ArticleEntropy (Basel, Switzerland)2022
Analysis of Accelerometer and GPS Data for Cattle Behaviour Identification and Anomalous Events Detection.
Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
18 citing papers in PubMed.
- Behavior Classification of Cattle in a Virtual Fencing System Using Tri-Axial Accelerometers and Machine Learning.Animals : an open access journal from MDPI · 2026Article
- Research on a Lightweight Recognition Model for Daily Cattle Behavior Toward Real-Time Monitoring.Veterinary sciences · 2025Article
- The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review.Animals : an open access journal from MDPI · 2025Review
- Multi-Sensor Integration and Machine Learning for High-Resolution Classification of Herbivore Foraging Behavior.Animals : an open access journal from MDPI · 2025Article
- Wearable Collar Technologies for Dairy Cows: A Systematized Review of the Current Applications and Future Innovations in Precision Livestock Farming.Animals : an open access journal from MDPI · 2025Review
- A dataset for detecting walking, grazing, and resting behaviors in free-grazing cattle using IoT collar IMU signals.Frontiers in veterinary science · 2025Article
- Mapping activity of grazing cattle using commercial virtual fencing technology.Frontiers in veterinary science · 2025Article
- Application of Precision Technologies to Characterize Animal Behavior: A Review.Animals : an open access journal from MDPI · 2024Review
- Connecting the dots: relationship between heart rate and overall dynamic body acceleration in free-ranging cattle.Conservation physiology · 2024Article
- Unsupervised Domain Adaptation for Mitigating Sensor Variability and Interspecies Heterogeneity in Animal Activity Recognition.Animals : an open access journal from MDPI · 2023Article
- Machine Learning-Based Sensor Data Fusion for Animal Monitoring: Scoping Review.Sensors (Basel, Switzerland) · 2023Article
- Uncovering Patterns in Dairy Cow Behaviour: A Deep Learning Approach with Tri-Axial Accelerometer Data.Animals : an open access journal from MDPI · 2023Article
- Assessment of a UWB Real Time Location System for Dairy Cows' Monitoring.Sensors (Basel, Switzerland) · 2023Article
- Cow Behavioural Activities in Extensive Farms: Challenges of Adopting Automatic Monitoring Systems.Sensors (Basel, Switzerland) · 2023Review
- Innovations in Cattle Farming: Application of Innovative Technologies and Sensors in the Diagnosis of Diseases.Animals : an open access journal from MDPI · 2023Review
- Machine learning approaches to predict and detect early-onset of digital dermatitis in dairy cows using sensor data.Frontiers in veterinary science · 2023Article
- High Precision Classification of Resting and Eating Behaviors of Cattle by Using a Collar-Fitted Triaxial Accelerometer Sensor.Sensors (Basel, Switzerland) · 2022Article
- Sensor Data Analytics: Challenges and Methods for Data-Intensive Applications.Entropy (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
In this paper, a method to classify behavioural patterns of cattle on farms is presented. Animals were equipped with low-cost 3-D accelerometers and GPS sensors, embedded in a commercial device attached to the neck. Accelerometer signals were sampled at 10 Hz, and data from each axis was independently processed to extract 108 features in the time and frequency domains. A total of 238 activity patterns, corresponding to four different classes (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.