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Scalable Traffic Video Analytics using Hadoop MapReduce

Authors:
Vaithilingam Anantha Natarajan
Subbaiyan Jothilakshmi
Venkat N Gudivada

Keywords: Traffic Video Analytics; Road Accidents.

Abstract:
Road traffic video analytics aims at using a number of techniques to achieve better traffic and road safety, control congestion and provide immediate care for accident victims. In this paper, we propose a near real-time traffic analytics system which can automatically detect road accidents from live video streams. The system alerts nearby hospitals and highway rescue teams when accidents occur. It also detects road congestion and broadcasts alternative route information to relevant commuters. We have implemented the system using Apache Hadoop. Analysis results are stored in Hive, which is a data warehouse built on top of Hadoop. This data includes overall traffic speed, traffic volume, and individual vehicle speed. Hive provides data summarization, query, and analysis. We have deployed and tested the system on a cluster computer.

Pages: 11 to 15

Copyright: Copyright (c) IARIA, 2015

Publication date: April 19, 2015

Published in: conference

ISSN: 2519-8386

ISBN: 978-1-61208-445-9

Location: Barcelona, Spain

Dates: from April 19, 2015 to April 24, 2016