Work place: SJCE research centre, Mysore, India

E-mail: tanuja_patgar@yahoo.com


Research Interests: Computer Networks, Network Architecture


Tanuja.P.Patgar received B.E degree in Electronics and Communication from Kuvempu university, Karnataka, India in 1996. In 2010, she received M.E in Control and Instrumentation from University Vishweshraya Collage of Engineering, Bangalore, India. She is currently a research scholar in the department of Electronics and Communication at Sri i Jayachamarajendra College of Engineering, Mysuru, and Karnataka, India under Visvesvaraya Technological University, Belgaum, India.Her research field is Wireless Sensor Network.

Author Articles
A Heterogeneous Access Remote Integrating Surveillance Heuristic Model for a Moving Train in Tunnel

By Tanuja.P.Patgar Shankaraiah

DOI: https://doi.org/10.5815/ijisa.2016.03.07, Pub. Date: 8 Mar. 2016

Many number of real time applications are available for train monitoring using satellite based navigation system with high level of speed and precision. But these systems have faced lot of issues such as multipath loss and line of sight which results in lesser accuracy measurements. When the train is moving in low satellite visible areas such as tunnels, mountains, forest etc, then no position information is available. The service failure in tunnel made big challenge to demonstrate a self supporting innovative platform for navigation of train. This paper is focused on designing a novel approach by integrating Wireless Sensor Network (WSN) and Radio Frequency Identification (RFID) system for continuous monitoring of train moving in tunnel. The wireless tracking controller based on quadratic optimal control theory is considering for analysis. Overall performance of the control design is based on Liapunov approach, where quadratic performance index is directly related to Liapunov functions. By minimizing and maximizing the performance index value corresponding to control inputs will trace the tracking error inaccuracies. As maximizing the performance index, the tracking error produces 0.04% inaccuracy. The data loss is 0.06% when minimizing the performance value. Simulation is carried out using Mat lab.

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