Design of intelligent acquisition system for moving object trajectory data under cloud computing

In order to study the intelligent collection system of moving object trajectory data under cloud computing, information useful to passengers and taxi drivers is collected from massive trajectory data. This paper uses cloud computing technology, through clustering algorithm and density-based DBSCAN a...

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Autores principales:	Zhang Yang, Asthana Abhinav, Asthana Sudeep, Khanna Shaweta, Mihai Ioan-Cosmin
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	cloud computing clustering algorithm taxi data collection dbscan algorithm Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/5ce7f0468f454293bb677c776fe34e51
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id	oai:doaj.org-article:5ce7f0468f454293bb677c776fe34e51
record_format	dspace
spelling	oai:doaj.org-article:5ce7f0468f454293bb677c776fe34e512021-12-05T14:10:51ZDesign of intelligent acquisition system for moving object trajectory data under cloud computing2191-026X10.1515/jisys-2020-0152https://doaj.org/article/5ce7f0468f454293bb677c776fe34e512021-06-01T00:00:00Zhttps://doi.org/10.1515/jisys-2020-0152https://doaj.org/toc/2191-026XIn order to study the intelligent collection system of moving object trajectory data under cloud computing, information useful to passengers and taxi drivers is collected from massive trajectory data. This paper uses cloud computing technology, through clustering algorithm and density-based DBSCAN algorithm combined with Map Reduce programming model and design trajectory clustering algorithm. The results show that based on the 8-day data of 15,000 taxis in Shenzhen, the characteristic time period is determined. The passenger hot spot area is obtained by clustering the passenger load points in each time period, which verifies the feasibility of the passenger load point recommendation application based on trajectory clustering. Therefore, in the absence of holidays, the number of passenger hotspots tends to be stable. It is reliable to perform cluster analysis. The recommended application has been demonstrated through experiments, and the implementation results show the rationality of the recommended application design and the feasibility of practice.Zhang YangAsthana AbhinavAsthana SudeepKhanna ShawetaMihai Ioan-CosminDe Gruyterarticlecloud computingclustering algorithmtaxi data collectiondbscan algorithmScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 763-773 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	cloud computing clustering algorithm taxi data collection dbscan algorithm Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	cloud computing clustering algorithm taxi data collection dbscan algorithm Science Q Electronic computers. Computer science QA75.5-76.95 Zhang Yang Asthana Abhinav Asthana Sudeep Khanna Shaweta Mihai Ioan-Cosmin Design of intelligent acquisition system for moving object trajectory data under cloud computing
description	In order to study the intelligent collection system of moving object trajectory data under cloud computing, information useful to passengers and taxi drivers is collected from massive trajectory data. This paper uses cloud computing technology, through clustering algorithm and density-based DBSCAN algorithm combined with Map Reduce programming model and design trajectory clustering algorithm. The results show that based on the 8-day data of 15,000 taxis in Shenzhen, the characteristic time period is determined. The passenger hot spot area is obtained by clustering the passenger load points in each time period, which verifies the feasibility of the passenger load point recommendation application based on trajectory clustering. Therefore, in the absence of holidays, the number of passenger hotspots tends to be stable. It is reliable to perform cluster analysis. The recommended application has been demonstrated through experiments, and the implementation results show the rationality of the recommended application design and the feasibility of practice.
format	article
author	Zhang Yang Asthana Abhinav Asthana Sudeep Khanna Shaweta Mihai Ioan-Cosmin
author_facet	Zhang Yang Asthana Abhinav Asthana Sudeep Khanna Shaweta Mihai Ioan-Cosmin
author_sort	Zhang Yang
title	Design of intelligent acquisition system for moving object trajectory data under cloud computing
title_short	Design of intelligent acquisition system for moving object trajectory data under cloud computing
title_full	Design of intelligent acquisition system for moving object trajectory data under cloud computing
title_fullStr	Design of intelligent acquisition system for moving object trajectory data under cloud computing
title_full_unstemmed	Design of intelligent acquisition system for moving object trajectory data under cloud computing
title_sort	design of intelligent acquisition system for moving object trajectory data under cloud computing
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/5ce7f0468f454293bb677c776fe34e51
work_keys_str_mv	AT zhangyang designofintelligentacquisitionsystemformovingobjecttrajectorydataundercloudcomputing AT asthanaabhinav designofintelligentacquisitionsystemformovingobjecttrajectorydataundercloudcomputing AT asthanasudeep designofintelligentacquisitionsystemformovingobjecttrajectorydataundercloudcomputing AT khannashaweta designofintelligentacquisitionsystemformovingobjecttrajectorydataundercloudcomputing AT mihaiioancosmin designofintelligentacquisitionsystemformovingobjecttrajectorydataundercloudcomputing
_version_	1718371668997439488

Design of intelligent acquisition system for moving object trajectory data under cloud computing

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