Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107213
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dc.contributorDepartment of Electrical and Electronic Engineeringen_US
dc.contributorResearch Institute for Sustainable Urban Developmenten_US
dc.creatorWang, Yen_US
dc.creatorHo, IWHen_US
dc.date.accessioned2024-06-13T01:04:37Z-
dc.date.available2024-06-13T01:04:37Z-
dc.identifier.isbn978-1-5386-3531-5 (Electronic)en_US
dc.identifier.isbn978-1-5386-3529-2 (Print)en_US
dc.identifier.urihttp://hdl.handle.net/10397/107213-
dc.description2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 08-13 October 2017, Montreal, QC, Canadaen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Y. Wang and I. W. -H. Ho, "On-road feature detection and fountain-coded data dissemination in vehicular ad-hoc networks," 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Montreal, QC, Canada, 2017 is available at https://doi.org/10.1109/PIMRC.2017.8292307.en_US
dc.subjectFountain codeen_US
dc.subjectOn-road feature detectionen_US
dc.subjectVANETen_US
dc.titleOn-road feature detection and fountain-coded data dissemination in vehicular ad-hoc networksen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/PIMRC.2017.8292307en_US
dcterms.abstractWithin the smart city framework, information dissemination in vehicular ad-hoc networks (VANET) is attracting considerable interest in both the research community and industry. Efficient data dissemination has long been a problem in ad-hoc networks. In VANET, the problem is even more challenging given the high mobility of vehicles, high density of buildings, and intermittent network connectivity. Realistic modelling of the mobility patterns of vehicles (instead of random models like Random Waypoint or Manhattan Models in previous works) is important for accurate performance evaluation. In this paper, the transmission of on-road feature detection data (images or videos) with fountain code in VANET is studied. Specifically, we propose a robust license plate detection module and applied fountain coding in the application layer to largely reduce the average transmission delay of multi-media data. The proposed system is rigorously evaluated under a semi-realistic simulation of an inter-bus communication network in the Mong Kok urban district in Hong Kong with the consideration of real-world traffic parameters, such as different traffic density at different hours of a day and building obstacles. Specifically, we find that fountain coded data dissemination shows better performance boost in more realistic signal propagation model in urban areas. In practice, the proposed system can be applied to bus lane occupancy control. For example, when a vehicle illegally occupies the bus lane, buses nearby can help recognize the vehicle and transmit the detected results through the VANET to patrol cars for the enforcement.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn Proceedings of 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 08-13 October 2017, Montreal, QC, Canadaen_US
dcterms.issued2017-
dc.identifier.scopus2-s2.0-85045253834-
dc.relation.conferenceIEEE International Symposium on Personal, Indoor and Mobile Radio Communications [PIMRC]en_US
dc.description.validate202404 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEIE-0583-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS9613716-
dc.description.oaCategoryGreen (AAM)en_US
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