Disaster Management - overview
Disaster Management is one of the focus areas of the research lab in Australia. Our approach is to take a holistic approach to decision making before, during and after emergencies and disasters. This requires relevant data to be captured, used to analyse the current situation, and be applied in predictive analytics to infer possible outcomes. To complete the cycle our research investigates appropriate visualizations of our predictive analytics for to allow decision makers to take the appropriate actions.
Using this approach, we have provided with the Fire Services Commissioner of Victoria; an information interoperability blueprint followed by high-level reference architecture. These combine to provide timely, tailored and relevant information for the future of emergency management. Currently we are involved in building the support for a mobile application and community resilience portal. These interfaces are to be ready for the upcoming fire season, where much of the data captured by the various fire services in Victoria is provided to better inform the public.
Parallel to these efforts, we are working with the fire services and others applying specialized analytics. Here we have used evacuation simulation to support decisions in investment in infrastructure. Additionally, used live social media analysis for crisis tracking to extend the fire services awareness with the latest communication channels.
For organizations such as the Victoria’s fire services to make use of these advanced analytics, in their strategic and operational decision processes, the models need to integrate with existing processes and systems. This requires a standardized way of composing models from the decision makers point of view, allowing swift inclusion into existing processes and system. Our collaborative work with the University of Melbourne on model composition standards and reference architecture for a supporting platform, also known as the Australian Disaster Management Platform, is developing this first platform.