Integrated gps and sensor grid for better tsunami early warning using wireless application protocol network

Abstract

The present study covers Bay of Bengal region for tsunami early warning using GPS and sensor grid for which 2004 real time tsunami data from Tamil Nadu coastal region has been used Oceanographic parameters such as conductivity salinity temperature pressure and Dissolved Oxygen were measured at various distance depth latitude and longitude Seismic and GPS data have been integrated along with this real time data before tsunami and after tsunami for analysis Anomalies due to tsunami had been observed in the geochemical parameters In this study we propose a novel down sampling approach based wavelet denoising filter for an integrated Tsunami warning system The Energy based quality measures are proposed to evaluate the quality of wavelet filter As a result of this present research it could be concluded that the type newlineof neural network applied is suitable for the tsunami classification of parameters namely Conductivity Salinity Temperature and Dissolved Oxygen combined with seismic signal energy captured using GPS The computed results from the numerical model were used to train and test the BPN model at various latitude longitude distance from seashore and Depth The proposed Tsunami early warning system checks the signals from the classifier and Real time seismic data Then the alert signal can be communicated to mobile network using servlets through the web browser used as Gate way newline newline