• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.735-740
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• 2022

The construction is the industry with the highest fatalities, and the fatalities has not decreased despite various institutional improvements. Accordingly, real-time safety management by applying artificial intelligence (AI) to CCTV images is emerging. Although some research on worker detection by applying AI to images of construction sites is being conducted, there are limitations in performance expression due to problems such as complex background due to the nature of the construction industry. In this study, the YOLO model and the OpenPose model were fused to improve the performance of worker detection and posture estimation to improve the detection performance of workers in various complex conditions. This is expected to be highly useful in terms of unsafe behavior and health management of workers in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.160-166
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• 2012

We performed the development and performance evaluation of reflective type heart rate measurement system for PAPS. We used chip LED and chip photo TR. for low power driving. The measured PPG signal is preprocessed using high pass filter and low pass filter, and the preprocessed signal is displayed by LabVIEW. Also LabVIEW include the algorithm that extract effective signal and calculate the heart rate. We made sure that it will be able to apply to measurement equipment with high accuracy and repetition from exercising subject using this system and algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.387-392
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• 2014

Now a days, there are various application functions to transmit from vehicles to the Internet and vice versa. And the communication can be operated through a roadside infrastructure including with possible use of routing protocols. Specifically, autonomous vehicles for remote driving and monitoring requires transmitting of high depth of multimedia such as video. Especially in a populated urban area, an efficient network is vital because of handling a great amount of the data. Therefore, in this paper, efficient network topology for a crossroad in urban area is suggested by performance evaluation of vehicular networks using a wireless LAN and a routing protocol. For the performance evaluation, various vehicular network topologies are designed and simulated in OPNet simulator.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.329-334
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• 2014

Recently, various electronic functions are developed for car drivers as the advent of electrical automobile. Especially, there are functions to examine for preventing drowsy or healthcare through monitoring brainwave(EEG) of drivers in real time. This function can be provided by transmitting driver's EEG, and the network function for transmission among cars or between car and road side infrastructure is a vital issue. Therefore, in this paper, to provide efficient routing protocol for transmitting EEG data at a cross road in an urban area, 5 different wireless communication network applied each routing protocol such as AODV, DSR, GRP, OLSR, and TORA is designed and simulated in the OPNet network simulator, then it is evaluated for the result.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.917-922
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• 2016

There are many researches related on the brain wave signals to monitor the state of human health. Especially, some patients in the medical hospital need to be monitored in case of emergencies such as a seizure, an epilepsy and so on. To support QoS of the brain wave network in the hospital is a vital issue and the Opnet simulator is used for this experiment. So the efficient network topology is required for the stability of the brain wave network service. The brain waves of the patients are collected from the sensor devices in the network. Two different sensor network topologies are suggested and simulated for the comparison of the network performance. One topology is localized and the other is non-localized network. The simulation is operated with the Opnet simulator.

• Proceedings of the KIEE Conference
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• 2008.10a
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• pp.83-84
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• 2008

인구의 증가로 인한 전력수요의 증가는 가공 및 지중 송진설비의 대용량화로 이어져왔다. 그러나 최근 도시 경관과 전자파로 인한 건강 등에 대한 관심이 급증하면서 주거지 주변 송전선로 실리에 대한 민원이 증가하고 있다 을에 대한 대안으로 대용량 전력송전이 가능하고 가공 및 지중송전의 단점을 보완한 가스결연 송전선로(Gas Insulated Transmission Line, GIL)가 개발되었다. 선진국에서는 가스 절연으로 우수한 절연성능과 안정성을 가지며, 기존 교통용 터널 또는 지하 전력구에 설치함으로써 주변 경관을 해치지 않고 낮은 전계 형성 등의 장점을 가진 가스절연송전선로의 연구와 개발에 많은 노력 기울이고 있다[$1{\sim}5$]. 본 논문에서는 전력기기들의 결함진단에 많이 사용되는 부분방전 측정을 가스절연 송전선로에 적용할 수 있는 최적의 측정용 센서를 개발하여 유사한 구조를 가지는 75kV GIS Mock-up과 Free moving particle 모의 방전 셀을 이용하여 발생시킨 부분방전 신호를 측정하여, 광대역 특성을 보이는 대수주기 패치 안테나와의 성능을 비교하였다.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.418-427
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• 2020

The measurement of meat freshness at meat markets is important for the health of consumers. Currently a variety of sensors have been studied for the measurement of the meat freshness. Therefore, the analysis of sensor data is needed for the reduction of measurement errors. In this paper, we analyze the freshness measurement data of ten sensors based on deep learning. The measured data are composed of beef, pork and chicken, whose reliability and noise-robustness are examined by a deep neural network. Further, to search for multiple sensors better than a torrymeter, PCA (principle component analysis) is carried. Then, we validated that the performance of the three sensors outperforms the torrymeter in the experiment.

• Journal of IKEEE
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• v.24 no.2
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• pp.523-528
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• 2020

With a widespread of sensor-rich mobile devices, the analysis of human activities becomes more general and simpler than ever before. In this paper, we propose two deep neural networks that efficiently and accurately perform human activity recognition (HAR) using tri-axial accelerometers. In combination with powerful modern deep learning techniques like batch normalization and LSTM networks, our model outperforms baseline approaches and establishes state-of-the-art results on WISDM dataset.

• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.128-134
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• 2011

The objective of this study is to analyze the major factors of indoor environment that affect the satisfaction of the occupancy in multi-family residential buildings. The results of this study can contribute to improving the comfort of the residents effectively as they are applied preferentially at the design and construction stages. The indoor environment factors investigated for the analysis included thermal, light, air and the acoustic environment. The individual factors were derived from the 'indoor environment' assessment indices of the green building certificate systems of various countries. Based on these, a questionnaire was prepared to conduct the Post Occupancy Evaluation. The survey results were statistically analyzed.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.657-662
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• 2019

The power consumption of wearable sensors and electrocardiogram regulators should be very low to extend the network lifetime and anticipated QoS( : Quality of Service) control such as error correction and authentication of data processed by WBAN( : Wireless Body Area Network) nodes is important. Therefore, QoS control is the most urgent concern to implement WBAN in health monitoring regulations. For optimal QoS control, we compare the energy efficiency and the average number of transmissions with IEEE 802.15.6 and the error correction method considering energy efficiency. The performance of the proposed error correction technique shows that the energy efficiency and the transmission rate are improved by adjusting the coding rate appropriately using the channel estimation.