Participatory Surveillance – Who’s Been Tracking You Today?

With the internet of things still trying to find its way, I wonder why more folk aren’t talking about participatory surveillance?

For years, websites have been gifting information to third parties that you have visited them (Personal Declarations on Your Behalf – Why Visiting One Website Might Tell Another You Were There), but as more people are instrumenting themselves, the opportunities for mesh network based surveillance are ever more apparent.

Take something like thetrackr, for example. The device itself is a small bluetooth powered device the size of a coin that you attach to your key fob or keep in your wallet:

The TrackR is a Bluetooth device that connects to an app running on your phone. The phone app can monitor the distance between the phone and device by analyzing the power level of the received signal. This link can be used to ring the TrackR device or have the TrackR device ring the phone.

The other essentially part is an app you run permanently on your phone that listens out for the trackr device. Not just yours, but anyone’s. And when it detects one it posts its location to a central server:

[thetrackr] Crowd GPS is an alternative to traditional GPS and revolutionizes the possibilities of what can be tracked. Unlike traditional GPS, Crowd GPS uses the power of the existing cell phones all around us to help locate lost items. The technology works by having the TrackR device broadcast a unique ID over Bluetooth Low Energy when lost. Other users’ phones can detect this wireless signal in the background (without the user being aware). When the signal is detected, the phone records the current GPS location, sends a message to the TrackR server, and the TrackR server will then update the item’s last known location in its database. It’s a way that TrackR is enabling you to automatically keep track of the location of all your items effortlessly.

And if you don’t trust the trackr folk, other alternatives are available. Such as tile:

The Tile app allows you to anonymously enlist the help of our entire community in your search. It works both ways — if you’re running the app in the background and come within range of someone’s lost item, we’ll let the owner know where it is.

This sort of participatory surveillance can be used to track stolen items too, such as cars. The TRACKER mesh network (which I’ve posted about before: Geographical Rights Management, Mesh based Surveillance, Trickle-Down and Over-Reach) uses tracking devices and receivers fitted to vehicles to locate other similarly fitted vehicles as they pass by them:

TRACKER Locate or TRACKER Plant fitted vehicles listen out for the reply codes being sent out by stolen SVR fitted vehicles. When the TRACKER Locate or TRACKER Plant unit passes a stolen vehicle, it picks up its reply code and sends the position to the TRACKER Control Room.

That’s not the only way fitted vehicles can be used to track each other. A more general way is to fit your car with a dashboard camera, then use ANPR (automatic number plate recognition) to identify and track other vehicles on the road. And yes, there is an app for logging anti-social or dangerous driving acts the camera sees, as described in a recent IEEE Spectrum article on The AI dashcam app that wants to rate every driver in the world. It’s called the Nexar app, and as their website proudly describes:

Nexar enables you to use your mobile telephone to record the actions of other drivers, including the license plates, types and models of the cars being recorded, as well as signs and other surrounding road objects. When you open our App and begin driving, video footage will be recorded. …

If you experience a notable traffic incident recorded through your use of the App (such as someone cutting you off or causing an accident), you can alert Nexar that we should review the video capturing the event. We may also utilize auto-detection, including through the use of “machine vision” and “sensor fusion” to identify traffic law violations (such as a car in the middle of an intersection despite a red stop light). Such auto-detected events will appear in your history. Finally, time-lapse images will automatically be uploaded.

Upon learning of a traffic incident (from you directly or through auto-detection of events), we will analyze the video to identify any well-established traffic law violations, such as vehicle accidents. Our analysis will also take into account road conditions, topography and other local factors. If such a violation occurred, it will be used to assign a rating to the license plate number of the responsible driver. You and others using our App who have subsequent contact with that vehicle will be alerted of the rating (but not the nature of the underlying incidents that contributed to the other driver’s rating).

And of course, this is a social thing we can all participate in:

Nexar connects you to a network of dashcams, through which you will start getting real-time warnings to dangers on the road

It’s not creepy though, because they don’t try to relate to number plates to actual people:

Please note that although Nexar will receive, through video from App users, license plate numbers of the observed vehicles, we will not know the recorded drivers’ names or attempt to link license plate numbers to individuals by accessing state motor vehicle records or other means. Nor will we utilize facial recognition software or other technology to identify drivers whose conduct has been recorded.

So that’s all right then…

But be warned:

Auto-detection also includes monitoring of your own driving behavior.

so you’ll be holding yourself to account too…

Folk used to be able to go to large public places and spaces to be anonymous. Now it seems that the more populated the place, the more likely you are to be located, timestamped and identified.

Author: Tony Hirst

I'm a Senior Lecturer at The Open University, with an interest in #opendata policy and practice, as well as general web tinkering...

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