On Feasibility of Crowdsourced Mobile Sensing for Smarter City Life

Aihara, Kenro; Bin, Piao; Imura, Hajime; Takasu, Atsuhiro; Tanaka, Yuzuru

doi:10.1007/978-3-319-39862-4_36

Cited by 6 publications

(1 citation statement)

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“…proposed a smart phone‐based driving recorder. The recorder records a video of the front environment while driving and provides a series of upload interfaces for users to report weather, traffic and other conditions to collect and aggregate information in the above fields (Aihara et al , ).…”

Section: Review Of Previous Work and Analysismentioning

confidence: 99%

Social weather: A review of crowdsourcing‐assisted meteorological knowledge services through social cyberspace

Zhu

Zhang

et al. 2019

Geoscience Data Journal

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Crowdsourcing has significantly motivated the development of meteorological services. Starting from the beginning of 2010s and highly motivating after 2014, crowdsourcing-driven meteorological services have evolved from a single collection and observation of data to the systematic acquisition, analysis and application of these data. In this review, by focusing on papers and databases that have combined crowdsourcing methods to promote or implement meteorological knowledge services, we analysed the relevant literature in three dimensions: data collection, information analysis and meteorological knowledge applications. First, we selected the potential data sources for crowdsourcing and discussed the characteristics of the collected data in four dimensions: consciousness, objectiveness, mobility and multidisciplinary.Second, based on the purpose of these studies and the extent of utilizing data as well as knowledge, we categorize the crowdsourcing-based meteorological analysis into three levels: relationship discovery, knowledge generalization and systemized service. Third, according to the application scenario, we discussed the applications that have already been put into use, and we suggest current challenges and future research directions. These previous studies show that the use of crowdsourcing in social space can expand the coverage as well as enhance the performance of meteorological 62 | ZHU et al.

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Section: Review Of Previous Work and Analysismentioning

confidence: 99%