Abstract
As smart vehicles begin to roam the streets, new possibilities will emerge for large-scale data acquisition tasks necessary for proactive smart cities applications. Unlike mobile devices, smart vehicles carry powerful sensors and are highly mobile; they can cover large areas and perform high quality sensing. However due to restricted reward structures and limited bandwidths of cellular and VANETs, not all vehicles can participate equally. Thus, we must find a method for selecting promising participants which can efficiently the required collect sensing information. In this chapter, we present ideas for participant selection under varying conditions from large scale crowdsensing to personalized crowdsensing. We present several algorithms using a common framework.
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Yu, TY., Zhu, X., Maheswaran, M. (2018). Vehicular Crowdsensing for Smart Cities. In: Maheswaran, M., Badidi, E. (eds) Handbook of Smart Cities. Springer, Cham. https://doi.org/10.1007/978-3-319-97271-8_7
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