• Safety and Health at Work
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• 제11권4호
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• pp.537-542
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• 2020

Background: Personal protective equipment (PPE) has been designed in such a way to reduce accident rates. Unfortunately, existing PPE is rather ineffective as it is not able to provide warning signals when hazard is around. The integration of intelligent systems is envisaged to increase the efficiency of existing PPE. Methods: This project designed a safety vest incorporated with metal detectors which can provide immediate warning to the field workers when there is metal hazard around. This product has greater freedom of design via smart manufacturing as it involves the assembly of few commercially available parts into a single entity. Briefly, the metal detector is a do it yourself (DIY) kit, and the safety vest is purchasable from any local market. The DIY kit was connected to a copper coil and being sewed into the safety vest. Results: The metal detector induces beeping sound when there is metal hazard around. A total of 121 engineering students were introduced to the prototype before being requested to answer a survey associated with the design. Respondents have rated >3.00/5.00 for the design simplicity, ease of usage, and light weight. Meanwhile, respondents suggested that the design should be further improved by increasing the metal detection range. Conclusion: It is envisaged that the introduction of this smart safety vest will allow the workers to carry out their duties securely by reducing the accident rates. Particularly, such design is expected to reduce workplace accident especially during night time at construction sites where the visibility is low.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3904-3922
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• 2022

As a research hotspot, pedestrian detection has a wide range of applications in the field of computer vision in recent years. However, current pedestrian detection methods have problems such as insufficient detection accuracy and large models that are not suitable for large-scale deployment. In view of these problems mentioned above, a lightweight pedestrian detection and early warning method using a new model called you only look once (Yolov5) is proposed in this paper, which utilizing advantages of Yolov5s model to achieve accurate and fast pedestrian recognition. In addition, this paper also optimizes the loss function of the batch normalization (BN) layer. After sparsification, pruning and fine-tuning, got a lot of optimization, the size of the model on the edge of the computing power is lower equipment can be deployed. Finally, from the experimental data presented in this paper, under the training of the road pedestrian dataset that we collected and processed independently, the Yolov5s model has certain advantages in terms of precision and other indicators compared with traditional single shot multiBox detector (SSD) model and fast region-convolutional neural network (Fast R-CNN) model. After pruning and lightweight, the size of training model is greatly reduced without a significant reduction in accuracy, and the final precision reaches 87%, while the model size is reduced to 7,723 KB.

• 한국전산구조공학회논문집
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• 제36권1호
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• pp.27-38
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• 2023

본 논문에서는 최근 4차 산업혁명을 통해 최신 ICT 기술을 접목하여 대한민국의 항만, 해운, 조선 및 기자재 산업이 물샐틈없는 완벽 공조를 통한 가치 사슬, Seamless Value Chain이 Smart Seamless Value Chain 성공적인 구축을 위한 산업 간의 협력관계를 정의하고, 이들 산업의 지속 가능한 발전을 위한 핵심 요소가 무엇인지를 고찰해 보았다. 이를 통해 오늘날 디지털화를 통한 탈탄소화를 실현하여 ESG 경영 달성을 위한 방향도 제시하였다. 그리고 특히 중소기업의 관점에서 미래시장을 대응하기 위한 방안으로서의 디지털화의 중요성과, 특히 중소 기자재 업체가 실현하는 디지털 화가 산업계 전반에서 어떤 역할을 하는지 중점적으로 고찰하였다. 이를 통해 산업 간의 연계 상태와 가치 사슬이 원활한 관계를 반드시 유지해야할 필요 사유를 동시에 보여준다. 그리고 대한민국의 산업에서 얻은 실패 사례를 통한 교훈으로 발판 삼아 향후 지능형 연결의 전략적 통로를 만드는 초석을 구축하는 방향성도 제시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1530-1544
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• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.210-212
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• 2021

현대사회는 4차 산업혁명의 영향으로 다양한 디지털 장비가 보급되고 있으며, 자동화 공정, 지능형 CCTV, 의료산업, 로봇, 드론 등 넓은 분야에서 사용되고 있다. 이에 따라 영상을 기반으로 동작하는 시스템에서 전처리 과정에 대한 중요성이 높아지고 있으며, 영상을 효과적으로 복원하기 위한 알고리즘이 주목받고 있다. 본 논문에서는 복합잡음 환경에서 영상을 복원하기 위해 결합가중치에 기반한 필터 알고리즘을 제안한다. 제안한 알고리즘은 입력 영상 및 필터링 마스크 내부의 화소값을 대상으로 공간적 거리에 따른 가중치와 화소값 차이에 따른 가중치를 각각 계산한다. 최종 출력은 두 가중치를 바탕으로 계산한 결합가중치를 마스크에 적용하여 필터링하였다. 제안한 알고리즘의 성능을 검증하기 위해 기존 필터 알고리즘과 비교하여 시뮬레이션하였다.

• 한국농촌건축학회논문집
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• 제26권2호
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• pp.37-46
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• 2024

The city is developing into a smart city. Smart villages and smart farms are developing in rural areas. Architectural technology needs synergy with smart cities, smart villages, and smart factories (intelligent factories) to help architectural experts understand smart farms and build facilities and equipment. Smart farms require design and construction technology with architectural structure and function. The purpose of this study was to investigate the current status and cases of smart farms in Korea and to investigate cases abroad. The conclusion is as follows. ① Smart farms are developing rapidly. The Korean government is expanding smart farms by utilizing ICT technology and infrastructure. ② 'Smart Farm Innovation Valley', which has been promoted since 2018, is a cutting-edge convergence cluster industrial complex that integrates production, education, and research functions such as start-ups and technological innovation. ③ In domestic cases, smart farms are operated in subway stations, buildings, supermarkets, and restaurants. ④ In the Japanese case, a dome-type smart farm was being operated. It utilized factory wastewater, waste heat, renewable energy, and used new materials. Otemachi Ranch raised livestock and provided a lounge on the 13th floor of the building. ⑤ In the cases of Korea and Japan, the smart farm technology is very similar. As stated earlier, since the food culture and agricultural technology of both countries are similar, we hope to promote the development of smart farms that can reduce concerns about future food by communicating and sharing mutual technologies.

• Nuclear Engineering and Technology
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• 제56권6호
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• pp.2220-2238
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• 2024

As a typical active equipment, pump machinery is widely used in nuclear power plants. Although the mechanism of pump machinery in nuclear power plants is similar to that of conventional pumps, the safety and reliability requirements of nuclear pumps are higher in complex operating environments. Once there is significant performance degradation or failure, it may cause huge security risks and economic losses. There are many pumps mechanical parameters, and it is very important to explore the correlation between multi-dimensional variables and condition. Therefore, a condition monitoring model based on Deep Denoising Autoencoder (DDAE) is constructed in this paper. This model not only ensures low false positive rate, but also realizes early abnormal monitoring and location. In order to alleviate the influence of parameter time-varying effect on the model in long-term monitoring, this paper combined equidistant sampling strategy and DDAE model to enhance the monitoring efficiency. By using the simulation data of reactor coolant pump and the actual centrifugal pump data, the monitoring and positioning capabilities of the proposed scheme under normal and abnormal conditions were verified. This paper has important reference significance for improving the intelligent operation and maintenance efficiency of nuclear power plants.

• 지능정보연구
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• 제16권2호
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• pp.73-94
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• 2010

개방병원에 환자의 입원을 의뢰한 담당 의사들은 환자들의 상태와 제대로 된 간호서비스를 받고 있는지에 대한 정보를 간호기록을 열람함으로써 확인할 수 있다. 하지만 간호기록은 병원의 내부자료로써 외부기관에 쉽게 공개할 수 없는 자료이고 표준화가 확립되어 있지 않아 병원별로 다르게 작성되고 있어 필요한 정보를 공유하는데 많은 어려움이 따른다. 따라서 본 연구에서는 개방병원 간호기록의 작성과 공유를 지원하기 위한 시스템을 개발하고자 하였다. 본 시스템은 우선 간호기록을 실제로 작성하는 간호사의 편의성을 고려하여 간호기록항목사전을 설정하게 하고 간호사와 의사간의 지능형 에이전트를 이용한 협상으로 작성과 공개의 항목을 확정하도록 하였다. 이 모든 과정은 의료기관간의 네트워킹을 지원할 수 있도록 웹기반시스템으로 설계되었고 실제 구현을 통하여 실현가능성을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권2호
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• pp.618-633
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• 2014

Relay technology is becoming more important for mobile communications and wireless internet of things (IoT) networking because of the extended access network coverage range and reliable quality of service (QoS) it can provide at low power consumption levels. Existing mobile multihop relay (MMR) technology uses fixed-point stationary relay stations (RSs) and a divided time-frame (or frequency-band) to support the relay operation. This approach has limitations when a local fixed-point stationary RS does not exist. In addition, since the time-frame (or frequency-band) channel resources are pre-divided for the relay operation, there is no way to achieve high channel utilization using intelligent opportunistic techniques. In this paper, a different approach is considered, where the use of mobile/IoT devices as RSs is considered. In applications that use mobile/IoT devices as relay systems, due to the very limited battery energy of a mobile/IoT device and unequal channel conditions to and from the RS, both minimum energy consumption and QoS support must be considered simultaneously in the selection and configuration of RSs. Therefore, in this paper, a mobile RS is selected and configured with the objective of minimizing power consumption while satisfying end-to-end data rate and bit error rate (BER) requirements. For the RS, both downlink (DL) to the destination system (DS) (i.e., IoT device or user equipment (UE)) and uplink (UL) to the base station (BS) need to be adaptively configured (using adaptive modulation and power control) to minimize power consumption while satisfying the end-to-end QoS constraints. This paper proposes a minimum transmission power consuming RS selection and configuration (MPRSC) scheme, where the RS uses cognitive radio (CR) sub-channels when communicating with the DS, and therefore the scheme is named MPRSC-CR. The proposed MPRSC-CR scheme is activated when a DS moves out of the BS's QoS supportive coverage range. In this case, data transmissions between the RS and BS use the assigned primary channel that the DS had been using, and data transmissions between the RS and DS use CR sub-channels. The simulation results demonstrate that the proposed MPRSC-CR scheme extends the coverage range of the BS and minimizes the power consumption of the RS through optimal selection and configuration of a RS.

• 한국건축시공학회지
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• 제11권3호
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• pp.283-291
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• 2011

본 연구는 건설공사 현장에 적용되고 있는 무선센서네트워크 관련 기술현황을 검토하고, USN 기반의 콘크리트 양생온도 관리방법에 대한 현장적용성 실험을 통하여 그 개선 방안을 도출하는데 목적이 있다. 건설분야에서의 USN 관련연구는 주로 공사의 품질관리 및 시설물 유지관리, 안전관리를 중심으로 이루어지고 있으나, 현장여건 및 통신네트워크 등 실용화를 위한 세부적인 연구가 필요한 것으로 나타났다. 또한 현장사무실에서의 실시간 원격모니터링에 의한 콘크리트의 온도관리가 콘크리트내 소형의 무선센서를 활용 하여 USN 환경에서도 가능한 것을 알 수 있었다. 다만, 센서의 매립깊이에 따른 전파인식정도나 내장건전지의 전력소모 및 전송방식 등 현장에서의 가변적 상황에 대응할 수 있는 보다 안정화된 다양한 시스템 구축을 위한 연구가 필요한 것으로 나타났다.