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2018 | OriginalPaper | Chapter

Mobile Crowdsourced Sensors Selection for Journey Services

Authors : Ahmed Ben Said, Abdelkarim Erradi, Azadeh Gharia Neiat, Athman Bouguettaya

Published in: Service-Oriented Computing

Publisher: Springer International Publishing

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Abstract

We propose a mobile crowdsourced sensors selection approach to improve the journey planning service especially in areas where no wireless or vehicular sensors are available. We develop a location estimation model of journey services based on an unsupervised learning model to select and cluster the right mobile crowdsourced sensors that are accurately mapped to the right journey service. In our model, the mobile crowdsourced sensors trajectories are clustered based on common features such as speed and direction. Experimental results demonstrate that the proposed framework is efficient in selecting the right crowdsourced sensors.

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Title: Mobile Crowdsourced Sensors Selection for Journey Services
Authors: Ahmed Ben Said
Abdelkarim Erradi
Azadeh Gharia Neiat
Athman Bouguettaya
Publisher: Springer International Publishing
Book: Service-Oriented Computing
Print ISBN: 978-3-030-03595-2

Electronic ISBN: 978-3-030-03596-9

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-03596-9_33

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