TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Cloud-based management of machine learning generated knowledge for fleet data refinement

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoKnowledge Discovery, Knowledge Engineering and Knowledge Management
Alaotsikko8th International Joint Conference, IC3K 2016, Porto, Portugal, November 9–11, 2016, Revised Selected Papers
KustantajaSpringer
Sivut267-286
Sivumäärä20
ISBN (elektroninen)978-3-319-99701-8
ISBN (painettu)978-3-319-99700-1
DOI - pysyväislinkit
TilaJulkaistu - 14 marraskuuta 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Porto, Portugali
Kesto: 9 marraskuuta 201611 marraskuuta 2016

Julkaisusarja

NimiCommunications in Computer and Information Science
Vuosikerta914
ISSN (painettu)1865-0929

Conference

ConferenceInternational Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
MaaPortugali
KaupunkiPorto
Ajanjakso9/11/1611/11/16

Tiivistelmä

The modern mobile machinery has advanced on-board computer systems. They may execute various types of applications observing machine operation based on sensor data (such as feedback generators for more efficient operation). Measurement data utilisation requires preprocessing before use (e.g. outlier detection or dataset categorisation). As more and more data is collected from machine operation, better data preprocessing knowledge may be generated with data analyses. To enable the repeated deployment of that knowledge to machines in operation, information management must be considered; this is particularly challenging in geographically distributed fleets. This study considers both data refinement management and the refinement workflow required for data utilisation. The role of machine learning in data refinement knowledge generation is also considered. A functional cloud-managed data refinement component prototype has been implemented, and an experiment has been made with forestry data. The results indicate that the concept has considerable business potential.

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