Intelligent Agents Networks Employing Hybrid Reasoning: Application in Air Quality Monitoring and Improvement

This paper presents the design and the development of an agentbased intelligent hybrid system. The system consists of a network of interacting intelligent agents aiming not only towards real-time air pollution monitoring but towards proposing proper corrective actions as well. In this manner, the concentration of air pollutants is managed in a real-time scale and as the system is informed continuously on the situation an iterative process is initiated. Four distinct types of intelligent agents are utilized: Sensor, Evaluation, Decision and Actuator. There are also several types of Decision agents depending on the air pollution factor examined. The whole project has a Hybrid nature, since it utilizes fuzzy logic – fuzzy algebra concepts and also crisp values and a rule based inference mechanism. The system has been tested by the application of actual air pollution data related to four years of measurements in the area of Athens.