High-Level Fusion for Crisis Response Planning

Abstract

Each year, natural and anthropogenic crises disrupt the lives of millions of people. Local, national, and international crisis response systems struggle to cope with urgent needs during and immediately after a crisis. The challenges multiply as population grows, density of urban areas increases, and coastal areas become more vulnerable to rising sea levels. A typical crisis scenario requires coordinating many diverse players, including local, national and international military, other governmental, and non-governmental organizations. Often, no single entity is in charge of the response, making coordination even more difficult. There is an urgent need for better ways to allocate resources, maintain situation awareness, and reallocate resources as the situation changes. Information fusion is vital to effective resource allocation and situation awareness. Some of the greatest inefficiencies stem from the inability to exchange information between systems designed for different purposes and operating under different ownership. Information integration and fusion are too often entirely manual. Greater automation could support more timely, better coordinated responses in situations where time is of the essence. The greatest need is not for low-level fusion of sensor reports to classify and track individual objects, but for high-level fusion to characterize complex situations and support planning of effective responses. This paper describes challenges of high-level fusion for crisis management, proposes a technical framework for addressing high-level fusion, and discusses how effectively addressing HLF challenges can improve efficiency of crisis response. We illustrate our ideas with a case study involving a humanitarian relief operation in a flooding scenario.