Synopsis
Advances in electronic location technology and the coming of age of mobile computing have opened the door for location-aware applications to permeate all aspects of everyday life. Location is at the core of a large number of high-value applications ranging from the life-and-death context of emergency response to serendipitous social meet-ups. For example, the market for GPS products and services alone is expected to grow to US$200 billion by 2015. Unfortunately, there is no single location technology that is good for every situation and exhibits high accuracy, low cost, and universal coverage. In fact, high accuracy and good coverage seldom coexist, and when they do, it comes at an extreme cost. Instead, the modern localization landscape is a kaleidoscope of location systems based on a multitude of different technologies including satellite, mobile telephony, 802.11, ultrasound, and infrared among others. This lecture introduces researchers and developers to the most popular technologies and systems for location estimation and the challenges and opportunities that accompany their use. For each technology, we discuss the history of its development, the various systems that are based on it, and their trade-offs and their effects on cost and performance. We also describe technology-independent algorithms that are commonly used to smooth streams of location estimates and improve the accuracy of object tracking. Finally, we provide an overview of the wide variety of application domains where location plays a key role, and discuss opportunities and new technologies on the horizon. Table of Contents: Introduction / The Global Positioning System / Infrared and Ultrasonic Systems / Location Esimation with 802.11 / Cellular-Based Systems / Other Approaches / Improving Localization Accuracy / Location-Based Applications and Services / Challenges and Opportunities / References
About the Author
Anthony LaMarca is the associate director of Intel Research Seattle. His research interests include location technologies, ubiquitous computing, distributed systems, and human-centered design. His former project, Place Lab, enabled wide-scale device positioning using radio beacons. He is currently leading the Everyday Sensing and Perception project with the goal of building high-coverage, high-accuracy techniques for inferring common contexts. He has a BS in computer science from the University of California at Berkeley and an MS and PhD in computer science from the University of Washington. Eyal de Lara is an associate professor in the Department of Computer Science at the University of Toronto. His research interest lies in the area of mobile and pervasive computing, and in the past he has led projects in the fields of content customization for mobile devices, accurate localization in indoor environments, and secure spontaneous communication. He has a BS in computer science from theInstituto Technologico y de Estudios Superiores de Monterrey (ITESM), Mexico, and an MS and PhD in electrical and computer engineering from Rice University.
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