文章基本信息

标题：Video Streaming Analytics for Traffic Monitoring Systems
本地全文：下载
作者：Muhammad Arslan Amin ; Muhammad Kashif Hanif ; Muhammad Umer Sarwar 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2018
卷号：9
期号：11
DOI：10.14569/IJACSA.2018.091192
出版社：Science and Information Society (SAI)
摘要：It is considered a difficult task to have check on traffic during rush hours. Traditional applications are man-ual, costly, time consuming, and the human factors involved. Large scale data is being generated from different resources. Advancement in technology make it possible to store, process, analyze, and communicate with large scale of video data. The manual applications are wiped out with the invention of automatic applications. Automatic video streaming analytics applications helps to reduce computational resources. The reason is cost efficient and accurate predictions while monitoring traffic on roads. This study reviews previously developed application of video streaming analytics for traffic monitoring systems using Hadoop that are able to efficiently analyze video streams.
关键词：Video streaming analytics; Traffic monitoring sys-tem; Video streams; Hadoop; GPU; CNN; Deep learning