Accurately estimating time of arrival of non-destructive waves of earthquakes will help develop a robust early warning system and give 30 seconds to 2 minutes lead time depending on the distance of epicentre location from the monitoring site or plant till the destructive surface waves hit the ground.

Researchers at IIT Madras have developed a new approach for accurate detection of earthquakes. This lead time, though appearing small, is sufficient to take critical precautions such as shutting down nuclear reactors, transportation such as metro and stop elevators, among numerous other measures that can save countless lives.

The research was undertaken by Kanchan Aggarwal under the guidance of Arun K Tangirala, Department of Chemical Engineering, IIT Madras.

The findings of the research were published in the peer-reviewed open access scientific journal PLOS ONE, says a release from IIT Madras.

Diverse predictive model

Tangirala said that the proposed framework is not necessarily limited to the detection of seismic events but is generic and can be used for fault detection and isolation in other domains as well.

The framework can incorporate any predictive models, including the Machine Learning and Deep Learning models, which will reduce the human intervention in the detection.

Tangirala is an expert in time-series analysis, multi-scale analysis of signals, system identification and estimation theory, among other areas. The research was partially funded by Board of Research in Nuclear Sciences, an advisory body of the Department of Atomic Energy.

Kanchan Aggarwal says that information of ‘P-wave’ arrival is crucial in determining other source parameters of the event such as magnitude, depth and epicentre location.

Therefore, a solution to the ‘P-wave’ detection problem that is robust, accurate and precise is essential in order to estimate the event details correctly and to reduce the damage caused by the earthquake or other triggered events.

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