Artificial Intelligence Based Early Warning System for Coastal Disasters

Abstract

Disaster indicates a serious disruption or deviation from the norm that generally occurs for a short period of time and affects the community and society as a whole by way of widespread harm or damage to humans, wildlife, environment, infrastructure and economy. It requires a response that encompasses multidimensional processes in order to mitigate, respond to and recover from its consequences. Disaster that impact the coastal areas is the focus of this chapter. Coastal areas are one of the most sensitive and altered ecosystems world-wide, as they are subject to many disasters and risks including high winds resulting in cyclones and underwater earthquakes initiating strong tidal waves or tsunamis. These disasters are responsible for the loss of lives and/or infrastructural damages in coastal areas. To address this entails the designing of early warning systems that disseminate relevant information effectively and efficiently, as alarms or warnings, to communities at risk during or before such disasters so that timely and adequate steps can be taken to minimize the loss and damages associated with such disasters. In this chapter, an attempt has been made to design an early warning system that uses artificial intelligence to predict the horizontal in-city flooding caused by underwater earthquakes. For experimental purposes, the tsunami dataset would be considered by the proposed early warning system.