A Regional Multi-Agent Air Monitoring Platform

Stanimir Stoyanov (), Emil Doychev, Asya Stoyanova-Doycheva, Veneta Tabakova-Komsalova (), Ivan Stoyanov and Iliya Nedelchev
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Stanimir Stoyanov: Department of Computer Systems, University of Plovdiv “Paisii Hilendarski”, 4000 Plovdiv, Bulgaria
Emil Doychev: Department of Computer Systems, University of Plovdiv “Paisii Hilendarski”, 4000 Plovdiv, Bulgaria
Asya Stoyanova-Doycheva: Department of Computer Systems, University of Plovdiv “Paisii Hilendarski”, 4000 Plovdiv, Bulgaria
Veneta Tabakova-Komsalova: Department of Computer Systems, University of Plovdiv “Paisii Hilendarski”, 4000 Plovdiv, Bulgaria
Ivan Stoyanov: Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Iliya Nedelchev: Department of Computer Systems, University of Plovdiv “Paisii Hilendarski”, 4000 Plovdiv, Bulgaria

Future Internet, 2025, vol. 17, issue 3, 1-28

Abstract: Plovdiv faces significant air pollution challenges due to geographic, climatic, and industrial factors, making accurate air quality assessment critical. This study presents a hybrid multi-agent platform that integrates symbolic and sub-symbolic artificial intelligence to improve the reliability of air quality monitoring. The platform features a BDI agent, developed using JaCaMo, for processing real-time sensor measurements and a ReAct agent, implemented with LangChain, to incorporate external data sources and perform advanced analytics. By combining these AI approaches, the platform enhances data integration, detects anomalies, and resolves discrepancies between conflicting air quality reports. Furthermore, its scalable and adaptable architecture lays the foundation for future advancements in environmental monitoring. This research represents the first stage in developing an AI-powered system that supports more objective and data-driven decision-making for air quality management in Plovdiv.

Keywords: air monitoring; intelligent agents; BDI agents; ReAct agents; ontologies (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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