Non-Invasive Cattle Body Temperature Measurement Using Infrared Thermography and Auxiliary Sensors

To achieve a sensitive and accurate method in body temperature measurement of cattle, this study explores the uses of infrared thermography (IRT), an anemometer, and a humiture meter as a multiple sensors architecture. The influence of environmental factors on IRT, such as wind speed, ambient temper...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-04, Vol.21 (7), p.2425
Main Authors: Wang, Fu-Kang, Shih, Ju-Yin, Juan, Pin-Hsun, Su, Ya-Chi, Wang, Yu-Chieh
Format: Article
Language:English
Subjects:
Accuracy
Air flow
Ambient temperature
Animals
Body Temperature
Cattle
core body temperature
Dairy cattle
Data processing
Disease
environmental factors
Frames (data processing)
Heat
Humidity
Infrared imaging
Infrared Rays
infrared thermography (IRT)
Milk production
multiple sensors architecture
noninvasive
Physiology
Radiation
Respiration
Root-mean-square errors
Sensors
Signal processing
Temperature
Temperature measurement
Thermography
Wind
Wind speed
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Summary:To achieve a sensitive and accurate method in body temperature measurement of cattle, this study explores the uses of infrared thermography (IRT), an anemometer, and a humiture meter as a multiple sensors architecture. The influence of environmental factors on IRT, such as wind speed, ambient temperature, and humidity, was considered. The proposed signal processes removed the IRT frames affected by air flow, and also eliminated the IRT frames affected by random body movement of cattle using the frame difference method. In addition, the proposed calibration method reduced the impact of ambient temperature and humidity on IRT results, thereby increasing the accuracy of IRT temperature. The difference of mean value and standard deviation value between recorded rectal reference temperature and IRT temperature were 0.04 °C and 0.10 °C, respectively, and the proposed system substantially improved the measurement consistency of the IRT temperature and reference on cattle body temperature. Moreover, with a relatively small IRT image sensor, the combination of multiple sensors architecture and proper data processing still achieved good temperature accuracy. The result of the root-mean-square error (RMSE) was 0.74 °C, which is quite close to the accurate result of the IRT measurement.
ISSN:1424-8220
1424-8220
DOI:10.3390/s21072425