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Article

IoT-Based Bee Swarm Activity Acoustic Classification Using Deep Neural Networks

Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, Slovenia
Sensors 2021, 21(3), 676; https://doi.org/10.3390/s21030676
Received: 15 December 2020 / Revised: 11 January 2021 / Accepted: 18 January 2021 / Published: 20 January 2021
(This article belongs to the Special Issue AI for IoT)
Animal activity acoustic monitoring is becoming one of the necessary tools in agriculture, including beekeeping. It can assist in the control of beehives in remote locations. It is possible to classify bee swarm activity from audio signals using such approaches. A deep neural networks IoT-based acoustic swarm classification is proposed in this paper. Audio recordings were obtained from the Open Source Beehive project. Mel-frequency cepstral coefficients features were extracted from the audio signal. The lossless WAV and lossy MP3 audio formats were compared for IoT-based solutions. An analysis was made of the impact of the deep neural network parameters on the classification results. The best overall classification accuracy with uncompressed audio was 94.09%, but MP3 compression degraded the DNN accuracy by over 10%. The evaluation of the proposed deep neural networks IoT-based bee activity acoustic classification showed improved results if compared to the previous hidden Markov models system. View Full-Text
Keywords: bee acoustic analysis; deep neural networks; activity monitoring; acoustic classification; lossy audio compression bee acoustic analysis; deep neural networks; activity monitoring; acoustic classification; lossy audio compression
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MDPI and ACS Style

Zgank, A. IoT-Based Bee Swarm Activity Acoustic Classification Using Deep Neural Networks. Sensors 2021, 21, 676. https://doi.org/10.3390/s21030676

AMA Style

Zgank A. IoT-Based Bee Swarm Activity Acoustic Classification Using Deep Neural Networks. Sensors. 2021; 21(3):676. https://doi.org/10.3390/s21030676

Chicago/Turabian Style

Zgank, Andrej. 2021. "IoT-Based Bee Swarm Activity Acoustic Classification Using Deep Neural Networks" Sensors 21, no. 3: 676. https://doi.org/10.3390/s21030676

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