| George Roussos |
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| Wednesday, 31 January 2007 | ||||
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He talks about motes, trails, microservers, feral robots, Snout, ZigBee, and other aspects of sensor networks, as they relate to learning.
This is what we have built with a query engine, which is what Google is for page rankings. What they can do is answer whatever question very, very quickly. And we do the same for this type of sensor data. Not only keywords, but also impressions and interactions within a space. You can associate whatever metadata you want with certain devices. It can be an identifier within a classification system, a keyword, or whatever. So you can query for specific keywords, and it will pick up all the related data. Now we have a live tool for reconstructing trails. You can view descriptions of any space, and you can upload records, which triggers an animation, like Media Player - you can play, step forward, replay your experience. And at every step it can trigger related information, say from a web site. You can also edit your own images, content, and so on. We tested it at the zoo, but we have yet to use it in a real space. This type of system can help you remember your experience, to see the specific path you've taken. For us as researchers, we can sit somebody down and replay their experience, and they can talk to us about what was happening. One thing we are looking at in my ubicomp class is appropriate models for sensor networks. One thing that has been envisioned is millions of microscopic sensors that you could just spray around a place. Well, that's not going to happen any time soon. Not for any other reason than it's hard to coordinate sensor systems like that; getting any sort of data is next to impossible. Since the sensors are so tiny, they are quite vulnerable. So what you need are three things - you need a kind of micro-server, you need external devices, and you need mobility. You can work with any kind of robots or sensors, but what really makes them work is the algorithm, and that's what we concentrate on.
In sensor networks, one of the things we are using is moteiv motes with a daughterboard that is completely free of the need for batteries. You can actually now build a power-scavenging device. It can get energy from light - even artificial light, if it's good enough. And it's a very tiny device - it does very limited things; everything is built in. It just wakes up and checks the sensor, and if it's over a specific threshold, then it will notify you; otherwise it will go back to sleep. For that, you consume very, very little energy, and all of it can be provided by a tiny photovoltaic panel. It has a capacitor in it to store energy. If this daughterboard detects something that is important, it can wake up the mote. You don't need synchronous operation of motes; they can be asleep like 99.999 percent of the time. You can run them for years like that. Right now we are looking at how to wake them all up for a synchronous mode of operation. The next step would be either to wake everybody up, or to use a microserver the next tier up. It might be powered by the mains, so power wouldn't be an issue. And it could wake the rest of the system. The other option would be to make a collective decision within the network. At the bottom layer, you have pure observation, where at its simplest, a sensor could just send you one or zero depending on a threshold. But that's not enough to make a decision, because what you might be interested in is the average of temperature within a distribution. So the higher-level description is that if the overall temperature is within this range, then I want an action at the system level. You have to translate that lower-level context of observations to the system level, and that's an interesting thing to be able to do. There are lots of interesting problems in that. You have to be able to do all the data 'smoothing' at the system level. There are other tiers like the business one, with questions like 'I don't care what comes in and what goes out, I only want to be notified if I don't have enough product to ship.' This is the decision-making level. So you have a coding of different tiers of hierarchy and context. Another thing we're doing, which is kind of associated, is how to build software radios. Rather than have fixed devices that can only talk one language like Bluetooth, it is now possible to use very low power electronics that can actually change their behaviour with software. You have an antenna, another component that does the analog-to-digital conversion, and then you may have some logic to do the signal processing. The ADC can actually have a very big range - in practical terms, from UHF to the gigahertz range within the same circuitry, with a single spread-spectrum antenna.
Right now we're concentrating on getting it to work, then the next step would be figuring out how and when to switch. To fit all the software you need to do the modulation and signal processing, you really have to cut down the code. But it is becoming feasible. If you get it right, you can talk GSM, GPRS, RFID. The circuitry that talks GSM is perfectly capable of talking RFID, so you don't actually need more hardware. It will take maybe a year, year and a half to see if it works. And assuming it does, the next step will be to look at more practical problems, like what it takes to switch between different protocols. In terms of learning, you have to look at types of representations, from a semiotic point of view. We have been working with Carey Jewitt and Sara Price on this. You have data loggers traditionally in schools, for chemistry and biology. How you visualise that data is important. Some data loggers can capture very rich data sets and capture a lot of data, that you can overlay on physical locations. My degree was in mathematics. I was a flight sergeant/programmer analyst for three years, as part of my national service in the Greek military. For a while I was This e-mail address is being protected from spam bots, you need JavaScript enabled to view it - a kind of geek badge of honour. All the military had an internal Internet exchange, so that they could communicate with each other without having to go onto the public Internet. I was in charge of that, and those servers. I got interested in learning from my wife Theano. I was reading all her stuff from early on. We are expecting our first child in May - a girl. It's funny how the doctors talk about the 'estimated time of arrival,' which is the same thing computers tell you when you're downloading something! The progress bar is reaching the end.... |
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