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The book explores the challenges of harmonizing diverse IoT data streams resulting from the Internet of Things, which generates vast amounts of sensor observations. It highlights the labor-intensive nature of this task due to varying formats, syntax, and semantics. To address these issues, the authors propose a knowledge-driven approach that leverages formalized public knowledge from Linked Open Data, aiming to streamline the harmonization process and reduce the associated effort.
Achat du livre
Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams, Matthias Frank
- Langue
- Année de publication
- 2021
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- Titre
- Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
- Langue
- Anglais
- Auteurs
- Matthias Frank
- Publié
- 2021
- Format
- souple
- Pages
- 236
- ISBN13
- 9783731510765
- Séries
- Description
- The book explores the challenges of harmonizing diverse IoT data streams resulting from the Internet of Things, which generates vast amounts of sensor observations. It highlights the labor-intensive nature of this task due to varying formats, syntax, and semantics. To address these issues, the authors propose a knowledge-driven approach that leverages formalized public knowledge from Linked Open Data, aiming to streamline the harmonization process and reduce the associated effort.