A novel navigation based decision algorithm to generate tsunami alerts using sensor nodes

Authors

  • Jain N Research Scholar, University School of Information, Communication and Technology, GGSIPU, Delhi, India
  • Virmani D Department of Computer Science, Bhagwan Parshuram Institute of Technology, New Delhi, India

Keywords:

NBDA, Tsunami, navigation, Haversine, Bearing angle, Decision, Prediction

Abstract

This research paper deals with a decision-based prediction system for generating tsunami alerts by analyzing realtime data that tags the sea turtle movement along the interiors of the Indian Ocean. In this paper Navigation based Decision Algorithm: NBDA which uses the Haversine Equations to detect the difference between the angle of the direction of Loggerhead Turtles at different durations of years from 2004 till 2012 is proposed. The dataset used here is provided by the OBIS Seamap-an official organization that maps the distribution of living species in Ocean present on their web portal having Latitude and Longitude values for turtle movement in the interiors of Indian Ocean obtained from underwater sensors. Using NBDA, The historic Tsunami year of 2004 is marked as the alert year on the basis of change in navigation directions of sea turtles in the Indian Ocean from the subsequent year of 2008. Proposed NBDA is validated with available real data which highlights 2004 as Tsunami Year. This Algorithm can further be used to design a prediction system to generate Tsunami Alert well in advance in real time by analyzing abnormal aquatic animal behavior.

References

Thomas B. Sanford Motionally induced electric and magnetic fields in the sea, Journal of Geophysical Research

R. H. Tyler 2005.A simple formula for estimating the magnetic fields generated by tsunami .Geophysical Research Letters, vol. 3,Isuue 9.0020

Joseph L. Kirschvink , April 2000 Earthquake Prediction by Animals: Evolution and Sensory Perception by.Bulletin of the Seismological Society of America, 90, 2, pp. 312–323

https://en.wikipedia.org/wiki/Haversine_formula.

Virmani, D., & Jain, N. (2016, September). Intelligent information retrieval for Tsunami detection using wireless sensor nodes. In Advances in Computing, Communications and Informatics (ICACCI), 2016 International Conference on(pp. 1103-1109). IEEE.4

Jain, N., &Virmani, D. (2017). Feature Classification for Underwater Seismic Prediction Using Wireless Sensor Nodes. In Proceedings of the International MultiConference of Engineers and Computer Scientists (Vol. 1).

Kirschvink, Joseph L. (2000) Earthquake Prediction by Animals: Evolution and Sensory Perception. Bulletin of the Seismological Society of America, 90 (2). pp. 312-323. ISSN 0037-1106.

Can undersea voltage measurements detect tsunamis? 2010..Earth Planets Space, vol.62(3), 353-358..

IR Schultz 2010 Effects of Electromagnetic Fields on Fish and Invertebrates 2013, US Department of Energy under Contract DE-AC05-76RL01830. Wen Shen, Zhihua Wei, Yunyi Li,” Multiple granular analysis of TCM data with applications on hepatitis B”, April 2015.

http://seamap.env.duke.edu/dataset/1014

https://en.wikipedia.org/wiki/Ocean_Biogeographic_Information_System

https://en.wikipedia.org/wiki/Spherical_coordinate_system https://www.siggraph.org/education/materials/HyperGraph/modelingmod_tran/3drota.htm.

Downloads

Published

2024-02-26

How to Cite

Jain, N., & Virmani, D. (2024). A novel navigation based decision algorithm to generate tsunami alerts using sensor nodes. COMPUSOFT: An International Journal of Advanced Computer Technology, 7(12), 2945–2949. Retrieved from https://ijact.in/index.php/j/article/view/465

Issue

Section

Original Research Article