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A semantic IoT early warning system for natural environment crisis management

: Posland, S.; Middleton, S.E.; Chaves, Fernando; Tao, R.; Necmioglu, O.; Bügel, Ulrich

Volltext urn:nbn:de:0011-n-3452913 (9.7 MByte PDF)
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Erstellt am: 26.6.2015

IEEE transactions on emerging topics in computing 3 (2015), Nr.2, S.246-257
ISSN: 2168-6750
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IOSB ()
early warning system; internet of things; crisis management; semantic web; scalable; time-critical; resilience

An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model. We use lightweight semantics for metadata to enhance rich sensor data acquisition. We use heavyweight semantics for top level W3C Web Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a deployed EWS infrastructure.