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dc.contributor.authorKhan, Zaheer
dc.contributor.authorAnjum, Ashiq
dc.contributor.authorTahir, Muhammad Atif
dc.contributor.authorSoomro, Kamran Ahmed
dc.date.accessioned2016-06-19T11:22:03Zen
dc.date.available2016-06-19T11:22:03Zen
dc.date.issued2015-02-18en
dc.identifier.citationKhan, Z., Anjum, A., Tahir, M., Soomro, K. (2015) 'Towards cloud based big data analytics for smart future cities', Journal of Cloud Computing, 4 (2)en
dc.identifier.issn2192-113Xen
dc.identifier.doi10.1186/s13677-015-0026-8en
dc.identifier.urihttp://hdl.handle.net/10545/613658en
dc.description.abstractA large amount of land-use, environment, socio-economic, energy and transport data is generated in cities. An integrated perspective of managing and analysing such big data can answer a number of science, policy, planning, governance and business questions and support decision making in enabling a smarter environment. This paper presents a theoretical and experimental perspective on the smart cities focused big data management and analysis by proposing a cloud-based analytics service. A prototype has been designed and developed to demonstrate the effectiveness of the analytics service for big data analysis. The prototype has been implemented using Hadoop and Spark and the results are compared. The service analyses the Bristol Open data by identifying correlations between selected urban environment indicators. Experiments are performed using Hadoop and Spark and results are presented in this paper. The data pertaining to quality of life mainly crime and safety & economy and employment was analysed from the data catalogue to measure the indicators spread over years to assess positive and negative trends.
dc.language.isoenen
dc.publisherSpringeren
dc.relation.urlhttp://www.journalofcloudcomputing.com/content/4/1/2en
dc.rightsArchived with thanks to Journal of Cloud Computingen
dc.subjectSmart cityen
dc.subjectData mining and analyticsen
dc.subjectBig dataen
dc.subjectCloud computingen
dc.titleTowards cloud based big data analytics for smart future citiesen
dc.typeArticleen
dc.contributor.departmentUniversity of Derby, UKen
dc.identifier.journalJournal of Cloud Computingen
refterms.dateFOA2019-02-28T14:27:38Z
html.description.abstractA large amount of land-use, environment, socio-economic, energy and transport data is generated in cities. An integrated perspective of managing and analysing such big data can answer a number of science, policy, planning, governance and business questions and support decision making in enabling a smarter environment. This paper presents a theoretical and experimental perspective on the smart cities focused big data management and analysis by proposing a cloud-based analytics service. A prototype has been designed and developed to demonstrate the effectiveness of the analytics service for big data analysis. The prototype has been implemented using Hadoop and Spark and the results are compared. The service analyses the Bristol Open data by identifying correlations between selected urban environment indicators. Experiments are performed using Hadoop and Spark and results are presented in this paper. The data pertaining to quality of life mainly crime and safety & economy and employment was analysed from the data catalogue to measure the indicators spread over years to assess positive and negative trends.


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