File(s) under permanent embargo
Cattle behaviour classification using 3-axis collar sensor and multi-classifier pattern recognition
conference contribution
posted on 2023-05-23, 12:11 authored by Dutta, R, Smith, D, Richard RawnsleyRichard Rawnsley, Bishop-Hurley, G, James HillsJames HillsIn this paper supervised machine learning techniques based multi-classifier pattern recognition system was developed and applied to classify cattle behavioural patterns recorded using collar systems fitted to individual dairy cows to infer their feeding behaviors. Cattle tag sensory system, consist of a piezoelectric micro-electromechanical chip containing a 3-axis accelerometer and a 3-axis magneto-resistive sensor (HMC6343-Honeywell, Plymouth, MN), data were collected at the Tasmanian Institute of Agriculture (TIA) Dairy Research Facility in Tasmania. A multi-classifier pattern recognition system was applied to classify five common cattle behaviour classes, namely, Grazing, Ruminating, Resting, Walking, and Scratching. Part of the recorded cattle tag data were labeled with the known behavioural patterns observed by the field experimental scientists. Pattern recognition system had a sensory data preprocessor to extract window based statistical features from the time series data, and a supervised multi-classifier system to learn the extracted features and generate a model to classify unknown data into one of the five behaviour classes.
History
Publication title
Proceedings of IEEE SensorsVolume
2014-DecemberPagination
1272-1275ISSN
1930-0395Department/School
Tasmanian Institute of Agriculture (TIA)Publisher
Institute of Electrical and Electronics Engineers Inc.Place of publication
United StatesEvent title
13th IEEE SENSORS Conference, SENSORS 2014Event Venue
Valencia, SpainDate of Event (Start Date)
2014-11-02Date of Event (End Date)
2014-11-05Rights statement
Copyright 2014 IEEERepository Status
- Restricted