Vision Mapping is a research project aimed at extend the sphere of pedestrian simulation and crowd analysis in the planning and design of buildings and precincts. Using our MassMotion software we have been analysing the science behind people’s field of vision and the impact this has on their decision making. Preliminary research has focussed on the representation of pedestrian’s cone of vision in retail contexts.  Currently retail layout and placement with shopping centres and terminals/interchanges is undertaken with an intuitive approach. The value of adding science and a methodology to the approach is in reducing the risk and cost of spaces that just don’t work, that people seem to ignore or plainly don’t see prior to construction.

As simulation tools continue to increase in their sophisitication, mapping a persons cone of vision will be a valuable tool when offered in conjunction with people modeling skills in 3D environments. This study includes a client focus to identify needs and markets for the research. We have been meeting with designers as well as retail centre owners and operators, leasing agents and airport or station operators and commercial managers to identify the needs and current best practice in the market place.

Next is the use of cameras to film actual fields of vision in poor and good performing retail environments. The footage will be used as part of a calibration process.

This video shows that over time, and with an increase of population going through the same fields, areas will become highlighted showing as ‘hot’ which indicates the line of vision, therefore the interest/ influence locations.

Links – MassMotion. http://www.oasys-software.com/products/engineering/massmotion.html

For further information on this project please contact David Young.

A few years ago Jon Morgan, our Building Physics leader in Australasia, made the following slide to illustrate just how many different software analysis tools his team uses on a regular basis. When you multiply that across all the services a firm like ours offers that is a lot of software.

Specialists need specialist tools and sometimes software doesn’t cut it. Computational Fluid Dynamics (CFD) has its place but it isn’t about to replace wind tunnel testing. DesignLink, which is open via a collaboration agreement, is one of the ways we address how to shift and manage data across projects.

With all this in mind, we have created Submerge to visualise multiple analysis results that are generated on projects in the one space. Large multi-disciplinary projects create huge datasets and we have been expending research and development effort to combine this data and create richer spaces for design navigation. The aim with so many disciplines is to clearly tell the story of an emergent design and Submerge is a data visualization tool that integrates the datasets into one 3D environment, providing an immersive and interactive presentation experience.

Above: Geometry and CFD analysis

Rather than presenting images from various analysis tools, we can now walk through the design with people and cars moving, or with the wind blowing as predicted by separate analysis programs.

The above image shows geometry (from Rhino via Grasshopper), wind streamlines (from CFD), structural analysis (from GSA) and Pedestrian analysis (from MassMotion) in the one 3D environment.

We have made it possible to publish the content so others can wander through in their own time and on their own computer. There is more work to do in 2012 with navigation, testing physical spaces for Submerge projection – our SoundLabs would be great – and playing with more controllers like the  Kinect. All good fun and its been nice to see client reaction to Submerge over the last few months.

[Above: Arup Office Realtime]

We just launched Arup Office Realtime, a data visualisation designed around the firm’s sustainability objectives. Office Realtime is a system that presents live data streamed to our offices and includes paper usage, electricity consumption, transport updates, carbon generated by air travel and more…

For nearly two years, Andrew Maher, myself and countless other Arupians dotted around the globe have discussed data visualisation as a way to better communicate the content we create on projects; and up until recently the challenge has been to find data or analysis results that present well and make immediate sense to the audience.  Part of the challenge with design and engineering data is that as soon as a design changes, so do the analysis results; affecting the intended visualisation immediately.  For a graphic designer to spend even a short amount of time visualising data, the results, and therefore the design, would have to remain unchanged for as long as possible.  But what about information that is already readily available and ordinarily invisible within the workplace?  And what about information that could be collected and be viewed in realtime?

[Above: Me, Andrew and Toby at the launch]

This project has some history,  around 18 months ago, Andrew Maher attended a meeting with our sustainability consultants to discuss how he could help to further develop the way they communicate their work. One of the outcomes was the 1200 Buildings data visualisation as visualisation was something clients were beginning to ask for.

Then in 2010, Gerard Healey dodged the ash cloud and undertook a world tour of intelligent buildings; those buildings in which active measures were being taken in design and operation to reduce the amount of energy consumed and to change their occupants behaviour.  Gerard sent back stories and photos for the Fields of Activity blog and it has been one of our most popular blog posts.

Soon after that, Mike Rainbow (Building Sustainability) approached Diana Coelho (Organisational Psychologist) and Andrew to help with a presentation for a new fit-out project. The client had a comprehensive sustainability strategy which was largely reliant on the building performance after the fit-out.  Mike suggested to client that we could make a small intervention to engage their staff and change behaviours – Mike’s idea was to highlight paper use in realtime and broadcast consumption back to staff. They liked the idea, but wanted to know who had done it previously – but who had done it?  No one, that we knew of.

Not long after that, as part of Arup’s Sustainability Policy (we implemented a certified Environmental Management System (ISO 14001) across the region), workshops were held for all Arup staff; an extraordinary effort in itself. One of the aims was to educate all about reducing energy and waste by at least 5% in 2011.  Following the workshops, I briefly discussed publishing paper usage with Aaron Yuen, our Key Environmental Representative in Melbourne, and Peter Bowtell, then Melbourne Office Leader, via the intranet. Andrew was having similar discussions with the same and many other people, including public transport companies, but on a much, much more grand a scale.  (At least twice a year, I feel like working with Andrew is a bit like Marconi and Tesla; we both have similar ideas, but it takes a few days, or a few weeks for us to come together and realise we’re talking about the same thing.)

[Above: Office launch]

Late last year, Andrew employed Tom Gasson, a computer science student, to start collecting the data that was available; printer usage, flights and carbon emissions region-wide, realtime computer usage, and energy data; and to start building a database, as well as using Processing to visualise the data.  He then approached Toby Welch and I about creating the web-based front-end to display the data on large LCD screens in the office entryways.  After all, what better way to encourage change than to promote current energy and waste usage to clients?  Part of Andrew’s inspiration was Sprint’s Now Network advertisement; a feat in programming perhaps, but a struggle to interpret at a glance; one has to view it as a proof of concept more than a working example.  Toby and I started to think about what we could do.

Yes, the irony of trying to reduce energy by displaying the information on large flatscreens does not escape us.  In our own defence, let’s just look at few initiatives we have had in place for the last year or more:

• Lighting in our offices is controlled by sensors.  No movement? No lights.
• All printers, including plotters, enter sleep mode after being idle for half an hour.
• In the Melbourne office, we have had a Paperless Office initiative in place for the last 4 years, and for an engineering firm, we print surprisingly few drawings.
• Provision of recycle bins for waste plastics, aluminium, and paper
• Recycling of IT equipment via a third party
• Utilisation of alternatives to air travel e.g. video conferencing
• Last year, across the region, IT rolled out mandatory overnight shutdowns for all computers.  This process can only be manually bypassed if you are still using your  computer in the hour prior to shutdown.

On top of the initiatives we already had in place, we also had specific requirements for the screens to display the information on.  They had to be LED, they had to be at least a six-star rating, and it had to be rated at less than 150W.  The screens we have since purchased are rated at 98W, around a third of a standard PC.

The initial planning of the project also enabled us to purchase energy meters to be installed in our Melbourne office.  The meters will allow energy consumption to be monitored in realtime, feed into our database, which can then allow reports to be run whenever we want or need them.

We began with a simple interface to observe and measure our data before Andrew Buckley took over the look and feel.  In the last week before the launch, we rewrote the backend code from scratch; finally settling for pure HTML5 and CSS3 and a compliant browser (Google Chrome).  We also worked on the idea that the incentive for behavioural change can be as easy as promoting healthy competition between offices.  To do this we are going to take the totals for each set of data, and work out the averages per capita for each office.  In the coming weeks, after the rollout to the east coast; we hope that people will think twice about printing those two page emails; knowing that staff in another office, on average, print 10 pages less a day than us.

[Above: The average Arupian page]

How is our custom approach to the dashboard different to a building management system (BMS)?  Building management systems are great – for building managers, but what if you just occupy one level?  Typically, BMS dashboards equate energy to cost and cost savings over time, but we wanted to show usage in terms of environmental impact, and not simply translate everything back to dollars and cents.  We’ve taken data that applies to everyone in our office, and presented it in an engaging, aesthetically pleasing way.

We’ve just rolled the Office Realtime out to the Melbourne office.  Our staff are impressed and keen to track usage over the coming months, and our Sustainability team is happy.  Very happy.  Next are launches in Sydney and Brisbane.  And all of this just to keep us conscious of how much impact we make; compared to how little impact we could make.

Want to know more?  Come see for yourself.  Did I mention that we also included public transport information on the display as well?  No?  Well that’s quite vital actually.  For staff and clients alike, as we leave the office we can now check when our tram is coming, or whether the train service is ok or not.  That’s actually one thing that our Office Realtime may not have the power to change.  Yet.

Here’s a list of the team, and without the support and enthusiasm of a larger number of people, the core project wouldn’t have happened in such a short amount of time.

Project Team:

Andrew Maher, Tom Gasson, Toby Welch, Andrew Buckley, Dean Morris &  Scott Fagg

Its a wrap for this year and what a year it has been. On Thursday9th December Arup held a workshop at the Victorian Space Science Education Centre (VSSEC) with VSSEC and Engineers Australia. We explored and imagined the potential for this facility to become both an educational and industry facility for concurrent design.

Many thanks to Mark Burry from SIAL, Peter Raisbeck from Uni Melb and Agustin Chevez from Geyer who all have interests in the area and with whom we look forward to continuing to work with in 2011. More in the new year, but needless to say the workshop built on the work we did during the year on digital technologies and new forms of procurement.

There will be plenty of posts to come in early 2011 that will explain what follows and more. As I look over the projects Digital Innovation has worked on this year, I don’t think I could have predicted either the breadth or the number. Just a scratching the surface here… we’ve developed iPad apps (as an Apple Enterprise Developer) in Brisbane, we’re in the cloud – the Amazon Cloud – with our GIS+ work in Perth. Interactive Reports really took off and made their way around the region and client feedback has been brilliant. From Sydney there will be posts on what we’ve done with the Makerbot printing as well as how we are using Microsoft’s Kinetic. In Melbourne we’ve been doing some very cool work in Grasshopper and the Melbourne Office Realtime will make its debut early in the New Year. The animation workshop we did with the VCA has spawned nascent film makers around the firm. Thanks also to Hassell for the feedback!

We’ve won some interesting ARC Linkage grants and I think they ought to have their own pages devoted to the work, which brings me to the site.  In 2011 there will be a revamp to include our design work. Digital Innovation has been literally embedded in some groups and Melbourne Buildings called theirs Design and Digital Innovation. Led by John Bahoric, they are regularly meeting, sharing work and including clients. This broadening of the DI project goes hand-in-hand with intentions of the firm and the site’s content and layout will reflect that.

Thanks to those we have worked with during the year. Thanks to the team and all those in Arup who contribute. Digital Innovation sits at the front end of our projects, surfing the wave. It couldn’t happen without the support of the firm’s leadership, the Australian Regional Board and in particular Peter Bowtell, our Australasian Buildings Leader and Chris Graham, our Chief Operating Officer.

I scrawled a note during the last summer break “2010 – data; mobile and visualisation” and now I’m off to scrawl some more. All the best for the New Year.

Andrew

I joined the Perth office in January this year from the Cardiff office, via a stint in London, as a GIS (Geographical Information Systems) and 3D Realtime specialist. My background is primarily in GIS, but over the last few years working with the graphics and 3D visualization teams I have become more and more involved in developing realtime environments for 3D models from a range of disciplines across the firm. For me combining the data and information aspects of GIS with high end visualizations is very appealing, and finding innovative ways to present data is something that can set us above the rest.

I have worked on a range of projects, from navigable environments of single rooms to entire cities, creating highway visualizations that allow users to explore planned road schemes and view modeled transport data. Just before I came to Australia I won the Welsh Water Chairman’s Innovation Award for work visualizing the sub-surface sewer systems in Cardiff in an interactive city model. I also presented some of the work at the Quest 3D user conference in Amsterdam.

Realtime 3D environments offer the user the opportunity to navigate themselves through a 3D model, viewing from any perspective and interrogating the model and imported data. Arup have a very strong capability in this field, and are able to very quickly create realtime representations of 3d models as they are being designed. Viewing a design in realtime 3d is a very powerful tool both in the design phase and in the final project stages where visualizations are becoming much sought after.

I import modeled data from a range of sources, including pedestrian, vehicle, blast and fire simulation packages. Subsurface utilities can be shown in their real world locations, and any data with a spatial location can be imported through GIS to create a single source for all 2D and 3D data to be visualized, even if it’s not been done before we can probably import your model and data!

Self contained applications that require no specialist software are compiled and distributed as a standalone file, containing all the models, textures and data required, allowing universal access. We use a variety of realtime engines to suit different purposes and scales of projects. Some examples that I have worked on since coming to Perth earlier this year, and from the UK using the Quest 3D platform, are showcased in the animation above.

I am always on the lookout for ways to push this technology forward, and for more project examples to apply these techniques to so if you have any question, ideas or would like to be involved please don’t hesitate to contact me

This is a story about what happens when you give a Mechatronics engineer a new toy and a free Friday afternoon.

I’ve always been interested in sensors and how to use the information they collect. After we recently purchased some Arduino boards, I set about exploring different methods of manipulating the virtual world from the physical world. I was looking for an alternative input device to the keyboard and mouse.

After conquering the mandatory “Hello World” program on the Arduino, I started experimenting with some of the sensors. Simpler sensors include those that are sensitive to light, temperature, pressure, sound and movement. This project started with a thermistor (temperature sensitive) and an LDR (light sensitive).

Using the sensed data to manipulate a Rhino model. I used a piece of open source software called UbiMash produced by Flora Salim and her team at SIAL. UbiMash enables a connection between the Arduino board (physical world) and Rhino modelling package (Virtual world).

The following video shows the final product. The shape changes height as the light levels change, and the colour changes as the sensed temperature changes.

What could it be used for? Sculpting models in Rhino? Interactive public art display?

Arduino code (modified version of code supplied by UbiMash):

int ledPin=9;
int ldrPin=1;
int lightVal=0;
int tempPin=2;
int tempVal=0;
void setup()
{
Serial.begin(9600);
Serial.flush();
pinMode(ledPin,OUTPUT);
}
void loop()
{
// for (int i = 0; i < length; i++) {
lightVal=analogRead(ldrPin);
analogWrite(ledPin,lightVal);
delay(lightVal);
analogWrite(ledPin,0);
delay(lightVal);
//Serial.print(i);
Serial.print(“light:”);
Serial.println(lightVal);
//Serial.print(“1: “);
tempVal = analogRead(tempPin);
Serial.print(“temp:”);
Serial.println(tempVal);
}
Rhino Code (some code provided by UbiMash)

Option Explicit

Call Main()
Sub Main()

 
  ‘ Create a new square surface
  Dim sqSize : sqSize = 200
  Dim ptOrigin : ptOrigin = Array(-sqSize,-sqSize,0)
  Dim ptX : ptX = Array(sqSize,-sqSize,0)
  Dim ptY : ptY = Array(-sqSize,sqSize,0)
  Dim dX : dX = Rhino.Distance(ptOrigin, ptX)
  Dim dY : dY = Rhino.Distance(ptOrigin, ptY)
  Dim arrPlane : arrPlane = Rhino.PlaneFromPoints(ptOrigin, ptX, ptY)
  Dim plane : plane = Rhino.AddPlaneSurface(arrPlane, dX, dY)
 
  ‘ Add (and get) more control points to the plane
  Rhino.RebuildSurface plane, Array(2,2), Array(5,5)
  ‘Dim points : points = Rhino.SurfaceEditPoints(plane,False,True)
  Dim j
  Dim sLight, sTemp, resLight, resTemp
  For j=0 To 250 Step 1
    ‘Retrieve ARDUINO Light and Temperature Sensor data
    sLight = “ARD|LIGHT”
    sTemp = “ARD|temp”   
    resLight = getSensorData(sLIGHT)
    resTemp  = getSensorData(sTemp) 
 
    ‘ Print out all control points
    Dim points : points = Rhino.SurfaceEditPoints(plane,False,True)
    Dim i
    For i=0 To UBound(points)
      points(i)(2) = 500 – resLight
    Next  
 
    points(0)(2) = 0
    points(4)(2) = 0   
    points(12)(2) = (500 – resLight) \ 2
    points(20)(2) = 0   
    points(24)(2) = 0
 
    ‘ Move the surface points
    Rhino.DeleteObject(plane)   
    plane = Rhino.AddSrfPtGrid(Array(5,5), points)

    ‘ Change the colour of the object  
    Dim blueCalc, redCalc
    blueCalc = 255 – (255\30) * (resTemp-490)
    If (blueCalc > 255) Then
      bluecalc = 255
    End If
    If (blueCalc < 0) Then
      bluecalc = 0
    End If
   
    redCalc  = (255/30)*(resTemp-490)
    If (redCalc < 0) Then
      redCalc = 0
    End If
    If (redCalc > 255) Then
      redCalc = 255
    End If     
    Call Rhino.Print( “blue: ” & blueCalc & ” red: ” & redCalc)
    Rhino.ObjectColor plane, RGB(redCalc, 0, blueCalc) 

    sleep(125)

  Next 
 
  Rhino.DeleteObject(plane)   
 
 
End Sub

Function getSensorData(varName)

  Dim objPlugIn, objTest
 
  ‘Rhino.Print “Attempting to get ResponsiveRhino”

  ‘ Get the TestRhinoScript plugin’s
  ‘ primary COM visible object
  On Error Resume Next
  Set objPlugIn = Rhino.GetPlugInObject(“ResponsiveRhino”)
  If Err Then
    MsgBox Err.Description
    Exit Function
  Else
    ‘Rhino.Print “Successfully get ResponsiveRhino”   
 
    ‘Get the current light sensor value
    getSensorData = objPlugIn.GetTopicValue(varName)
         
  End If

End Function

Back in November 2009 we ran the first Arup HackDay. During HackDay people from around Arup gathered to create new tools and mash data over a 24 hour period. One of the tools created at HackDay by Andrew Tsakmakis was re-purposed to create the Secret Lives of Projects.

I’ve long been interested in project-based organisations and how new knowledge can be transferred from one project to another. The Secret Lives of Projects is a visualisation of the content created during an Arup project. It is a thought piece around the question “What is the shape of a project?” and an attempt to visualise some of the patterns of content creation as we work on projects.

The original tool was developed to index data with several features for quick searches. We did some more work after HackDay and pointed it towards a project directory. We then extracted meta-data from email archives and files. People in the email archive were identified and their business units and locations matched. We then linked billing data.

In the excerpt from communication network (below) the nodes reflect a pattern of communication through the project as people email each other. Nodes with yellow or blue dots grow as they bill time and so a picture emerges of who is speaking with whom and who are the key players working on the project. If this tool ran in real-time on your desktop could you tell if people were in the loop or not?

We worked with Greg More from OOM Creative to build an application using Adobe AIR and Flex. The video shows some of the visualisations from the AIR application.

Smartphone user waiting for tram, Sydney

This update is in three parts: ‘our approach’; ‘the hardware’; and ’sensing’. This entry is continued from ‘the hardware’.

It turns out few people have Bluetooth turned on and visible by default. When my colleague at Arup Jason McDermott helped create an urban sensing installation in central Sydney (Smart Light Fields) they observed around 8% of passers-by had Bluetooth on and visible. A colleague in Barcelona reckons it’s more like 20-30% around La Ramblas (is Bluetooth more prevalent in Europe due to a more mature applications market?).

Either way, we can only see a sample of passers-by with Bluetooth. So our approach is to then move through a stack of sensing, moving on to wi-fi (on smart-phones and other connected devices like netbooks), GSM and so on.

Wi-fi is particularly interesting, as we’d initially thought it wouldn’t register much – as the phone needs to be configured to auto-connect to networks, and a network and router i.e. a wireless access point (WAP), needs to be present to enable that. Even if we could prime the environment with a router (leaving aside the provision of amenities and apps approach – see later), we’d assumed a very small percentage of phones would be detectable. If you know the MAC address of a device, you can ‘ping’ it – but how to discover the MAC address? Leaving aside issues of privacy and ethics momentarily, this was proving a challenge just on a technical basis alone.

However, CRIN have been pursuing an approach called “packet injection” (which most wi-fi dongles don’t support, but some do). To cut a long story short, using this, you can prompt a wi-fi port to respond to and reveal its MAC address. It sounds somewhat scary – and there are those ethical issues to the fore about how we reveal the presence of this system, how to reveal its seams, and so on – but this could be extraordinarily powerful It would mean that all wi-fi-enabled devices i.e. most smartphones, all netbooks, could be triggered to reveal their MAC addresses. This initial process can take up to a minute – again, lending itself to environments where phones/devices are stationery or slow-moving, relative to movement at least – but once you have the MAC address, you can trigger it far more quickly.

A couple of sensors might be deployed here. One, in ‘wide range’ at an entrance, say, would be learning MAC addresses. The other might be tighter and more focused, pinging those addresses already discovered – this only takes a second or two once discovered.

GSM is more complex again, and we’ll report on that later (but in essence, unless you’re network provider you can’t trigger a phone to communicate (strictly speaking you can, but it’s illegal to), and so you rely on how often phone sends a ‘ping’, which it does when it’s crossing a cell location area boundary, when it’s on a call or SMSing, or every 2 hours 20 or so in Australia, depending on how the network configures such things.) With 3G the update periods are shorter, and there’s likely to be more data transfer occurring, which can also be detected. 4G, 3.5G (LTE/WiMAX etc.) are even more likely to be capable of being detected.

The next challenge then, other than refining both sensing processes, is to combine the Bluetooth and wi-fi sensing together to give an aggregate view of phones/devices across both. A lot of shuffling of pings and prompts and duplicates is required here. Beyond that, to get the hardware prototype to a state where we can test in a few environments – at UTS and perhaps at Arup, and then into the wild.

So now we have significant process in both the sensing side (Bluetooth and wi-fi both delivering results, albeit independently at the moment, and the hardware side, with a ‘box of tricks’ coming together nicely.

One of the key questions this might be able to answer are those deceptively simple questions about how people use transport. “How many people get off the number 12 bus here and change to the number 34?”, for instance. Although answers are usually attempted via spot-surveys and manual tracking, this very simple analysis is actually difficult to get at in any systematic sense – particularly when scaled up to all buses, all bus-stops, and in real-time. (The shift to real-time data driving decision-making in urban planning is fundamental, and not without complexities, but will surely happen. This project is a prototype of some elements involved in that future.) Other questions might be: How many people switch from platform 3 to 4 at this time? How many people are on-board the next bus? And so on.

There are issues around how to scale up the data to an urban population. As Anne Galloway and others remind us, not everyone has a mobile phone, never mind a smart-phone. So although we’re investigating a mode of sensing mobility that would be far more wide-spread and real-time than current methods (leaving aside floating car data) we have to be careful about extrapolating the results. We also have to be careful about ethics and privacy too, and we’ll be investigating that shortly, covering both the visibility of the seams of the system, and the levels of aggregation necessary to preserve anonymity in visualisation. As Richard Sennett has said, the great promise of cities is that they enable both anonymity and community – we want to work with that balancing act, not against it.

All the above assumes a ‘passive’ sensing of what phones/devices are present in a space i.e. no direct intervention into the environment encouraging access. However, if there was a smart transit application built for these environments – say delivering real-time transit information, including arrival/departure times, connection times and possibilities, congestion levels, environmental data etc. – this would give people a reason to turn on Bluetooth and/or wi-fi on in the first place. If transit operators offer a good quality informational amenity to passengers, the passengers’ quality of service is improved, potentially leading to great patronage – but in addition, these users can then also be sensed, offering the kind of strategic data we’ve been discussing to transit operators.

As a side-line, we’re also looking at office environments, and how responsive environments could be enabled by these real-time feeds on presence. Many ideas there, which we’ll pick up in a subsequent post.

David Lowe and Jason McDermott

This update is in three parts: ‘our approach’; ‘the hardware’; and ’sensing’. This entry is continued from ‘our approach’.

CRIN have explored some simple hardware platforms, particularly the Gumstix and Beagleboard ’sawn-off’ PCs (strictly, ‘computers-on-module’). Below, a few shots from a recent session discussing the hardware. Be warned, this will get a little geeky.

Note the core board here is a Gumstix Overo Earth – the smaller component – sitting on top of a larger expansion board, which gives us further connectivity, including an outlet for multiple USB connections amongst others (spec here). This is needed as CRIN are taking the ‘array of dongles’ approach to sensing via four Bluetooth dongles all scanning simultaneously. (You can see a couple of those behind the box in the shot below.)

Note also a 3G dongle is needed to deliver data from the board to the internet (and to enable updates to the software to be received on the board too).

There is also a wi-fi dongle, ready for the next stage of scanning (notes on that to follow).

The power adaptor, or battery pack, as seen here, is by far the biggest component. If the boxes are installed where reliable, secure power is available, then the box can be rationalised heavily, down to not much larger than the augmented Gumstix itself. In many cases – most urban bus-stops, public transport vehicles themselves, offices etc. – this power will be available. In far-flung suburban bus-stops, it may not be. So the battery approach isn’t ideal, but may be necessary in some environments. (Also, CRIN (David Lowe, Alex Gibson) reckon the program code is running at about 7% CPU at the moment. By rationalising other aspects of the software, the power load can come down even more. However, Alex is exploring running a background task to keep the 3G connection open (those service plans are not particularly designed for this, of course.)

CRIN can also wirelessly update the software on the boards, when required, by SSH-ing onto the card via their IP address (using Dynamic DNS, which avoids the issue of IP addresses changing regularly due to DHCP, usually used when connecting through an ISP like Dodo. Dodo have been chosen as the 3G connectivity as they’re one of the few to offer a long term pre-paid plans. Again, it’s interesting how these ancillary services can inadvertently shape the research. Though bandwidth not an issue here, due to the tiny packets of data being transferred.)

The data is being updated to Pachube. The problem here is that Pachube only currently supports 15 minute updates, and we also require a broader longitudinal history than it enables. Both of these aspects are being addressed by Pachube though, so we see great value in continuing to patronise that platform with our data (and here it is, for what it’s worth at this pre-installation point). The memory card on the board – a basic micro-SD card – has more than enough room for years worth of data stored locally, but getting the data into ‘the cloud’ via Pachube makes it far more malleable.

CRIN are going to test how scalable this approach is – say, by putting seven Bluetooth dongles on a Gumstix board, which are then scanning at slightly different start times. Results across all seven could be aggregated, and with duplicates removed, give a significantly better return in terms of phone detection.

The total cost of the box (all internals, connectivity etc.) is looking like it’s around $400 at this point. Note, at this stage, the boxes are being chosen for their robustness and unobtrusiveness. At a later date we will consider the visual design and affordances of such boxes, as the need to convey the existance of this system might figure for ethical and adaptive design reasons. Besides, why not make a nice box?

We’ll consider next steps, and the other sensing approaches in the ’stack’ in the next post.

Mobile phone user on CityRail, Sydney

This update is in three parts: ‘our approach’; ‘the hardware’; and ’sensing’.

A quick technical update on our mobile phone sensing project with UTS (see earlier post for context). This project is exploring technical approaches to sensing the presence of mobile phones in transit environments (bus, train, ferry etc.) as well as pedestrians, in order to provide real-time data on such activity, potentially informing urban planning and transport planning decisions. Such approaches might reveal how the city is being used, in real-time. This write-up will get a little geeky in places, but we share it in the hope you’ll find something interesting in the overall idea or the particular approach, and do feel free to contribute via the comments form at the bottom of each post. We’re interested in your feedback.

Our colleagues at the Centre for Real-Time Information Networks (CRIN) at UTS have made significant progress in terms of both the sensing process and the hardware prototypes.

Dealing with the first part, we’ve been exploring a ’stack’ approach to sensing phones, starting with scanning for Bluetooth, then wi-fi, then GSM, and so on. This is partly due to ease of sensing, and partly exploring ethical issues i.e. if people have Bluetooth turned on, or wi-fi connecting to routers automatically, can we assume they are more likely to be happy to be sensed? (Probably not, due to poor design on the part of mobile phone software meaning many may leave it on by default without paying much attention to it thereafter, but part of the point of the research is to explore these issues of privacy and security as well as technical approaches.)

And dealing with the first of those wireless technologies, CRIN have made particular progress in terms of sensing Bluetooth. Using the basic Bluetooth scanning functionality in a PC or Mac Mini, say, we can sense people with Bluetooth turned on and visible if they’re walking past slowly, due to the relatively slow default scan rate i.e. it takes a while for the scanners to detect and observe the phones in the vicinity (the scan rate takes over a second, and is dependent on the number of devices. In essence the scanning uses multiples of 1.28 seconds, with the number of multiples increasing the liklihood of finding all devices. A good quick summary can be found in this PDF.)

As we’re trying to spot a couple of things – for example, both passengers in transit or waiting at a bus-stop (more static) and also pedestrians (moving at around 1-5m/s) – and given the likelihood of groups in these scenarios and the low numbers of people scannable, we needed to increase the Bluetooth scan time.

There are legal and illegal ways to do this. Choosing the former route, CRIN have made great progress in terms of speeding up the scan time, and the detection rate. Software is being written in Python, on the Linux operating system – rather than say Processing on Mac OSX, where the need to parse higher-level languages with limited direct interfaces between Bluetooth drivers and Java would slow things down a little – and several hardware approaches have also been explored, with the current solution considering using multiple Bluetooth dongles in an array, staggering scan times

The range of Bluetooth (class one) effectively turns out to be around 5-20m (depending on the particular dongles employed, the structures in that environment, and so on. Wi-fi is much broader). Of course, in transit, on a bus, train, or tram, or relatively stationery at a bus-stop/platform, the captive audience is much easier to spot.

(NB: the RTA assumes people walk about 1.2 m/s on average, according to their transport planning regulations.)

Essentially, the array of Bluetooth dongles is now able to scan phones much faster, and certainly within our intended environments of buses, trains, bus-stops, platforms, stations etc. Recall that the original rationale for this project is to generate real-time feeds on transit activity in urban areas, as most current transit data is not real-time, not particularly scalable, doesn’t uncover individual ‘multi-modal’ trips where someone might walk to a bus-stop and then switch to a train, say.

Given this impetus, the scan-rate from the Bluetooth array achieved above is certainly good-enough as a start. The next requirement is to wirelessly communicate this data in real-time to ‘the cloud’, via a small robust ‘box’ that could be installed in such environments.

In the next post, we’ll discuss the emerging hardware prototype.