IEEE Intelligent Systems
Special Issue on AI for Disaster Management and Resilience
Deadline for submission: November 15, 2018
Notification of acceptance: April 30, 2019
This special issue will highlight research initiatives toward the next generation disaster management that leverage AI to strengthen disaster resilience at all levels of society.
There is a growing need for developing new AI techniques that process large-scale crisis data to get the “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, limit economic impact, provide effective disaster relief, and make communities stronger and more resilient.
Topics of interest include:
- harnessing big data from the Web or Social Web to facilitate disaster
and risk management
- emergency/disaster-related data mining and knowledge management methodologies
- 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 response
- 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 (yurulin [at] pitt.edu), University of Pittsburgh, USA
- Carlos Castillo (chato [at] acm.org), Pompeu Fabra University, Spain
- Jie Yin (jie.yin [at] sydney.edu.au), The University of Sydney, Australia
More information:
https://protect-au.mimecast.com/s/vpdmCP7yOZtlmnMKUzyWeI?domain=publicat...