Data Acquisition Framework for Smart Weather Station Aurora

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dc.contributor.authorBeysens, J.
dc.contributor.authorHaro, M.
dc.contributor.authorBerguerand, R.
dc.date.accessioned2025-03-17T12:30:22Z
dc.date.available2025-03-17T12:30:22Z
dc.date.issued2023
dc.description.abstractAfter winning the tinyML Challenge 2022, CSEM co-organized in 2023 the follow-up Smart Weather Station challenge, to build a maintenance-free weather station without moving parts using tinyML technology. We developed a data collection framework with our prototype Aurora to build a large-scale and realistic dataset of acoustic wind and rain intensities from environmental recordings. This dataset will enable the creation of the next-generation tinyML models to efficiently estimate local weather conditions.
dc.identifier.citationCSEM Scientific and Technical Report 2023, p. 20
dc.identifier.urihttps://hdl.handle.net/20.500.12839/1640
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleData Acquisition Framework for Smart Weather Station Aurora
dc.typeCSEM Report
dc.type.csemdivisionsBU-M
dc.type.csemresearchareasASICs for the Edge
dc.type.csemresearchareasIoT & Vision
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