High-resolution raindrop counting via instantaneous frequency sensing on hydrophobic elastic membranes.
In this paper, we introduce a novel approach that paves the way for the creation of affordable, high-precision rainfall sensors utilizing microphone data. The cornerstone of this methodology is an innovative algorithm capable of converting audio recordings into distinctive features, which are subseq...
| 發表在: | PLoS ONE |
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| 主要作者: | |
| 格式: | Article |
| 語言: | 英语 |
| 出版: |
Public Library of Science (PLoS)
2024-01-01
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| 在線閱讀: | https://doi.org/10.1371/journal.pone.0311995 |
| 總結: | In this paper, we introduce a novel approach that paves the way for the creation of affordable, high-precision rainfall sensors utilizing microphone data. The cornerstone of this methodology is an innovative algorithm capable of converting audio recordings into distinctive features, which are subsequently processed by a compact machine learning model. Our findings demonstrate that this technique can attain a temporal resolution of 10 milliseconds with an accuracy of 80%, underscoring its potential to overcome the limitations imposed by the necessity for power infrastructure and specialized expertise in traditional rain sensing methods. |
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| ISSN: | 1932-6203 |