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.”
“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 |
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.”
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.
"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
|
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.
About Seattle Lab
