• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.247-257
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• 2020

Livestock epidemics, such as foot and mouth disease, are causing enormous economic losses due to their strong infectious power. Early detection of infectious diseases in livestock is very important, but it is difficult to diagnose early in individual farms, and there are frequent cases of transmission through inter-farm movement such as veterinarians and feeding vehicles. In this study, we studied the technology that enables rapid diagnosis without veterinarian farm visits and prevents further spread by automatically monitoring the body temperature of livestock using ubiquitous-based information and communication technology in the early stage of onset and sending it in real time. We have presented a technique for systematically managing livestock epidemics at the farm level, regional level, and national level by using the community mapping technique by using the remote medical treatment system linked to the automatically collected information. In this process, community mapping items for each step and stakeholders were derived for crowd sourcing based spatial information technology.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.117-124
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• 2021

Livestock behavioral analysis is a factor that has a great influence on livestock health management and agricultural productivity increase. However, most digital devices introduced for behavioral analysis of livestock do not provide raw data and also provide limited analysis results. Such a closed system makes it more difficult to integrate data and build big data, which are essential for the introduction of advanced IT technologies. Therefore, it is necessary to supply farm-scale data collection devices that can be easily used at low cost. This study presents a data collection system for analyzing the behavior of livestock. The system consists of a number of miniature computing units that operate wirelessly, and collects livestock body temperature and acceleration data, location information, and livestock environment data. In addition, this study presents an algorithm for estimating the behavior of livestock based on the collected acceleration data. For the experiment, a system was built in a Korean cattle farm in Icheon, Gyeonggi-do, and data were collected for 20 Korean cattle, and based on this, the empirical and analysis results were presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.297-300
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• 2015

이 논문에서는 가축관리의 효율성을 높일 수 있는 IoT 기술 기반의 지능형 축산정보 통합관리 시스템 및 구축 방안을 제안한다. 제안한 시스템은 체온, 활동량, 군집도와 같은 개체특성 정보와 온도, 습도, CO2 농도 등의 축사환경 정보를 무선센서 네트워크를 통해 실시간으로 수집한다. 수집된 정보는 가축개체별 생애주기 사양관리 스케쥴과 연동되어 신속한 관리가 필요한 이상상황을 자동으로 인식한다. 또한, 축적된 양질의 축산지식 정보는 허가된 범위 내에서 접종사, 수정사, 수의사, 축산공무원 등 축산종사자에게 공유된다. 제안한 시스템은 대규모 축사에서 수정, 분만, 질병관리 등 사양관리 시기를 자동으로 감지하여 축주에게 알려줄 수 있기 때문에 최소한의 시간과 비용으로 가축관리 효율성과 생산성을 높일 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1318-1327
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• 2012

With the recent increased risk of livestock disease spread and human infection, livestock disease control has become very important. Consequently, there has been an increased attention on an implantable real-time monitoring and traceability system for individual cattle. Therefore, we have developed a robust monitoring and traceability system based on an implantable MFAN/RFID sensor tag. Our design combines the MFAN technology that is capable of robust wireless communication within cattle sheds and the 900MHz RFID technology that is capable of wireless communication without battery. In MFAN/RFID implantable sensor tag monitoring system, UHF sensor tag is implanted under the skin and accurately monitors the body temperature and biological changes without being affected by external environment. In order to acquire power needed by the tag, we install a MFAN/RFID tranceiver on the neck of cattle. The MFAN coordinator passes through the MFAN node and the RFID-reader-combined MFAN/RFID transceiver and transmits/receives the data and power for the sensor tag. The data stored in the MFAN coordinator is transmitted via the internet to the livestock history monitoring system, where it is stored and managed. By developing this system, we hope to alleviate the problems related to livestock disease control.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.292-301
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• 2016

Because damages arising from the occurrence of foot-and-mouth disease (FMD) are very great, it is essential to make a preemptive diagnosis to cope with it in order to minimize those damages. The main symptoms of foot-and-mouth disease are body temperature increase, loss of appetite, formation of blisters in the mouth, on hooves and breasts, etc. in a cow or a bull, among which the body temperature check is the easiest and quickest way to detect the disease. In this paper, an algorithm to detect FMD from the hooves of cattle was developed and implemented for preemptive coping with foot-and-mouth disease, and a hoof check test is conducted after the installation of a high-resolution camera module, a thermo-graphic camera, and a temperature/humidity module in the cattle shed. Through the algorithm and system developed in this study, it is possible to cope with an early-stage situation in which cattle are suspected as suffering from foot-and-mouth disease, creating an optimized growth environment for cattle. In particular, in this study, the system to cope with FMD does not use a portable thermo-graphic camera, but a fixed camera attached to the cattle shed. It does not need additional personnel, has a function to measure the temperature of cattle hooves automatically through an image algorithm, and includes an automated alarm for a smart phone. This system enables the prediction of a possible occurrence of foot-and-mouth disease on a real-time basis, and also enables initial-stage disinfection to be performed to cope with the disease without needing extra personnel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1421-1427
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• 2018

Due to the rapid development of Internet-of-Things technology, different types of smart sensors are now devised and deployed widely. These smart sensors are now used in animal husbandry which was traditionally managed by the experience of farmers, such that wearable sensors for livestock, and the smart farm which is equipped with multiple sensors are utilized to increase the efficiency of livestock management. Herein, we consider a scheme in which the body temperature and the level of activity are measured by smart sensor which is attached to the neck of dairy cattle and the health condition is monitored based on collected data. Especially, we find that the estrous of dairy cattle which is one of most important metric in milk production, can be predicted with high precision using various machine learning techniques. By utilizing the proposed prediction scheme, estrous of cattle can be detected immediately and this can improve the efficiency of cattle management.

• Journal of Biosystems Engineering
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• v.16 no.4
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• pp.363-371
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• 1991

It is important to measure the somatic informations for stockbreeding automatization. This study was carried out for the development of wireless measurement system of temperature in living animals. New method to measure somatic temperature was developed using the single-channel wireless instrument. This system was constructed by oscillator, temperature sensor, wireless transmitter and receiver circuit, single processing circuit, and microcomputer. Two types of sensor were used and compared to measure the temperature. The thermistor sensor was more sensitive and accurate than platinum resistance sensor, however both sensors were performed efficiently. The single-channel wireless measurement systems developed could measure the somatic temperature successfully and offered a versatile system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2351-2357
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• 2010

Recently, USN technology has been spreaded to all areas of application systems. In addition to urban application systems such as u-City, u-Home and u-Education, u-Farming(ubiquitous farming) technology supports agricultural innovations in the farm. In the u-farming environment for livestock or plant production, key environmental factors i.e. temperature, humidity and luminosity are to be set optimally to increase productivity and safety by applying USN technology. This approach could change agricultural environment. In this paper, we proposed an implantable micro sensor node to be implanted into laying hen to monitor deep body temperature. This sensor node uses SoC(System-on-Chip) designed for USN. In addition to that, we discussed about further considerations on the practical use of proposed sensor node.

• Journal of Veterinary Clinics
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• v.20 no.3
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• pp.357-363
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• 2003

These studies were carried out to develop non-contact thermometer to take easily the body temperature of domestic animals instead of taking rectal temperature. For the studies, 86 cattle, 57 horses, 72 pigs, 43 goats, and 42 dogs were used and body parts as neck, flank, axilla, lateral abdomen, gluteus, inguinal region, or jugular groove were chosen for taking temperature according to different species. Two types of commercial non-contact thermometers were used to take the temperature of certain body part and at the same time the rectal temperature using digital thermo-meter was taken to compare the difference of temperature between rectum and certain body part. The difference of mean temperature in cattle between rectum and axilla and flank were 0.52 and $2.41^{\circ}C$, respectively, using non-contact thermometer I, whereas $3.02^{\circ}C$ between rectum and flank using thermometer II. The difference of mean temperature in horses between rectum and axilla, gluteus, and jugular groove were 0.52, 1.49, and $0.26^{\circ}C$, respectively, using thermometer I, whereas 2.28 ane $0.92^{\circ}C$ between rectum and gluteus or jugular groove using thermometer II. The difference of mean temperature in swine between rectum and flank, inguinal region, and neck were 1.23, 0.21, and $0.8^{\circ}C$, respectively, using thermometer I, whereas 1.42, 0.711, and $1.25^{\circ}C$ using thermometer II The difference of mean temperature in goats between rectum and lateral abdomen and inguinal region were 1.02 and $0.12^{\circ}C$, respectively, using thermometer I, whereas 1.96 and $1.01^{\circ}C$ using thermometer II. The difference of mean temperature in dogs between rectum and lateral abdomen, inguinal region, and neck were 3.26, 0.24, and $2.37^{\circ}C$, respectively, using thermometer I, whereas 3.45, 0.56, and $2.61^{\circ}C$ using thermometer II.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.127-137
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• 2018

Parturition is an important event for farmers as it provides economic gains for the farms. Thus, the effective management of parturition is essential to farm management. In particular, the unit price of cattle is higher than other livestock and the productivity of cattle is closely associated to farm income. In addition, 42% of calving occurs in the nighttime so accurate parturition predictions are all the more important. In this paper, we propose a method that accurately predicts the calving date by applying core body temperature of cattle to deep learning. The body temperature of cattle can be measured without being influenced by the ambient environment by applying an ingestible bio-sensor in the cattle's rumen. By experiment on cattle, we confirmed this method to be more accurate for predicting calving dates than existing parturition prediction methods, showing an average of 3 hour 40 minute error. This proposed method is expected to reduce the economic damages of farms by accurately predicting calving times and assisting in successful parturitions.