Friday, 22 October 2010

End of week 3

This week I have read a bunch more papers on NIALM, and collected five of the best papers which provide an overview of the topic. These overview papers are few and far between, as the vast majority of papers contain a tiny background section and an in depth description of a proposed technique.

I've also been to a few more lectures on sustainable energy and power systems analysis. The lectures from both modules seem quite interesting and I'm working through some exercises with Sam.

I have been really impressed with Mendeley reference manager application, and am now using it to share references with Sam and also to store my reference database in the cloud.

I've continued to work through the Intelligent Agents course material, with only two lecture's worth left. I hope to finish it early next week and move on to look at some machine learning material, and how it can be applied to NIALM.

I had a chat with Bhargav about his topic for his MSc project. As I understood it, his project is focusing on the application of machine learning techniques to data collected from sub-metered appliances, with the aim to provide automatic behavioural interventions to encourage energy savings. We discussed how research detailed heavily in the literature discusses modelling appliances as Finite State Machines, and how this high-level information could be useful in providing behavioural interventions.

Inspired by this thought, I wondered whether this would be apparent in my own data collected by a Plogg connected to my work computer and monitors. With a quick plot of the half-hourly power and energy consumption I could already see a number of different states from the power saving settings of my machine; when my computer was on, when it had turned my monitors off, when it had gone to sleep, and when it was off. The fact that these states are recognisable at the low-grained data of 30 minutes intervals of the load data has convinced me that it should be possible to construct an FSM for a specific computer, or even a generalised FSM for a number of computers.

2 comments:

  1. I think in the case of the use of a computer, the FSM might look fully connected - i.e., you could move from one state to any other possible state. Does that help or hurt what you are trying to do with that FSM? But to start with, what is the point of an FSM for this?

    ReplyDelete
  2. I agree, it makes sense that you can move from the 'on' or 'in-use' state to every other state, so maybe an FSM isn't necessary. More useful is the identification of states from load graph. This would mean making high level suggestions very easy, for instance, 'you didn't shut your machine down over the weekend' or 'you could save more energy by using sleep instead of just turning off the monitors at lunch'.

    ReplyDelete