• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.17-27
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• 2019

In this study, we conducted a study to predict the photovoltaic power by constructing the sensor based meteorological data observation system and the accurate terrain data obtained by using LiDAR surveying. The average sunshine hours in 2018 is 4.53 hours and the photovoltaic power is 2,305 MWh. In order to analyze the effect of photovoltaic power on the installation angle of solar modules, we installed module installation angle at $10^{\circ}$ intervals. As a result, the generation time was 4.24 hours at the module arrangement angle of $30^{\circ}$, and the daily power generation and the monthly power generation were the highest, 3.37 MWh and 102.47 MWh, respectively. Therefore, when the module arrangement angle is set to $30^{\circ}$, the generation efficiency is increased by about 4.8% compared with the module angle of $50^{\circ}$. As a result of analyzing the influence of the seasonal photovoltaic power by the installation angle of the solar module, it was found that the photovoltaic power was high in the range of $40^{\circ}{\sim}50^{\circ}$, where the module angle was large from November to February when the weather was cold. From March to October, it was found that the photovoltaic power amount is $10^{\circ}{\sim}30^{\circ}$ with small module angle.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.5
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• pp.657-673
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• 2019

A monitoring method based on acoustic emission (AE) sensor has been widely used to evaluate the damage of structures in underground rock. The acoustic emission signal generated from cracking in material is analyzed as various acoustic emission parameters in time and frequency domain. To investigate from initial crack generation to final failure of rock material, it is important to understand the characteristics of acoustic emission parameters according to the stress ratio and rock strength. In this study, uniaxial compression tests were performed using very strong and weak rock specimen in order to investigate the acoustic emission parameters when the failure of specimen occurred. In the results of experimental tests, the event, root-mean-square (RMS) voltage, amplitude, and absolute energy of very strong rock specimen were larger than those of the weak rock specimen with an increase of stress ratio. In addition, the acoustic emission parameters related in frequency were more affected by specification (e.g., operation and resonant frequency) of sensors than the stress ratio or rock strength. It is expected that this study may be meaningful for evaluating the damage of underground rock when the health monitoring based on the acoustic emission technique will be performed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.622-629
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• 2019

Recently, the government is taking new approaches to change the fact that the accident rate and accident death rate of the construction industry account for a high percentage of the whole industry. Especially, it is investing heavily in the development of construction technology that is fused with ICT technology in line with the current trend of the 4th Industrial Revolution. In order to cope with this situation, this paper proposed a concept to recognize and share the work situation information between the construction machine driver and the surrounding worker to enhance the safety in the place where construction machines are operated. In order to realize the part of the concept, we applied image processing technology using camera based on artificial intelligence to earth-moving work. Especially, we implemented an algorithm that can recognize the surrounding worker's circumstance and identify the risk situation through the experiment using the compaction equipment. and image processing algorithm based on YOLO-v3. This algorithm processes 15.06 frames per second in video and can recognize danger situation around construction machine with accuracy of 90.48%. We will contribute to the prevention of safety accidents at the construction site by utilizing this technology in the future.

• The Journal of Bigdata
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• v.6 no.1
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• pp.23-35
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• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.102-116
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• 2021

For the safe operation of autonomous vehicles, the representative technology of the 4^th industrial revolution era, a combination of various technologies such as sensor technology, software technology and car technology is required. An autonomous vehicle is a vehicle that recognizes current location and situation by using the various sensors, and makes its own decisions without depending on the driver. Perfect recognition technology is required for fully autonomous driving. Since the precise road maps provide various road information including lanes, stop lines, traffic lights and crosswalks, it is possible to minimize the cognitive errors that occur in autonomous vehicles by using the precise road maps with location information of the road facilities. In this study, the definition, necessity and technical trends of the precise road map have been analyzed, and the HD(High Definition) map prototype based on the web GIS has been built in the autonomous driving-specialized areas of Daegu Metropolitan City(Suseong Medical District, about 24km), the Happy City of Sejong Special Self-Governing City(about 33km), and the FMTC(Future Mobility Technical Center) PG(Proving Ground) of Seoul National University Siheung Campus using the MMS(Mobile Mapping System) surveying results given by the National Geographic Information Institute. In future research, the built-in precise road map service will be installed in the autonomous vehicles and control systems to verify the real-time locations and its location correction algorithm.

• Journal of radiological science and technology
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• v.28 no.4
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• pp.317-325
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• 2005

The recent medical treatment guidelines and the development of information technology make hospitals reduce the expense in surrounding environment and it requires improving the quality of medical treatment of the hospital. That is, with the new guidelines and technology, hospital business escapes simple fee calculation and insurance claim center. Moreover, MIS(Medical Information System), PACS(Picture Archiving and Communications System), OCS(Order Communicating System), EMR(Electronic Medical Record), DSS(Decision Support System) are also developing. Medical Information System is evolved toward integration of medical IT and situation si changing with increasing high speed in the ICT convergence. These changes and development of ubiquitous environment require fundamental change of medical information system. Mobile medical information system refers to construct wireless system of hospital which has constructed in existing environment. Through RFID development in existing system, anyone can log on easily to Internet whenever and wherever. RFID is one of the technologies for Automatic Identification and Data Capture(AIDC). It is the core technology to implement Automatic processing system. This paper provides a comprehensive basic review of RFID model in Korea and suggests the evolution direction for further advanced RFID application services. In addition, designed and implemented DB server's agent program and Client program of Mobile application that recognized RFID tag and patient data in the ubiquitous environments. This system implemented medical information system that performed patient data based EMR, HIS, PACS DB environments, and so reduced delay time of requisition, medical treatment, lab.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.98-105
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• 2022

It is essential for vertical smart farms that artificially grow crops in an enclosed space to properly utilize air environment facilities to create an appropriate growth environment. However, domestic vertical smart farm companies are creating a growing environment by relying on empirical data rather than systematic methods. Using IoT to create a growing environment based on systematic and precise monitoring can increase crop production yield and maximize profitability. This study aims to construct a monitoring system using IoT and to analyze the cause by demonstrating the imbalance of temperature environment, which is a significant factor in crop cultivation. 1) The horizontal temperature distribution of the multi-layer shelf was measured with different operating methods of LED and air conditioner. As a result, there was a temperature difference of "up to 1.7℃" between the sensors. 2) As a result of measuring the vertical temperature distribution, the temperature difference was "up to 6.3℃". In order to reduce this temperature gap, a strategy for proper arrangement and operation of air conditioning equipment is required.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.260-269
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• 2022

In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.299-312
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• 2021

Autonomous vehicles using V2X can drive safely information on areas outside the sensor coverage of autonomous vehicles conventional autonomous vehicles. As V2X technology has emerged as a key component of autonomous vehicles, research on V2X security is actively underway research on risk analysis due to failure of V2X communication is insufficient. In this paper, the service scenario and function of autonomous driving system V2X were derived by presenting the intersection scenario of the autonomous vehicle, the malfunction was defined by analyzing the hazard of V2X. he ISO26262 Part3 process was used to analyze the risk of malfunction of autonomous vehicle V2X. In addition, a fault injection scenario was presented to verify the fail-safe of the simulation-based intersection scenario.