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Prevention of Traffic Through Inculcating and Sharing Information via Vehicular Cloud

Author(s):

Simran Patel , Loknete Gopinathji Munde Institute Of Engineering Education & Research, Nashik; Rameshwari Patil, Loknete Gopinathji Munde Institute Of Engineering Education & Research, Nashik; Varsha Mahale, Loknete Gopinathji Munde Institute Of Engineering Education & Research, Nashik; Pooja Mali, Loknete Gopinathji Munde Institute Of Engineering Education & Research, Nashik

Keywords:

Navi Tweet, social sensors, SVN, traffic images, vehicular clouds, vehicular networks

Abstract

What is the traffic? Traffic is the movement of people and goods from one place to another. The movement typically occurs along a specific pathway that can be called a guideway. With the ever-expanding economy of cars whole the world, traffic congestion is a severe problem that can have a bad impact on the economy, the surroundings, and human sentiment. Now today’s ordinary cars to tomorrow's self-driving cars increases in technology will enable vehicles to be prepared with highly complicated sensing devices, such as cameras. As vehicles achieve the ability to act as mobile sensors that carry useful and important traffic data, people and vehicles are sharing recognize data to increase the driving experience. This paper recapitulate a vehicular cloud service for road route planning, where users which is used this system (Application) collaborate to share traffic images by using their vehicles’ on-board cameras. We present the architecture of a conspire traffic image–sharing system called Social Vehicle Navigation ,which allows user who drive vehicle to report vehicular cloud and then this cloud through share visual traffic data called NaviTweets. A group of NaviTweets is then infiltrate, refined, and compressed into a concise, user-friendly understanding information about the route of interest, called a Traffic Digest. These systematize can provide more pertinent and true information about the on road situation specially related to traffic and can aggregate predictions like estimated materialization, thereby supporting users’ route decision making. That’s why this paper presents the all information from requirement gathering to implementation. all content given in this paper all get implemented and running on the Android smartphone platform, that’s why increase congestion and pollution percentage so that this system By conveying advance adequate notification drivers could make educated decisions that would reduce the traffic congestion, improve traffic invulnerability, and reduce fuel and time

Other Details

Paper ID: IJSRDV5I10884
Published in: Volume : 5, Issue : 1
Publication Date: 01/04/2017
Page(s): 1264-1267

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