Main restraints curbing a deep integration of Semantic Sensor Networks with complex and articulated architectures, basically residein too elementary allowed discovery capabilities. Several studies agree advanced querying and retrieval mechanisms are needed to truly fulfill the potential of the SSN paradigm. This paper presents a novel SSN framework, supporting a resource discovery grounded on semantic-based matchmaking. Offered contributions are: a backward-compatible extension of Constrained Application Protocol (CoAP) resource discovery; data mining exploitation to detect high-level events from raw data; employment of non-standard inference services for retrieving and ranking resources; adoption of W3C standard SSN-XG ontology to annotate data, events and device features. The effectiveness of the proposed approach is motivated by a case study regarding fire risk prevention and air conditioning control in a university building.
A logic-based CoAP extension for resource discovery in semantic sensor networks / Ruta, Michele; Scioscia, Floriano; Loseto, Giuseppe; Gramegna, Filippo; Pinto, Agnese; Ieva, Saverio; Di Sciascio, Eugenio. - ELETTRONICO. - 904:(2012), pp. 17-32. (Intervento presentato al convegno 5th International Workshop on Semantic Sensor Networks. A workshop of the 11th International Semantic Web Conference 2012 (ISWC 2012) tenutosi a Boston, MA nel November 12, 2012).
A logic-based CoAP extension for resource discovery in semantic sensor networks
Michele Ruta;Floriano Scioscia;Filippo Gramegna;Agnese Pinto;Saverio Ieva;Eugenio Di Sciascio
2012-01-01
Abstract
Main restraints curbing a deep integration of Semantic Sensor Networks with complex and articulated architectures, basically residein too elementary allowed discovery capabilities. Several studies agree advanced querying and retrieval mechanisms are needed to truly fulfill the potential of the SSN paradigm. This paper presents a novel SSN framework, supporting a resource discovery grounded on semantic-based matchmaking. Offered contributions are: a backward-compatible extension of Constrained Application Protocol (CoAP) resource discovery; data mining exploitation to detect high-level events from raw data; employment of non-standard inference services for retrieving and ranking resources; adoption of W3C standard SSN-XG ontology to annotate data, events and device features. The effectiveness of the proposed approach is motivated by a case study regarding fire risk prevention and air conditioning control in a university building.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
