# A Regional Multi-Agent Air Monitoring Platform
## 4 The ACreM Platform
### Air Monitor Agent
Inferences can be made about the occurrence of certain pollution events, the impact of specific pollutants in a region, or even the prediction of potential air quality incidents to which local authorities and citizens should respond. This section introduces the basic ontologies for storing the underlying knowledge for air quality management and explains the concept of knowledge processing in the **ACreM** platform. The Air Pollution Ontology captures structured knowledge about air pollutants, their sources, and their environmental and health impacts. This ontology forms the foundation for understanding and analyzing air quality data, providing a semantic framework for integrating dynamic data from IoT sensors and other real-time inputs. In the ACreM platform, air quality parameters, including pollutant types and regulatory thresholds, are formally structured within the ontology to ensure consistency and accurate reasoning. The ontology defines key pollutants such as PM10, PM2.5, NO2, SO2, CO, and O3 as distinct classes, each associated with attributes specifying their emission sources, health impacts, and chemical properties. Additionally, threshold values are integratedbased on internationally recognized standards, such as WHO and EU air quality guidelines, using properties like hasLimitValue for concentration thresholds and hasDuration for applicable timeframes. This structured representation allows the system to dynamically compare real-time sensor data with regulatory limits, identify anomalies, and support decision-making processes for air quality management in the Plovdiv region. The ontology represents a comprehensive taxonomy of air pollutants, organized hierarchically to reflect their chemical and physical characteristics. The taxonomy includes classes for the following (Figure 14):  
* Particulate Matter (PM)--differentiated into PM10 and PM2.5 based on particle size, with attributes for their sources, effects, and regulatory limits. * Gaseous Pollutants--includes NO2, SO2, CO, and O3, each described in terms of their chemical properties, emission sources, and atmospheric behaviors. For each pollutant class, the ontology includes annotation properties (Figure 15):
* rdfs:comment provides detailed descriptions of the pollutant's characteristics, sources, and health impacts. * dterms:description aligns with the Dublin Core Metadata Initiative's guidelines. It is commonly used to provide concise, descriptive information about ontology elements. Figure 12: Segment of the AM’s Plan Library and reasoning cycle. To describe the standard norms according to the WHO Global Air Quality Guidelines of the World Health Organization, axioms have been created for each pollutant. For example, the axiom defining the maximum values for nitrogen dioxide is presented in Figure 16.  
Figure 14: Air Pollution Ontology taxonomy. Figure 13: Sample agent test session. Figure 10.0 Annotation properties of the Carbon_Monoxide class in the Air Pollution Ontology. The SubClass Of axiom for the Nitrogen_Dioxid class models the regulatory limits for nitrogen dioxide (NO\({}_{2}\)) based on its concentration over two distinct timeframes: annual and daily. These constraints are represented using specific properties that associate the pollutant with its permissible limits and their durations:  
* The annual average concentration of nitrogen dioxide is constrained to a maximum of 10 \(\mathrm{\SIUnitSymbolMicro g}\)/m\({}^{3}\), represented by the property hasLimitValue. This limit is further specified as applying over an \"annual\" duration using the hasDuration property. * The daily average concentration is constrained to a maximum of 25 \(\mathrm{\SIUnitSymbolMicro g}\)/m\({}^{3}\). Similarly, the hasDuration property specifies that this limit applies to a \"daily\" timeframe. * Such axioms are developed for all pollutant classes in the ontology. These axioms enable the ontology to precisely capture and differentiate between the temporal applicability of air quality standards.