Open AccessTraffic Flow Calculation using Big Data
Author(s) -
S. Kalaiarasi,
G. Leela,
K. Nikesh,
Ch. Raghava Prasad
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.b2534.129219
Subject(s) - gridlock , big data , computer science , traffic flow (computer networking) , meteorology , computer security , geography , data mining , politics , political science , law
Traffic is one of the primary issues in world. It makes numerous medical issues people on foot and bikers. It is additionally one of the practical setting of a nation. U.S.A. alone squandered almost $160 billion of fuel in year 2014 alone. Mumbai remains at no.1 position in the rundown of most exceedingly awful traffic stream while Delhi taking no.4 position. In this task we use BIGDATA for guaranteeing that the explorers doesn't get struck in the rush hour gridlock. BIGDATA can enable clients to settle on better travel choices, lighten traffic blockage, diminish carbon outflows, and improve traffic activity proficiency. Our goal of traffic stream forecast is to give a superior traffic stream data. Traffic stream forecast has picked up its significance because of fast development in urban areas and increment in rush hour gridlock blockage. Traffic stream forecast intensely relies upon authentic and ongoing traffic information gathered from different sensor sources, including inductive circles, radars, cameras, portable Global Positioning System, publicly supporting, internet based life, and so on. In this paper, we propose a profound learning-based traffic stream forecast technique.