eprintid: 4330
rev_number: 10
eprint_status: archive
userid: 378
dir: disk0/00/00/43/30
datestamp: 2020-12-26 09:29:35
lastmod: 2020-12-26 09:29:35
status_changed: 2020-12-26 09:29:35
type: article
metadata_visibility: show
creators_name: Cong Phi Khanh, Phung
creators_name: Tran, Duc-Tan
creators_name: Tu Duong, Van
creators_name: Hong Thinh, Nguyen
creators_name: Tran, Duc-Nghia
title: The new design of cows' behavior classifier based on acceleration data and proposed feature set
ispublished: pub
subjects: Communications
subjects: ElectronicsandComputerEngineering
subjects: isi
subjects: isi_scopus_conf
keywords: cow, monitoring, acceleration, sensor, classification
abstract: Monitor and classify behavioral activities in cows is a helpful support solution for livestock based on the analysis of data from sensors attached to the animal. Accelerometers are particularly suited for monitoring cow behaviors due to small size, lightweight and high accuracy. Nevertheless, the interpretation of the data collected by such sensors when characterizing the type of behaviors still brings major challenges to developers, related to activity complexity (i.e., certain behaviors contain similar gestures). This paper presents a new design of cows' behavior classifier based on acceleration data and proposed feature set. Analysis of cow acceleration data is used to extract features for classification using machine learning algorithms. We found that with 5 features (mean, standard deviation, root mean square, median, range) and 16-second window of data (1 sample/second), classification of seven cow behaviors (including feeding, lying, standing, lying down, standing up, normal walking, active walking) achieved the overall highest performance. We validated the results with acceleration data from a public source. Performance of our proposed classifier was evaluated and compared to existing ones in terms of the sensitivity, the accuracy, the positive predictive value, and the negative predictive value.
date: 2020
date_type: published
official_url: http://dx.doi.org/10.3934/mbe.2020151
id_number: 10.3934/mbe.2020151
contact_email: hongthinh.nguyen@vnu.edu.vn
full_text_status: public
publication: Mathematical Biosciences and Engineering
volume: 17
number: 4
pagerange: 2760-2780
refereed: TRUE
issn: 1551-0018
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citation:   Cong Phi Khanh, Phung and Tran, Duc-Tan and Tu Duong, Van and Hong Thinh, Nguyen and Tran, Duc-Nghia  (2020) The new design of cows' behavior classifier based on acceleration data and proposed feature set.  Mathematical Biosciences and Engineering, 17  (4).   pp. 2760-2780.  ISSN 1551-0018     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4330/1/10.3934_mbe.2020151.pdf