Technological advancement and innovation are helping to enhance emergency management through improved risk reduction and mitigation and better post-disaster recovery and restoration. The Internet of Things, cyber-physical systems, geo-technologies, cloud and edge computing, and the various forms of big data and machine learning are key drivers behind current digital transformations and will play an increasingly important role in all phases of emergency management. The range of relevant advanced and emerging technologies is enormous. Some are already widespread and largely concerned with the flow and analysis of data emanating from citizens, authorities, and sensors before, during, and after a disaster. Some technologies are uniquely suited to disaster situations, whether it is an existing user base and low bandwidth requirements (e.g., text communications) or the capacity to cover vast and inaccessible areas (e.g., satellite imagery). Advanced technologies deployed in disaster response extend to hardware, such as robots and drones. Integration of diverse technologies is a typical characteristic in disaster planning and mitigation, such as when machine learning is deployed in fields as diverse as robotics or social media analysis.
Wider and impactful adoption of advanced technologies will depend on overcoming a number of challenges, from the design of smart algorithms, methodologies, and applications to vigilance in ensuring domain relevance and stakeholder acceptance and adoption.
This special section of OJ-CS aims to examine the gaps, challenges, and required capacities. We solicit contributions describing state-of-the-art technologies and applications for future disaster management and resilience. The anticipated submissions will be previously unpublished, original contributions, including theoretical and analytic studies, review articles, and experimental works. Topics include, but are not limited to, the following as they relate to disaster response and resilience:
Visit the Author Information page for details on how to submit.
Rajendra Akerkar, Western Norway Research Institute, Norway (rak@vestforsk.no)
André Skupin, San Diego State University, USA (skupin@sdsu.edu)
