The Daily ACK

I'm in "All The Ways to Find You: GPS and other Wireless Signals" with Nick Brachet from Skyhook Wireless the people that do that sort of thing...


Nick Brachet
Nick is going to talk today about all the ways to find and locate a phone, laptop or desktop at any time. First, the easiest and most fun location technology, where is the storm

Count the seconds between the time you see a lightning strike, and the time you hear thunder, divide by 3. The result is the distance to the storm in kilometers...

A lot of location systems work this way, they know the location of a fixed point, and they measure your distance to that point.

To unambiguously locate you you need at least three reference point, the more points you have the more accurate your location can be pinned down. In practice of course you never know anything exactly, so even with multiple references point you always have a error.

A GPS receiver measures the distance to a satellite by calculating the time it takes for a signal to travel from the satellite to the receiver. But what is the satellite's time? what is my time? A fourth satellite is needed for time synchronisation. But where are the satellites, precisely? As well as a time stamp each navigational message includes the position of the satellite and its path in its orbit, and a subset of the almanac - data about the other satellites in orbit, including a rough position. However the ephemeris (and the almanac) may be delivered via other mechanisms, e.g. backhaul via the cell phone network.

For location technology there are many metrics, one of these is how long it takes to get a location fix. With GPS on a cold start it takes on average 23 seconds, with a warm start, where the time and ephemeris is still valid the time-to-fix is much less, around 4.2 seconds on average. Faint signals (-135dBm and lower) complicate decoding process and may cause the receiver to drop frames, increasing the time-to-fix.

Typical GPS receivers need -140dBm or better, and cannot decode below -145dBm. Outside you normally get a signal from -125 to -130dBM. Inside in your home you get a signal from between -135 to -145dBM, however in a high-rise building the signal will go down to typically between -135 to -160dBm.

Accuracy is very important, and there are many factors contribute to error, the most important is timing inaccuracy. One of the biggest problems is multi-path signals, the satellite signals bouncing off surfaces (building, planes, etc). End-user accuracy is typically 10-30m in a good area. That's not generally good enough, onboard navigation systems generally fix your position by assuming your car is actually on a road.

Moving on to Wi-Fi positioning. There are hundreds of millions of access-points around, so it's easy to determine your location? Okay, but we need to trilaterate. We need the distance to at least 3 access-points and the exact position of the access-points. It turns out there is a quadratic relationship between the signal strength you receive and the distance to the access point. So in practice, distance to an access-point can be estimated by measuring received signal strength. The second problem is solved by driving, and walking around neighbourhoods, malls, campuses and collecting Wi-Fi signal fingerprints, then calculate each access-point's position by (reverse) trilateration.

Conventional wisdom for the range of an access point is about 500ft, but some times they have much larger coverage, some over a kilometer wide. This can happen for many reasons, perhaps the signal is boosted, but perhaps the signal is just bouncing off water, or there was just nothing in the way to prevent the signal propagating. The access point might be in a high-rise building.

The time-to-fix in network mode, where the client collects the Wi-Fi fingerprints, but the location is calculated remotely. However in tiling mode, where the client has a small portion of the database cached locally, and your location is calculated locally the time-to-fix can be sub-second.


Coverage in Europe
So Wi-Fi positioning an GPS positioning complement each other very well...

Accuracy, distance to access-points is only an estimate and we have unmanaged reference points, and access points do move. But many readings compensate. The end-user accuracy is typically 20 to 30m in good coverage areas.

...and we're done.

Sense Networks emerged from stealth mode earlier today with a press release announcing both themselves and their products. It shows that even behind the most boring press releases some very cool technology can be lurking.

I wouldn't have taken a second look at the company based on the rather dry press release, but fortuntely they took the time last week to talk to Brady Forrest over on the O'Reilly Radar, who in turn took the time to talks about Sense Networks and CitySense. They also got some coverage from TechCrunch as well, but you'd expect that. TechCrunch covers everybody...

CREDIT: Sense Networks

CitySense shows you how active locations are (top) and which ones are abnormally active (bottom) in real time.
This startup is interesting. A big problem for location-aware startup companies is that they need location data. Normally they try and get this from their users, but most of the time their applications aren't really that useful until they get a critical mass of users. But getting a critical mass of users without having any a useful application is almost impossible. It's a classic Catch-22...

Sense Networks on the other had has been able to obtain data from taxi cabs, and it uses the origin and destination data from those taxi journeys to model the city. Then on top of this initial data they can then add in their user data, in accordance with a reassuringly strict privacy policy. Users get immediate benefits from the application, as Sense Networks have found that they can get a fairly good picture of the ebb and flow of city life just using the data from the taxi journeys, and that means it is that much easier to gather a critical mass of users to make sure their application takes off...

The immediate worry is that initially at least, reliant as they are on data from taxis, the application will model a specific demographic rather than showing a true representation of how the city functions. However that might be my European perspective getting in the way. The way a US city works, even a faux European city such as New York or Boston, is very different to the way a UK or European city works. Over here they might be better off relying on data from local buses rather than on taxis.

However that aside, I've seen a couple of attempts at solving similar, but actually less ambitious, problems. They've more or less all failed due to the "critical number of users" problem. But to get off the ground Sense Networks doesn't need a critical number of users, they can answer the question "Where is everybody?" without them. With them they hope to be able to answer the question "Where is everybody like me?", that's impressive stuff...

Of course as well as the current Blackberry application, Citysense is coming soon to the iPhone. But I guess that's only to be expected?

Update: As predicted, we have a new 3G iPhone.

Although developers are officially denied access to the iPhone as a platform, and restricted to Web technologies to deploy applications for the phone, it hasn't stopped people developing unofficial native applications.

CREDIT: Engadget

However as far as I know Navizon "virtual GPS" is the first commercial application. Apart from the fact that I don't think their application is worth paying for, I've knocked similar things together in Python on my Nokia in an afternoon, it seems like a risky strategy. Rumours are circulating that Apple may brick unlocked iPhones with the next firmware update, which might leave Navizon with a number of very unhappy customers. Additionally, while Apple might tolerate the open source community hacking on their new phone, will they be so forgiving of a commercial developer? This is going to be an interesting one to follow along with...

Update: Tom Robinson has a good article on alternative methods for geolocation.

News from the O'Reilly Where 2.0 conference of the upcoming release of the much predicted Google street side view (via O'Reilly Radar).


The new Google street side view layer in Google Maps
Of course this isn't new, after all Amazon A9 did this back in 2005, but neither was online mapping applications when Google Maps launched. The question isn't whether they're were first, it's whether their interface is so much better than what's gone before (yet again) that they corner the market. That, and from the sounds of things, whether this gets integrated into Google Earth.

However while the guys over at O'Reilly seem to be able to see this on the Google Maps pages right now, it looks like the rest of us will have to wait for the official announcement during Where 2.0 later today. I certainly can't see the new features and from the comments on their post it doesn't look like I'm alone on that one.

Update: I can confirm that adding &gl=us (via Lifehacker) to the URL does indeed allow you to use the new features, at least from the UK, and from what I remember it blows the interface for the long defunct A9 service out of the water. The way you can click and drag around your location is actually pretty slick.

Update: The guys over at the Google Lat Long blog have pointed us to a video showing how to use the new features.