Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams

Matthias T. Frank

ISBN 10: 3731510766 / ISBN 13: 9783731510765

Edité par Karlsruher Institut Für Technologie Jul 2021, 2021

A propos de cet article

This item is printed on demand - it takes 3-4 days longer - Neuware -The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data. 236 pp. Englisch.

N° de réf. du vendeur 9783731510765

Détails bibliographiques

• Titre: Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
• Éditeur: Karlsruher Institut Für Technologie Jul 2021
• Date de parution: 2021
• Langue: anglais
• ISBN à 10 chiffres: 3731510766
• ISBN à 13 chiffres: 9783731510765
• Reliure: Taschenbuch
• État de l'article: Neu

A propos de ce titre

Synopsis

The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data.