Abstract: 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.

Muhammad Arslan Amin, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Muhammad Kamran Sarwar, Ayesha Kanwal and Muhammad Azeem, “Video Streaming Analytics for Traffic Monitoring Systems” International Journal of Advanced Computer Science and Applications(IJACSA), 9(11), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091192

@article{Amin2018,
title = {Video Streaming Analytics for Traffic Monitoring Systems},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2018.091192},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091192},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {11},
author = {Muhammad Arslan Amin and Muhammad Kashif Hanif and Muhammad Umer Sarwar and Muhammad Kamran Sarwar and Ayesha Kanwal and Muhammad Azeem},
}