Authors :
Ashna Lakshmanan; Sangeerth S Nambiar; Nasariya Parvin M; Sanya; Nikhil Dharman M K
Volume/Issue :
Volume 8 - 2023, Issue 4 - April
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/3nOWdKP
DOI :
https://doi.org/10.5281/zenodo.7922907
Abstract :
Disasters or hazards have the potential to
cause catastrophic damage and significant socioeconomic
loss. The year 2022 has been recorded as the eighth
consecutive year with 10 or more billion-dollar weather
or climate related disasters. As a result, an AI powered
Disaster Management system is developed. It aims to
strengthen disaster mitigation strategies using AI
technology. It helps in detecting and preparing for the
extreme weather and other hazards, and also to
communicate to people and communities effectively
about the necessary response. AI helps response teams to
understand the hazards or accidents, monitor events in
real time and anticipate specific pitfalls in the face of
impending or on-going disasters. The disasters can either
be predicted with the help of AI technology by training
machine learning models or be detected from live news
feeds. AI is used during different phases of disaster
operation first, vaticination and protuberance; also, to
help communicate what has passed; and in the
monitoring and early discovery of implicit new pitfalls.
Disasters or hazards have the potential to
cause catastrophic damage and significant socioeconomic
loss. The year 2022 has been recorded as the eighth
consecutive year with 10 or more billion-dollar weather
or climate related disasters. As a result, an AI powered
Disaster Management system is developed. It aims to
strengthen disaster mitigation strategies using AI
technology. It helps in detecting and preparing for the
extreme weather and other hazards, and also to
communicate to people and communities effectively
about the necessary response. AI helps response teams to
understand the hazards or accidents, monitor events in
real time and anticipate specific pitfalls in the face of
impending or on-going disasters. The disasters can either
be predicted with the help of AI technology by training
machine learning models or be detected from live news
feeds. AI is used during different phases of disaster
operation first, vaticination and protuberance; also, to
help communicate what has passed; and in the
monitoring and early discovery of implicit new pitfalls.
