The Intelligent Mechanism for Data Collection and Data Mining in the Vehicular Ad-Hoc Networks (VANETs) Based on Big-Data-Driven

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dc.contributor.authorMahmoudian, Mahshad
dc.contributor.authorZanjani, S. Mohammadali
dc.contributor.authorShahinzadeh, Hossein
dc.contributor.authorKabalci, Yasin
dc.contributor.authorKabalci, Ersan
dc.contributor.authorEbrahimi, Farshad
dc.date.accessioned2024-11-07T13:23:59Z
dc.date.available2024-11-07T13:23:59Z
dc.date.issued2023
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description5th IEEE Global Power, Energy and Communication Conference (GPECOM) -- JUN 14-16, 2023 -- Nevsehir, TURKEY
dc.description.abstractBig data technology has attracted the main attention of researchers in almost all sciences. The Vehicular Ad-Hoc Network (VANET) enables information exchange between vehicles, other devices, and public networks, playing a key role in road safety and intelligent transportation systems. With the proliferation of connected vehicles and the development of novel mobile apps and technologies, VANETs will generate vast quantities of data that need to be transmitted quickly and reliably. Furthermore, analyzing a wide range of data types can enhance VANET's performance. By utilizing big data technologies, the Ad-Hoc Vehicular Network can extract valuable insights from a large amount of operational data, thus improving traffic management processes, including planning, engineering, and operations. VANETs have access to big data during real-time operations. This paper presents VANET features as big data features in the literature, followed by a discussion of methods for utilizing big data to study VANET features. Combining automotive ad networks and big data facilitates the easy management of a large number of driving factors, as the data mining process in big data enables quick decision-making based on statistical analysis or graphical representations of data.
dc.description.sponsorshipIEEE,Nevsehir Haci Bektas Veli Univ,IEEE Ind Applicat Soc,IEEE Ind Elect Soc,IEEE Power Elect Soc,IEEE Power & Energy Soc,Univ Nova Lisboa,Univ Palermo
dc.identifier.doi10.1109/GPECOM58364.2023.10175794
dc.identifier.endpage500
dc.identifier.isbn979-8-3503-0198-4
dc.identifier.issn2832-7667
dc.identifier.scopus2-s2.0-85166474931
dc.identifier.scopusqualityN/A
dc.identifier.startpage495
dc.identifier.urihttps://doi.org/10.1109/GPECOM58364.2023.10175794
dc.identifier.urihttps://hdl.handle.net/11480/13847
dc.identifier.wosWOS:001043011400084
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2023 5th Global Power, Energy and Communication Conference, Gpecom
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectVehicular ad-hoc networks
dc.subjectVehicles
dc.subjectBig Data
dc.subjectHadoop
dc.subjectMap Reduce
dc.subjectSecurity
dc.subjectSensors
dc.subjectTraffic Management
dc.subjectSmart Cities
dc.subjectInternet of Things (IoT)
dc.subjectMobile ad-hoc networks
dc.titleThe Intelligent Mechanism for Data Collection and Data Mining in the Vehicular Ad-Hoc Networks (VANETs) Based on Big-Data-Driven
dc.typeConference Object

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