Geospatial Data Quality Self-Assuring Model for Disaster Management System

The objective of this paper is to propose a geospatial data quality (G-DQ) self assuring model using an intelligent multiagent (IMA) technique, which is capable to monitor network status, evaluate G-DQ, generate assuring strategies, and apply it to the disaster management system. To do this, we have employed the IMA algorithm concept based on the advanced artificial intelligence for developing information security models and agent-based evaluation of G-DQ as well as assuring strategy. Our approach differs from others in that, it is able to analyze G-DQ in quantitative manner, it can generate and apply assuring strategies automatically, and it supports a coherent design concept for G-DQ self-assuring system. Simulation results show that the proposed approach increases the efficiency and results in quality information acquisition.