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A shared bus profiling scheme for smart cities based on heterogeneous mobile crowdsourced data

journal contribution
posted on 2020-02-01, 00:00 authored by X Kong, F Xia, Jianxin LiJianxin Li, M Hou, M Li, Yong XiangYong Xiang
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.

History

Journal

IEEE Transactions on Industrial Informatics

Volume

16

Issue

2

Pagination

1436 - 1444

Publisher

Institute of Electrical and Electronics Engineers

Location

Piscataway, N.J.

ISSN

1551-3203

eISSN

1941-0050

Language

eng

Publication classification

C1 Refereed article in a scholarly journal