Acoustic insights: advancing object classification in urban landscapes using distributed acoustic sensing and convolutional neural networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU151177" target="_blank" >RIV/00216305:26220/24:PU151177 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1117/12.3021990" target="_blank" >http://dx.doi.org/10.1117/12.3021990</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1117/12.3021990" target="_blank" >10.1117/12.3021990</a>

Result language
angličtina
Original language name
Acoustic insights: advancing object classification in urban landscapes using distributed acoustic sensing and convolutional neural networks
Original language description
The paper introduces an innovative object classification method for urban environments, employing distributed acoustic sensing (DAS) to address the complexities of urban landscapes. Utilizing omnipresent optical telecommunication cables, our approach involves a modified convolutional neural network (CNN) with transfer learning, achieving up to 85% accuracy. This method reuses most of the original network for feature extraction, with a final layer customized for new urban datasets – initially trained at the Brno University of Technology and then adapted to city center data. The model effectively identifies urban elements like vehicles and pedestrians, showcasing the potential of DAS for real-time classification in urban management and planning.
Czech name
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Czech description
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Project
<a href="/en/project/VK01030121" target="_blank" >VK01030121: Middle range distributed fiber-optic sensing system for acoustic vibration and temperature monitoring on critical infrastructures</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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