Speeder Bot highlights speeding motorists in these Sheffield neighbourhoods – with 1 in 3 drivers going over the limit
Meet Sheffield Speeder Bot – the dad who is collecting data about speeding vehicles and publishing it on Twitter.
The tweets catalogue vehicles going above 45mph in 20-30mph areas. The highest recorded was 58mph in Walkley – but the vehicles are unidentifiable so they could potentially be police or ambulances.
The data is legally accessible and Matthew pays for a programme which analysis and details it on a spreadsheet then automatically tweets it.
He explained: “Sat nav companies know the speed of the road, the speed of your car and whether you’re going above or below and they usually use that data for traffic flows.
“It’s not something a lot of people think about, so people don’t know that information is there. All the sat nav companies combine their data but it’s open source.
“People who develop software for courier or logistics companies might buy the data and I get it from a company called here.com.
“When I started, I set the programme to tweet any vehicles going 35mph and it sent about 200 tweets in 24 hours.
“That’s why I’ve raised it to above 45mph. If you set the filter at a low speed it sends out hundreds of tweets a day and in some ways that’s good because it shows the sheer number of people speeding, but also it gives you information blindness and people just scroll past.
“The speeds above 50mph are headline grabbing but it’s actually less than one per cent of the traffic and it could be a police car.
“But one in three people going through Walkey and Hillsborough are speeding above 30mph.
“There is a lot of speeding at lower levels with people doing 10mph over the limit, doing 28-32mph in a 20mph zone.”
Matthew says he’s not an “eco warrior angel” and has been caught for speeding himself but he thinks the data could be useful for Sheffield Council or the police.
“If you had six months of data before a putting in a cycle lane or active travel neighbourhood, you could see whether it had made a difference by comparing facts and figures.
“There’s a lot of learning and guesswork and I don’t have an end game but I am starting to see patterns in the data.
“For example, the time that people most exceed the speed limit is between 6am and 7am so if there’s a police speed van at lunchtime I can tell them that it’s not going to make any difference. The police have limited resources so it could help them.
“A lot of people say this would be really good outside a school but speeding is a neighbourhood problem. My kid could get hurt outside the church hall, speeding is a problem three streets down from a school, so it needs to be looked at as a whole area.”