Computational Challenges for Artificial Intelligence and Machine Learning in Environmental Research

Martin Werner, Gabriel Dax, Moritz Laass

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

2 Zitate (Scopus)

Abstract

In the last decades, environmental research has started to adopt a data-driven perspective enabled by huge sensor networks, satellite-based Earth observation, and almost ubiquitous Internet access. Some of these data-driven approaches are expected to make visions of a sustainable future come true. For example, by enabling societies to live in sustainable smart cities, or to feed the world with precision agriculture. Or by fighting environmental pollution or global deforestation with increased observational power. However, there is a serious gap between some of the current expectations put into data-driven techniques and the maturity of the field of spatial machine learning and artificial intelligence or computer science in general. We give a few examples of open research issues that computer science has to solve in order to make data-driven approaches to environmental sciences successful.

OriginalspracheEnglisch
Titel50. Jahrestagung der Gesellschaft fur Informatik
UntertitelBack to the Futures, INFORMATIK 2020
Redakteure/-innenRalf H. Reussner, Anne Koziolek, Robert Heinrich
Herausgeber (Verlag)Gesellschaft fur Informatik (GI)
Seiten1009-1017
Seitenumfang9
ISBN (elektronisch)9783885797012
DOIs
PublikationsstatusVeröffentlicht - 2020
Veranstaltung50. Jahrestagung der Gesellschaft fur Informatik, INFORMATIK 2020 - 50th Annual Conference of the German Informatics Society, INFORMATIK 2020 - Karlsruhe, Deutschland
Dauer: 28 Sept. 20202 Okt. 2020

Publikationsreihe

NameLecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
BandP-307
ISSN (Print)1617-5468

Konferenz

Konferenz50. Jahrestagung der Gesellschaft fur Informatik, INFORMATIK 2020 - 50th Annual Conference of the German Informatics Society, INFORMATIK 2020
Land/GebietDeutschland
OrtKarlsruhe
Zeitraum28/09/202/10/20

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