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Více o knize
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.
Nákup knihy
Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams, Matthias Frank
- Jazyk
- Rok vydání
- 2021
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Doručení
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- Titul
- Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
- Jazyk
- anglicky
- Autoři
- Matthias Frank
- Vydavatel
- Karlsruher Institut für Technologie
- Rok vydání
- 2021
- Vazba
- měkká
- Počet stran
- 236
- ISBN13
- 9783731510765
- Série
- Anotace
- 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.