Title: Research on quick extraction method for integrated information of intelligent transportation system scheduling based on internet of things

Authors: Xiangjun Tian

Addresses: Puyang Institute of Technology, Henan University, Puyang, Henan 457000, China

Abstract: In order to improve the remote monitoring capability for the integrated information of intelligent transportation system (ITS) scheduling, a quick extraction method for integrated information of ITS scheduling based on tracking and recognition of the distributed internet of things (IoT) sensor information fusion is proposed. Using the comprehensive information of IoT node scheduling, the adaptive distributed optimisation positioning design of the IoT node is extracted. Combining pattern recognition technology for scheduling information processing; the integrated information mining and scheduling feature extraction is implemented by quantitative fusion tracking method, which realises the automatic mining of intelligent transportation system integration information. The simulation results show that the proposed method has better automatic clustering for extracting integrated information of ITS scheduling, as well as faster extraction speed and higher matching ability. It also has a good application value in the integrated information of ITS scheduling.

Keywords: internet of things; IoT; intelligent transportation system; ITS; scheduling; integrated information; extraction; clustering.

DOI: 10.1504/IJIPT.2020.107979

International Journal of Internet Protocol Technology, 2020 Vol.13 No.3, pp.144 - 150

Received: 21 Nov 2018
Accepted: 23 Mar 2019

Published online: 01 Jul 2020 *

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