Data semantic enrichment for complex event processing over IoT Data Streams
This thesis generalizes techniques for processing IoT data streams, semantically enrich data with contextual information, as well as complex event processing in IoT applications. A case study for ECG anomaly detection and signal classification was conducted to validate the knowledge foundation.
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/175603 |
| Acceso en línea: | https://hdl.handle.net/2117/175603 |
| Access Level: | acceso abierto |
| Palabra clave: | Internet of things Semantic Web IoT HTM ECG edge computing real-time analytics CNN eHealth semantic enrichment complex event processing CEP big data streams kafka faust signal processing Internet de les coses Web semàntica Àrees temàtiques de la UPC::Informàtica |
| Sumario: | This thesis generalizes techniques for processing IoT data streams, semantically enrich data with contextual information, as well as complex event processing in IoT applications. A case study for ECG anomaly detection and signal classification was conducted to validate the knowledge foundation. |
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