io datalabs


UTMC Control Room Sneak Peek!


Two flights of stairs upwards, in an unassuming building on Newcastle University's campus, the Tyne and Wear Urban Traffic Management & Control (UTMC) group occupy a small suite of rooms.

There's a coffee room and a meeting room- but the third is the most interesting. This is the nerve centre - and four or five staff terminals sit facing an impressive three metre-wide wall-mounted display.

James eagerly accepted an invitation to take a digital tour.

What and Why...

The system aggregates data from a selection of sources - including CCTV, car park, flow, air quality and weather data.

This is useful for monitoring the flow across the city, under normal conditions and for unusual events - from concerts to emergencies.

They use the information for public awareness - distributed via their Twitter and Facebook accounts.

There's also a facility for planning- to set up triggers and response patterns. For example, if the sensors suggest congestion, traffic light patterns can be changed to ease the flow. This may be as simple as lengthening the duration of green lights - thus lessening the frequency of the ten second changeovers.

I was authorised to take a few snaps, and these speak for the capabilities of the system...


CCTV Overview

CCTV Overview

Feeds from around a hundred CCTV cameras across the region. The majority show static periodic updates, but they can be pulled as live feeds.

UTMC are keen to point out that these are purely for monitoring traffic flow. The resolution is too low to identify people or number plates. You'll also notice a few of the cameras have black blocks digitally obscuring residential properties from the feeds. They also do not store any of the feeds- they're just for live viewing.

Overview Map

Mapped incidents

On the left is a table of roadworks and a list of planned events. The map on the right displays this information, and the traffic flow sensors (the coloured circles).

Congestion Monitoring (SCOOT)

Congestion across a sensor point

Congestion can be measured by underground sensors. Daily expected profiles can be mapped against current live data.

X axis: time of day; Y axis: percentage congestion.

Journey Time (ANPR)

Traffic flow; duration of a journey section

X axis: time of day; Y axis: journey duration in seconds between two points on a section of road (here, A167).

Profiles of particular days (red line) may be compared with current live data (black line). The red dotted line is the target.

Car Park Occupancy

Car park occupancy

X axis: time of day; Y axis: number of cars.

Profiles of particular days (Thursday- red line, Sunday- grey line) can be compared with live data (black line). Notice the curves mapping against shop opening times.

This Data is Open!

Alert readers may note that the data sources presented are suspiciously similar to those powering our recent hack event, for which UTMC kindly provided feeds.

UTMC are extremely keen for developers to use their source data for creative and public benefit, and they now provide a significant chunk of this as open data.

They have a public website demonstrating the potential, but the opportunities for specific applications of the data and mixins with other sources are vast and potentially profitable. Furthermore, it's likely that another source of high public value will be added over the next year...

If you play with this data and create something interesting, please let us and them know!

Thanks Ray K, the UTMC Control Staff and Graham J for the viewing.