@article{ref1,
title="Intelligent computing hardware for collision avoidance and warning in high speed rail networks",
journal="Journal of ambient intelligence and humanized computing",
year="2020",
author="Immanuel Rajkumar, R. and Sundari, G.",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="One of the very important issue is safety of transport vehicle, particularly in increasing number of trains on the same tracks and collision avoidance warning system. We have successfully developed Linux based hardware, modules and software code for IoT enabled Train Tracking and Collision avoidance warning system. A strong tracking of the vehicle an entire system and their updates of data in database and analysis of the database from multi-angles may reduce the occurrence of an accident even in the critical failure situation. In view of this we have made two types of train tracking system using Linux based robust hardware, which simultaneously monitors the movement of train by two different mechanism and the data collected are instantaneously stored in cloud server. Based on the live data analysis, the signalling of trains to different tracks or halt can be estimated. The estimated computational results will be highly useful in providing collision avoidance alerts. Also, we have developed user interactive GUI screen for onboard train module as well as on various analytics utilizing server module data. This paper strongly recommends a secure & safety process purely depend on tracking of any device simultaneously by two different mechanism. The system developed in the present work is cost effective, hence this system can be added as an additional safety layer to the existing safety systems in the train.<p /> <p>Language: en</p>",
language="en",
issn="1868-5137",
doi="10.1007/s12652-019-01661-z",
url="http://dx.doi.org/10.1007/s12652-019-01661-z"
}