Abstract
In an emergency situation failure to respond in a timely manner poses a significant threat. Data needed for timely response comes from various sources and sensors. These individual data streams when viewed in isolation may appear irrelevant, however, when analyzed collectively may identify potential threats. An effective and timely response also requires collaboration and information sharing among various government agencies at all levels. This collaboration information sharing among agencies can be achieved using service-oriented architecture, where agencies provide access to their information resources and applications using Web services. Each of these agencies has its own rules/policies for providing their services. It is therefore, important to verify the correctness of the emergency response processes with respect to the rules/policies of the collaborating agencies involved in the execution of such processes. In this paper we present an approach which addresses the above challenges. Specifically, the proposed approach: a) employs multi stream data mining for identification of potential threats and disambiguation of alarms; b) provides a methodology for the discovery and selection of relevant Web services; c) employs a timed automata based verification methodology for determining the correctness of emergency response processes with respect to the rules of the collaborating agencies. We provide an overview of the initial implementation of the proposed approach.