KNOWLEDGE-ORIENTED SENSOR WEB FOR DISASTER MANAGEMENT: FROM SENSING TO DECISION MAKING

The shocking consequences of disasters and natural hazards have already proven the urgency and necessity of disaster management and emergency response. Timely and updated information reflecting the newest disaster situation is extremely important for effective emergency response and efficient actions. While significant research has been demonstrated on the current research of disaster management, the problem of how to offer timely, even real time data and information to disaster managers and emergency responders is still far from solution. The emergence of sensor web does provide a promising way to solve this problem. However, most of current sensor web researches are mainly focused on data collection, sensing and real time monitoring of the disaster targeted, little research has been done on the process of decision making during disaster management and emergency responses. Especially, for improving the strategies of disaster management, in the context of sensor web, the inherent relationship between sensing and decision making really needs to be explored deeply. For an operationally effective disaster management, its sensing, monitoring, detection and decision making must be integrated seamlessly. In order to tackle with the limitations above, this paper presents a conceptual framework of knowledge-oriented sensor web for disaster management. Through the proposed architecture, disaster sensing and disaster decision making can be integrated closely by using multi-agent system and rule-based expert system. Thus, the existing sensor web can be potentially extended and greatly enhanced from mere disaster sensing and monitoring to