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Jung DH, Kim NY, Moon SH, Jhin C, Kim HJ, Yang JS, Kim HS, Lee TS, Lee JY, Park SH. Deep Learning-Based Cattle Vocal Classification Model and Real-Time Livestock Monitoring System with Noise Filtering. Animals (Basel) 2021; 11:ani11020357. [PMID: 33535390 PMCID: PMC7911430 DOI: 10.3390/ani11020357] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 01/24/2021] [Accepted: 01/27/2021] [Indexed: 11/16/2022] Open
Abstract
The priority placed on animal welfare in the meat industry is increasing the importance of understanding livestock behavior. In this study, we developed a web-based monitoring and recording system based on artificial intelligence analysis for the classification of cattle sounds. The deep learning classification model of the system is a convolutional neural network (CNN) model that takes voice information converted to Mel-frequency cepstral coefficients (MFCCs) as input. The CNN model first achieved an accuracy of 91.38% in recognizing cattle sounds. Further, short-time Fourier transform-based noise filtering was applied to remove background noise, improving the classification model accuracy to 94.18%. Categorized cattle voices were then classified into four classes, and a total of 897 classification records were acquired for the classification model development. A final accuracy of 81.96% was obtained for the model. Our proposed web-based platform that provides information obtained from a total of 12 sound sensors provides cattle vocalization monitoring in real time, enabling farm owners to determine the status of their cattle.
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Affiliation(s)
- Dae-Hyun Jung
- Smart Farm Research Center, Korea Institute of Science and Technology (KIST), Gangneung 25451, Korea; (D.-H.J.); (C.J.); (J.-S.Y.); (H.S.K.); (T.S.L.); (J.Y.L.)
| | - Na Yeon Kim
- Department of Bio-Convergence Science, College of Biomedical and Health Science, Konkuk University, Chungju 27478, Korea; (N.Y.K.); (S.H.M.)
- Asia Pacific Ruminant Institute, Icheon 17385, Korea
| | - Sang Ho Moon
- Department of Bio-Convergence Science, College of Biomedical and Health Science, Konkuk University, Chungju 27478, Korea; (N.Y.K.); (S.H.M.)
| | - Changho Jhin
- Smart Farm Research Center, Korea Institute of Science and Technology (KIST), Gangneung 25451, Korea; (D.-H.J.); (C.J.); (J.-S.Y.); (H.S.K.); (T.S.L.); (J.Y.L.)
- Department of Smartfarm Research, 1778 Living Tech, Sejong 30033, Korea
| | - Hak-Jin Kim
- Department of Biosystems and Biomaterial Engineering, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea;
| | - Jung-Seok Yang
- Smart Farm Research Center, Korea Institute of Science and Technology (KIST), Gangneung 25451, Korea; (D.-H.J.); (C.J.); (J.-S.Y.); (H.S.K.); (T.S.L.); (J.Y.L.)
| | - Hyoung Seok Kim
- Smart Farm Research Center, Korea Institute of Science and Technology (KIST), Gangneung 25451, Korea; (D.-H.J.); (C.J.); (J.-S.Y.); (H.S.K.); (T.S.L.); (J.Y.L.)
| | - Taek Sung Lee
- Smart Farm Research Center, Korea Institute of Science and Technology (KIST), Gangneung 25451, Korea; (D.-H.J.); (C.J.); (J.-S.Y.); (H.S.K.); (T.S.L.); (J.Y.L.)
| | - Ju Young Lee
- Smart Farm Research Center, Korea Institute of Science and Technology (KIST), Gangneung 25451, Korea; (D.-H.J.); (C.J.); (J.-S.Y.); (H.S.K.); (T.S.L.); (J.Y.L.)
| | - Soo Hyun Park
- Smart Farm Research Center, Korea Institute of Science and Technology (KIST), Gangneung 25451, Korea; (D.-H.J.); (C.J.); (J.-S.Y.); (H.S.K.); (T.S.L.); (J.Y.L.)
- Correspondence: ; Tel.: +82-33-650-3661
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