An agent-based intelligent environmental monitoring system

Fairly rapid environmental changes call for continuous surveillance and on-line decision making. There are two main areas where IT technologies can be valuable. In this paper we present a multi-agent system for monitoring and assessing air-quality attributes, which uses data coming from ameteorological station. A community of software agents is assigned to monitor and validate measurements coming from several sensors, to assess air-quality, and, finally, to fire alarms to appropriate recipients, when needed. Data mining techniques have been used for adding data-driven, customized intelligence into agents. The architecture of the developed system, its domain ontology, and typical agent interactions are presented. Finally, the deployment of a real-world test case is demonstrated. Introduction Environmental information systems (EIS) is a generic term that describes the class of systems that perform one or more of the following tasks: environmental monitoring, data storage and access, disaster description and response, environmental reporting, planning and simulation, modeling and decision making. As the requirements for accurate and timely information in these systems are increasing, the need for incorporating advanced, intelligent features in EIS is revealed. In this context, advances in the information technology (IT) sector are promising to satisfy these requirements. Enviromatics (an abbreviation of the term “environmental informatics”) is the research initiative examining the application of information technology in environmental research, monitoring, assessment, management, and policy (IFIP, 1999). The deployment of modern, intelligent systems for monitoring and evaluating meteorological data series and assessing air quality is only one of several enviromatics applications. Our focus in this work is to take advantage of powerful tools for software development and demonstrate their application for monitoring air-quality attributes. Air Quality Operational Centers (AQOC) have been established worldwide in areas with potential air pollution problems. Their responsibility is to monitor critical atmospheric variables and publish regularly their analysis results. Currently, real-time decisions are made by human experts, whereas mathematical models are used for The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at www.em eraldinsight.com/res earchregister www.em eraldinsight .com/1477-7835. htm The authors would like to express their gratitude to the Agent Academy Consortium for their valuable help. Special thanks go to the IDI-EIKON team for their efforts within Agent Academy project to deploy the O3RTAA system and to CEAM for the provision of the ONDA dataset. The Agent Academy project is partially funded by the European Commission under the IST programme (IST-2000-31050). MEQ 15,3