• 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 Auto-vehicle Safety Association
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• v.7 no.2
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• pp.39-43
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• 2015

NDIR (Non-dispersive infrared Rays) alcohol sensor has been prototyped and its temperature characteristics were measured. In order to design novel optical alcohol sensor, elliptical structures with one common foci were modeled and analyzed their optical properties. After analyzing elliptic optical structures, a prototype alcohol sensor module was tested according to the temperature variations from $-20^{\circ}C$ to $35^{\circ}C$. The offset voltages of alcohol sensor decreased from 1.1056 V at the temperature $-20^{\circ}C$ to 0.7339 V at $35^{\circ}C$. However, the highest sensitivity of alcohol sensor showed about $303{\mu}V/ppm$ at room temperature.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1503-1508
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• 2009

This study applied image processing techniques, constructed to real-time, to thermal infrared camera image. Thermal infrared image data was utilized for hot mapping, cool mapping, and rainbow mapping according to changing temperature. It was histogram image processing techniques so that detected shade contrast function of the thermal infrared image, and the thermal infrared image's edge was extracted to classification of object. Moreover, extraction of temperature from image was measured by using the image information program.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.1
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• pp.32-39
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• 2013

Although space-borne satellites are useful in obtaining information all around the world, they cannot observe at a suitable time and place. In order to overcome these limitations, an airborne remote sensing system was developed in this study. It is composed of a SAR sensor and a thermal infrared sensor. Additionally GPS, IMU, and thermometer/hygrometer were attached to the plane for radiometric and geometric calibration. The brightness of SAR image varies depending on surface roughness, and capillary waves on the sea surface, which are easily generated by sea winds, induce the surface roughness. Thus, sea surface wind can be estimated using the relationship between quantified SAR backscattering coefficient and the sea surface wind. On the other hand, thermal infrared sensor is sensitive to measure object's temperature. Sea surface temperature is obtained from the thermal infrared sensor after correcting the atmospheric effects which are located between sea surface and the sensor. Using these two remote sensing sensors mounted on airplane, four test flights were carried out along the west coast of Korea. The obtained SAR and thermal infrared images have shown that these images were useful enough to monitor coastal environment and estimate marine meteorology data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.153-158
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• 2019

In this paper, we analyze the infrared feature for the small coast targets according to the surrounding environment for autonomous flight device equipped with an infrared imaging sensor and we propose Cross Duality of Neural Network (CR-DuNN) method which can classify the target and clutter in coastal environment. In coastal environment, there are various property according to diverse change of air temperature, sea temperature, deferent seasons. And small coast target have various infrared feature according to diverse change of environment. In this various environment, it is very important thing that we analyze and classify targets from the clutters to improve target detection accuracy. Thus, we propose infrared feature learning algorithm through LSTM neural network and also propose CR-DuNN algorithm that integrate LSTM prediction network with Du-CNN classification network to classify targets from the clutters.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.115-118
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• 2000

Uncooled pyroelectric infrared detectors based on BST(B $a_{-x}$S $r_{x}$Ti $O_3$) thin films have been fabricated by RF magnetron sputtering and surface Micromachining technology. The detectors form BST thin film ferroelectric capacitors grown by RF magnetron sputtering on N/O/N(S $i_3$ $N_4$/ $SiO_2$/S $i_3$ $N_4$) membrane. The sputtered BST thin film exhibits highly c-axis oriented crystal structure that no poling treatment for sensing applications is required. This is an essential factor to increase the yield for realization of an infrared image sensor. surface-Micromachining technology is used to lower the thermal mass of the detector by giving maximum sensor efficiency Gold-black is evaporated on top of the sensing elements used the thermal evaporator. fabricated uncooled pyroelectric infrared detectors is highly output voltage at the low temperature(1$^{\circ}C$).).).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.263-270
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• 2018

Land surface temperature is known to be an important factor in understanding the interactions of the ground-atmosphere. However, because of the large spatio-temporal variability, regular observation is rarely made. The existing land surface temperature is observed using satellite images, but due to the nature of satellite, it has the limit of long revisit period and low accuracy. In this study, in order to confirm the possibility of replacing land surface temperature observation using satellite imagery, images acquired by TIR (Thermal Infrared) sensor mounted on UAV (Unmanned Aerial Vehicle) are used. The acquired images were transformed from JPEG (Joint Photographic Experts Group) to TIFF (Tagged Image File Format) format and orthophoto was then generated. The DN (Digital Number) value of orthophoto was used to calculate the actual land surface temperature. In order to evaluate the accuracy of the calculated land surface temperature, the land surface temperature was compared with the land surface temperature directly observed with an infrared thermometer at the same time. When comparing the observed land surface temperatures in two ways, the accuracy of all the land covers was below the measure accuracy of the TIR sensor. Therefore, the possibility of replacing the satellite image, which is a conventional land surface temperature observation method, is confirmed by using the TIR sensor mounted on UAV.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3079-3089
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• 2015

In this paper, a smart constrained application protocol (CoAP)-based gateway with a border router is proposed for home safety services to remotely monitor the trespass, fire, and indoor air quality. The smart CoAP gateway controls a home safety sensor node with a pyroelectric infrared motion sensor, a fire sensor, a humidity and temperature sensor, and a non-dispersive infrared CO2 sensor and gathers sensing data from them. In addition, it can convert physical sensing data into understandable information and perform packet conversion as a border router for seamless connection between a low-power wireless personal area network (6LoWPAN) and the Internet (IPv6). Implementation and laboratory test results verify the feasibility of the smart CoAP gateway which especially can provide about 97.20% data throughput.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.69-76
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• 2019

Microheaters with different structures were fabricated and compared to find an optimal configuration enhancing the performances of $C_2H_2$ gas sensor. Three temperature sensors were integrated on the surface of the insulation layer over the microheater, and resistance changes were observed to check the generated heat from the microheater. A low operating voltage of 1mV was applied to the temperature sensor to minimize any influence of thermal heat from the resistance type temperature sensor, whereas high voltages in the range between 10 and 20V were applied to the microheater. A microheater structure generating maximum heat at low voltage was determined. The generated heat was verified by the temperature sensors on the top of the $Si_3N_4$ and infrared camera. A long term stability and accuracy of the microheater were observed. The developed microheater was applied to enhance the performances of $C_2H_2$ gas sensor and successfully confirmed that the developed microheater greatly contributes to the improvement of sensitivity and selectivity of gas sensor.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.226-235
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• 2023

This study aimed to supplement the shortcomings of the Multiple-sensor-based Frost Observation System (MFOS). The developed frost observation system is an improvement of the existing system. Based on the leaf wetness sensor (LWS), it not only detects frost but also functions to predict surface temperature, which is a major factor in frost occurrence. With the existing observation system, 1) it is difficult to observe ice (frost) formation on the surface when capturing an image of the LWS with an RGB camera because the surface of the sensor reflects most visible light, 2) images captured using the RGB camera before and after sunrise are dark, and 3) the thermal infrared camera only shows the relative high and low temperature. To identify the ice (frost) generated on the surface of the LWS, a LWS that was painted black and three sheets of glass at the same height to be used as an auxiliary tool to check the occurrence of ice (frost) were installed. For RGB camera shooting before and after sunrise, synchronous LED lighting was installed so the power turns on/off according to the camera shooting time. The existing thermal infrared camera, which could only assess the relative temperature (high or low), was improved to extract the temperature value per pixel, and a comparison with the surface temperature sensor installed by the National Institute of Meteorological Sciences (NIMS) was performed to verify its accuracy. As a result of installing and operating the MFOS v2, which reflects these improvements, the accuracy and efficiency of automatic frost observation were demonstrated to be improved, and the usefulness of the data as input data for the frost prediction model was enhanced.