In recent years, there have been an increasing number of large-scale crises, such as natural disasters and pandemics or armed attacks that have had major impacts on individual lives and infrastructure. Rapid onset disasters, often difficult to prepare for and respond to, make disaster management a challenging task. To carry out good management and subsequently to make the right decisions, accurate information gathering and processing techniques are needed. There are various schemes for acquiring information such as crowdsourcing as well as social media platforms that enable all citizens to provide texts, images, and videos. Data collected is often massive, heterogeneous, and unreliable, and requires processing methods and technologies such as cloud computing, natural language processing, data mining, spatial database, to understand the impact of and response to disaster events in a timely fashion.

The aim of this special section is to bring together academics and practitioners to learn about and share the latest research developments on the utilization of computing for disaster management.
Topics
• Crowdsourcing & disaster management
• Big data analytics & disaster management
• Cloud computing & disaster management
• Context-aware computing & disaster management
• Internet of things & disaster management
• Smart city & disaster management
• Pervasive computing & disaster management
• Social network analysis & disaster management
• Natural language processing & disaster management
• COVID-19 issues management & computing
• Mining and analyzing public perceptions towards disaster events
• Extracting the disaster impacts by novel computing techniques
Submission Guidelines:
New papers, or extended versions of papers presented at related conferences, are welcome. Submissions must not be currently under review for publication elsewhere. Conference papers may be submitted only if they are substantially extended (more than 50%), and must be referenced. All submitted papers will be peer-reviewed using the normal standards of CAEE, and accepted based on quality, originality, novelty, and relevance to the theme of the special section.
Before submission, authors should carefully read the Guide for Authors available at
https://www.elsevier.com/journals/computers-and-electrical-engineering/0045-7906/guide-for-authors
Authors should submit their papers through the journal's web submission tool at https://www.editorialmanager.com/compeleceng/default.aspx by selecting “SI-cdm” under the “Issues” tab.
For additional questions, contact the Guest Editor Dr Hamed Vahdat-Nejad vahdatnejad@birjand.ac.ir