Special issue on AI for Disaster Management and Resilience
IEEE Intelligent System is hosting a special issue on AI for Disaster Management and Resilience, which we are co-editing with Yu-Ru Lin from University of Pittsburgh, USA and Jie Yin from University of Sydney, Australia.
- Submission: November 15, 2018
- Notification of acceptance: 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 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, 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.
