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DC Field | Value | Language |
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dc.contributor.author | Pathania, Ayush | - |
dc.contributor.author | Vyas, Devesh | - |
dc.contributor.author | Goel, Shubham [Guided by] | - |
dc.date.accessioned | 2023-09-08T12:07:15Z | - |
dc.date.available | 2023-09-08T12:07:15Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9896 | - |
dc.description | Enrolment No. 191249, 191248 | en_US |
dc.description.abstract | In urban areas, obstruction is a difficult problem to manage since the number of automobiles continually rises faster than the traffic infrastructure that can sustain them. In the case of fender benders, it gets considerably more scary. Several facets of modern life are affected by this issue, including financial results, traffic accidents, the expansion of nursery outflows, time spent, and health issues. Modern cultures may rely on the flow of traffic the board structure in this particular situation to prevent congestion and its unfavourable effects. In order to improve overall traffic competence and the health of the transportation systems, traffic the board frameworks are composed of a variety of executive and user tools. In addition, to deal with this issue, the traffic executive structure gathers information from a variety of sources, analyses this information to determine risks that could reduce traffic competence, and then offers a variety of forms of assistance to control those risks. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Traffic management | en_US |
dc.subject | Neural network | en_US |
dc.subject | Machine learning | en_US |
dc.title | Dynamic Traffic Management System | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Dynamic Traffic Management System.pdf | 2.54 MB | Adobe PDF | View/Open |
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