Recognizing user context via wearable sensors

Clarkson, Brian; Mase, Kenji; Pentland, Alex

doi:10.1109/iswc.2000.888467

Cited by 95 publications

(64 citation statements)

References 5 publications

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“…There are also some related work in context awareness studies [18], [19], [20]. In [19] the authors propose to use light intensity to distinguish rooms.…”

Section: Related Workmentioning

confidence: 99%

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Distinguishing locations across perimeters using wireless link measurements

Zhang

Kasera

Patwari

et al. 2011

2011 Proceedings IEEE INFOCOM

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Abstract-Perimeter distinction in a wireless network is the ability to distinguish locations belonging to different perimeters. It is complementary to existing localization techniques. A drawback of the localization method is that when a transmitter is at the edge of an area, an algorithm with isotropic error will estimate its location in the wrong area at least half of the time. In contrast, perimeter distinction classifies the location as being in one area or the adjacent regardless of the transmitter position within the area. In this paper, we use the naturally different wireless fading conditions to accurately distinguish locations across perimeters. We examine the use of two types of wireless measurements: received signal strength (RSS) and wireless link signature (WLS), and propose multiple methods to retain good distinction rates even when the receiver faces power manipulation by malicious transmitters. Using extensive measurements of indoor and outdoor perimeters, we find that WLS outperforms RSS in various fading conditions. Even without using signal power WLS can achieve accurate perimeter distinction up to 80%. When we train our perimeter distinction method with multiple measurements within the same perimeter, we show that we are able to improve the accuracy of perimeter distinction, up to 98%.

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“…There are also some related work in context awareness studies [18], [19], [20]. In [19] the authors propose to use light intensity to distinguish rooms.…”

Section: Related Workmentioning

confidence: 99%

“…In [19] the authors propose to use light intensity to distinguish rooms. In [20] a wearable camera and microphone are utilized for recognizing an individual's situation. A recent work in ambience fingerprinting [18] made further advancement in this area.…”

Section: Related Workmentioning

confidence: 99%

Distinguishing locations across perimeters using wireless link measurements

Zhang

Kasera

Patwari

et al. 2011

2011 Proceedings IEEE INFOCOM

View full text Add to dashboard Cite

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“…Others have shown the value of sensors in identifying a person's context [7,15], especially the determination of speech as a significant factor [17].…”

Section: Sensors and Classificationmentioning

confidence: 99%

WatchMe: Communication and Awareness Between Members of a Closely-Knit Group

Marmasse

Schmandt

Spectre

2004

UbiComp 2004: Ubiquitous Computing

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Abstract.WatchMe is a personal communicator with context awareness in a wristwatch form; it is meant to keep intimate friends and family always connected via awareness cues and text, voice instant message, or synchronous voice connectivity. Sensors worn with the watch track location (via GPS), acceleration, and speech activity; this is classified and conveyed to the other party, where it appears in iconic form on the watch face. When a remote person with whom this information is shared examines it, their face appears on the watch of the person being checked on. The working prototype was used as the focus of interviews to gauge the desirability of such a device.WatchMe is a watch-based personal communicator that draws upon features of both mobile telephony and context-aware ubiquitous computing and integrates them in a user interface that is novel to both these domains. WatchMe extracts information from sensors to provide awareness and availability information to one's closest friends. It supports multiple modes of verbal communication (text messaging, voice messaging, and synchronous voice communication) enabling the recipients of the awareness information to choose the best communication modality. Photographs serve as emotional references to our loved ones, appearing on the watch when one of them is thinking of us. MotivationEveryone has a small group of people with whom they are emotionally close, a set of people who are very important in their lives. These are typically family members and/or intimate friends; people from our "inner circle" whom we call insiders. Nothing can replace the richness of face-to-face communication with these people; however, with our ever mobile and hectic lives, that is not always possible. Our aim is to use mobile communication ubiquitous computing to enable these people to keep in contact with each other. We would like to increase and facilitate communication, in a variety of modalities, among these small sets of intimate people. It is our hypothesis that people would want communication with this very select group of dear people

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“…The recognition includes location of the users. On the other hand, in research fields of wearable mobile computing, most approaches have focused on user-centric recognition mechanism; they specifically examine activity recognition by using sensors worn by the users, such as wristwatch-type accelerometers (Van Laerhoven et al, 2008;Clarkson et al, 2000). Hence, context-aware systems that use both wearable body sensors and environmental sensors have been few.…”

Section: Introductionmentioning

confidence: 99%