Moving Toward a Future of Ubiquitous Computing
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` Technology & Research Technology@Intel Magazine Moving Toward a Future of Ubiquitous Computing
`
`Moving Toward a Future of Ubiquitous Computing
`Overview: Computing Woven Seamlessly into Everyday Life
`A factory technician, hired to bring an old manufacturing facility up to
`spec, is conducting a site visit. As he walks through the unfamiliar
`production floor, the screen of his personal digital assistant (PDA) lights
`up with manuals and notes from previous technicians about the
`idiosyncrasies of the various machines he passes.
`
`While visiting a dozen key stores across the country, the national sales
`manager of a major retail chain uses her cell phone to take photos at
`each location. At the end of her trip, she presses a key on her notebook
`computer, and the photos appear on a Web page wirelessly transmitted
`from her cell phone.
`
`A graduate student wanders through a university campus. As he passes
`the chemistry building, his PDA screen shows that his favorite professor
`is scheduled to deliver a public presentation in room 405 later that day.
`He adds the item to his calendar.
`
`The technology to enable these scenarios and more is now being
`explored at Intel. We are moving toward a future in which computing will
`be ubiquitous, woven seamlessly into the fabric of everyday life. Intel
`researchers, in collaboration with leading academic and industry
`researchers, are engaged in several projects to explore technologies
`and usage models for everyday uses of computing. In their research,
`they are addressing fundamental issues that must be resolved in order
`to enable "anytime, anywhere" computing, such as how to develop a
`low-cost infrastructure for location-dependent applications, and how to
`ensure the security and privacy of content as it moves between an
`increasing array of devices.
`
`Ubiquitous computing research is helping to further Intel's vision of
`proactive computing. Under this model, computers anticipate what
`people need and, when appropriate, take proactive steps to meet those
`needs, with little or no user interaction.
`
`Article Sections
`
`Overview
`Personal Server:
`Next-Generation Mobile
`Computing
`Precision Location
`Technology
`Place Lab: Low-Cost
`Location Technology
`Recognizing and Predicting
`Human Activity
`Looking Ahead
`Summary
`More Info
`
`In This Issue
`
`Reliability, Availability, and
`Serviceability for the
`Always-on Enterprise
`Intel and Intoto Bring VoIP
`Home
`Grid Computing Looking
`Forward
`Exploring the Next Ten
`Percent
`Moving Toward a Future of
`Ubiquitous Computing
`About
`Home
`
`To make ubiquitous computing a reality will require the collaboration of researchers in a broad range of
`disciplines, within computer science and beyond. Intel's ubiquitous computing research team includes
`experts in hardware design, systems, networking, signal processing, machine learning, human-computer
`interface (HCI), and social sciences.
`
`Personal Server: Next-Generation Mobile Computing
`The Challenge: What if you could carry all of your personal media with you (including applications,
`documents, photos, videos and MP3 files) in a convenient pocket form factor, and have wireless access to
`it when standing in front of a PC, kiosk, or large display, anywhere in the world? That might significantly
`improve your mobile computing experience.
`
`The Solution: Intel researchers are developing a new class of mobile device
`that leverages advances in processing, storage, and communications
`technologies to provide ubiquitous access to personal information and
`applications through the existing fixed infrastructure. The device, called a
`personal server, is a small, lightweight computer with high-density data
`storage capability. It requires no display, so it can be smaller than a typical
`PDA. A wireless interface enables the user to access content stored in the
`device through whatever displays are available in the local environment. For
`example, in the digital home, the personal server could wirelessly stream
`audio and video stored on the device to a PC or digital home TV.
`
`The personal server is primarily a software capability, and it can be
`integrated into any mobile device. Intel researchers have developed and
`successfully demonstrated a prototype personal server that is integrated into
`a Linux*-based cell phone platform, and they continue to refine the
`technology.
`
`Publicly available infrastructure must be capable of interacting with the
`personal server. Toward that end, Intel researchers are developing the
`software infrastructure necessary to support the seamless interaction
`required to make the personal server an attractive mobile solution.
`
`Personal Server prototype
`integrated into a Motorola
`E680* Intel® XScale™/
`Linux-based cell
`
`Potential Impact: The personal server, when integrated into a cell phone (already a "killer application")
`could make mobile computing far more convenient than a laptop, while ensuring the privacy and
`accessibility of data. Local wireless connections will also have higher bandwidth and lower latency than
`metropolitan networks such as GPRS (General Packet Radio Services) and thus will enable large files to be
`transferred quickly and at much lower cost. As this approach to mobile computing is not limited by the
`physical size of the device's display, the personal server can be made very small, but users will still be able
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`Moving Toward a Future of Ubiquitous Computing
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`to work effectively at a remote location using a large, high-quality display. As storage continues to increase
`in density, this model will become even more attractive, and will provide reassurance to users that they will
`always have their documents and media available when they're on the go.
`
`Precision Location Technology
`The Challenge: Global Positioning System (GPS) technology is widely used for location-dependent
`applications such as navigating outdoors and providing emergency (E911) services. However, this
`technology has limitations: GPS receivers do not work indoors or in "urban canyons" where high-rise
`buildings obstruct the line between the GPS satellite and receiver. In addition, there are a number of
`applications that require greater accuracy than a typical GPS receiver can provide, but only require this
`accuracy in a small local region.
`
`The Solution: Intel researchers are developing high-precision location technology that will work indoors as
`well as outdoors. A key objective is to develop technology that is accurate to within one meter.
`
`Researchers have developed a prototype system that consists of WLAN (wireless local area network)
`laptop computers and fixed access points (APs). The laptop communicates with each AP to determine its
`distance from the AP using a Time-Of-Arrival (TOA) method developed by Intel. The laptop also knows the
`location of every AP. The laptop, knowing its distance from any two APs, and knowing their location, can
`triangulate its own position. This position can then be utilized at the laptop or transmitted back to the
`network for infrastructure-based applications.
`
`Potential Impact: When integrated into consumer electronics (CE) devices, high-precision, WLAN-based
`location technology could be an ideal complement to GPS location capabilities. The technology could be
`used in a variety of potential applications, such as navigating indoors and tracking equipment in real time
`(imagine a physician in a hospital who is searching for the nearest defibrillator). The technology maintains
`privacy; users control who has access to their location information.
`
`Place Lab: Low-Cost Location Technology
`The Challenge: For ubiquitous computing to achieve mass adoption, location-enhanced computing must
`be low cost and must work over a wide area, both indoors and outdoors.
`
`The Solution: To address this challenge, Intel Research Seattle has developed Place Lab, a toolkit that
`allows commodity devices to estimate their location based on nearby radio sources such as 802.11 access
`points and GSM cell towers. Place Lab is an open source project and runs on a variety of notebook, PDA
`and cell phone platforms. The toolkit enables notebooks, PDAs and cell phones to locate themselves by
`listening for radio beacons such as 802.11 access points, GSM cell phone towers, and fixed Bluetooth*
`devices that are already installed in large numbers throughout the environment. These beacons all have
`unique or semi-unique IDs, such as MAC (Media Access Control) addresses. Devices that use Place Lab
`can determine their locations privately, without having to reveal their location information to a central
`service.
`
`Potential Impact: By running on commodity devices and utilizing existing infrastructure, Place Lab allows
`devices to easily and inexpensively estimate their locations. Combined with the open source approach,
`Place Lab is encouraging the development and deployment of wide-area location-enhanced applications
`and services. Place Lab is already running campus-wide at both the University of California at San Diego
`(UCSD) and the Georgia Institute of Technology. These installations aim to provide location-based services
`for research and educational networks, and to help researchers understand how such systems are used.
`
`Recognizing and Predicting Human Activity
`The Challenge: To realize Intel's vision of proactive computing, in which devices embedded throughout the
`environment anticipate human needs and sometimes offer proactive assistance, the devices must be able
`to accurately anticipate human activities.
`
`The Solution: Intel Research Seattle, in collaboration with the University of Washington, is developing a
`system that can automatically infer a wide range of everyday human activities (such as cooking pasta,
`taking a pill, or washing dishes) and provide proactive assistance, if needed, to complete an activity. The
`system, called SHARP (System for Human Activity Recognition and Prediction), relies on RFID (radio
`frequency identification) technology and the latest techniques in data mining and machine learning. Here's
`how the system works: While a person performs an activity, data is gathered from sensors affixed to every
`object the person uses. The data is fed into a reasoning engine—a machine learning algorithm that
`analyzes the data, compares it to a large set of activity models, and infers which model is the best match.
`
`How Machine Learning Systems Work
`SHARP is an example of a machine learning system. These systems vary, but all contain three
`components:
`Sensors that gather data about the physical world—in the case of SHARP, RFID tags gather data
`about which objects are being used to perform an activity, and additional sensors are used to
`capture other data, such as motion, temperature or visible light measurements.
`Models—Beliefs or prior knowledge about real-world processes (human activities, in the case of
`SHARP).
`Reasoning Engine—The machine learning algorithm, which analyzes sensor data, compares it to a
`large set of models, infers which model is the closest match for the data, improves the models based
`on observed data, and recommends appropriate actions.
`
`Potential Impact: The main focus of SHARP research is on helping the aging and those with cognitive
`impairment to perform their daily activities, enabling them to continue living at home for as long as possible.
`To that end, researchers have developed a proof-of-concept prototype called the Caregiver's Assistant,
`which uses SHARP technology to automatically detect the activities of an elder without requiring direct
`observation, freeing the caregiver to focus on the quality of care. Another prototype application, the CareNet
`Display, is an interactive, digital picture frame that augments a person's photograph with information about
`her daily life. The Display can be used by family and friends to coordinate an elder's care. There are many
`other potential applications of SHARP technology, from training medical students in performing procedures
`to capturing "best known methods" of performing maintenance in a factory.
`
`Looking Ahead
`Thus far, Intel's ubiquitous computing research has targeted foundational problems, including how to
`enable ubiquitous information access (Personal Server), incorporate location capabilities into technology
`(Precision Location and Place Lab), and automatically infer human activity (SHARP). These research
`projects have already begun to yield results. In the next phase of the agenda, researchers will focus on
`larger societal issues, and on reducing the complexity of technology.
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`Moving Toward a Future of Ubiquitous Computing
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`http://www.intel.com/technology/magazine/research/ubiquitous-computi...
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`Developing Technology for the Greater Good
`In collaboration with leading academic researchers, Intel's ubiquitous computing researchers are focusing
`on larger societal problems for which technology could potentially provide solutions. They are exploring how
`technology can help people to live at home longer as they grow old, how it can support health and wellness,
`and how technology can address challenges in learning disabilities such as autism.
`
`In collaboration with UC Berkeley and the University of Washington, Intel researchers will explore how
`technology can be employed in the developing regions of the world, to increase personal income for the
`disadvantaged, spur economic development, and improve the quality of life. The most basic technology
`needs in these regions are connectivity in rural areas, intermittent networking, low-cost devices, and user
`interfaces. Already, Intel technologists and social scientists are at work in the developing regions of Asia,
`studying how people live, work and play, identifying their computing needs, and testing new technologies.
`
`Researchers have already demonstrated how simple uses of technology can make a big impact in the
`developing world. For example, today in India, rural farmers can go to a local kiosk where there's an
`Internet-connected computer and get information about market conditions or deal directly with a grain buyer
`rather than working through a complicated and archaic system of middlemen. This simple use of technology
`can often double a farmer's income by helping him to sell his grain quickly and avoid spoilage.
`
`Summary
`Today, people's experience of computer technology is, for the most part, time-consuming and frustrating.
`Intel researchers are looking to address the increasing, sometimes overwhelming, complexity that comes
`with digital living and will explore ways to measurably simplify the digital experience.
`
`Much research has yet to be done to determine how to simplify technology. The challenge grows as devices
`become more capable and thus more complex. The complexity increases substantially as users demand
`that their digital devices work together seamlessly. Intel researchers, in collaboration with their colleagues
`in leading universities, are starting to leverage machine learning and new networking and data access
`techniques to address the challenge of making digital living less frustrating and more intuitive.
`
`Contact the Editor
`Tell us what you think about this article.
`
`More Info
`You can find more information about some of the research and technologies mentioned in this article at the
`Intel Web site:
`Ubiquitous Computing at Intel
`Place Lab
`Personal Server
`Precision Location Technology
`Intel Research Seattle
`Exploratory Research at Intel
`
`All information provided related to future Intel products and plans is preliminary and subject to change at any time, without notice.
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