Locomotive surveillance is the most active research topic and still faces big technical challenges in railway safety control system. An end-to-end locomotive tracking and continuous monitoring system is necessary for safety measures in satellite visible and low satellite visible environment. These smart systems aim to updates the information on location, exact detection, speed limitation and also rail track information. This paper contributes to develop an intelligent tracking and monitoring system based on Internet of Things (IoT) platform using Differential Global Positioning System (DGPS) for improved tracking accuracy of locomotive in both environments. Interacting Multiple Model (IMM) tracking algorithm based on Di-filter model is proposed for analysis that make it easy to pinpoint the location and its status of the locomotive.
| Published in | International Journal of Sensors and Sensor Networks (Volume 5, Issue 3) |
| DOI | 10.11648/j.ijssn.20170503.11 |
| Page(s) | 34-42 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2017. Published by Science Publishing Group |
DGPS, Di-filter, IMM Algorithm, Model Matching, Tracking Surveillance Model
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APA Style
Tanuja Parameshwar Patgar, Shankaraiah. (2017). Trajectory Tracking of locomotive Using IMM-Based Robust Hybrid Control Algorithm. International Journal of Sensors and Sensor Networks, 5(3), 34-42. https://doi.org/10.11648/j.ijssn.20170503.11
ACS Style
Tanuja Parameshwar Patgar; Shankaraiah. Trajectory Tracking of locomotive Using IMM-Based Robust Hybrid Control Algorithm. Int. J. Sens. Sens. Netw. 2017, 5(3), 34-42. doi: 10.11648/j.ijssn.20170503.11
AMA Style
Tanuja Parameshwar Patgar, Shankaraiah. Trajectory Tracking of locomotive Using IMM-Based Robust Hybrid Control Algorithm. Int J Sens Sens Netw. 2017;5(3):34-42. doi: 10.11648/j.ijssn.20170503.11
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Download@article{10.11648/j.ijssn.20170503.11,
author = {Tanuja Parameshwar Patgar and Shankaraiah},
title = {Trajectory Tracking of locomotive Using IMM-Based Robust Hybrid Control Algorithm},
journal = {International Journal of Sensors and Sensor Networks},
volume = {5},
number = {3},
pages = {34-42},
doi = {10.11648/j.ijssn.20170503.11},
url = {https://doi.org/10.11648/j.ijssn.20170503.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20170503.11},
abstract = {Locomotive surveillance is the most active research topic and still faces big technical challenges in railway safety control system. An end-to-end locomotive tracking and continuous monitoring system is necessary for safety measures in satellite visible and low satellite visible environment. These smart systems aim to updates the information on location, exact detection, speed limitation and also rail track information. This paper contributes to develop an intelligent tracking and monitoring system based on Internet of Things (IoT) platform using Differential Global Positioning System (DGPS) for improved tracking accuracy of locomotive in both environments. Interacting Multiple Model (IMM) tracking algorithm based on Di-filter model is proposed for analysis that make it easy to pinpoint the location and its status of the locomotive.},
year = {2017}
}
TY - JOUR T1 - Trajectory Tracking of locomotive Using IMM-Based Robust Hybrid Control Algorithm AU - Tanuja Parameshwar Patgar AU - Shankaraiah Y1 - 2017/08/10 PY - 2017 N1 - https://doi.org/10.11648/j.ijssn.20170503.11 DO - 10.11648/j.ijssn.20170503.11 T2 - International Journal of Sensors and Sensor Networks JF - International Journal of Sensors and Sensor Networks JO - International Journal of Sensors and Sensor Networks SP - 34 EP - 42 PB - Science Publishing Group SN - 2329-1788 UR - https://doi.org/10.11648/j.ijssn.20170503.11 AB - Locomotive surveillance is the most active research topic and still faces big technical challenges in railway safety control system. An end-to-end locomotive tracking and continuous monitoring system is necessary for safety measures in satellite visible and low satellite visible environment. These smart systems aim to updates the information on location, exact detection, speed limitation and also rail track information. This paper contributes to develop an intelligent tracking and monitoring system based on Internet of Things (IoT) platform using Differential Global Positioning System (DGPS) for improved tracking accuracy of locomotive in both environments. Interacting Multiple Model (IMM) tracking algorithm based on Di-filter model is proposed for analysis that make it easy to pinpoint the location and its status of the locomotive. VL - 5 IS - 3 ER -
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