Version 1
: Received: 14 November 2020 / Approved: 16 November 2020 / Online: 16 November 2020 (10:44:29 CET)
How to cite:
Rigakis, I.; Potamitis, I.; Tatlas, N.A.; Potirakis, S.M.; Ntalampiras, S. TreeVibes: Modern tools for Global Monitoring of Trees Against Borers. Preprints2020, 2020110411. https://doi.org/10.20944/preprints202011.0411.v1
Rigakis, I.; Potamitis, I.; Tatlas, N.A.; Potirakis, S.M.; Ntalampiras, S. TreeVibes: Modern tools for Global Monitoring of Trees Against Borers. Preprints 2020, 2020110411. https://doi.org/10.20944/preprints202011.0411.v1
Rigakis, I.; Potamitis, I.; Tatlas, N.A.; Potirakis, S.M.; Ntalampiras, S. TreeVibes: Modern tools for Global Monitoring of Trees Against Borers. Preprints2020, 2020110411. https://doi.org/10.20944/preprints202011.0411.v1
APA Style
Rigakis, I., Potamitis, I., Tatlas, N.A., Potirakis, S.M., & Ntalampiras, S. (2020). TreeVibes: Modern tools for Global Monitoring of Trees Against Borers. Preprints. https://doi.org/10.20944/preprints202011.0411.v1
Chicago/Turabian Style
Rigakis, I., Stelios M. Potirakis and Stavros Ntalampiras. 2020 "TreeVibes: Modern tools for Global Monitoring of Trees Against Borers" Preprints. https://doi.org/10.20944/preprints202011.0411.v1
Abstract
Is there a wood-feeding insect inside a tree or wooden structure? We investigate several ways on how deep learning approaches can massively scan recordings of vibrations stemming from probed trees to infer their infestation state with wood-boring insects that feed and move inside wood. The recordings come from remotely controlled devices that sample the internal soundscape of trees on a 24/7 basis and wirelessly transmit brief recordings of the registered vibrations to a cloud server. We discuss the different sources of vibrations that can be picked up from trees in urban environments and how deep learning methods can focus on those originating from borers. Our goal is to match the problem of the accelerated—due to global trade and climate change— establishment of invasive xylophagus insects by increasing the capacity of inspection agencies. We aim at introducing permanent, cost-effective, automatic monitoring of trees based on deep learning techniques, in commodity entry point as well as in wild, urban and cultivated areas in order to effect large-scale, sustainable pest-risk analysis and management of wood boring insects such as those from the Cerambycidae family (longhorn beetles).
Keywords
Cerambycidae; xylophagus insects; monitoring
Subject
Engineering, Automotive Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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