Mobile crowdsourced sensors selection for journey services
| Author | Ben Said, Ahmed |
| Author | Erradi, Abdelkarim |
| Author | Gharia Neiat, Azadeh |
| Author | Bouguettaya, Athman |
| Available date | 2023-04-10T09:10:03Z |
| Publication Date | 2018 |
| Publication Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Resource | Scopus |
| 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. Springer Nature Switzerland AG 2018. |
| Sponsor | Acknowledgment. This research was made possible by NPRP 9-224-1-049 grant from the Qatar National Research Fund (a member of The Qatar Foundation) and DP160100149 and LE180100158 grants from Australian Research Council. The statements made herein are solely the responsibility of the authors. |
| Language | en |
| Publisher | Springer Verlag |
| Subject | Crowdsourcing IoT Sensors selection Spatiotemporal data Travel planning service Unsupervised learning |
| Type | Conference Paper |
| Pagination | 463-477 |
| Volume Number | 11236 LNCS |
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