Real-Time Monitoring of Animals and Environment in Broiler Precision Farming—How Robust Is the Data Quality?

Michael Selle, Fabian Spieß, Christian Visscher, Silke Rautenschlein, Arne Jung, Monika Auerbach, Jörg Hartung, Christian Sürie and Ottmar Distl ()
Additional contact information
Michael Selle: Institute of Animal Breeding and Genetics, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany
Fabian Spieß: Institute for Animal Nutrition, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany
Christian Visscher: Institute for Animal Nutrition, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany
Silke Rautenschlein: Clinic for Poultry, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany
Arne Jung: Clinic for Poultry, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany
Monika Auerbach: Clinic for Poultry, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany
Jörg Hartung: Institute of Animal Breeding and Genetics, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany
Christian Sürie: Farm for Education and Research Ruthe, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany
Ottmar Distl: Institute of Animal Breeding and Genetics, University of Veterinary Medicine Hannover (Foundation), 30559 Hannover, Germany

Sustainability, 2023, vol. 15, issue 21, 1-14

Abstract: Increasing digitalization in animal farming, commonly addressed as Precision Livestock Farming (PLF), offers benefits in terms of productivity, sustainability, reduced labor and improved monitoring of animal welfare. However, the large amounts of collected data must be stored, processed and evaluated in a proper way. In practice, challenges of continuous and exact data collection can arise, e.g., from air pollutants like dust occluding cameras and sensors, degrading material, the ever-present commotion caused by animals, workers and machines, regularly required maintenance or weak signal transmission. In this study, we analyzed the quality of multi-source spatio-temporal data from a broiler house with 8100 birds over a period of 31 months collected by the Farmer Assistant System (FAS). This is a ceiling-suspended robot equipped with several sensors and cameras that continuously collect data while moving through the barn. The data analysis revealed numerous irregularities: missing values, outliers, repetitive measurements, systematic errors, and temporal and spatial inconsistencies. About 40–50% of all records collected with the early version of the FAS had to be sorted out. The newer version of FAS provided cleaner data, although still about 10–20% of the data had to be removed. Our study has shown that where sophisticated technological systems meet a challenging environment, a thorough and critical review of data completeness and quality is crucial to avoid misinterpretation. The pipeline developed here is designed to help developers and farmers detect failures in signal processing and localize the problem in the hardware components. Scientists, industrial developers and farmers should work more closely together to develop new PLF technologies to more easily advance digitization in agriculture.

Keywords: precision livestock farming; broiler; real-time monitoring; big data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/21/15527/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/21/15527/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:21:p:15527-:d:1272450

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().