• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.91-98
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• 2016

Outbreaks of highly contagious livestock diseases can cause direct and indirect economic impacts such as lower productivity of cattle farms, fall in tourism in damaged areas and countries, and decline in exports. They also incur tremendous social costs associated with disease elimination and restoration work. Thus, it is essential to prevent livestock diseases through monitoring and prediction efforts. Currently, however, it is still difficult to provide accurate predictive information regarding occurrences of livestock diseases, because existing cattle health monitoring or forecasting systems are only limited to monitor environmental conditions of livestock barns and check activities of cattle by using a pedometer or thermal image. In this paper, we present a biosensor-based cattle health monitoring system capable of collecting bio-signals of farm animals in an effective way. For the presented monitoring system, we design an integrated monitoring device consisting of a sensing module to measure bio-signals of cattle such as the heartbeat, the breath rate and the momentum, as well as a Zigbee module designed to transmit the biometric data based on Wireless Sensor Network (WSN). We verify the validity of the monitoring system by the comparison of the correlations of designed device with a commercial ECG equipment through analyzing the R-peak of measured signals.

• Journal of Veterinary Clinics
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• v.16 no.2
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• pp.439-442
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• 1999

An animal health monitoring system in Gyeongnam area (near-Chinju) was studied to evaluate the environmental risk factors, physical examinations and 4 disease entities(abomasal displacement, traumatic reticulopericarditis ＆ -peritonitis, milk fever and lameness) in 40(34 in second year)dairy herds (total 1253 dairy cattle). In feeding environments, we examined housing system, forage percentage in ration, stall types, playground, cleanness of stall. In housing system, most of herds (60%) have tie-stall types and 36 herds are open-type housing. The forage ratio of ration was less than 50% in most of herds (67%). 39 herds had their own playgrounds and the frequency of playground cleanness was irregular, Physical examinations included the T(temperature), P (pulse), R (respiration), abnormalities of superficial lymph nodes, claw examination and total CBC with blood from tail veins. T, P, R are within normal limits (T : 38.1$\pm$0.6$^{\circ}C$, P : 84.6$\pm$12.9/min., R : 24.0$\pm$7.6/min. ,respectively), the swelling of lymph nodes were shown in 13 cattle and overall claw trimming was required in 3 herds. In blood examination, 23 cattle showed leuko-cytosis and 7 cattle showed low RBC and hemoglobin level, the other cattle were within normal limits (WBC : 8.90$\pm$2.06 10$^3$/ul., RBC : 6.36$\pm$1.02 10$^{6}$ ul, Hb : 9.83$\pm$ 1.20 g/dl PCV : 27.43$\pm$5.67 %, respectively). In 4 disease entities, we found some metallic foreign bodies in men of 13 cattle, which had predisposing factors of traumatic reticulopericarditis and reticuloperitonitis, 13 abomasal displacement, 51 milk fever and lameness in 39 cattle.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.22-34
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• 2012

In this paper, we design and implement an advanced cattle shed management system using a infrared wireless sensor nodes and surveillance camera. Our system provides three main capabilities, such as 24-hours cattle shed monitoring, trespassing detection, automatic control of cattle shed. For this, our system can monitor cattle shed as well as the condition of cows/bulls for 24 hours per day by using surveillance cameras. Our system also can detect intruders inside the cattle shed by using infrared wireless sensor nodes. In addition, our system can control the power of electric equipments in the cattle shed by using a power controller. Finally, we combine the three components into a system by using a smartphone application program and verify the effectiveness of our system by a testbed.

• Journal of Environmental Health Sciences
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• v.41 no.5
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• pp.277-288
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• 2015

Objectives: There are many hazardous agents at livestock farms. In particular, gases can be detrimental to both workers and animals. This study evaluated ammonia and hydrogen sulfide concentrations in broiler hen barns and beef cattle barns according to sampling location and height. Methods: Three broiler hen barns and three beef cattle barns were selected for gas monitoring in this study. Ammonia and hydrogen sulfide concentrations were measured using a direct-reading instrument which could measure the target gases simultaneously. Gas monitoring was conducted at human breathing height and animal breathing height at three points in each livestock farm. Results: Ammonia concentrations at the broiler hen barns ranged from 3.3 to 12.5 ppm by sampling location and height, but hydrogen sulfide was not detected. In the beef cattle barns, ammonia ranged from 3.1 to 16.3 ppm and low concentrations of hydrogen sulfide were detected at some animal breathing heights. The gas concentrations detected at each livestock farm were significantly higher in the animal breathing zones than in human breathing zones (p<0.0001). Conclusions: We found a difference in gas concentrations between human breathing zones and animal breathing zones. Gas monitoring should be conducted to improve the related environment considering both workers' and animals' health and safety.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1519-1530
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• 2020

As livestock farms grow in size, the number of breeding individuals increases, making it difficult to manage livestock. Livestock farms require an integrated management system such as a monitoring system, an access control system, and an abnormal behavior detection system to manage livestock houses. In this paper, a smart korean cattle livestock management system using IoT and AI technology was proposed for livestock management in livestock farms. The smart korean cattle farm management system consists of a monitoring and control system, a vehicle access management system, and an abnormal cattle behavior detection system. It is expected that this will help manage large-scale livestock houses, and additional research is needed to improve the performance of abnormal behavior detection in the future.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.519-534
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• 2023

Rumination in cattle is closely related to their health, which makes the automatic monitoring of rumination an important part of smart pasture operations. However, manual monitoring of cattle rumination is laborious and wearable sensors are often harmful to animals. Thus, we propose a computer vision-based method to automatically identify multi-object cattle rumination, and to calculate the rumination time and number of chews for each cow. The heads of the cattle in the video were initially tracked with a multi-object tracking algorithm, which combined the You Only Look Once (YOLO) algorithm with the kernelized correlation filter (KCF). Images of the head of each cow were saved at a fixed size, and numbered. Then, a rumination recognition algorithm was constructed with parameters obtained using the frame difference method, and rumination time and number of chews were calculated. The rumination recognition algorithm was used to analyze the head image of each cow to automatically detect multi-object cattle rumination. To verify the feasibility of this method, the algorithm was tested on multi-object cattle rumination videos, and the results were compared with the results produced by human observation. The experimental results showed that the average error in rumination time was 5.902% and the average error in the number of chews was 8.126%. The rumination identification and calculation of rumination information only need to be performed by computers automatically with no manual intervention. It could provide a new contactless rumination identification method for multi-cattle, which provided technical support for smart pasture.

• Journal of Veterinary Clinics
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• v.17 no.1
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• pp.28-31
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• 2000

An animall health monitoring system in Gyeongnam area(near Chinju) was studied to analysis of biochemical risk factors in 617 herds. Clinical serum factors such as glutamate oxaloacetate transaminase(GOT), glutamate pyruvate transaminase(GPT), Ca, P, Mg, glucose, and cholesterol were measured with automatic biochemical analyzer(Ra-X7T Techmmicon, USA). In serum analysis, 613 cattle were within normal llimits(GOT: 9.5-85 IU-dl, GPT: 25-77IU/dl, total protein: 5.8-8.5g/dl, Ca: 4.2-12.4mg/dl, P: 4.6-9.7mg/dl, Mg: 1.5-3.0mg/dl, glucose: 48-120mg/dl, Cholesterol: 70-170mg/dl), the other cattle showed high glucose and high cholesterol level. It is proposed that clinical serum factors to be estimated may be valuable for developing of animal health monitoring system model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2148-2161
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• 2019

In this paper, we present a real-time cattle action recognition algorithm to detect the estrus phase of cattle from a live video stream. In order to classify cattle movement, specifically, to detect the mounting action, the most observable sign of the estrus phase, a simple yet effective feature description exploiting motion history images (MHI) is designed. By learning the proposed features using the support vector machine framework, various representative cattle actions, such as mounting, walking, tail wagging, and foot stamping, can be recognized robustly in complex scenes. Thanks to low complexity of the proposed action recognition algorithm, multiple cattle in three enclosures can be monitored simultaneously using a single fisheye camera. Through extensive experiments with real video streams, we confirmed that the proposed algorithm outperforms a conventional human action recognition algorithm by 18% in terms of recognition accuracy even with much smaller dimensional feature description.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.4
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• pp.504-510
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• 2003

Rumen ecology plays an important role in the fermentation process and in providing end-products for ruminants. These studies were carried out to investigate variations in rumen factors namely pH, $NH_3-N$ and microorganisms in cattle and swamp buffaloes. Furthermore, studies on diurnal patterns of rumen fermentation and the effect of rumen digesta transfer from buffalo to cattle was conducted. Based on these studies, diurnal fermentation patterns in both cattle and buffaloes were revealed. It was found that rumen NH3-N was a major limiting factor. Rumen digesta transfer from buffalo to cattle from buffalo to cattle was achievable. Monitoring rumen digesta for 14d after transfer showed an improved rumen ecology in cattle as compared to that of original cattle and buffalo. It is probable that buffalo rumen digesta could be transferred. However, further research should be undertaken in these regards in order to improve rumen ecology especially for buffalo-based rumen.

• Korean Journal of Veterinary Research
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• v.42 no.3
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• pp.377-382
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• 2002

Bovine piroplasmosis caused by Theileria sergenti is a major cause of economic loss in livestock industry. Five cattle infected with Theileria sergenti showing severe and fatal anemia, confirmed by indirect immunofluorescent assay(IFA), were used in this study. Four cattle were treated with diminazene aceturate and one was not treated as the control. The therapeutic effect of diminazene aceturate against Theileria sergenti infection was monitored by detecting the 32kDa polypeptide specific for Theileria sergenti by the western blotting with both polyclonal and monoclonal antibodies. The 32kDa polypeptide detected at the beginning of diminazene aceturate treatment was not detectable after the treatment. It is postulated that the detection of the 32kDa polypeptide specific for Theileria sergenti may be a good tool for the diagnosis and monitoring the treatment progress of Theileria sergenti infection.