### A survey on smartphone-based systems for opportunistic user context recognitionA survey on smartphone-based systems for opportunistic user context recognition

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 Author Hoseini-Tabatabaei, Amir ♦ Gluhak, Alexander ♦ Tafazolli, Rahim Source ACM Digital Library Content type Text Publisher Association for Computing Machinery (ACM) File Format PDF Copyright Year ©2013 Language English
 Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science Subject Keyword Pervasive computing ♦ Opportunistic sensing ♦ Smartphone ♦ User context recognition Abstract The ever-growing computation and storage capability of mobile phones have given rise to mobile-centric context recognition systems, which are able to sense and analyze the context of the carrier so as to provide an appropriate level of service. As nonintrusive autonomous sensing and context recognition are desirable characteristics of a personal sensing system; efforts have been made to develop opportunistic sensing techniques on mobile phones. The resulting combination of these approaches has ushered in a new realm of applications, namely opportunistic user context recognition with mobile phones. This article surveys the existing research and approaches towards realization of such systems. In doing so, the typical architecture of a mobile-centric user context recognition system as a sequential process of $\textit{sensing},$ $\textit{preprocessing},$ and context recognition phases is introduced. The main techniques used for the realization of the respective processes during these phases are described, and their strengths and limitations are highlighted. In addition, lessons learned from previous approaches are presented as motivation for future research. Finally, several open challenges are discussed as possible ways to extend the capabilities of current systems and improve their real-world experience. ISSN 03600300 Age Range 18 to 22 years ♦ above 22 year Educational Use Research Education Level UG and PG Learning Resource Type Article Publisher Date 2013-07-03 Publisher Place New York e-ISSN 15577341 Journal ACM Computing Surveys (CSUR) Volume Number 45 Issue Number 3 Page Count 51 Starting Page 1 Ending Page 51

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Source: ACM Digital Library