Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2013
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dc.contributor.authorNirmani, A-
dc.contributor.authorThilakarathne, L-
dc.contributor.authorWickramasinghe, A-
dc.contributor.authorSenanayake, S-
dc.contributor.authorHaddela, P. S-
dc.date.accessioned2022-04-22T05:59:03Z-
dc.date.available2022-04-22T05:59:03Z-
dc.date.issued2018-12-05-
dc.identifier.citationA. Nirmani, L. Thilakarathne, A. Wickramasinghe, S. Senanayake and P. S. Haddela, "Google Map and Camera Based Fuzzified Adaptive Networked Traffic Light Handling Model," 2018 3rd International Conference on Information Technology Research (ICITR), 2018, pp. 1-6, doi: 10.1109/ICITR.2018.8736158.en_US
dc.identifier.isbn978-1-7281-1470-5-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2013-
dc.description.abstractRising traffic congestion has turned into a certain issue as the number of vehicles on roads are increasing. This research study was conducted to develop `Google Map and Camera Based Fuzzified Adaptive Networked Traffic Light Handling Model'. The main road with six major junctions was selected as the target route for the project. During this study, we were able to plan a limit and control traffic congestion utilizing two neural networks which process together to provide an efficient, productive and optimized solution based on real-time situations. Real-time video streams and Google Map traffic layer were used as primary input sources to the system. The Main algorithm was used to reduce traffic at a specific point whereas secondary algorithm was used to produce optimum decisions for the overall network. As a further advancement, REST endpoint was implemented to get the best route considering all the accessible data. With the aid of the previously mentioned techniques, an optimal traffic management model was developed.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2018 3rd International Conference on Information Technology Research (ICITR);Pages 1-6-
dc.subjectGoogle Mapen_US
dc.subjectCamera Baseden_US
dc.subjectHandling Modelen_US
dc.subjectTraffic Lighten_US
dc.subjectAdaptive Networkeden_US
dc.subjectCamera Based Fuzzifieden_US
dc.titleGoogle map and camera based fuzzified adaptive networked traffic light handling modelen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICITR.2018.8736158en_US
Appears in Collections:Department of Information Technology-Scopes
Research Papers - IEEE
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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