In the morning, Tushar and I watched Kamin Whitehouse’s talk on MIT Technology Review and learned the importance of work environment: he highlighted the fact that Americans spend 60% of their time in their homes, thus innovation in home is important.
So we did some rearrangement of furniture and organization of wires. We had been avoiding the lab room because it felt crowded. Now, it is so fresh I think I could wake up earlier in the morning to work in the lab room(or maybe not).
Having got Helios one step closer to working (the bug is on Nick’s side now) the rest of the day was spent cleaning out the lab (it looks great now…we just need to configure the Hue Tap, and hide the gently decaying walls somehow) and reading up on Kamin Whitehouse‘s research group and their projects.
Whitehouse’s group had several interesting projects underway, and even though they weren’t using machine learning on end-user programming they had stumbled upon some powerful innovations. I want to talk about my favorite so far, the Marauder’s Map.
Lit. Review
With the intentions of ending the week well, I decided to go through Mozer’s paper. Our seniors and professor considered this to be a model paper given the extensive use of reinforcement learning by the researchers.
I read this paper written my a few researchers in University of Michigan. The name Newman drew me in, since I have seen the name multiple times in this field. This paper was like many others: a study on how people interact with a smart home system they came up with.
I was quickly skimming through the paper since I was quite well-aware of what most HCI papers talk about, but slowed down a bit when I found an interesting approach to testing how well their system OSCAR works. OSCAR is a form of end-user programming that allows user to flexibly control their devices of networked devices at home. The paper did not mention this explicitly, but from a photo, I could tell that OSCAR in a physical form is a tablet that people can interact with.
Lit. Review
After a quick but brain-boggling look at Machine Learning yesterday, we returned to more HCI oriented papers today. I chose to read CAMP: A Magnetic Poetry Interface for End-User Programming of Capture Applications for the Home (Truong et al.).
The secret to controlling your smart home?
I read a paper written by Microsoft on HomeOS. Just from reading, I do have to give credit to them for being pioneers in the field. We do know that there are some difficulties using their system and devices, but their innovative idea on PC abstraction is indeed very promising for smart homes and user satisfaction.
Microsoft advocates centralized PC operating system for home and decentralized network of devices because 1)all devices will be connected and this connection will allow for smart home functionality, 2)it is easy to add devices since they are not closed system, 3)users already know how how to use computers, and 4) it is easier for developers to implement functionality without worrying about devices.
Inventions come from complaints. They are created to make our lives easier.
We complain all the time, but it seems like we forget about them when we actually try to come up with solutions. So, it’s a good idea to document your complaints;)
Brown has a website where students can rant about their inconveniences caused by Brown. It is called “What to Fix at Brown”, a.k.a. wtf Brown.
I have to think hard to recall what I have been complaining about in terms of dorm life, but here are a few that could be related to smart homes of some sort:
Yesterday we’d asked Professor Littman for a text on machine learning. The result of our query was a hefty tome – Artificial Intelligence, a Modern Approach by Peter Norvig (one of my role-models) and Stuart Russell. The concepts were straightforward enough to understand but the text was littered with forehead-wrinkle-inducing jargon (eg: classification, regression, realizable hypothesis spaces). I managed to get through a section or two, stopping at ‘learning decision trees’; it was slow going especially since I was making a personal (metaphor filled) summary on my research wiki.
I read a paper called “Toward User-Centric Feature Composition for the Internet of Things“ written by Zave, Cheung, and Yarosh. This was a good paper to start with because it defined what “Internet of Things” stand for and what is expected out of it.
Internet of Things in a broad sense stand for a smart home where sensors and actuators are connected through the Internet. So far, there are more complaints than satisfaction because people expect the system to behave “intuitively” which may not be so natural for computers. On top of that, each individual is a complex being distinct from others, which makes it hard to come up with a model that fits everyone. Continue reading
Today I waded through a paper outlining the shortcomings of the Nest smart thermostat and its limited success at learning users’ preferences. I also read a long rant from a tech blogger who had tried and failed at basic home automation. The combined (albeit limited) picture I got from the two articles conjured a somewhat bleak status quo for machine learning and user-programming in smart homes. Which of course, is just what an eager young researcher wants to hear (I’ll also try reading some more upbeat literature tomorrow).
It looks good, doesn’t it?
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