Behavior Classification and Analysis of Grazing Sheep on Pasture with Different Sward Surface Heights Using Machine Learning

Jin, Zhongming; Guo, Lei; Shu, Hang; Qi, Jingwei; Li, Yongfeng; Xu, Beibei; Zhang, Wenju; Wang, Kaiwen; Wang, Wensheng

doi:10.3390/ani12141744

Cited by 8 publications

(7 citation statements)

References 39 publications

(62 reference statements)

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“…This review includes articles with Qualsyst score percentages ≥60%. As a result, 23 articles were included for in-depth analysis [ 7 , 13 , 14 , 15 , 16 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 ]; the remaining 5 articles were excluded since their score was below the acceptance percentage [ 45 , 46 , 47 , 48 , 49 ]. The flow diagram of the review phases’ is shown in Figure 2 .…”

Section: Resultsmentioning

confidence: 99%

“…However, sensor fusion can be applied to other animal populations. In the high level: pigs [ 33 ], felines [ 13 , 32 ], koalas [ 31 ], goats [ 29 ], and birds [ 32 ], regarding feature level: pigs [ 35 ], fish [ 43 ], dogs [ 27 ], camouflaged animals [ 34 ], and sheep [ 14 ]. Meanwhile, for the low-level: horses [ 39 ], dogs [ 7 ], primates [ 16 ], and sheep [ 15 ].…”

Section: Resultsmentioning

confidence: 99%

“…In addition, wearable devices based on the Inertial Measurement Unit (IMU) sensor device are becoming more prevalent. It can be used, for example, to support the automatic behavior classification of grazing sheep and the evaluation of production performance [ 14 , 15 ]. There are also promising applications for the interaction between different animals, search and rescue missions, and the protection of animals from poaching and theft [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Machine Learning-Based Sensor Data Fusion for Animal Monitoring: Scoping Review

Aguilar-Lazcano

Espinosa-Curiel

Ríos-Martínez

et al. 2023

Sensors

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The development of technology, such as the Internet of Things and artificial intelligence, has significantly advanced many fields of study. Animal research is no exception, as these technologies have enabled data collection through various sensing devices. Advanced computer systems equipped with artificial intelligence capabilities can process these data, allowing researchers to identify significant behaviors related to the detection of illnesses, discerning the emotional state of the animals, and even recognizing individual animal identities. This review includes articles in the English language published between 2011 and 2022. A total of 263 articles were retrieved, and after applying inclusion criteria, only 23 were deemed eligible for analysis. Sensor fusion algorithms were categorized into three levels: Raw or low (26%), Feature or medium (39%), and Decision or high (34%). Most articles focused on posture and activity detection, and the target species were primarily cows (32%) and horses (12%) in the three levels of fusion. The accelerometer was present at all levels. The findings indicate that the study of sensor fusion applied to animals is still in its early stages and has yet to be fully explored. There is an opportunity to research the use of sensor fusion for combining movement data with biometric sensors to develop animal welfare applications. Overall, the integration of sensor fusion and machine learning algorithms can provide a more in-depth understanding of animal behavior and contribute to better animal welfare, production efficiency, and conservation efforts.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Machine Learning-Based Sensor Data Fusion for Animal Monitoring: Scoping Review

Aguilar-Lazcano

Espinosa-Curiel

Ríos-Martínez

et al. 2023

Sensors

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“…[1][2][3]. In the field of livestock production, health monitoring of ruminants such as cattle and sheep using information technology has also been receiving attention [4][5][6][7][8][9]. Specifically, pH level monitoring of cattle's rumen is critical because having significantly low pH levels in cattle's rumen is strongly linked with rumen acidosis, a deadly condition that causes an overproduction of acid [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Comparative Studies on Electrodes for Rumen Bacteria Microbial Fuel Cells

Yashiro

Yamamoto

Muneta

et al. 2023

Sensors

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Microbial fuel cells (MFCs) using rumen bacteria have been proposed as a power source for running devices inside cattle. In this study, we explored the key parameters of the conventional bamboo charcoal electrode in an attempt to improve the amount of electrical power generated by the microbial fuel cell. We evaluated the effects of the electrode’s surface area, thickness, and rumen content on power generation and determined that only the electrode’s surface area affects power generation levels. Furthermore, our observations and bacterial count on the electrode revealed that rumen bacteria concentrated on the surface of the bamboo charcoal electrode and did not penetrate the interior, explaining why only the electrode’s surface area affected power generation levels. A Copper (Cu) plate and Cu paper electrodes were also used to evaluate the effect of different electrodes on measuring the rumen bacteria MFC’s power potential, which had a temporarily higher maximum power point (MPP) compared to the bamboo charcoal electrode. However, the open circuit voltage and MPP decreased significantly over time due to the corrosion of the Cu electrodes. The MPP for the Cu plate electrode was 775 mW/m2 and the MPP for the Cu paper electrode was 1240 mW/m2, while the MPP for bamboo charcoal electrodes was only 18.7 mW/m2. In the future, rumen bacteria MFCs are expected to be used as the power supply of rumen sensors.

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“…In recent years, the health monitoring of ruminants such as cows and sheep has become increasingly important. (1)(2)(3)(4)(5)(6) In particular, pH monitoring of the cow's rumen has attracted attention because of the strong relationship between the pH and the deadly disease of rumen acidosis. (7)(8)(9) Giving cows rapidly digestible carbohydrates, which is effective for the stable production of rich milk and marbled beef, can cause rumen acidosis.…”

Section: Introductionmentioning

confidence: 99%

Stability Evaluation of Reference and Indicating Electrodes of pH Sensor During Monitoring of Cow’s Rumen

Shimodan¹,

Yamamoto²,

Sawada³

et al. 2023

Sensors and Materials

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Drift has been a problem for rumen pH sensors, but it is not known whether the reference electrode or the indicating electrode of the pH sensor is the main cause of the drift. In this study, the drift of each electrode was evaluated by placing pH sensors in a cow's rumen and temporarily removing them at intervals over a four-month period. Our experiment revealed that the drift of the indicating electrode caused by changes in sensitivity is the critical drift issue in realizing a stable rumen pH sensor, although the drift is caused by both the reference electrode and the indicating electrode. The sensitivity of the indicating electrode was around 57.0 mV/pH unit at the start of the experiment but dropped to 37.1 and 49.0 mV/pH unit for Cow1 and Cow2, respectively, after placing the pH sensors in the rumen for four months. By assuming a change in the rumen's pH of around 2 pH units, the maximum drift caused by the indicating electrode appears to be 0.68 pH unit. From the observation of the indicating electrode, we found that the drift was caused by impurities on the glass surfaces, and the pH sensitivity was recovered by removing these impurities. Because the glass electrode cannot be cleaned when in the cow's rumen, the development of a glass electrode with resistance to impurities is required for rumen pH sensors.

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Behavior Classification and Analysis of Grazing Sheep on Pasture with Different Sward Surface Heights Using Machine Learning

Cited by 8 publications

References 39 publications

Machine Learning-Based Sensor Data Fusion for Animal Monitoring: Scoping Review

Machine Learning-Based Sensor Data Fusion for Animal Monitoring: Scoping Review

Comparative Studies on Electrodes for Rumen Bacteria Microbial Fuel Cells

Stability Evaluation of Reference and Indicating Electrodes of pH Sensor During Monitoring of Cow’s Rumen

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