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Interpolation Methods to Improve Data Quality of Indoor Positioning Data for Dairy Cattle
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Dalarna University, School of Information and Engineering, Statistics.ORCID iD: 0000-0002-3183-3756
Department of Agriculture and Food, RISE Research Institutes of Sweden (RISE), Lund, Sweden.
Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, Denmark.
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2022 (English)In: Frontiers in Animal Science, E-ISSN 2673-6225, Vol. 3, article id 896666Article in journal (Refereed) Published
Abstract [en]

Position data from real-time indoor positioning systems are increasingly used for studying individual cow behavior and social behavior in dairy herds. However, missing data challenges achieving reliable continuous activity monitoring and behavior studies. This study investigates the pattern of missing data and alternative interpolation methods in ultra-wideband based real-time indoor positioning systems in a free-stall barn. We collected 3 months of position data from a Swedish farm with around 200 cows. Data sampled for 6 days from 69 cows were used in subsequent analyzes to determine the location and duration of missing data. Data from 20 cows with the most reliable tags were selected to compare the effects of four different interpolation methods (previous, linear interpolation, cubic spline data interpolation and modified Akima interpolation). By comparing the observed data with the interpolations of the simulated missing data, the mean error distance varied from around 55 cm, using the previously last observed position, to around 17 cm for modified Akima. Modified Akima interpolation has the lowest error distance for all investigated activities (rest, walking, standing, feeding). Larger error distances were found in areas where the cows walk and turn, such as the corner between feeding and cubicles. Modified Akima interpolation is expected to be useful in the subsequent analyses of data gathered using real-time indoor positioning systems.

Place, publisher, year, edition, pages
2022. Vol. 3, article id 896666
National Category
Animal and Dairy Science
Identifiers
URN: urn:nbn:se:du-44343DOI: 10.3389/fanim.2022.896666OAI: oai:DiVA.org:du-44343DiVA, id: diva2:1719699
Funder
Swedish Research Council Formas, 2019-02111Swedish Research Council Formas, 2019-02276Kjell and Marta Beijer FoundationAvailable from: 2022-12-15 Created: 2022-12-15 Last updated: 2023-03-17Bibliographically approved

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Alam, MoududRönnegård, Lars

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CiteExportLink to record
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Citation style
  • apa
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