An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective

Article


Munawar, Hafiz Suliman, Mojtahedi, Mohammad, Hammad, Ahmed W. A., Ostwald, Michael J. and Waller, S. Travis. 2022. "An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective." Buildings. 12 (1), pp. 1-23. https://doi.org/10.3390/buildings12010080
Article Title

An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective

ERA Journal ID210216
Article CategoryArticle
AuthorsMunawar, Hafiz Suliman, Mojtahedi, Mohammad, Hammad, Ahmed W. A., Ostwald, Michael J. and Waller, S. Travis
Journal TitleBuildings
Journal Citation12 (1), pp. 1-23
Article Number80
Number of Pages23
Year2022
PublisherMDPI AG
Place of PublicationSwitzerland
ISSN2075-5309
Digital Object Identifier (DOI)https://doi.org/10.3390/buildings12010080
Web Address (URL)https://www.mdpi.com/2075-5309/12/1/80
Abstract

The Hawkesbury-Nepean Valley, Australia’s longest coastal catchment, is spanned by a river system of more than 470 km, that runs from Goulburn to Broken Bay, covering a total area of over 2.2 million hectares. This region has remained prone to flood events, with considerable mortalities, economic impacts and infrastructural losses occurring quite regularly. The topography, naturally variable climatic conditions and the ‘bathtub’ effect in the region are responsible for the frequent flood events. In response, the Government at the national/federal, state and local level has focused on the design of efficient flood risk management strategies with appropriate evacuation plans for vulnerable communities from hospitals, schools, childcare and aged care facilities during a flood event. Despite these overarching plans, specialized response and evacuation plans for aged care facilities are critical to reducing the loss incurred by flood events in the region. This is the focus of this present paper, which reviews the history of flood events and responses to them, before examining the utilization of artificial intelligence (AI) techniques during flood events to overcome the flood risks. An early flood warning system, based on AI/Machine Learning (ML) strategy is being suggested for a timely decision, enhanced disaster prediction, assessment and response necessary to overcome the flood risks associated with aged care facilities within the Hawkesbury-Nepean region. A framework entailing AI/ML methods for identifying the safest route to the destination using UAV and path planning has been proposed for timely disaster response and evacuation of the residents of aged care facilities.

KeywordsArtificial intelligence; Early warning system; Flood event; Hawkesbury-Nepean valley; Image processing; Machine learning
FunderCentral Drug Research Institute
Byline AffiliationsUniversity of New South Wales
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