Gaia-AgStream: An Explainable AI Platform for Mining Complex Data Streams in Agriculture

Autor(en): Schoenke, J.
Aschenbruck, N. 
Interdonato, R.
Kanawati, R.
Meisener, A.-C.
Thierart, F.
Vial, G.
Atzmueller, M.
Herausgeber: Boumerdassi, S.
Ghogho, M.
Renault, E.
Stichwörter: Agriculture; Agroecology; Anomaly detection; Biodiversity; Carbon farming; Complex networks; Data fusion; Data integration; Data quality; Data reduction; Data streaming; Distributed systems; Explainable AI; Explainable artificial intelligence; Information management; Knowledge graph; Knowledge graphs; Machine learning; Open Data; Quality control; Root cause analysis; Semantic Web; Sensor data fusion; Sensor networks; Sensors network; Uncertainty analysis, Agro ecologies; Uncertainty management; Uncertainty management, Machine learning
Erscheinungsdatum: 2021
Herausgeber: Springer Science and Business Media Deutschland GmbH
Enthalten in: Communications in Computer and Information Science
Band: 1470 CCIS
Startseite: 71
Seitenende: 83
Beschreibung: 
Conference of 1st International Conference on Smart and Sustainable Agriculture, SSA 2021 ; Conference Date: 21 June 2021 Through 22 June 2021; Conference Code:268539
ISBN: 9783030882587
ISSN: 18650929
DOI: 10.1007/978-3-030-88259-4_6
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119875445&doi=10.1007%2f978-3-030-88259-4_6&partnerID=40&md5=3ee852e65c1f129b82bc022ceead0f53

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