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*Call for PapersIEEE Intelligent SystemsSpecial Issue on AI for Disaster
Management and Resilience*

Submission: November 15, 2018

Notification of decision: February 15, 2019

Final acceptance notification: April 30, 2019

In recent years, there have been an increasing number of large-scale
crises, such as natural disasters or armed attacks, that have had major
effect on individual lives and infrastructure, and have caused the
devastation to communities. During these mass emergencies, victims,
responders, and volunteers increasingly use social media and mobile devices
to provide real-time situation updates, i.e., reports on damage, or request
and offer help. This has generated vast volumes of crisis data in different
forms and from different sources. There are a number of challenges
associated with the near-real-time processing of vast volumes of
information in a way that makes sense for people directly affected, for
volunteer organizations, and for official emergency response agencies.
There is a growing need for developing new AI techniques that process
large-scale crisis data to gain a "big picture" of an emergency, detect and
predict how a disaster could develop, analyze the impact of disasters and
the effect of negative externalities in a cyber-physical society, and
assist in disaster response and resource allocation. These AI techniques
can allow better preparation for emergency situations, help save lives and
reduce loss, limit economic impact, provide effective disaster relief, and
make communities stronger and more resilient.

This special issue is to call for research initiatives toward the next
generation disaster management that leverage AI to strengthen disaster
resilience at all levels of society in the new age of mass emergencies. Topics
of interest include (but are not limited to):

* harnessing big data from the Web or Social Web to facilitate disaster and
risk management

* emergency- or disaster-related data mining and knowledge management

* extracting actionable insights from crisis data to support decision making

* integrating community-provided data with data from official sources

* digital volunteering and all forms of citizen participation in disaster

* analyzing and/or establishing trust in local and global communities

* understanding and/or designing socio-technical systems in mass emergencies

* building resilience to disasters through the Internet of Things and
ubiquitous intelligence

* successful applications of disaster management and response systems

* fairness, accountability, and transparency of AI systems for
emergency/disaster response

Guest Editors

Yu-Ru Lin ([log in to unmask]), University of Pittsburgh, USA

Carlos Castillo ([log in to unmask]), Pompeu Fabra University, Spain

Jie Yin ([log in to unmask]), The University of Sydney, Australia

* For general information about the special issue, contact Yu-Ru Lin
(include the keyword "Intelligent Systems AI & Disaster" in the subject
line) at [log in to unmask]

* For general author guidelines, see

* For submission details, see [log in to unmask]

* To submit an article, go to (log
in and then select "Special Issue on AI & Disaster").

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