Data Acquisition Framework for Smart Weather Station Aurora
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Author
Beysens, J.
Haro, M.
Berguerand, R.
DOI
Abstract
After 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.
Publication Reference
CSEM Scientific and Technical Report 2023, p. 20
Year
2023