Research Papers

Online sensors and wavelet-based filter approach for tsunami case study

[+] Author Affiliations
Manickam Umadevi

Anna University, College of Engineering, Department of Geology, Guindy, Chennai 600 025, India

Ganadipathy Tulsi’s Jain Engineering College, Chittoor-Cuddalore Road, Kaniyambadi, Vellore 632 102, India

Seshachalam Srinivasulu

Anna University, College of Engineering, Department of Geology, Guindy, Chennai 600 025, India

J. Appl. Remote Sens. 7(1), 073517 (Aug 22, 2013). doi:10.1117/1.JRS.7.073517
History: Received March 8, 2013; Accepted July 1, 2013
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Abstract.  The Tsunami classification model with real-time sensors placed at different locations and at different depths is proposed. To exclude the artifact effects in the sensor values, a wavelet-based denoising scheme is integrated in the model. In addition, a downsampling approach has been proposed to achieve maximum flat delay response, and the present results are compared with the Pc McClellan method. Various parameters such as conductivity, salinity, pressure, temperature, and dissolved oxygen are measured and sensed using multisensor grid architecture. Our results show that by sensing the above parameters and subject them online, it is possible to clearly distinguish the pre- and post-tsunami behaviors.

© 2013 Society of Photo-Optical Instrumentation Engineers

Citation

Manickam Umadevi and Seshachalam Srinivasulu
"Online sensors and wavelet-based filter approach for tsunami case study", J. Appl. Remote Sens. 7(1), 073517 (Aug 22, 2013). ; http://dx.doi.org/10.1117/1.JRS.7.073517


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