Networked Wearable Sensors for Monitoring Health and Activities of an Equine Herd: An IoT Approach to Improve Horse Welfare
Year: 2024
Type: article
Abstract: In the past decade, wearable sensors for animals have been significantly advanced. When paired with advanced analysis tools such as machine learning, they can unveil correlations of the sensed information with animals' health and well-being. While they hold great promise, large-scale deployment in a herd has been quite limited due to intrinsic challenges in network communication among the sensors. Herein, in this study, based on our previous success of developing wearable vital sign sensors for individual horses, we demonstrate application of networking these wearable sensors in a herd. A single device not only features a Photoplethysmography (PPG) sensor that measures heart rates with 95% accuracy but also incorporates a GPS module for location tracking, a 3-axis accelerometer and gyroscope for motion detection, offering a holistic sensing solution. Secondly, a network that interconnects these sensors in an equine herd for long-range communication and high-speed computation has been designed and implemented. Through such an internet of things (IoT) network, collective health, and behaviors of the horses in a herd setting can be studied, thus their differences when compared to an individual horse setting can be understood. Such an IoT system is one of the first in the field, if not the only one, designed specifically for use with horses, thus paving a new route to precision agriculture.
Source: IEEE Sensors Journal
Institution: University of Missouri
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,495
Funder: University of Missouri
OpenAlex ID: W4401537024