Abstract
This paper presents the design and the development of an agent-based 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.
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Iliadis, L.S., Papaleonidas, A. (2009). Intelligent Agents Networks Employing Hybrid Reasoning: Application in Air Quality Monitoring and Improvement. In: Palmer-Brown, D., Draganova, C., Pimenidis, E., Mouratidis, H. (eds) Engineering Applications of Neural Networks. EANN 2009. Communications in Computer and Information Science, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03969-0_1
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DOI: https://doi.org/10.1007/978-3-642-03969-0_1
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