In the beginning of his talk he discussed an interesting (and after he said it very obvious) option of Green Computing: move computing towards the energy source as it is easier to transmit data than to transmit power. Thinking about this I could imagine that Google’s server farms are move to a sunny dessert and then the calculations are done while the sun is shining… and using the cold of night to cool down… This could be extended to storage: storing data is easier than storing energy – this should open some opportunities.
Rob Harle’s page for details. It is however easy to imagine the potential this has if regular shoes can sense movement in everyday use. He hinted to think about the options if one could go to doctor and analyze the change in walking pattern over the last year.
In various examples Andy showed how Ubisense is used in commercial applications, production, and training. It seems that medium resolution tracking (e.g. below 1 meter accuracy) can be reliably achieved with such an off the shelf systems, even in harsh environments. He mentioned that the university installations of the system at an early product stage were helpful to improve the product and grow the company. This is interesting advices, and could be a strategy for other pervasive computing products, too. For close observers of the slides there were some interesting inside in the different production methods between BMW and Austin Martin and the required quality
Power usage is a central topic in his labs work and he showed several examples of how to monitor power usage in different scenarios. On example is monitoring power usage on the phone, implemented as an App that looks at how power is consumed and how re-charging is done. This data is then collected and shared – at current over 8000 people are participating. For more details see Daniel T. Wagner’ page. A further example is the global personal energy meter. He envisions that infrastructure, e.g. trains and building, are broadcasting information about the use of energy and that they provide information about one individuals share of this.
With an increasing proliferation of mobile phones the users’ privacy becomes a major issue. He showed in his talk an example, where privacy is provided by faking data. In this approach fake data, e.g. for calendar events, location data, and address book, is provided to apps on the phone. By these means you can alter what an application sees (e.g. location accuracy).
For more details and papers see the website of the digital technology group: http://www.cl.cam.ac.uk/research/dtg/www/