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Where do we find missing data in a commercial real-time location system? Evidence from 2 dairy farms
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.ORCID iD: 0000-0003-2817-5331
Department of Agriculture and Food, RISE Research Institutes of Sweden, Lund, Sweden.ORCID iD: 0000-0002-1359-2952
Dalarna University, School of Information and Engineering, Statistics. (Microdata Analysis)ORCID iD: 0000-0002-3183-3756
Dalarna University, School of Information and Engineering, Statistics.ORCID iD: 0000-0002-1057-5401
2021 (English)In: JDS Communications, ISSN 2666-9102, Vol. 2, p. 345-350Article in journal (Refereed) Published
Abstract [en]

Real-time indoor positioning using ultra-wideband devices provides an opportunity for modern dairy farms to monitor the behavior of individual cows; however, missing data from these devices hinders reliable continuous monitoring and analysis of animal movement and social behavior. The objective of this study was to examine the data quality, in terms of missing data, in one commercially available ultra-wideband–based real-time location system for dairy cows. The focus was on detecting major obstacles, or sections, inside open freestall barns that resulted in increased levels of missing data. The study was conducted on 2 dairy farms with an existing commercial real-time location system. Position data were recorded for 6 full days from 69 cows on farm 1 and from 59 cows on farm 2. These data were used in subsequent analyses to determine the locations within the dairy barns where position data were missing for individual cows. The proportions of missing data were found to be evenly distributed within the 2 barns after fitting a linear mixed model with spatial smoothing to logit-transformed proportions (mean = 18% vs. 4% missing data for farm 1 and farm 2, respectively), with the exception of larger proportions of missing data along one of the walls on both farms. On farm 1, the variation between individual tags was large (range: 9–49%) compared with farm 2 (range: 12–38%). This greater individual variation of proportions of missing data indicates a potential problem with the individual tag, such as a battery malfunction or tag placement issue. Further research is needed to guide researchers in identifying problems relating to data capture problems in real-time monitoring systems on dairy farms. This is especially important when undertaking detailed analyses of animal movement and social interactions between animals.

Place, publisher, year, edition, pages
2021. Vol. 2, p. 345-350
National Category
Agricultural and Veterinary sciences Computer and Information Sciences
Research subject
Complex Systems – Microdata Analysis, General Microdata Analysis - methods
Identifiers
URN: urn:nbn:se:du-39055DOI: 10.3168/jdsc.2020-0064OAI: oai:DiVA.org:du-39055DiVA, id: diva2:1620315
Projects
CSI-DT (SLU)
Funder
Swedish Research Council Formas, 2019-02111Available from: 2021-12-15 Created: 2021-12-15 Last updated: 2023-04-14Bibliographically approved

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Alam, MoududRönnegård, Lars

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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