Deciphering technological advancements for efficient disaster management and community resilience

Abstract

Disaster management is typically conducted to prevent and respond to disasters. Technological innovations certainly contribute to both, but it remains unclear how. With the rapid technological advancements over the past decade, a comprehensive understanding of the latest technological advancements and their integrated applications in detecting and mitigating the destructive impacts of disasters has emerged as a critical concern for more effective disaster management. This systematic literature review focuses on three primary phases: pre-disaster, during the disaster, and post-disaster. It examines advanced monitoring technologies and sophisticated data analyses to facilitate immediate interventions. The comprehensive disaster management framework proposed in this study evaluates various regions based on their historical disaster occurrences and assigns a specific risk index to each region, thereby enabling the assessment of the preparedness of disaster response systems according to each region's potential. Furthermore, Big Data obtained through surveillance systems and the Internet of Things (IoT) communication sensors are processed using artificial intelligence (AI) and machine learning (ML) algorithms, enhancing computational awareness and sensitivity to changes in detection and notification patterns. By accurately delineating the input and output pathways, this framework aims to optimize supply chain management during emergencies, thereby contributing to achieving the United Nations (UN) Sustainable Development Goals (SDGs) by 2030. Through a systematic review of 135 journal articles, this study highlights the latest technological advancements for expedited disaster detection and response and proposes a structured framework to optimize disaster management and enhance societal resilience.