• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.161-168
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• 2019

Recently, video equipments such as CCTV, which is spreading rapidly, is being used as a means to monitor and cope with abnormal situations in almost governments, companies, and households. However, in most cases, since recognizing the abnormal situation is carried out by the monitoring person, the immediate response is difficult and is used only for post-analysis. In this paper, we present the results of the development of video surveillance system that automatically recognizing the abnormal situations and sending such events to the smartphone immediately using the latest deep learning technology. The proposed system extracts skeletons from the human objects in real time using Openpose library and then recognizes the human behaviors automatically using deep learning technology. To this end, we reconstruct Openpose library, which developed in the Caffe framework, on Darknet framework to improve real-time processing. We also verified the performance improvement through experiments. The system to be introduced in this paper has accurate and fast behavioral recognition performance and scalability, so it is expected that it can be used for video surveillance systems for various applications.

• Journal of Environmental Impact Assessment
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• v.30 no.5
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• pp.297-304
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• 2021

The environmental impact assessment(EIA) project in Korea has undergone changes and revisions in various evaluation items for about 30 years after the introduction of the Environmental Conservation Act (1997). However, despite the importance of land use evaluation items under the current EIA Act, there are insufficient studies to consider. Therefore, this study focused on the land-use evaluation items based on the EIA guidelines, reviewed 90 of the evaluation documents and consultation documents, and tried to suggest implications and supplementary points forthe domestic EIA land-use evaluation items. As a result, the paradigm was changing from land efficiency centered on development in the past to land efficiency centered on the natural environment and resource conservation. However, in spite of the manual for fitting the paradigm change, opinions on the conservation of the natural environment are still being drawn in the consultation document, so it needs improvement. Two improvements in the impact assessment process suggested in this study are the establishment of standardized spatial data and a quantitative impact and reduction method evaluation tool based on it. In particular, there is a need for a plan evaluation tool for land use arrangement and distribution that can solve the needs of minimizing damage to the natural environment and securing green space and a green network.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.213-223
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• 2022

This study was conducted to establish a Habitat Suitability index (HSI) based on literature research and field surveys on ecology and habitat of 'Hynobius leechii'. And this study will be used as basic data for qualitative evaluation of habitat environment. The survey sites were divided into natural habitats close to the prototype habitat and artificial restoration areas where Hynobius leechii was monitored. So the types of habitats were diversified. Hynobius leechii is a vulnerable species to climate change because it is affected by the microhabitat and has low mobility. HSI variables of Hynobius leechii were extracted through domestic and overseas literature, and standards were extracted from literature research and field survey. The standards were presented as a value of the physical allowable category in consideration of realization. To verify the study, an in-depth consultation was conducted by amphibians experts. HSI variables of Hynobius leechii were included 9 variables such as Overstory canopy cover(%), Understory cover(%), Water-pH, Soil-pH, Soil relative humidity(%), Leaf litter depth(cm), Rock substrates (%), Type of Coarse woody, Distance from Street or Pollutant(m).

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.47-58
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• 2022

In recent years, navigation aids, which plays as sea traffic lights, have been digitized, and are developing beyond simple sign purpose to provide various functions such as marine information collection, supervision, control, etc. For example, Busan Port which is located in South Korea is leading the application of the advanced technologies by installing cameras on buoys and recording video images to supervise maritime accidents. However, there are difficulties to perform their major functions since the advanced technologies require long-term battery operation and also management and maintenance of them are hampered by marine characteristics. This study proposes a system that can automatically notify maritime objects passing around buoys by analyzing image information. In the existing sensor-based accident prevention systems, the alarms are generated by a collision detection sensor. The system can identify the cause of the accident whilst even though it is difficult not possible to fundamentally prevent the accidents. Therefore, in order to overcome these limitations, the proposed a maritime object detection system is based on marine characteristics. The experiments demonstrate that the proposed system shows about 5 times faster processing speed than other existing algorithms.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.21-31
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• 2021

As the COVID-19 pandemic rapidly changes healthcare around the globe, the need for smart healthcare that allows for remote diagnosis is increasing. The current classification of respiratory diseases cost high and requires a face-to-face visit with a skilled medical professional, thus the pandemic significantly hinders monitoring and early diagnosis. Therefore, the ability to accurately classify and diagnose respiratory sound using deep learning-based AI models is essential to modern medicine as a remote alternative to the current stethoscope. In this study, we propose a deep learning-based respiratory sound classification model using data collected from medical experts. The sound data were preprocessed with BandPassFilter, and the relevant respiratory audio features were extracted with Log-Mel Spectrogram and Mel Frequency Cepstral Coefficient (MFCC). Subsequently, a Parallel CNN network model was trained on these two inputs using stacking ensemble techniques combined with various machine learning classifiers to efficiently classify and detect abnormal respiratory sounds with high accuracy. The model proposed in this paper classified abnormal respiratory sounds with an accuracy of 96.9%, which is approximately 6.1% higher than the classification accuracy of baseline model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.115-131
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• 2022

Carbon dioxide (CO₂) emissions from the transportation sector in South Korea accounts for 16.5% of all CO₂ emissions, and road transportation accounts for 96.5% of this sector's emissions in South Korea. Hence, constant research is being carried out on methods to reduce CO₂ emissions from this sector. With the emerging use of smart crossings, attempts to monitor individual vehicles are increasing. Moreover, the potential commercial deployment of autonomous vehicles increases the possibility of obtaining individual vehicle data. As such, CO₂ emission research was conducted at five signalized intersections in the Gangnam District, Seoul, using data such as vehicle type, speed, acceleration, etc., obtained from image detectors located at each intersection. The collected data were then applied to the MOtor Vehicle Emission Simulator (MOVES)-Matrix model-which was developed to obtain second-by-second vehicle activity data and analyze daily CO₂ emissions from the studied intersections. After analyzing two large and three small intersections, the results indicated that 3.1 metric tons of CO₂ were emitted per day at each intersection. This study reveals a new possibility of analyzing CO₂ emissions using actual individual vehicle data using an improved analysis model. This study also emphasizes the importance of more accurate CO₂ emission analyses.

• Journal of Environmental Impact Assessment
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• v.32 no.2
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• pp.61-71
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• 2023

As differences in the impact of each species on a spatial scale occur, analysis at the landscape scale is necessary to evaluate the impact of a development project. In previous studies, the Incidence Function Model (IFM) based on meta population theory was used to analyze the impact of species on the environment that changes according to urban development. However, since the model was required at least 10 occupied areas, it is difficult to use it for species that are difficult to monitor such as endangered species. Therefore, we proposed the Incidence Function Model (IFM) using species distribution model to fill the species data. In addition, we reviewed whether the developed model can be used in environmental impact assessment. As a result of the analysis, the minimum occupancy of Prionailurus bengalensis on urban development decreased to 56.5% and the possibility of survival to 28.7%. We confirmed that It rapidly decreased from the reference points of 230 and 70habitats through analysis of the meta-population capacity according to the decrease in the number of habitats. These results can be assessing the environment impact of each species on habitat loss. And it can support decision-making on the minimum number and area of habitat for species protection. This study is expected to be used as basic data for environment impact assessment on before and after development projects and mitigation measures plans, thereby increasing the effectiveness of reduction plans.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.215-229
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• 2023

Objectives: To validate the effectiveness of a real-time chemical exposure monitoring system developed by KOSHA (Korea Occupational Safety and Health Agency), we applied the system to a workplace in the electronics industry for 153 days. Methods: The monitoring system consisted of a PID chemical sensor, a LTE communication equipment, and a web-based platform. To monitor chemical exposure, four sets of sensors were placed in two manufacturing tasks - inspection and jig cleaning - which used TCE as a degreasing agent. We reviewed previous reports of work environment measurements and conducted a new work environment measurement on one day during the period. The PID sensor systems detected the chemical exposure levels in the workplace every second and transmitted it to the platform. Daily average and maximum chemical exposure levels were also recorded. Results: We compared the results from the real-time monitoring system and the work environment measurement by traditional methods. Generally, the data from the real-time monitoring system showed a higher level because the sensors were closer to the chemical source. We found that 28% of jig cleaning task data exceeded the STEL. Peak exposure levels of sensor data were useful for understanding the characteristics of the task's chemical use. Limitations and implications were reviewed for the adoption of the system for preventing poisoning caused by chemical substances. Conclusions: We found that the real-time chemical exposure monitoring system was an efficient tool for preventing occupational diseases caused by chemical exposure, such as acute poisoning. Further research is needed to improve the reliability and applicability of the system. We also believe that forming a social consensus around the system is essential.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.21-22
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• 2020

낙동강 하굿둑(이하 하굿둑)은 1987년 부산 사하구와 강서구 사이에 건설되어 하류 지역의 바닷물 유입을 막아 부산, 울산, 경남 등에 안정적으로 생활·농업·공업 등의 분야에 용수를 공급하는 역할을 해왔다. 현재, 하굿둑의 수문은 낙동강 상류로부터 하류로 흘러내려오는 민물(담수)을 방류하기 위해서만 하굿둑 수문을 개방하고 있다. 하구는 하천의 담수와 바다의 염수가 서로 만나는 구역으로 바닷물과 염수의 밀도차에 의한 혼합으로 자연상태의 하구에서는 담수와 염수가 섞이는 기수역이 형성되며, 이러한 특성으로 하구 인근의 지역에서는 일반적인 하천 및 해양, 연안과는 분명히 구별되는 생태계가 조성된다. 하굿둑 건설이후 바닷물(해수)과 민물(담수)이 만나는 낙동강 어귀에 기수생태계가 사라지면서 바닷물이 유입될 수 있도록 하여 생태계를 복원해야 한다는 필요성이 제기되어 왔으며, 하굿둑이 지역에 기여해온 사실은 분명하나 하굿둑으로 인해 생태계 단절이 발생하고 기수생태계가 파괴되었기 때문에 이를 해결하기 위해서는 하굿둑을 개방하여 과거 기수생태계를 복원해야 한다는 목소리가 높아지고 있다. 이에 따라 정부에서는 하굿둑의 기수생태계 복원을 위해서 관계기관 합동으로 의사결정을 하고 효율적인 개방 방안을 모색하는 실무협의회를 구성하여 운영 중이고, 실무협의회 논의를 통해 5개 주요 관계기관(환경부, 국토부, 해양수산부, 부산광역시, K-water) 공동으로 "낙동강하굿둑 운영개선 및 생태복원 방안 연구용역"을 추진 중이다. 2018년 1단계 용역이 완료되었으며, 2019년부터 2단계 연구용역을 추진 중이고 하굿둑 개방의 수준별로 각종 영향을 검토한 후 대책을 마련하여 기수생태계 복원 방안을 수립하는데 그 목적이 있다. 2단계 연구용역에서는 과학적이고 합리적인 기수생태계 복원방안 마련을 위해서 실제로 해수를 유입시키는 3차례의 실증실험 및 수리모형실험 등을 추진한다. 기존 연구들에서도 수문개방에 따른 해수유입 영향에 대해 모델링을 통해서 분석했지만 이는 검증이 이루어지지 않은 결과로 이번 용역에서는 실제 해수를 유입시키고 염분의 침투 및 각종 수생태 영향을 모니터링 한 후 그 결과를 반영하여 모델링을 고도화하고 있다. 최종적으로 고도화된 모델링 결과를 기반으로 기수생태계 조성 방안별로 염분, 수질, 수생태, 침퇴적 등 각종 분야에 대한 정확한 영향을 분석하고 이에 대한 대책을 포함하여 최종적으로 바람직한 기수생태계 복원 방안을 제시할 계획이다. 기수생태계 복원 방안이 계획에만 그치지 않고 실행으로 연결시키기 위해서 필요성에 대한 이해를 바탕으로 공감대를 형성해 나아가고 있으며 지역주민, 전문가, 관계기관 등 민(民)·관(官)·학(學) 다양한 의견을 수렴하여 하구지역내 수량-수질-수생태를 종합적으로 고려하여 복원 방안을 마련 후 사회적인 합의를 추진하여 확정할 예정이며, 하구의 안정적인 관리를 위해 AI 등 4차 산업혁명기술을 적극 적용하는 스마트한 하구물관리(Smart Estuary Watershed Management)"를 활용한 "하구통합물관리" (Estuary Integrated Watershed Management) 등 과학적인 관리를 추진할 계획이다.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.2
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• pp.1-12
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• 2023

In the current era of the global mobile smart device revolution, electronic devices are required in all spaces that people interact with. The establishment of the internet of things (IoT) among smart devices has been recognized as a crucial objective to advance towards creating a comfortable and sustainable future society. In-mold electronic (IME) processes have gained significant industrial significance due to their ability to utilize conventional high-volume methods, which involve printing functional inks on 2D substrates, thermoforming them into 3D shapes, and injection-molded, manufacturing low-cost, lightweight, and functional components or devices. In this article, we provide an overview of IME and its latest advances in application. We review biomimetic nanomaterials for constructing self-supporting biosensor electronic materials on the body, energy storage devices, self-powered devices, and bio-monitoring technology from the perspective of in-mold electronic devices. We anticipate that IME device technology will play a critical role in establishing a human-machine interface (HMI) by converging with the rapidly growing flexible printed electronics technology, which is an integral component of the fourth industrial revolution.