One unique aspect of Intel’s university labs is that the position of lab director rotates every two to three years to ensure that the research agendas stay fresh. In September 2003, James Landay became the second Director of Intel Research Seattle, succeeding Gaetano Borriello, who continues to collaborate with the lab. Landay, a tenured Professor of Computer Science at the University of Washington, will return to that position full-time in the fall of 2006, after completing a three-year rotation at the lab. At that time Landay will be succeeded by University of Washington professor David Wetherall. In his role as Director of Intel Research Seattle, Landay is applying his research background and interests in the areas of user interface design methods, evaluation, and prototyping tools to the domain of ubiquitous computing.
One unique aspect of Intel’s university labs is that the position of lab director rotates every two to three years to ensure that the research agendas stay fresh. In July 2006, David Wetherall became the third Director of Intel Research Seattle, succeeding James Landay and Gaetano Borriello, who continue to collaborate with the lab. Under Landay’s leadership, the lab focused on research with the greatest potential to make an impact on the world. In his new role as Director of Intel Research Seattle, Wetherall will be applying his research background and interests in the areas of networking, and in particular, the protocols that underlie the Internet and all other forms of communications networks, to explore new networking protocols that enable communication and connectivity between wireless devices.
“Wireless devices are proliferating, due to their tremendous convenience and the fact that the technology is racing ahead in terms of capabilities,” says Wetherall. “My interest in wireless systems meshes well with the lab’s agenda of exploring technologies to support ubiquitous computing. As lab director, I’ll be able to continue my research into protocols for wireless systems, and to do so with real applications that matter to real people. That’s very rewarding, and it adds significant realism to the research.”
Anthony LaMarca, who joined the lab in 2001, was named Associate Director in the spring of 2005. In his new role, one of LaMarca’s key responsibilities is to help to translate the lab’s research into potential products, by identifying and building relationships with groups within Intel that can help to move the research downstream toward product development.
The lab provides an environment where researchers can rapidly explore new ideas and also develop larger agendas. In 2005 there were three large research programs underway, in the areas of human activity inferencing, location-enhanced computing, and digital simplicity.
About David Wetherall
David Wetherall is an Associate Professor of Computer Science at the University of Washington and Director of Intel Research Seattle. He joined the UW faculty in 1999 after receiving his Ph.D. in computer science from MIT; he received his B.E. in electrical engineering from the University of Western Australia in 1989.
Wetherall's thesis research pioneered active networks, an architecture in which new network services can be introduced rapidly using mobile code. His research interests span the range from networking to distributed systems and programming languages. Wetherall received an NSF CAREER award in 2002 and became a Sloan Fellow in 2004.
About Anthony LaMarca
Anthony LaMarca joined Intel Research Seattle in August 2001. Anthony is a Principal Engineer and was named Associate Director in the spring of 2005. His research is focused on developing software infrastructure for ubiquitous computing applications.
Before joining Intel, LaMarca worked for two years at Yahoo!, doing advanced development and research. Before Yahoo, he was a researcher in the Computer Science Lab (CSL) at Xerox PARC. During his three years at PARC, he worked on projects such as Placeless Documents that tried to help users cope with the large amounts of data they encounter in their daily lives.
LaMarca earned his BA in computer science from UC Berkeley in 1989, and his Ph.D. in computer science from the University of Washington in 1997. His PhD dissertation focused on developing and analyzing memory-efficient variants of classic searching and sorting algorithms.
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"The lab has enabled the University of Washington to recruit star talent to campus. James Landay was, in part, attracted to UW by the opportunity to lead the lab and help build a foundation for his own research program in Seattle. Adding James to our community has been an unexpected but very welcome benefit."
Gaetano Borriello
Professor of Computer Science and Engineering
University of Washington
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The lab provides an environment where researchers can rapidly explore new ideas and also develop larger agendas. Today there are two large research programs under way, in the areas of human activity inferencing and location-enhanced computing, and a third is being formed to address ubiquitous computing in the digital home.
Human Activity Recognition
The Human Activity Recognition project is the Seattle lab’s major initiative in the area of activity inferencing research. The team, which includes researchers from Intel Research Seattle and the University of Washington, is taking an “invisible man” approach to recognizing and predicting human activity based on observing the objects a person touches, and the context in which the objects are used. The research uses RFID (radio frequency identification) technology and the latest techniques in data mining and machine learning to gather data about the physical world and from it, infer a wide range of human activities.
James Landay explains: “If we put RFID tags on everyday objects, and you are wearing a bracelet with an embedded RFID reader, we can monitor which objects you touch,” he says. “We don’t have to see you. If we simply know what objects you’re using, in what order, and where, we can infer quite accurately what you’re doing. For example, if we know, from the sensor data, that you took a teapot to the sink, filled it with water, put it on the stove, got out a teabag, grabbed a cup and some milk or sugar, we can pretty unambiguously infer that you’re making tea.”
The researchers have developed a bracelet with an embedded RFID reader dubbed the iBracelet. It was developed in collaboration with students in the Industrial Design Department of the University of Washington.
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"I collaborate with the lab on the Human Activity Recognition project, along with my university colleagues and students. Our research involves activity recognition using sensors such as RFID [radio frequency identification] tags. Specifically, we develop novel, probabilistic techniques for activity recognition using raw sensor data. The really exciting aspect of this project is the benefits it might generate for the health care sector in general and elderly people in particular."
Dieter Fox
Assistant Professor, Computer Science and Engineering
University of Washington and Director, Robotics and State Estimation Lab
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Today the iBracelet is being used in an Intel fab, to assist technicians with preventive maintenance. “Using the iBracelet, we can track technicians as they move through their checklist of activities, and we might be able to identify better ways to do preventive maintenance,” says Landay. “This could translate into millions of dollars’ worth of improvements over time.”
Wireless Identification and Sensing Platform (WISP)
A complementary technology in development at the lab is the Wireless Identification and Sensing Platform (WISP), which combines an RFID tag with a sensor, enabling the device to communicate richer data about a person’s activities. “Rather than a long-range RFID reader simply telling you it sees, say, ‘ID 6,’ which might be the RFID tag on a can of soda, it could tell you, ‘I see ID 6, and it’s being shaken hard right now,’” says Landay. That allows us to know which objects are moving or being manipulated by people, without them having to wear the iBracelet or any other form of RFID reader.”
The sensor data measured by WISPs is not limited to motion. A WISP could contain any of a variety of sensors, from accelerometers and barometers to temperature and light sensors.
A key advantage of WISPs is that they don’t require batteries. They harvest energy in the same way that standard RFID tags do, through the radio waves sent by the RFID reader. This opens up a number of possibilities for using WISPs. “You can imagine putting WISPs into the walls of a home or building when you build it,” says Landay. “Then, over time, you could use an RFID reader to check the current temperature in the wall, to determine if there’s an air leak, or check the strain if there’s an earthquake, to assess whether it caused damage. The WISPs could be embedded in the wall indefinitely, since they don’t need batteries.”
CareNet Display
A key application of this activity inference technology is in the eldercare arena, in monitoring the activities of older adults in their homes, to infer the state of their health and well-being and help them to carry out activities of daily living. “Elder care has been a major focus of Intel Research, from the proactive health project, which focuses on applications to assist the elderly, through the work of our lab, which addresses the fundamental technology to make the vision of proactive health come to fruition,” says Landay.
The Seattle lab's Computer-Supported Coordinated Care (CSCC) vision is aimed at advancing proactive health technology. One outcome of the team’s research is the CareNet display, an interactive, digital picture frame that augments a photograph of an elder with information about her daily life. The photo can help distant relatives or nearby caregivers monitor elders in their homes and determine when more assistance may be needed.
The Seattle lab’s researchers have adopted the CareNet display for cell phones. The goal is to give caregivers greater mobility and easier access to information about those in their care—anytime, anywhere.
Mobile Sensor Board (MSB)
Much of the lab’s early inference work focused on interactions with physical objects. More recently, researchers have developed a mobile sensor board (MSB) that captures richer data and can be used to infer a broader range of physical activities.
“Using RFID technology, we’re pretty good at telling whether a person is cooking, cleaning, or brushing their teeth because of the objects they manipulate when doing those tasks,” says Landay. “With a MSB, we can infer physical activities that may not involve using objects. By applying machine learning to the data provided by the MSB, we could infer, for example, whether you’re sitting or standing, taking the stairs or elevator, or whether you’re walking, running, or bicycling.”
The MSB contains seven types of sensors, including an accelerometer; digital compass; barometric pressure, temperature, humidity and audio sensors; and three types of light sensors. The MSB attaches to the Intel® Mote, which contains Bluetooth wireless technology , enabling the board to communicate wirelessly with Bluetooth-enabled cell phones or other devices. The MSB is roughly the size of a pager and can be worn in a variety of locations.
Physical fitness is one promising application area to which the MSB is being applied. According to Landay: “Medical researchers are really interested in the technology, because they have a hard time measuring patients’ exercise levels, which relate to health problems like obesity and diabetes. Generally physicians rely on self-reporting, but people typically aren’t very accurate at reporting their activity levels.”
The MSB could provide richer data than, say, a pedometer, which simply counts steps and can’t measure exertion levels (a strenuous four-mile run may include the same number of steps as a two-mile walk). Built into a cell phone, the technology could motivate people by giving them instant, accurate feedback about their exercise levels. “We’re looking at a number of personal fitness applications, with the goal of helping people to make small changes in their lives to improve their fitness, like noticing when they take the stairs rather than the elevator,” says Landay.
Digital Simplicity
The overall objective of the lab’s newest research project in the area of ubiquitous computing is to simplify people’s personal lives, through technology that is easy to use. One key focus is technology for the digital home. “There will be a lot of ubiquitous computing devices and scenarios in the home of the future,” says Landay. “When people start to acquire a variety of home devices, how will they interact with them? If each device works differently, it will be very difficult for the average user.”
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"We’ve gotten to the point where it’s reasonably easy for most people to figure out the basic operations of PCs, and the big breakthrough that enabled this was a graphical user interface (GUI). The basic low level language that people use to interact with GUIs is the same: you move the mouse around and point and click at objects and pull down menus, and so forth, and whether you’re on a Mac or a PC, it works pretty much the same. This simple underlying language also makes it easier for users who want to learn more advanced concepts. We need something similar for controlling devices in the digital home of the future."
James Landay
Director, Intel Research Seattle
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To tackle the challenge, researchers are taking their cue from the evolution of the PC industry. The growth of the industry was driven in part by the development of a simple graphical user interface (GUI), which made it easier for users to navigate any PC, using the same familiar mouse actions and pull-down menus. Researchers hope to find a common underlying interaction pattern among digital home devices that would enable them to create a similar easy-to-use interface for these devices. That way, a user would only have to learn to operate one device in order to use all of the others.
One goal of the Digital Simplicity project is to be able to offer guidance to device designers. “It’s really important that designers have the right knowledge to build devices for the digital home in such a way that they are easy to discover and use,” says Landay. “Once we reach the point where we know the best ways for designers to develop easy-to-use interfaces, we can focus on empowering the users themselves. Is there a higher level where we can allow users to be able to configure their own home environment to do what they want, or have the environment learn what they want? These are some of the open questions that this project is investigating.”
Activity-based Perspective
One key to making applications and devices that simplify personal lives is to focus on high-level activities, Landay believes. “It’s my opinion that the devices that people think of as simple today take an activity-based perspective,” he says, and cites TiVo as an example. “TiVo pays attention to what you normally watch and records it automatically. So if you watched, say, ‘CSI’ before, it records it. And even if you haven’t watched it before, TiVo makes it very easy for you to say, ‘record CSI.’ It doesn’t ask you to know what channel it’s on, or what time. It focuses on the program, because that’s the activity you’re thinking about—watching the program. Through that activity perspective, TiVo closes the gap between what you’re trying to achieve and what the device supports.” Landay contrasts the TiVo approach with the perennial struggle of consumers to program their VCRs. “You have to know what time the program is on, what channel, and how to program your VCR to record that channel at that time. People have had problems with this for years. It’s gotten simpler, but it’s still hard.”
In the future, says Landay, we will want technology to support more complex, high-level activities such as “letting Grandma live a healthy, independent life.” That could involve a prompting system for Grandma when she forgets how to cook a meal. It might include an interface for medical data that is sent to her doctor. It will also require supporting Grandma’s care network, through easy-to-use devices such as the CareNet Display, described earlier.
More generally, supporting high-level, long term activities requires an understanding of the long-term goal of the activity (“maintaining fitness” rather than “counting the number of steps I take,” for example). It also requires a knowledge of the multiple people and roles required to achieve the goal (such as Grandma’s care network). And it requires that supporting information be available at all times. “The information you need must available in whatever device you are using at the moment,” says LaMarca. “We have to build supporting applications that run on your phone, on your TV, and on other digital appliances.” Finally, supporting high-level activities requires that technology adapts over time, as the user and his or her support network evolves.
As the Digital Simplicity researchers experiment in developing these supporting technologies, one challenge they face is how to evaluate them. “It’s a real challenge to evaluate technologies that are designed to support goals that span long periods of time,” says LaMarca. “These are not the sorts of applications that you evaluate in the lab. “You can’t bring people in, pay them for an hour and say ‘try our new technology and see if it helps you maintain your fitness level.’ We need to develop new measurement tools for evaluating success in real world settings.”
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Place Lab
The goal of the Place Lab project, which has now transitioned out of the Seattle lab, was to develop low-cost, easy-to-use positioning technology to support location-enhanced applications. Place Lab takes advantage of the proliferation of IEEE 802.11 or “WiFi” hotspots in homes, businesses, university campuses, and in public spaces. It enables a WiFi-enabled client device to automatically determine its position by passively listening for the unique MAC identifier that each access point broadcasts periodically, then mapping them to their geographic coordinates and using that data to calculate the device’s position.
By using existing WiFi infrastructure, Place Lab overcomes two key problems that have stalled research efforts in location-enhanced computing: the need for both expensive equipment and technological expertise. This combination had made widespread deployment difficult, and discouraged the development of location-enhanced applications.
To overcome these hurdles, Place Lab researchers focused on finding a way to access—virtually for free— location information that may not be as accurate as the best GPS reading but which is good enough for many applications. The ultimate goal is to make the additional cost for location-enhanced computing very low, to encourage widespread adoption.
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"I think Place Lab is shaping up to be a quintessential example of how collaborative research between industry and academia can proceed effectively and make a real impact. The scale of Place Lab is such that it could only progress through the consistent efforts of a lab like Intel Research Seattle. The openness of the project has enabled a growing number of researchers at academic institutions to explore Place Lab as a platform for projects of their own interests, which increases the impact of the research done in the lab."
David McDonald
Assistant Professor, Information School, University of Washington
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To eliminate the need for technical expertise, Intel researchers focused on making Place Lab technology accessible. “We provide a toolkit that does all the work for you,” says Landay. “You simply get to work on your application, which asks our toolkit ‘where am I’ and use that information intelligently.”
While Place Lab initially focused on 802.11, the research team also explored how this style of location estimation can be done with cellular technologies such as GSM. The researchers experimented with using GSM as a sole location technology on commercially available cell phones. They also investigated how Place Lab could work with multiple location technologies (802.11, GSM and Bluetooth) simultaneously in the same device. The idea is to take multiple readings and combine them on the fly, to produce what the Place Lab team calls “always best location.”
The Place Lab research has been largely completed and the current focus is on investigating potential applications of the new technology both inside and outside of Intel. One location-based application researchers are exploring is recommendation systems for the physical world. For example, knowing the location of the restaurant where you just had dinner, an application could recommend other restaurants you might enjoy.
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| Related Links |
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Berkeley Lab
Pittsburgh Lab
Seattle Lab
People and Practices Research Group
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