Sensors 2013, 13(12), 17292-17321; doi:10.3390/s131217292

Mobile Sensing Systems

1 Grupo de Arquitectura y Concurrencia (GAC), Departamento de Ingeniería Telemática, Universidad de Las Palmas de Gran Canaria, Campus Universitario de Tafira, Las Palmas de Gran Canaria (Gran Canaria) 35017, Spain 2 Integrated Management Coastal Research Institute, Universidad Politécnica de Valencia, C/Paranimf, n° 1, Grao de Gandia 46730, Spain
* Author to whom correspondence should be addressed.
Received: 5 November 2013; in revised form: 2 December 2013 / Accepted: 13 December 2013 / Published: 16 December 2013
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2013)
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Abstract: Rich-sensor smart phones have made possible the recent birth of the mobile sensing research area as part of ubiquitous sensing which integrates other areas such as wireless sensor networks and web sensing. There are several types of mobile sensing: individual, participatory, opportunistic, crowd, social, etc. The object of sensing can be people-centered or environment-centered. The sensing domain can be home, urban, vehicular… Currently there are barriers that limit the social acceptance of mobile sensing systems. Examples of social barriers are privacy concerns, restrictive laws in some countries and the absence of economic incentives that might encourage people to participate in a sensing campaign. Several technical barriers are phone energy savings and the variety of sensors and software for their management. Some existing surveys partially tackle the topic of mobile sensing systems. Published papers theoretically or partially solve the above barriers. We complete the above surveys with new works, review the barriers of mobile sensing systems and propose some ideas for efficiently implementing sensing, fusion, learning, security, privacy and energy saving for any type of mobile sensing system, and propose several realistic research challenges. The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high.
Keywords: individual mobile sensing; crowd sensing; mobile operating systems; mobile cloud; smart phone; sensors; ubiquitous sensing; web sensing

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MDPI and ACS Style

Macias, E.; Suarez, A.; Lloret, J. Mobile Sensing Systems. Sensors 2013, 13, 17292-17321.

AMA Style

Macias E, Suarez A, Lloret J. Mobile Sensing Systems. Sensors. 2013; 13(12):17292-17321.

Chicago/Turabian Style

Macias, Elsa; Suarez, Alvaro; Lloret, Jaime. 2013. "Mobile Sensing Systems." Sensors 13, no. 12: 17292-17321.

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