Multi-sensor Fusion-based Cow Health Monitoring IoT System

With the development of the Internet of Things (IoT), digital technology has been adopted on livestock farms. In this study, a system for monitoring the health status of dairy cows is proposed, utilizing multi-type sensor fusion and IoT technology. The system uses physiological and behavioral data obtained from a tail sensor attached to the cows to establish prenatal and estrus prediction models. Additionally, environmental sensors installed in the barn monitor parameters such as temperature, humidity, carbon dioxide concentration, and organic gas concentration to automatically regulate the barn’s fan and sprinkler based on preset threshold values. The system also monitors the health and tail behavior of the cows and predicts their calving and estrus times based on the collected data. Experimental results demonstrate that the system exhibits high accuracy and reliability in monitoring the health of dairy cows.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/trustcom63139.2024.00371
Citations
1
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
0.35
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Multi-sensor Fusion-based Cow Health Monitoring IoT System

Zhenyu Lai, Liangyan Wang, Qinglei Bu, Jialei Zhang et al.
1 citations
Food Supply Chain Traceability
0.35
article

Multi-sensor Fusion-based Cow Health Monitoring IoT System

Zhenyu Lai, Liangyan Wang, Qinglei Bu, Jialei Zhang, Quan Zhang, Jie Sun, Bowen Jia, Yijia Xu
article en
1 citations

Abstract

With the development of the Internet of Things (IoT), digital technology has been adopted on livestock farms. In this study, a system for monitoring the health status of dairy cows is proposed, utilizing multi-type sensor fusion and IoT technology. The system uses physiological and behavioral data obtained from a tail sensor attached to the cows to establish prenatal and estrus prediction models. Additionally, environmental sensors installed in the barn monitor parameters such as temperature, humidity, carbon dioxide concentration, and organic gas concentration to automatically regulate the barn’s fan and sprinkler based on preset threshold values. The system also monitors the health and tail behavior of the cows and predicts their calving and estrus times based on the collected data. Experimental results demonstrate that the system exhibits high accuracy and reliability in monitoring the health of dairy cows.

Xi’an Jiaotong-Liverpool University (CN)
Zero hunger
Openalex Percentile: Top 32%
Food Supply Chain Traceability
0.35
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