MFCC 특징 벡터를 이용한 실시간 산란계 발성음 분석 시스템
Real-time Laying Hens Sound Analysis System using MFCC Feature Vectors
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초록
산란계사와 같이 매우 좁은 환경에서 많은 개체를 사육하는 경우 작은 환경 변화에도 큰 피해를 받을 수 있다. 이와 같은 문제를 해결하기 위해 본 연구에서는 끊임없이 소리를 발생하는 산란계의 특성을 이용하여 산란계 발성음 분석 시스템을 제안한다. 기존의 산란계 발성음 시스템은산란계사의 제한된 상황만을 고려하거나 실제 산란계사에 적용하기에는 어려움을 가지고 있다. 이러한 문제를 극복하기 위하여 본 논문에서는 MFCC 특징 벡터를 이용한 9가지의 산란계 소리분석을 통해 실제 산란계사 환경에서 발생하는 수 있는 7가지의 상황을 실시간으로 감지할 수 있는 새로운 산란계 발성음 분석 모델을 제안한다. 본 논문에서 제안한 분석 모델을 실제 산란계사에서 성능 평가를 진행한 결과, 평균 AUC 0.93의 분류 성능을 나타내어 기존의 주파수 기반의 특징 분석 방법에 비해 약 43% 향상된 결과를 보여주었다.
Abstract
Raising large numbers of animals in very narrow environments such as laying hens house can be very damaged from small environmental change. Previously researched about laying hens sound analysis system has a problem for applying to the laying hens house because considering only the limited situation of laying hens house. In this paper, to solve the problem, we propose a new laying hens sound analysis model using MFCC feature vector. This model can detect 7 situations that occur in actual laying hens house through 9 kinds of laying hens sound analysis. As a result of the performance evaluation of the proposed laying hens sound analysis model, the average AUC was 0.93, which is about 43% higher than that of the frequency feature analysis method.
참고문헌 (13)
- A. Muminov, "Virtual Fences for Controlling Livestock using Satellite-tracking and Warning Signals", 2016 International Conference on Information Science and Communications Technologies(ICISCT), pp.1~7 (2016)
- K. Smith, "An Integrated Cattle Health Monitoring System", 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, pp.4659~4662 (2006)
- R. K. Gupta, "Detection of Lameness of Cow Based on Body Weight using Artificial Neural Network", 2014 International Conference on Computing for Sustainable Global Development (INDIACom), pp.337~341 (2014)
- A. Kumar, "A Zigbee-Based Animal Health Monitoring System", IEEE Sensors Journal,, 15(1), pp.610~617 (2015)
- Celia Rosline. A, "Fuzzy Query Processing in Wireless Sensor Networks for Animal Health Monitoring", 2014IEEE International Conference on Advanced Communications, pp.1094~1098 (2014)
- G. Sántha, "Accelerometer based Activity Monitoring System for Behavioural Analysis of Free-roaming Animals", 2013 IEEE 11th International Symposium on Intelligent Systems and Informatics(SISY), pp.199~203 (2013)
- D. Banerjee, "Remote Activity Classification of Hens Using Wireless Body Mounted Sensors", 2012 9th International Conference on Wearable and Implantable Body Sensor Networks, pp.107~112 (2012)
- Melaku Tefera, "Acoustic Signals in Domestic Chicken (Gallus gallus): A Tool for Teaching Veterinary Ethology and Implication for language learning", Ethiop. Vet. J., 16, pp.77~84 (2012)
- 이종욱, "Stress Detection and Classification of Laying Hens by Sound Analysis", Animal Bioscience, 28(4), pp.592~598 (2015), 아세아·태평양축산학회[DOI]
- Daeyoung Na, "Detailed Sound Analysis System for Real Time Detection of Changes in Laying Hens Feeding Environment using SVM", International Workshop on Convergence Information Technology(IWCIT2017), pp.59~62 (2017)
- P. Mermelstein, "Pattern Recognition and Artificial Intelligence", pp.374~388 (1976)
- D. R. Cox, "The Regression Analysis of Binary Sequences", Journal of the Royal Statistical Society, 20(2), pp.215~242 (1958)
- O. Rouhani-Kalleh, "Algorithms for Fast Large Scale Data Mining Using Logistic Regression", 2007 IEEE Symposium on Computational Intelligence and Data Mining, pp.155~162 (2007)