Londons CCTV cameras are about to get a lot smarter, thanks to a new partnership between Transport for London, the capitals transport agency, and VivaCity Labs. Together, the pair are rolling out 20 new artificial intelligence enabled cameras across the centre of the city.

But why? The reason TfL are interested in the cameras is a bit of a no-brainer: as the organisation are responsible for making sure Londoners can get around the city, the more data they have, the better. If they can more accurately monitoring crowding and congestion, and understand the journeys people are actually taking, it can inform both how TfL plans infrastructure improvements for the future (would extra cycle lanes here be a good idea?), and immediate traffic management challenges (keep the lights green for 3 seconds longer on this road after a football match).

Last July, TfL rolled out its Tube tracking full time - which uses the wifi signals from our phones to follow us around the Tube network for similar reasons. But taking the Tube is only one type of journey; what about cars, buses, bikes and pedestrians? TfL already has hundreds of traffic cameras placed around London (you can even watch them in close to real time), but these cameras are dumb, and to understand what is going on in the pictures requires a human operator to take a look and decide what the pictures are telling us.

Hence, enter stage left VivaCity Labs. The VivaCity Sensor Platform makes use of an artificial intelligence layer on top of the cameras, to analyse images and reveal insights that TfL might find useful.

Image: VivaCity

For example, point it at a road and it will count all of the vehicles that pass by - but instead of just counting vehicles like many existing systems, it will classify the vehicles by type, giving TfL a breakdown on the number of cars, vans, lorries and so on. It will also estimate the speed of each road user (though the companys documentation points out this is not for law enforcement). According to the launch press release, VivaCitys cameras are up to 98 per cent accurate.

In a response to a Freedom of Information request from Gizmodo UK, TfL also revealed that one unique feature of the camera is that it will be able to be trained to spot new and specific vehicle types, such as London buses or cargo-bikes, to differentiate them from similar vehicles. In other words, TfL could soon have data on Londons busiest Deliveroo routes.

The cameras are also able to identify how people are moving within a cameras field of vision - so it could conceivably be used to, for example, see how long it takes people to cross the road or how the road space is being used.

Judging by the map of locations, it appears that for this initial rollout, cameras are being placed around Londons inner ring-road, following basically the Congestion Charge zone, as well as on a number of bridges and pinch points in the central core of the city.

This makes a lot of sense: presumably the eventual plan is to replace the actual Congestion Zone cameras with the VivaCity sensors. This is wild speculation but not only would that mean they can provide more detailed analytics, but by being generic cameras running software, it could ultimately mean saved money and more flexibility. Specialist cameras would not be require for Congestion Zone enforcement, and if TfL wanted to expand or retract the zone, itd simply be a case of pressing a button on some software to switch on number plate logging at other VivaCity camera locations, rather than a bigger manual process. (Again, wild speculation but we can imagine a future where the Congestion Zone moves dynamically - maybe covering a wider area on weekdays than weekends, say.)

Overall, 43 cameras are being placed around 20 locations for a trial period of two years. Heres a full list of locations:

Image:VivaCity

The rollout will, of course, provoke privacy concerns. After all, these cameras are not just taking pictures, but are interpreting them too. Though in all of its communications on the new cameras, TfL has downplayed any privacy concerns, saying in its original press release that All video captured by the sensors is processed and discarded within seconds, meaning that no personal data is ever stored.

The data, it emphasises, is processed in the camera units themselves - and it is only the outputted data, such as counts of the number of vehicles, that is being sent back to TfL for storage. All of the images collected by the cameras are apparently discarded within seconds.

Whats most illustrative of TfLs careful approach is that it has confirmed to Gizmodo UK that it does not intend to use one other feature of VivaCitys product: the ability to track vehicles as they travel across the city using number-plate recognition.

In response to our FOI, TfL says this:

Our requirements for this data include cycle and pedestrian counts, full traffic classified counts (13 types of traffic), turning movement counts, link delays, queue length monitoring and pedestrian crowding.

Notice how all of these tasks can be carried out with just a single camera - rather than require data to be stored and matched up elsewhere. Weve asked TfL to confirm whether or not our hunch is correct.

However, there are still gaps that might leave privacy experts asking questions. According to TfL, VivaCity Labs has produced a number of Privacy Impact Assessments, but because they were carried out by VivaCity, TfL says that it does not hold the assessments - and of course, being a private company, VivaCity is not subject to Freedom of Information laws. This also implies that VivaCity, not TfL, are the data controller of this data. Weve asked TfL for a more detailed explanation of its rationale for not releasing these private assessments.

Ultimately, this camera rollout sits at the nexus of a very familiar debate. As we saw with TfLs WiFi tracking system, there is a very real trade-off between giving planners better data and respecting privacy. TfL does, once again, appear to have behaved broadly responsibly - but it is still an important debate to have. The future is one where every CCTV camera will, by default, have this sort of functionality baked in - so better to debate now whether the gains are worth it, rather than risk waiting until it is too late.

Featured Photo byPawe CzerwiskionUnsplash

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Revealed: Where TfL Is Deploying 20 AI Cameras Around London, and Why - Gizmodo UK