SensOrchestra: Collaborative Sensing for Symbolic Location Recognition
| Autor: | Senaka Buthpitiya, Feng-Tso Sun, Martin L. Griss, Heng-Tze Cheng |
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| Rok vydání: | 2012 |
| Předmět: |
FOS: Computer and information sciences
Multimedia Computer science Bandwidth (signal processing) Ambient noise level Word error rate Response time Energy consumption computer.software_genre Activity recognition 80309 Software Engineering Phone Human–computer interaction Context awareness Computer Engineering computer |
| Zdroj: | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783642293351 MobiCASE |
| DOI: | 10.1007/978-3-642-29336-8_11 |
| Popis: | "Symbolic location of a user, like a store name in a mall, is essential for context-based mobile advertising. Existing fingerprint- based localization using only a single phone is susceptible to noise, and has a major limitation in that the phone has to be held in the hand at all times. In this paper, we present SensOrchestra, a col- laborative sensing framework for symbolic location recognition that groups nearby phones to recognize ambient sounds and images of a location collaboratively. We investigated audio and image features, and designed a classifier fusion model to integrate estimates from diff erent phones. We also evaluated the energy consumption, band- width, and response time of the system. Experimental results show that SensOrchestra achieved 87.7% recognition accuracy, which reduces the error rate of single-phone approach by 2X, and eliminates the limitations on how users carry their phones. We believe general location or activity recognition systems can all benefifit from this collaborative framework." |
| Databáze: | OpenAIRE |
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