The weekend before last was Rewired State’s Carbon and Energy Hack Weekend I previously mentioned the event and my plans for it. I did not get the chance to spend both days that weekend working on my project, I decided to retake the project this weekend and put the finishing touches to it.
My aim was to develop a prototype for an ambient information display by connecting it to a “real-time” energy data feed. I also wanted to explore the different ways in which we can present the data on the device. The ambient display is initially intended for personal or home use, my fist task for the event was to find a suitable data feed.
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The guys at Carbon Culture provided me with an interesting resource. They supply, amongst other feeds, a real-time energy consumption data stream coming from nº10 Downing Street at 30 minute intervals. I realise nº10 surpasses a typical household both in terms of size and energy consumption, I assume however The Camerons, like anyone else, can benefit from an increased awareness of their energy consumption behaviour.
I’m using the device to display the live feed in three ways:
A trend graph that shows the last 8 hours of data.
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A parallel graph that compares two readings, for instance now vs. yesterday at the same time, or now vs. an hour ago. The comparison graph is coloured green or red depending on the direction of change in the data.
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Finally, an arrow that represents the direction of the fluctuation in the data feed. In other words if energy consumption increases in comparison to an hour before the arrow points upwards in red, on the other hand if consumption decreases it points downwards in green.
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In my opinion both the comparison graph and the arrow showing the fluctuation in data work much better than the trend graph. Both representations are much more concerned with the “now” and they suit the realtime nature of the data. The trend graph requires context to be understood, if we only take a day worth of data to provide that context a single spike in the distribution changes the shape of the graph dramatically from one hour to the next, which can be confusing. Counting only with 8 columns to provide context means we have a reduced resolution to give insights on the data. A potential solution would be to use a larger data set as context, a month let’s say, to plot the proportion of a daily distribution.
A feature of ambient displays, and this display in particular, is that it does not show values of data but maps fluctuation in the proportions of that data to colour and shapes. As a result relative representations like the comparison graph and arrow are more immediate and work much better.
The incoming data feed for Downing Street in kW h for the last 8 hours looks something like this:
[59.833999999973457, 62.183333333348862, 60.283333333325572, 59.197435897454852, 59.26666666669189, 64.550000000017462, 63.999122807028463, 64.388888888875954]
Since we have a very low resolution 8×8 display the data is re-scaled to fit a 0-8 range.
[1.8324886226952222, 4.9049101796373273, 2.4201197604444991, 1.0, 1.0905389221639117, 8.0, 7.2795713835399347, 7.7893013971657767]
Finally since we cannot display 1.83 pixels the data is rounded to its nearest integer in order to be displayed.
[2, 5, 2, 1, 1, 8, 7, 8]
Here is a clip of that sequence displayed:
Place-stat displaying live energy data feed from nº10 Downing Street from Gonzillaaa on Vimeo.
A script running on my laptop pulls data from Downing street at regular time intervals, it processes and shapes the data to be displayed, and sends it wirelessly to the device via Bluetooth. For those interested in seeing how this works have a look at the code.
Why use an ambient display?
- As I mentioned before, none of us have a mental model of what 1kW h looks like, we might understand the formal abstraction of what it represents but there isn’t a single image of how it looks like.
Those who work with energy and carbon data know energy in watt hours is the multiplication of power in watts and time in hours. So 1kW h is a unit of energy equal to 1000 watt hours. But that does not mean much to most people.
- Since we don’t have a mental model to clearly describe our energy consumption we think of energy in relation to other things. We consume more or less than yesterday, object A consumes more that object B. If you look at many of the devices that fall in the category of smart meters with exceptions like Wattson and the Energy Joule they mostly rely on the presentation of data in kW h on alphanumeric displays. I believe there is ample room for exploration.
- Finally our goal is to improve our energy consumption behaviour. Behaviour change technologies are frequently informed by the work of BJFogg and his team at the Stanford Persuasive Technology Lab.
According to Fogg’s Behaviour Model a crucial aspect to enabling change in behaviour is to create “Triggers” and place them in the path of motivated people. Ambient computing enables us to embed information in the places we inhabit, making it “glanceable”, easily accessible and provide people with the least path of resistance to action.
What’s next?
I think there is a lot of room for the development of a flexible and low cost display system that enables us to access information in a spatially relevant way. As sensing energy consumption from appliances and other devices becomes common place, the tightly coupled sensing and displaying systems that are commonplace today will give way to other possibilities.
I am keen to test my assumptions with this work and develop the project further. I want to develop the hardware and software as an easy to use self assembly kit people can buy and use in their homes, offices, workplaces etc. Interested? Want to help? Get in touch.
Thanks to the Rewired State Carbon and Energy weekend organising team and the guys at Carbon Culture for their in-situ API support.