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dc.contributor.authorHewei, Guan
dc.contributor.authorSadiq, Ali Safaa
dc.contributor.authorTahir, Mohammed Adam
dc.date.accessioned2021-03-08T15:59:14Z
dc.date.available2021-03-08T15:59:14Z
dc.date.issued2022-01-01
dc.identifier.citationHewei G., Sadiq A.S., Tahir M.A. (2022) Fuzzy-Logic Approach for Traffic Light Control Based on IoT Technology. In: Balas V.E., Semwal V.B., Khandare A. (eds) Intelligent Computing and Networking. Lecture Notes in Networks and Systems, vol 301, pp. 75-85. Springer, Singapore. https://doi.org/10.1007/978-981-16-4863-2_7en
dc.identifier.isbn9789811648625
dc.identifier.issn2367-3370en
dc.identifier.doi10.1007/978-981-16-4863-2_7
dc.identifier.urihttp://hdl.handle.net/2436/623968
dc.descriptionThis is an accepted manuscript of a book chapter published by Springer in Lecture Notes in Networks and Systems on 01/01/2022. The accepted version of the publication may differ from the final published version.en
dc.description.abstractTraffic congestion is an extremely common phenomenal issue, it occurs in many cities around the world, especially in those cities with high car ownership. Traffic congestion not only causes air pollution and fuel wastage, but it also leads to an increased commuting time and reduces the work time availability. Due to these reasons, traffic congestion needs to be controlled and reduced. The traffic light is the most widely adopted method to control traffic, however, most traffic lights in use are designed based on the predefined interval, which cannot cope with traffic volume change very well. Therefore, Internet of Things (IoT) based traffic lights or adaptive traffic lights are developed in the recent years as a complement of the traditional traffic lights. The adaptive traffic light can be built based on monitoring current traffic situation or using Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication. In this paper, a new design of adaptive traffic light is proposed, this traffic light system is based on fuzzy logic and it introduces volunteer IoT agent mechanism, which introduces more accurate results.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherSpringeren
dc.relation.ispartofIntelligent Computing and Networking
dc.relation.urlhttps://link.springer.com/chapter/10.1007/978-981-16-4863-2_7en
dc.sourceIntelligent Computing and Networking
dc.subjectinternet of thingsen
dc.subjecttraffic controlen
dc.subjectfuzzy logicen
dc.titleFuzzy-logic approach for traffic light control based on IoT technologyen
dc.typeConference contributionen
dc.date.updated2021-03-04T17:33:56Z
dc.title.bookIntelligent Computing and Networkingen
dc.title.seriesLecture Notes in Networks and Systems
dc.conference.nameInternational Conference on Intelligent Computing and Networking
dc.conference.locationThakur College of Engineering and Technology, Mumbai, India
pubs.finish-date2021-02-27
pubs.start-date2021-02-26
dc.date.accepted2021-02-05
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW08032021ASen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2023-01-01en
dc.source.booktitleIntelligent Computing and Networking
dc.source.volume301
dc.source.beginpage75
dc.source.endpage85
refterms.dateFCD2021-03-08T15:57:24Z
refterms.versionFCDAM


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