MobSens: Making Smart Phones Smarter

Kanjo, Eiman; Bacon, Jean; Roberts, Debbie; Landshoff, P. V.

doi:10.1109/mprv.2009.79

Cited by 75 publications

(52 citation statements)

References 9 publications

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“…In this section we discuss sensors that can be used for sensing the surroundings of a user, such as a camera, magnetometer and microphone. Exploiting their capabilities for sensing environmental state, some researchers have utilised a network of mobile phones as a sensor network for environmental monitoring purposes [Kanjo et al, 2009].…”

Section: Ambient Sensorsmentioning

confidence: 99%

“…Many studies have already exploited the more powerful computational capability of the backend server for further analyzing the data (e.g. [Miluzzo et al, 2008], [Azizyan et al, 2009], [Kanjo et al, 2009], [Gaonkar et al, 2008]). Finally, in order to control and minimize the power consumption of the sensing applications, a judicious selection of the different power saving functions based upon application requirements, residual battery power, and a phone's current energy consumption profile is required.…”

Section: Comparison Of Different Approachesmentioning

confidence: 99%

“…Bluetooth, HTTP+3G, HTTP+ Wi-Fi); the battery level of the device, the energy cost of the connections along with the available data rate and connection coverage are the parameters needed to determine the connection of the choice. Some other suggestions are methods such as letting the user switch off the screen [Kanjo et al, 2009], selecting a proper sensor based upon the power demands and the required accuracy (e.g. [Gaonkar et al, 2008]), changing the sampling rate [Miluzzo et al, 2008], adapting the communication type (e.g.…”

Section: Comparison Of Different Approachesmentioning

confidence: 99%

“…[Gaonkar et al, 2008]), changing the sampling rate [Miluzzo et al, 2008], adapting the communication type (e.g. Bluetooth) to the user's activity [Crk et al, 2009] and offload part of the data processing from the phone onto a backend server [Kanjo et al, 2009] to help to reduce the power consumption. The proper application of such methods leads to developing a power aware duty cycle for both sensing and uploading while the application responsiveness is not affected.…”

Section: Comparison Of Different Approachesmentioning

confidence: 99%

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

2013

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The ever growing computation and storage capability of mobile phones has 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. Particularly, as nonintrusive autonomous sensing and context recognition are one of the most desirable characteristics of a personal sensing system; commendable 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 sensing, pre-processing and context recognition phases are introduced. The main techniques used for the realization of the respective processes during these phases are described, highlighting strengths and limitations of those. 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.

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Section: Ambient Sensorsmentioning

confidence: 99%

Section: Comparison Of Different Approachesmentioning

confidence: 99%

Section: Comparison Of Different Approachesmentioning

confidence: 99%

Section: Comparison Of Different Approachesmentioning

confidence: 99%

See 2 more Smart Citations