A Review of Monitoring Techniques for Livestock Respiration and Sounds

Handa, Divya; Peschel, Joshua M.

doi:10.3389/fanim.2022.904834

Cited by 6 publications

(2 citation statements)

References 49 publications

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“…The monitoring of human respiration is crucial for the early detection of diseases and the management of personal health [ 1 ]. However, traditional respiratory monitoring technologies can be uncomfortable or complicated, making them impractical for daily use [ 2 , 3 , 4 ]. Humidity is a clear indicator that can be used to monitor respiration, and high-performance humidity sensors can play a vital role in health assessments and disease predictions [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Fast-Response Non-Contact Flexible Humidity Sensor Based on Direct-Writing Printing for Respiration Monitoring

Chen

et al. 2023

Biosensors

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Respiratory monitoring is crucial for evaluating health status and identifying potential respiratory diseases such as respiratory failure, bronchitis, and pneumonia. Humidity sensors play a significant role in this regard, and efforts are being made to improve their performance. However, achieving ideal sensor parameters such as sensitivity, detection range, and response speed is challenging. In this work, we propose a flexible preparation method for a double-layer humidity sensor using PDMS as a substrate and a GNP/MWCNT composite material as a sensor element. This sensor exhibits high sensitivity (1.4 RH-1), a wide detection range (20–90%), ultra-fast response (0.35 s) and recovery (2.5 s), high repetitiveness (500 cycles), good long-term stability, and excellent flexibility. Due to these advantages, this sensor has potential applications in real-time clinical and home medical care, such as accurate human respiratory monitoring and non-invasive skin humidity monitoring. Hence, this humidity sensor can be a powerful tool to monitor respiratory moisture levels for diagnosing and treating respiratory diseases effectively.

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Section: Introductionmentioning

confidence: 99%

Fast-Response Non-Contact Flexible Humidity Sensor Based on Direct-Writing Printing for Respiration Monitoring

Chen

et al. 2023

Biosensors

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“…The traditional method for estimating respiration rate (RR) in cows is manually counting the flank movements [18]. While this method has been widely used, alternative approaches have emerged in recent years, such as the use of differential pressure sensors to measure pressure changes at the nose, infrared thermography techniques, or sensitive air temperature sensors to detect temperature changes in inhaled and exhaled airflow through the nostrils [19][20][21][22][23][24]. These newer methods offer potential advantages in terms of accuracy and non-invasiveness.…”

Section: Introductionmentioning

confidence: 99%

A Non-Contact and Fast Estimating Method for Respiration Rate of Cows Using Machine Vision

Wang,

Chen,

Yang

et al. 2023

Agriculture

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Detecting respiration rate (RR) is a promising and practical heat stress diagnostic method for cows, with significant potential benefits for dairy operations in monitoring thermal conditions and managing cooling treatments. Currently, the optical flow method is widely employed for automatic video-based RR estimation. However, the optical flow-based approach for RR estimation can be time-consuming and susceptible to interference from various unrelated cow movements, such as rising, lying down, and body shaking. The aim of this study was to propose a novel optical flow-based algorithm for remotely and rapidly detecting the respiration rate of cows in free stalls. To accomplish this, we initially collected 250 sixty-second video episodes from a commercial dairy farm, which included some episodes with interfering motions. We manually observed the respiration rate for each episode, considering it as the ground truth RR. The analysis revealed that certain cow movements, including posture changes and body shaking, introduced noise that compromises the precision of RR detection. To address this issue, we implemented noise filters, with the Butterworth filter proving highly effective in mitigating noise resulting from cow movements. The selection of the region of interest was found to have a substantial impact on the accuracy of RR detection. Opting for the central region was recommended for optimal results. The comparison between the RR estimated by the modified cow respiration rate (MCRR) algorithm and the ground truth RR showed a good agreement with a mean absolute relative error of 7.6 ± 8.9% and a Pearson correlation coefficient of 0.86. Additionally, the results also indicated that reducing the original frame rate from 25 to 5 frames per second and adjusting the image pixel size from 630 × 450 to 79 × 57 pixels notably reduced computational time from 39.8 to 2.8 s, albeit with a slight increase in mean absolute relative error to 8.0 ± 9.0%.

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A review and future trends of precision livestock over dairy and beef cow cattle with artificial intelligence

Michelena,

Fontenla-Romero,

Luis Calvo-Rolle

2024

Logic Journal of the IGPL

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The demand for meat and dairy products is expected to rise significantly in the current demographic and economic growth context. Concurrently, various factors, including financial crises and reduced profitability, have decreased the number of livestock farms. Consequently, the livestock industry is undergoing intensification, with an increased number of cows per farm. This shift makes the management of animals increasingly complex. Amid these challenges, the society’s growing concern for animal health and welfare and the quality of consumed products underscores the importance of systems that aid in the individual and herd-level monitoring and control within livestock operations. In this scenario, precision livestock farming has become essential with the emergence of new sensors and technologies and the evolution of artificial intelligence. Against this backdrop, this paper reviews systems and techniques used in precision livestock farming to detect anomalies caused by reproductive processes and diseases in dairy and beef cattle. The article analyzes sensors and technologies employed, presents key studies conducted, and discusses the most commonly used artificial intelligence techniques in detecting prevalent anomalies.

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A Review of Monitoring Techniques for Livestock Respiration and Sounds

Cited by 6 publications

References 49 publications

Fast-Response Non-Contact Flexible Humidity Sensor Based on Direct-Writing Printing for Respiration Monitoring

Fast-Response Non-Contact Flexible Humidity Sensor Based on Direct-Writing Printing for Respiration Monitoring

A Non-Contact and Fast Estimating Method for Respiration Rate of Cows Using Machine Vision

A review and future trends of precision livestock over dairy and beef cow cattle with artificial intelligence

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