• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.117-127
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• 2024

Purpose: The purpose is to conduct basic research to save energy and improve the safety of manufacturing plant infrastructure by comprehensively monitoring energy management, temperature, humidity, dust and gas, air quality, and machine operation status in small and medium-sized manufacturing plants. Method: To this end, energy-related data and environmental information were collected in real time through digital power meters and IoT sensors, and research was conducted to disseminate and respond to situations for energy saving through monitoring and analysis based on the collected information. Result: We presented an application plan that takes into account energy management, cost reduction, and safety improvement, which are key indicators of ESG management activities. Conclusion: This study utilized various sensor devices and related devices in a smart factory as a practical case study in a company. Based on the information collected through research, a basic system for energy saving and safety improvement was presented.

• Korean Journal of Environmental Agriculture
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• v.24 no.4
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• pp.386-390
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• 2005

This study was conducted to develop the biofilter fur reducing ammonia $(NH_3)$ and hydrogen sulfide $(H_2S)$ gas emission from a pig house. A biofilter was designed and constructed by a type of squeeze air into the column type of air flow upward. Its column size was ${\Phi}260{\times}360mm$. It was used pressure drop gauge, turbo blower, air temperature, velocity sensor and control program that was programed by LabWindows CVI 5.5. Mixing materials were consisted with composted pine tree bark and perlite with 7:3 ratio (volume). The biofilter media inoculated with ammonia (Rhodococcus equi A3) and hydrogen sulfide (Alcaligenes sp. S5-5.2) oxidizing microorganisms was installed in a commercial pig house to analyzed the effectiveness of biogas removal for 10 days. Removal rates of ammonia and hydrogen sulfide gases were 90.8% and 81.5%, respectively. This result suggests that the pine compost-perlite mixture biofilter is effective and economic for reducing ammonia ana hydrogen sulfide gases.

• Journal of Environmental Health Sciences
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• v.46 no.6
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• pp.627-635
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• 2020

Objectives: Indoor air quality has become more important aspeople spend most of their times indoors. Since students spend most of their times at home or at school, they are more likely to be exposed to indoor air pollutants. Ventilation in school classrooms can affect health and learning performance. In this study, ventilation deficiency was evaluated in school classrooms using Monte Carlo simulation. Methods: This study used sensor-based monitoring for six months to measure carbon dioxide (CO2) concentrations in classrooms in elementary, middle, and high schools. The volume of the classroom and the number of students were investigated, and the students' body surface area was used to calculate the CO2 emission rate. The distribution of ventilation rates was estimated by measured CO2 concentration and a mass-balance model using Monte Carlo simulation. Results: In the elementary, middle, and high schools, the average CO2 concentrations exceeded 1000 ppm, indicating that the ventilation rates were insufficient. The ventilation rates were deficient from July to August and in December, but showed relatively high ventilation rates in October. Forty-three percent of elementary schools, 56% of middle schools, and 62% of high schools showed insufficient ventilation rates. Conclusions: The ventilation rates calculated in elementary, middle and high schools were found to be quite insufficient. Therefore, proper management is needed to overcome the lack of ventilation and improve air quality.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.1-17
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• 2022

This study analyzed the PM_2.5 pattern by using data measured for one year from June 2020 to May 2021 by 21 low-cost sensors installed near the Changwon National Industrial Complex in Changwon, Gyeongsangnam-do. For the PM_2.5 pattern, the land use types around the measuring points and meteorological factors such as air temperature and wind speed were considered. The PM_2.5 concentration was high from November to March in winter, and from 1 to 9 in the morning and early in the morning by time zone. The concentration of PM_2.5 was higher as it got closer to the industrial area, but the concentration was lower in the residential area and public facility area. In terms of meteorological factors, the higher the air temperature and wind speed, the lower the concentration of PM_2.5. As a result of this study, it was possible to identify the PM_2.5 patter near Changwon National Industrial Complex. This result will be useful data that can be used in urban and environmental planning to improve air quality including PM_2.5 in urban area in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.536-539
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• 2018

In this paper, we propose a system that analyzes environment information by using deep learning and then provides a suitable environment for users by predicting environmental information change. As the level of living improves, interest in improving the quality of life is increasing. In particular, as the air quality deteriorated due to the recent occurrence of dust, smog, fine dust, and ultrafine dust, the indoor air quality as well as the outdoor air became a serious problem. The increase of indoor pollution due to the lack of ventilation and the use of chemicals is a serious problem for modern people who have a lot of indoor living. In order to solve this indoor air pollution, a system has been proposed that measures the state of air quality through sensors and maintains proper temperature and humidity. However, existing system has a difficulty to apply most of the atmospheric environment information to various users depending on sensors only. The system proposed in this paper predicts the indoor environment by analyzing the indoor pollution information collected through the sensor using the deep learning. Then, the predicted indoor environment is modeled and learned in this system, and the environment suitable for the user is suggested. Afterwards, the system receives feedback from the user and repeats the process of re-learning the proposed environment so that it can create the optimal environment for the user.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.5
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• pp.753-758
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• 2016

Moisture content influences physiological characteristics of microbes and physical structure of solid matrices during composting of animal manure. If moisture content is maintained at a proper level, aerobic microorganisms show more active oxygen consumption during composting due to increased microbial activity. In this study, optimum moisture levels for composting of two bedding materials (sawdust, rice hull) and two different mixtures of bedding and beef manure (BS, Beef cattle manure+sawdust; BR, Beef cattle manure+rice hull) were determined based on oxygen uptake rate measured by a pressure sensor method. A broad range of oxygen uptake rates (0.3 to 33.3 mg $O_2/g$ VS d) were monitored as a function of moisture level and composting feedstock type. The maximum oxygen consumption of each material was observed near the saturated condition, which ranged from 75% to 98% of water holding capacity. The optimum moisture content of BS and BR were 70% and 57% on a wet basis, respectively. Although BS's optimum moisture content was near saturated state, its free air space kept a favorable level (above 30%) for aerobic composting due to the sawdust's coarse particle size and bulking effect.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.48-54
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• 2020

Researchers recognized air pollution changes causing diseases and difficulties in living due to environmental pollution following various human activities, and have studied how to avoid fine dust harmful to the human respiratory system to be healthy. To this end, Arduino is used to equip fine dust level sensors in drones to measure the fine dust levels, visualize the measurements with LED indicator colors depending on the measurements to inform users of the danger of fine dust, and use the benefits of drones to specify dangerous fine dust zones and measure the fine dust levels. Users can see the changes depending on the fine dust levels in real time with the LED indicators. This will contributes to measuring fine dust levels easily in dangerous areas. Mission Planner (ArduPilot) is used to set up the GPS of drone, and store the data from the dust sensor as contents. This study aims to establish a method for improving the environment to measure fine dust levels with drones with LED indicators for fine dust, and reduce fine dust.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.1
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• pp.27-37
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• 1997

Internal combustion engine is the main source of environmental pollutants and therefore better technology is required to reduce harmful elements from the exhaust gases all over the world. Especially, harmful elements from the exhaust gases are caused by incomplete combustion of mixture inside the engine cylinder and this abnormal combustion like misfire or partial burning is the direct cause of the air pollution and engine performance degradation. the object of this research is to detect abnormal combustion like misfire and to keep the engine performance in the optimal operating state. Development of a new system therefore could be applied to a real car. To realize this, the spark-plug in a conventional ignition system is used as a misfire detection sensor and breakdown voltage is analyzed. In this research, bias voltage(about 3kV) was applied to the electrodes of spark-plug and breakdown voltage signal is obtained. This breakdown voltage signal is analyzed and found that a combustion phenomena in engine cylinder has close relationship with harmonic coefficient K which was introduced in this research. Newly developed combustion diagnostic method( breakdown voltage signal analysis) from this research can be used for the combustion diagnostic and combustion control system in an real car.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.4
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• pp.51-58
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• 2008

This paper presents a new design of the precision stage for the reticle in lithography process and a low hunting control method for the stage. The stage has three axes for X, Y, ${\theta}_z$ those actuated by three voice coil motors individually. The designed reticle stage system has three gap sensors and voice coil motors, and supported by four air bearings and the forward/inverse kinematics of the stage were solved to get an accurate reference position. When a stage is in regulating control mode, there always exist small fluctuations(stage hunting) in the stage movement. Because the low stage hunting characteristic is very important in recent lithography and nano-level applications, a special regulating controller for ultra low hunting is proposed in this paper. Also this research proposed the 2-step transmission system for preventing the noise infection from environmental devices. The experimental results showed the proposed regulating control system reduced hunting noise as 35nm(rms) when a conventional PID generates 77nm(rms) in the same mechanical system. Besides the reticle stage has 100nm linear accuracy and $1{\mu}rad$ rotation accuracy at the control frequency of 8kHz.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.22 no.3
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• pp.57-68
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• 2017

Continuous monitoring of spatial and temporal changes in key marine environmental parameters such as SST (sea surface temperature) near IORS (Ieodo Ocean Research Station) is demanded to investigate the ocean ecosystem, climate change, and sea-air interaction processes. In this study, we aimed to develop the system for continuously measuring SST using a TIR (thermal infrared) sensor mounted at the IORS. New SST algorithm is developed to provide SST of better quality that includes automatic atmospheric correction and emissivity calculation for different oceanic conditions. Then, the TIR-based SST products were validated against in-situ water temperature measurements during May 17-26, 2015 and July 15-18, 2015 at the IORS, yielding the accuracy of 0.72-0.85 R-square, and $0.37-0.90^{\circ}C$ RMSE. This TIR-based SST observing system can be installed easily at similar Ocean Research Stations such as Sinan Gageocho and Ongjin Socheongcho, which provide a vision to be utilized as calibration site for SST remotely sensed from satellites to be launched in future.