• Journal of Digital Contents Society
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• v.18 no.2
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• pp.249-256
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• 2017

As single-person households increase, demands for self interior design has been also increasing. The furniture arrangement takes big part of interior design. But sometimes people need professional helps for the proper and effective arrangement of furniture which makes self-interior design harder. Often, people share information and advices about interior design through Social Network Service. Experts could help directly but this approach would have several issues: First, the detailed and accurate advice would be difficult because experts have to examine the space through 2D pictures or video. Second, they have to make an appointment which would cause inconvenience to both customer and expert. In this paper, the furniture arrangement application for real-time sharing of interior design based on virtual reality is proposed to make up for the weak points. People can precisely share information and advice about self-interior design through this application in realtime, reducing waste of time and energy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.69-75
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• 2002

The important issues of facility database management in GIS are to collect up-to-date information and to update information in accordance with new-establishment, repair and replacement of the facilities. Therefore, it is necessary to develop a system which has capability of monitoring facilities as well as managing database efficiently. The purpose of this study is to propose possibility of implementation of mobile GIS solution for the facility management. In order to achieve the goal, to process existing digital maps and to receive on-site information through the wireless communication service are required. In addition, the system is required to process spatial information obtained by GPS and digital photogrammetric technique with real-time updating database in server. The system increases efficiency both in work flow and monitoring for facility management by providing optimal routing information to the sites and real-time two-way communication using VoIP(Voice over Internet Protocol). The system is expected to perform real-time database management effectively. In consequence, the system could appropriately response on-site situations in various practical applications. The proposed technology could contribute to improve nation's leading-edge technology.

• Convergence Security Journal
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• v.20 no.5
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• pp.11-17
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• 2020

With the increase in cases of using Bluetooth devices used in the electric vehicle charging systems, security issues are also raised. Although various technical efforts have beed made to enhance security of bluetooth technology, various attack methods exist. In this paper, we propose an intelligent Bluetooth intrusion detection system based on a well-known machine learning method, Hidden Markov Model, for the purpose of detecting intelligently representative Bluetooth attack methods. The proposed approach combines packet types of H4, which is bluetooth transport layer protocol, and the transport directions of the packet firstly to represent the behavior of current traffic, and uses the temporal deployment of these combined types as the final input features for detecting attacks in real time as well as accurate detection. We construct the experimental environment for the data acquisition and analysis the performance of the proposed system against obtained data set.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.25-27
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• 2022

Recently, with the development of the 4th industry, environmental issues such as air pollution have become serious, and in particular, a lot of air pollutants are generated in industrial sites. There are various types of air pollutants, and among them, carbon monoxide is essential for fires occurring in industrial sites, so it should be possible to monitor in real time. In addition, there is a need for a remote monitoring system that can measure various environmental factors other than air pollutants in real time. In this paper, we propose a monitoring system using wireless communication to remotely measure the industrial environment. The proposed monitoring system collects data to the Arduino of the transmitter by using a carbon monoxide sensor, a combustible gas sensor, a temperature and humidity sensor, and a flame sensor, and then transmits it to the receiver using ZigBee. The transmitted data is stored in the database of the receiver Raspberry Pi, and the stored data can be monitored in real time through the monitoring system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.123-133
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• 2024

Existing autonomous driving technology has been developed based on sensors attached to the vehicles to detect the environment and formulate driving plans. On the other hand, it has limitations, such as performance degradation in specific situations like adverse weather conditions, backlighting, and obstruction-induced occlusion. To address these issues, cooperative autonomous driving technology, which extends the perception range of autonomous vehicles through the support of road infrastructure, has attracted attention. Nevertheless, the real-time analysis of the 3D centroids of objects, as required by international standards, is challenging using single-lens cameras. This paper proposes an approach to detect objects and estimate the centroid of vehicles using the fixed field of view of road infrastructure and pre-measured geometric information in real-time. The proposed method has been confirmed to effectively estimate the center point of objects using GPS positioning equipment, and it is expected to contribute to the proliferation and adoption of cooperative autonomous driving infrastructure technology, applicable to both vehicles and road infrastructure.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.103-108
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• 2024

In this paper, a smart elevator system was studied using real-time object detection technology based on YOLO(You only look once)v5. When an external elevator button is pressed, the YOLOv5 model analyzes the camera video to determine whether there are people waiting, and if it determines that there are no people waiting, the button is automatically canceled. The study introduces an effective method of implementing object detection and communication technology through YOLOv5 and MQTT (Message Queuing Telemetry Transport) used in the Internet of Things. And using this, we implemented a smart elevator system that determines in real time whether there are people waiting. The proposed system can play the role of CCTV (closed-circuit television) while reducing unnecessary power consumption. Therefore, the proposed smart elevator system is expected to contribute to safety and security issues.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.880-885
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• 2024

For Safety Assisted Engineering works, real-time simulators have emerged as a mandatory tool among all the key actors involved in the nuclear industry (utilities, designers and safety authorities). EDF, Electricité de France, as the leading worldwide nuclear power plant operator, has a crucial need for efficient and updated simulation tools for training, operating and safety analysis support. This paper will present the work performed at EDF/DT to develop a new generation of engineering simulator to fulfil these tasks. The project is called SiRENE, which is the acronym of Re-hosted Engineering Simulator in French. The project has been economically challenging. Therefore, to benefit from existing tools and experience, the SiRENE project combines: - A part of the process issued from the operating fleet training full-scope simulator. - An improvement of the simulator prediction reliability with the integration of High-Fidelity models, used in Safety Analysis. These High-Fidelity models address Nuclear Steam Supply System code, with CATHARE thermal-hydraulics system code and neutronics, with COCCINELLE code. - And taking advantage of the last generation and improvements of instructor station. The intensive and challenging uses of the new SiRENE engineering simulator are also discussed. The SiRENE simulator has to address different topics such as verification and validation of operating procedures, identification of safety paths, tests of I&C developments or modifications, tests on hydraulics system components (pump, valve etc.), support studies for Probabilistic Safety Analysis (PSA). etc. It also emerges that SiRENE simulator is a valuable tool for self-training of the newcomers in EDF nuclear engineering centers. As a modifiable tool and thanks to a skillful team managing the SiRENE project, specific and adapted modifications can be taken into account very quickly, in order to provide the best answers for our users' specific issues. Finally, the SiRENE simulator, and the associated configurations, has been distributed among the different engineering centers at EDF (DT in Lyon, DIPDE in Marseille and CNEPE in Tours). This distribution highlights a strong synergy and complementarity of the different engineering institutes at EDF, working together for a safer and a more profitable operating fleet.

• The Journal of the Convergence on Culture Technology
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• v.3 no.3
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• pp.21-25
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• 2017

In this paper, we review relevant technologies of Mixed Reality(MR) and show important components of perspective that can overcome technical limitations of the current MR. An MR technology combines real and virtual objects in a real environment, and runs interactive in real time, and is regarded as an emerging technology in a large part of the future of Information Technology(IT). We've grouped the major obstacles limiting the wider use of MR technologies into three themes: technological limitations (i,e., tracking, rendering, authoring, and registration), user interface(UI) limitations(i.e., UI metaphor for MR interaction), and social acceptance issues.

• The Journal of Information Systems
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• v.6 no.1
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• pp.223-256
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• 1997

Since the business scales of retailing companies become to be very large and the number of items dealt increases explosively, automation of inventory management becomes one of the most important issues to solve in retailing industry. In order to accomplish this automation of inventory management, there must be a great need to a method which can perform real-time decision making on inventory control in an automatic fashion, while communicating with inventory information systems like POS system and automatic warehousing system. But even in this circumstance, there are also many obstructions to such automation like varying demands, limited capacity of warehouse and exhibition room, need for strategic consideration on inventory control, etc., in a real sense. Due to these reasons, it seems very difficult that most large-scaled retailing companies get fully automated inventory management system. To overcome those difficulties and reflect them into inventory control, we propose a automated inventory control methodology for retailing industry based on neural network and policy model. Especially, policy model is devised to deal with dynamic varying demands and using this model, strategic goals on inventory can be considered into inventory control mechanism. Our proposed approach is implemented in workstation and its performance is also empirically verified also against to real case of one of the major retailing firm in Korea.