Below is a small experiment I’m currently running; very informally I’m updating a pachube feed (‘cups of coffee today’) with the current location data. It’s a bit of an odd experiment – I’m not really always drinking coffee, but once I set it up (using the pachube iphone app, which is pretty simple to use) I discovered that it logged the location of each coffee cup consumed. Not so exciting I know, but I’m interested in the notion that my daily activities and movements can be logged, tracked in some sense and collected to form an image – be that automatically or manually logged data. It’s by no means new territory, but I’m keen to see how it all works out. There’s a chance that the ‘update feed by twitter’ tool will come in handy, but who knows at this point.
So as I said, It’s a bit of a mish-mash, however there are a few things of interest. 1. I can log 0 cups of coffee, which will update the location but keep my caffeine intake low. 2. When i do have a cup of coffee the daily tally will increase and I’ll be able to see where and when it all happens (at work, that’s a no brainer..). 3. Along comes this openstreetmap based project from the pachube apps page – Trails.Have a look for yourself, just how well or unwell my coffee consumption is going over the last 24 hours.. Hopefully, if you’re reading this you’ll see a map below, with a gps overlay of location (x,y) and consumption (z) data. If not, then perhaps I’ve not updated in a while. Nonetheless, it’s got me thinking about these new consumer (no pun intended) tools which are now readily available – and free.Not sure where this will go, not exactly sure where it belongs, but it’s worth mentioning at least.Drink up!
Tag Archive for visualisation
pachube coffee and gps
fluid updated
I’ve spent a bit more time cleaning up the fluid blobs examples I made last week, this time limiting the Region of Interest and fiddling with the fluid interaction. Also newly included is a smarter way to interact with the blobs (in the code, i mean), pulling out more precise locational data. I’ll be looking to mine this one a bit more extensively than I did with the filtration fields installation – and since I seem to be getting better now at things I was attempting before – this should be a lot more fun.In the mix still is some video over network action, as well as potentially a database record of the motion over time. I’d like to develop this as an interactive (from the visualisation point of view) interface where you could select a day, week or month and view the fluid ripples as they occur, like a fluid time-lapse of the actual motion from the courtyard. We’ll see.
Fluid Blobs v2 from Jason McDermott on Vimeo.
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fluid blobs
Linked below are some early results from a new series of sketches I’ve been working on using Processing. These sketches continue in a long line of projects I’ve completed recently using simple camera tracking algorithms to infer interesting patterns of movement in urban spaces.The first example is a calibrated blob tracking experiment, using the excellent and very well documented OpenCV library for processing. A few simple modifications to the setup parameters allow for a very customisable tool, able to withstand many of the constraints live webcam installs can throw up. I’ve tested this in a number of places (my bedroom wall, lit by a single lamp tends to be the best contrast) and will have more to say on the nature of live webcam video in the future.
OpenCV blob tracking – calibrated from Jason McDermott on Vimeo.
The second example is a first attempt at combining the live blob tracking with the wonderfully funky and playful MSA Fluid library also for processing. This lib is geared towards touch screen interfaces and screen based mouse interactivity – but I immediately thought it would be the perfect partner for my webcam based projects (or even accelerometer/phidget/slider/midi sensor data). It wasn’t very difficult to swap out the mousex/pmousex variables for centroid x/y data, so the first test has been deemed a success. I showed this yesterday to Frank/Ale/Amy/george/anyone who would stop for more than 2 minutes in the interactivation studio and it was a big hit 
OpenCV + MSA Fluid (Processing) from Jason McDermott on Vimeo.
The third example is significant for a couple of reasons – it is another combination this time using recorded video of an actual installation space (filtration fields / DAB courtyard) thus requiring another version of the calibration – but also my first experiments in putting together an arrayed interface between the blobs and the fluid.To explain further; Firstly it’s easy to switch out the mouse for ‘something else’ and inferring movement velocity for a single object/blob is simple. Secondly I wasn’t so sure about the way to apply this singular blob mousex/pmousex-esque technique to many objects at once. Thirdly I wasn’t sure if it would all explode in one big fluorescent, particle mess!
OpenCV + MSA Fluid (processing) test 3 from Jason McDermott on Vimeo.
[Update]< <note, v3 will be embedded when vimeo uploads my video. since when does a new video have to wait in a queue for 30 minutes??>>In the end I’d say it’s mission accomplished, certainly with calibration tweaks to occur before I’m happy to unleash this on an unsuspecting public. I’d be interested to see how this could influence peoples’ behaviour in the space – whether or not we would see people dancing/swimming/painting the space of the courtyard. I’m curious also to see how this kind of new interaction with the space of the DAB could filter into a new perception of the building as not merely a space to move through but one which is open to new forms of physical conversation.
