot Gareth Rees built in Finchampstead, Berkshire.
The data changed enforcement behaviour: 'We were using the data as a parish council to try and get the police to target various times of the day when it was at its worst... and they did do that for us,' said councillor John Adams, who called the resident's work 'a brilliant job'.
Why it worked
A two-frame speed calculation needs no calibration regime or camera certification — the hack anyone can copy for a fraction of an enforcement camera.
Hourly 'worst offender' posts convert an invisible aggregate into a daily public spectacle, which is what creates pressure without a single ticket.
The same dataset doubles as a patrol-scheduling tool, so the shame feed and the official response reinforce each other.
What can be applied
When enforcement is scarce, publish the violation: an automated public count turns anecdote into data, and data into police hours, for the price of one camera and a script.
Aftermath
The Wall of Shame continues to post hourly, with daily counts above 1,000; the parish council says it is using the data to direct police patrols to peak violation times.
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