- Title
- A shared bus profiling scheme for smart cities based on heterogeneous mobile crowdsourced data
- Creator
- Kong, Xiangjie; Xia, Feng; Li, Jianxin; Hou, Mingliang; Li, Menglin; Xiang, Yong
- Date
- 2020
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/171995
- Identifier
- vital:14432
- Identifier
-
https://doi.org/10.1109/TII.2019.2947063
- Identifier
- ISBN:1551-3203 (ISSN)
- Abstract
- Mobile crowdsourcing (MCS), as an effective and crucial technique of Industrial Internet of Things, is enabling smart city initiatives in the real world. It aims at incorporating the intelligence of dynamic crowds to collect and compute decentralized ubiquitous sensing data that can be used to solve major urbanization problems such as traffic congestion. The shared bus, as a neotype transportation mode, aims at improving the resource utilization rate and maintaining the advantages of convenience and economy. In this article, we provide a scheme to profile shared buses through heterogeneous mobile crowdsourced data (TRProfiling). First, we design an MCS-based shared bus data generation and collection solution to overcome the aforementioned data scarcity issue. Then, we propose a travel profiling to profile resident travel and design a method called multiconstraint evolution algorithm to optimize the routes. Experimental results demonstrate that TRProfiling has an excellent performance in satisfying passengers' travel requirements. © 2005-2012 IEEE.
- Publisher
- IEEE Computer Society
- Relation
- IEEE Transactions on Industrial Informatics Vol. 16, no. 2 (2020), p. 1436-1444
- Rights
- Copyright © 2019 IEEE
- Rights
- This metadata is freely available under a CCO license
- Rights
- Open Access
- Subject
- 0905 Civil Engineering; Industrial Internet of Things (IIoT); mobile crowdsensing; route planning; shared buses; travel profiling (TP)
- Full Text
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