Monthly Archives: December 2009

IDAT106 – Digital Ghosts

From my discussions with Shaun we though of how to represent the information in a more visual way. I liked the idea that the bluetooth only suggests that a person is there but gives no real location or form to them. I looked for a number of examples of photography that shows blurred almost ghost like figures. I particually liked this:
An image from Alexey Titarenko’s “City of Shadows” series.
This picture is taken using a camera with a very low shutter speed. They way these anonymous people form a cloud. Using the data to create this kind of effect could be a good way to visualise the information collected.

IDAT106 – Modelling space

I thought I would try to create a rough 3D model of a section of Union street using google Sketchup. Using a model such as this is useful to view an area from different perspectives and experiment within it.

Then I created domes to simplistically represent the range of various bluetooth devices in the space.

IDAT106 – Further Bluetooth device location

A bluetooth device is non directional and has no sense of space or direction, it only knows when another device is in range and has started talking to it; so on its own a single device is very limited. A couple of my posts including this address several of the ways useful for visualising the actual space using this data.

Another solution using multiple adapters to extrapolate multiple dimensions is to have multiple devices at a single location. As mentioned in a previous post there are three classes of bluetooth device each with a different theoretical range. The class of adapter can indicate the distance of the detected device. However there will be large variations, for a device to be detected two-way communication must be briefly established, if one device is a Class 3 with only a couple of metres range it will not be able to communicate with a Class 1 device that is 50 meters away because the maximum range between two devices is that of the lowest. However higher class devices also tend to be more sensitive and are able to detect weaker classes’ signals out of those devices normal range so I would expect to see a slightly improved range for them. This will mean that detecting class 3 devices may not be possible with a class 1 device on the other side of the road.

With three bluetooth adapters each indicating various distances it can be possible to locate a device within this space. If the device appears on all three adapters the device must be passing closely to the scanner. If it appears on the class 1 adapter only then it can be determined to be beyond the range or penetration of the other scanners. One problem is that cars provide shielding preventing bluetooth contact, possibly only allowing the most powerful adapter to detect it. When this is combined with the use of multiple locations to determine speed and therefore the method of locomotion these can be correctly identified as cars due to the unique ID and displayed correctly. Further testing is required to identify if this is viable.

IDAT106 – Bluetooth device location

One possibility we have explored is that because of the way we have observed Union street to be used as a conduit rather than a destination with the vast majority of people passing through the space without interacting within it. The idea is to use two of these devices positioned at either end of Union Street or multiple devices along it. This would allow us to add another dimension to our projected visualisation. For example speed can be calculated by collating devices that have matching unique ID’s to form a narrative. At one location a person’s device is detected, the time is recorded and the person continues down the street where their device is detected by another scanner and the time is logged. The time difference can be calculated and if the distance is known then an approximate speed can be given.

From the speed we can also try to predict how the device is being carried. 1.5m/s would suggest walking speed whereas something faster would possibly indicate the use of a car.

IDAT106 – Bluetooth

As I we are using Bluetooth for our project it seems prudent to say a little bit about it.

Bluetooth is a wireless protocol for exchanging data over short distances from fixed and mobile devices.

Going into the technical details, “Bluetooth uses a radio technology called frequency-hopping spread spectrum, which chops up the data being sent and transmits chunks of it on up to 79 frequencies. In its basic mode, the modulation is Gaussian frequency-shift keying (GFSK). It can achieve a gross data rate of 1 Mb/s. Bluetooth provides a way to connect and exchange information between devices such as mobile phones, telephones, laptops, personal computers, printers, Global Positioning System (GPS) receivers, digital cameras, and video game consoles through a secure, globally unlicensed Industrial, Scientific and Medical (ISM) 2.4 GHz short-range radio frequency bandwidth. The Bluetooth specifications are developed and licensed by the Bluetooth Special Interest Group (SIG). The Bluetooth SIG consists of companies in the areas of telecommunication, computing, networking, and consumer electronics.”

Infact everything you will ever want to know (most likely not alot) about Bluetooth can be found here.

A key thing of interest for me from this are the different power classes which would have a significant effect on how good at detecting phones we can be.

“In most cases the effective range of class 2 devices is extended if they connect to a class 1 transceiver, compared to a pure class 2 network. This is accomplished by the higher sensitivity and transmission power of Class 1 devices.”

So using a Class 1 adapter would be better even if most mobile devices only use a class 2 or 3.

EDIT: After looking into it, it should be very easy to get one of these class 1 bluetooth adapters with 100m range and cover an entire street, including cars passing through.