Abstract
The fourth industrial era, known as ‘Industry 4.0’ (I4.0), aided and abetted by the digital revolution, has attracted increasing attention among scholars and practitioners in the last decade. The adoption of I4.0 principles in Disaster Risk Management (DRM) research and associated industry practices is particularly notable, although its origins, impacts and potential are not well understood. In response to this knowledge gap, this paper conducts a systematic literature review and bibliometric analysis of the application and contribution of I4.0 in DRM. The systematic literature review identified 144 relevant articles and then employed descriptive and content analysis of a focused set of 70 articles published between 2011 and 2021. The results of this review trace the growing trend for adoption of I4.0 tools and techniques in disaster management, and in parallel their influence in resilient infrastructure and digital construction fields. The results are used to identify six dominant clusters of research activity: big data analytics, Internet of Things, prefabrication and modularization, robotics and cyber-physical systems. The research in each cluster is then mapped to the priorities of the Sendai framework for DRR, highlighting the ways it can support this international agenda. Finally, this paper identifies gaps within the literature and discusses possible future research directions for the combination of I4.0 and DRM.
Highlights
In the last decade, there has been a rapid digital transformation of industrial production systems
I4.0 technology (‘I4 T’), which facilitates the physical processes and information flows in a value chain, can arguably assist organizations to achieve sustainable goals through reduction of lead time, improvement of work environment and quality of products [10]
This paper proposes a systematic literature review of I4 T in disaster science
Summary
There has been a rapid digital transformation of industrial production systems This has led to more intelligent, flexible, integrated and efficient processes [1,2,3]. The combination of I4 T and Lean can be linked to performance improvement, increasing flexibility, productivity and quality, and reducing the delivery time and cost of projects [19,20] In parallel with these developments in I4.0, Construction 4.0 and I4 T, an unexpected connection has become evident to a further field. Ogie et al [23] systematically reviewed the application of machine learning techniques and AI in disaster communication tools Their findings reveal the capacity of AI to predict and monitor multi-hazard early warning systems and information extraction for situational awareness.
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