Abstract
There is a critical need to develop a mobile-based emergency response system (MERS) to help reduce risks in emergency situations. Existing systems only provide short message service (SMS) notifications, and the decision support is weak, especially in man-made disaster situations. This paper presents a MERS ontology-supported case-based reasoning (OS-CBR) method, with implementation, to support emergency decision makers to effectively respond to emergencies. The advantages of the OS-CBR approach is that it builds a case retrieving process, which provides a more convenient system for decision support based on knowledge from, and solutions provided for past disaster events. The OS-CBR approach includes a set of algorithms that have been successfully implemented in four components: data acquisition; ontology; knowledge base; and reasoning; as a sub-system of the MERS framework. A set of experiments and case studies validated the OS-CBR approach and application, and demonstrate its efficiency.
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