Data Fusion of GPS Trackers and Activometers Mounted on Milking Cows for Alpine Pasture Exploitation Monitoring
Extensive grazing in alpine environments represents a livestock management strategy that contributes to landscape conservation, animal welfare, and allows the production of high-quality dairy products. Digital technologies offer a potential solution to these challenges by supporting farmers and facilitating generational turnover. In this work, 20 lactating cows were monitored during the grazing season using GPS devices to track movements across the pasture area and activometers composed of an accelerometer-based collar that recorded cow neck movements continuously, classifying them into three possible behaviours: rumination, feeding and resting. Data provided by the activometers were collected with a resolution of 15 min intervals, reporting the duration of each activity, while GPS data were collected at an average frequency of 5 min. GPS data were filtered for potential outliers and subsequently aligned with activometers data through a Visual Basic for Applications (VBA) algorithm. This data fusion optimization enabled the creation of a robust integrated dataset in which each GPS position was associated with the animal’s predominant activity, allowing the analysis of grazing patterns and the generation of high-resolution grazing maps. The combination of these two digital tools proved effective in assessing animal behaviour in mountainous environments, providing operational indicators to support pasture management and improve forage biomass utilisation.
Authors
- Milena Povolo (ORCID: https://orcid.org/0000-0003-2708-7364)
- Valeria Pelizzola (ORCID: https://orcid.org/0009-0007-0835-5710)
- Giovanni Cabassi (ORCID: https://orcid.org/0000-0003-2318-6365)
- Andrea Lazzari (ORCID: https://orcid.org/0000-0002-1347-0146)
- Lucia Monti (ORCID: https://orcid.org/0000-0001-7211-649X)
- Claudia Gambale (ORCID: https://orcid.org/0009-0003-3971-6487)
- Dario Benedini
Institutions
- Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (IT)
Publication Details
- Journal
- AgriEngineering
- Published
- 2026-10-13
- DOI
- https://doi.org/10.3390/agriengineering8100438
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Regione Lombardia