Title: An evolutionary service solution for spatio-temporal data analysis in highway domain

Authors: Jie Zhou; Weilong Ding

Addresses: School of Information Science and Technology, North China University of Technology, No. 5 Jinyuanzhuang Road, Beijing, 100144, China; Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, No. 5 Jinyuanzhuang Road, Beijing, 100144, China ' School of Information Science and Technology, North China University of Technology, No. 5 Jinyuanzhuang Road, Beijing, 100144, China; Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, No. 5 Jinyuanzhuang Road, Beijing, 100144, China

Abstract: In highway domain, many routine analyses are required on business spatio-temporal data to monitor and control the traffic situation in time. Such analytics as big data applications through traditional ways remain inherent challenges due to the inflexibility of the holistic procedure, the variety of the computational jobs and the diversity of the customised visualisation. In this paper, we propose a service solution in a specific highway domain for business technicians to build their own data analytical applications conveniently and rapidly. On massive toll data through respective services, our solution provides evolutionary capacity to load, process and reveal spatio-temporal data for building comprehensive data analysis. In a practical project, our work proves the feasibility and advantages by exhaustive case studies.

Keywords: highway; data analysis; evolutionary solution; spatio-temporal data.

DOI: 10.1504/IJIITC.2019.104735

International Journal of Intelligent Internet of Things Computing, 2019 Vol.1 No.1, pp.43 - 52

Received: 06 Jul 2019
Accepted: 05 Aug 2019
Published online: 29 Jan 2020 *