• Journal of the Korean earth science society
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• v.31 no.6
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• pp.563-572
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• 2010

Both multi-channel temperature monitoring and geophysical electric survey were performed together for an embankment to assess the leakage zone. Temperature variation according to space and time on the inner parts of engineering constructions (e.g.: dam and slope) can be basic information for diagnosing their safety problem. In general, as constructions become superannuated, structural deformation (e.g.: cracks and defects) could be generated by various factors. Seepage or leakage of water through the cracks or defects in old dams will directly cause temperature anomaly. This study shows that the position of seepage or leakage in dam body can be detected by multi-channel temperature monitoring using thermal line sensor. For that matter, diverse temperature monitoring experiments for a leakage physical model were performed in the laboratory. In field application of an old earth fill dam, temperature variations for water depth and for inner parts of boreholes located at downstream slope were measured. Temperature monitoring results for a long time at the bottom of downstream slope of the dam showed the possibility that temperature monitoring can provide the synthetic information about flowing path and quantity of seepage of leakage in dam body. Geophysical data by electrical method are also added to help interpret data.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1611-1617
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• 2018

The body temperature of livestock is directly related to the health of livestock such that it changes immediately when there exists health problem. Accordingly, the monitoring of livestock's temperature is one of most important tasks in farm management. However, the temperature of livestock is usually measured using skin-attached sensor which is significantly affected by the outside temperature and the condition of attachment which results in the inaccurate measurement of temperature. Herein we have proposed new scheme which estimates the body core temperature of cow based on measured data from neck-attached smart sensor. Especially, we have considered both schemes which estimate the exact temperature and which detect the unusually high temperature based on machine learning. We have found that the occurrence of high temperature can be detected accurately. The proposed scheme can be used in monitoring of health condition of cow and improving the efficiency of farm management.

• Geophysics and Geophysical Exploration
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• v.21 no.2
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• pp.82-93
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• 2018

Resistivity monitoring data at embankment dams are affected by the seasonal temperature variation. Especially when the seasonal temperature variation is large like Korea, the temperature effects may not be ignored in the longterm resistivity monitoring. Therefore, temperature effects can make it difficult to accurately interpret the resistivity monitoring data. In this study, through analyzing the time series of ground temperature collected at an embankment dam, ground temperature variations are calculated approximately. Then, based on the calculated temperature profile with depth, the inverted resistivity model of the embankment dam is corrected to remove the temperature effects. From these corrections, it was confirmed that the temperature effects are significant in the upper, superficial part of the dam, but can be ignored at depth. However, temperature correction based only on the temperature distribution in the dam body cannot remove the temperature effect thoroughly. To overcome this problem, the effect of temperature variation in the reservoir water seems to be incorporated together with the air temperature variation.

• Journal of Animal Environmental Science
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• v.20 no.3
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• pp.91-96
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• 2014

The temperature of a pig is the most key point in determining, it's health status. We wanted to monitor the body temperature of pig to find out if any changes would occur, we used 3 minipigs (about 20 kg) who were feed using a feeding system while being confined in a pig house. The infrared testings were taken from a height of 30 cm above the pigs backs over a period of 28 days. We were able to conclude that the results between the back and indoor temperature were y = 0.5487x + 18.459. These values were compared with the values found after infrared sensor results were taken. We found an error range of $0.004{\sim}1.82^{\circ}C$ and an average of $0.58^{\circ}C$. In conclusion, using an infrared thermometer made monitoring of pigs back possible. This system seems to be feasible and effective in monitoring pig temperature.

• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.62-66
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• 2014

This study aims to implement the emergency monitoring robot system which predicts the current state of the patients without visiting the medical institutions by measuring the basic health status of the user's blood pressure, heartbeat, and basic health status of body temperature in the disaster emergency situation based on the Smart Grid. By arranging a large number of sensor(blood pressure, heartbeat, body temperature sensor) and measuring the bio signs, so the attached wireless XBee sensor can be stored in DB of robot, and it aims to draw the current state of the patients by analysis of stored bio data. Among 300 data obtained from the sensor, 1st data to 100th data were used for learning, and from 101st data to 300th data were used for assessment. 12 results were different among the total 300 assessment data, so it shows about 96% accuracy.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.886-894
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• 2014

Recently, domestic animal disease caused tremendous damage to farmhouses and the damage stretched in nationwide with the spread of epidemic disease. To prevent animal diseases from happening again, the system development to easily measure the temperature of sick animals and identify of them is needed, thereby quickly treat them, reducing losses of farmhouses. However, a lack of related equipment and human resource hampered its effort to minimize its losses. This study tries to develop diagnosis system as part of measures to curb these domestic animal diseases. This paper present the 센서 node based on IEEE 802.15.4 which can be attached to the animal body for real-time temperature measurement. We design and implement tiny chip-type that can be attached to the body of animals. Then, we use available power only when measuring temperatures in a long term-basis. In this paper, the 센서 node was applied to horse's neck. We measure the horse's body temperature between $32.2^{\circ}C{\sim}33.7^{\circ}C$ and analyze phenomenon data for 4 months.

• Journal of Biomedical Engineering Research
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• v.41 no.1
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• pp.55-61
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• 2020

Recently, there have been many research on fever management using u-healthcare technology. Especially, fever of infants requires continuous monitoring of body temperature by parents. For infants between 4 weeks and under 5 years old, it is recommended to use an electronic thermometer or chemical thermometer in the axilla, or to use an infrared thermometer. However, in order to overcome the reality of not being able to waste significant time on continuous monitoring, there have been demands of patch type thermometers with the internet of things (IoT) and wireless communication technologies. Existing IoT thermometers are difficult to attach to infants' body because they do not take into account its size, and their interoperability is not guaranteed because they do not comply with standards in communication. Therefore, in this study, a patch-type thermometer with a diameter of 20 mm and a weight of 2.9 g was developed to manage the fever of infants, while it communicates wirelessly with Bluetooth Low Energy (BLE) communication protocol and complies with IEEE 11073 PHD(Personal Health Device) at the same time. We verified its performance under the requirements of thermometers regulated by the Korean Ministry of Food and Drug Safety.

• Smart Structures and Systems
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• v.19 no.3
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• pp.269-277
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• 2017

Recently, there has been significant interest in structural health monitoring for civil engineering applications. In this research, a specially designed tendon, proposed by embedding FBG sensors into the center king cable of a 7-wire strand tendon, was applied for long-term health monitoring of tensile forces on a ground anchor. To make temperature independent sensors, the effective temperature compensation of FBG sensors must be considered. The temperature sensitivity coefficient ${\beta}^{\prime}$ of the FBG sensors embedded tendon was successfully determined to be $2.0{\times}10^{-5}^{\circ}C^{-1}$ through calibrated tests in both a model rock body and a laboratory heat chamber. Furthermore, the obtained result for ${\beta}^{\prime}$ was formally verified through the ground temperature measurement test, expectedly. As a result, the ground temperature measured by a thermometer showed good agreement compared to that measured by the proposed FBG sensor, which was calibrated considering to the temperature sensitivity coefficient ${\beta}^{\prime}$. Finally, four prototype ground anchors including two tension ground anchors and two compression ground anchors made by replacing a tendon with the proposed smart tendon were installed into an actual slope at the Yeosu site. Tensile forces, after temperature compensation was taken into account using the verified temperature sensitivity coefficient ${\beta}^{\prime}$ and ground temperature obtained from the Korean Meteorological Administration (KMA) have been monitored for over one year, and the results were very consistent to those measured from the load cell, interestingly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.585-588
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• 2009

Wireless Sensor Network (WSN) is consisted of lots of tiny sensor nodes with limited processing power and computing resources. Thus, the most critical and fundamental element of WSN technology is sensor node, which gathers environmental information and transmits it to the user application systems. Due to the technological advancement, sensor nodes are become smaller and more intelligent, hence, expand their application area. Specifically, implantable wireless sensor node technology, to monitor and treat disease by implanting tiny sensor nodes into human body or livestock, shows further directions of WSN. In this paper, we have designed an implantable wireless sensor node to monitor livestock body temperature in real time. We also discussed on the additional considerations to implement real time bio-monitoring systems.