• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.55-57
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• 2018

In Simultaneous Localization and Mapping (SLAM), the robot acquire its map of environment while simultaneously localize itself relative to the map. Now a day, a map acquired by the mobile robots limit to specific area, in an indoor environment and cannot able to navigate autonomous between different floors. We propose a design that could able to overcome this issue in order to navigate multiple floors with one end goal mission to a target destination in the course of autonomous navigation. In this research, we consider all the floors have identical structural arrangement. Internet of Things (IoT) playing crucial role in bridging between "things" and Robot Operating System (ROS) enabled mobile robots.

• Smart Media Journal
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• v.13 no.1
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• pp.60-66
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• 2024

The Internet of Things, which began by connecting sensors through a network, is developing into an intelligent IoT by combining it with artificial intelligence technology. Elevators are essential for high-rise buildings in the city, and elevators move from floor to floor and perform the functions of transporting goods and moving users. It is necessary to provide safe and convenient services for elevator users in high-rise buildings or special environments (hospitals, etc.). In an environment where rapid patient transportation is important, such as large hospitals, there is a problem that hospital staff and the general public often use the elevator for patients. In particular, when moving patients where golden time is important, the waiting time to board the elevator is a major hindrance. In order to solve this problem, this study proposes an intelligent IoT system for elevator calling using smartphone Bluetooth. First, we experimented with the elevator calling IoT system using smartphone Bluetooth, and as a result of the experiment, it was confirmed that it can authenticate elevator users and reduce unnecessary waiting time for boarding. In addition, we propose an intelligent IoT system that connects with intelligent IoT.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.21-26
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• 2020

An autonomous driving system is based on the deep learning system built by big data which are obtained by various IoT sensors. The miniaturization and high performance of the IoT sensors are needed for diverse devices including the autonomous driving system. Specially, the miniaturization of the sensors leads to compel the miniaturization of the fixer structures. In the viewpoint of the miniaturization, metallic structure is a best solution to attach the small IoT sensors to the main body. However, it is hard to manufacture the small metallic structure with a conventional machining process or manufacturing cost greatly increases. As one of solutions for the problems, in this work, metallic FDM (Fused depositon modeling) based on metallic filament was proposed and the FDM process was investigated to fabricate the small metallic structure. Final part was obtained by the post-process that consists of debinding and sintering. In this work, the relationship between infill rate and the density of the part after the post-process was investigated. The investigation of the relationship is based on the fact that the infill rate and the density obtained from the post-processing is not same. It can be said that this work is a fundamental research to obtain the higher density of the printed part.

• Annual Conference of KIPS
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• 2017.04a
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• pp.673-676
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• 2017

Accompanying the Internet of Things (IoT) is a demand of advanced applications and services utilizing the potential of the IoT environment. Monitoring the environment for a provision of context-aware services to the human beings is one of the new trends in our future life. The IoTivity Cloud is one of the most notable open-source platform bringing an opportunity to collect, analyze, and interpret a huge amount of data available in the IoT environment. Based on the IoTivity Cloud, we aim to develop a novel platform for comprehensive monitoring of a future network, which facilitates on-demand data collection to enable the network behavior prediction and the quality of user experience maintenance. In consideration of performance evaluation of the monitoring platform, this paper presents results of a preliminary test on the data acquisition/supply process in the IoTivity Cloud.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.4
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• pp.995-1012
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• 2016

In Internet of Things (IoT) environments, devices or sensors everywhere can automatically collect data without the individual awareness, further combine and share data using ubiquitous network, and thus the development of IoT raises new challenges in respect of personal data protection and privacy. This study aims to identify main issues related to data protection in the IoT and propose adequate measures. We analyzed the types of personal data controllers and processors in IoT and figured out the issues regarding the processing of personal data and the rights to privacy of data subject. Accordingly, we suggested the institutional ways (e.g., establishment of user-friendly notice and flexible consent system, re-identification risk monitoring system, data protection in cross-border transfer, and user education) to improve the situation of personal data protection in IoT and finally proposed the improvement tasks to carry out first based on the degree of urgency and importance.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.477-482
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• 2015

In this paper, an android platform with Unity engine was proposed for the effective 3D presentation of IoT sensor's position to IoT(Internet of Things) users. This android platform based home-gateway was designed with the cooperation of 3D unity engine for 3D texture according to MovieTexture simultaneously. As a result, the 3D presentation technology of IoT sensors was described with Unity based 3D modeling. In this proposed smart gateway, the 3D position was presented with the received RSSI(Received Signal Strength Indicator) and angle of IoT sensors. This 3D Unity launcher can be used for the 3D position, monitoring, and the life managing of IoT sensors with the beacon and 3 dimensional cube-style after the 3D conversion of 2D.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.81-86
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• 2020

With the development of the intelligent Internet of Things AIoT that goes beyond the IoT of the Internet of Things, the industry is changing overall. In addition, with the advent of the 4th Industrial Revolution, revolutionary changes and developments are also taking place in the automobile industry. A representative example is "autonomous driving vehicle". Because the domestic and foreign interests in autonomous vehicles have increased, many developments have been made, and although limited, they have developed into the commercialization stage. However, the structure of the autonomous vehicle that collects, analyzes, and controls data using various sensors installed in the vehicle, not the driver, is often insufficiently exposed to hacking due to the lack of multiplexed devices for security. In this case, as this can be a threat not only to the driver, but also to the surrounding environment, this paper proposes a new data processing function to improve the system security of autonomous vehicles.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.159-169
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• 2024

This paper proposes a new real-time fire monitoring and evacuation navigation system by integrating Augmented Reality (AR) technology with Internet of Things (IoT) technology. The proposed system collects temperature data through IoT temperature measurement devices installed in buildings and automatically transmits it to a MySQL cloud database via an IoT platform, enabling real-time and accurate data monitoring. Subsequently, the real-time IoT data is visualized on a 3D building model generated through Building Information Modeling (BIM), and the model is represented in the real world using AR technology, allowing intuitive identification of the fire origin. Furthermore, by utilizing Vuforia engine's Device Tracking and Area Targets features, the system tracks the user's real-time location and employs an enhanced A^* algorithm to find the optimal evacuation route among multiple exits. The paper evaluates the proposed system's practicality and demonstrates its effectiveness in rapid and safe evacuation through user experiments based on various virtual fire scenarios.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.869-881
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• 2016

Purpose: The objective of this study is to verify the economic validation of quality management integrated train freight car by analyzing economic evaluation indicators such as benefit and cost, net present value, and inter rate of return. Methods: First, we itemize benefit and cost field by reviewing literatures; Benefit consists of 1)Safety, 2)Operation, and 3)Maintenance; Cost consists of 1)Set-up fee, 2)Wireless internet fee, and 3)Cloud storage using fee. Second, based on these estimated values, we conduct an economic evaluation analysis. Among them, benefit and cost, net present value, and internal rate of return are selected. Results: As a result, all estimated values are highly over criterion of economic validity($$B/C{\geq}_-1$$, $$NPV{\geq}_-0$$, $$IRR{\geq}_-R$$); 1)benefit over cost ratio is 28.22, 2)Net present value is 8,121.66million KRW, and 3)Internal rate of return value is 2272%. Conclusion: The findings of this study will help making a decision when train industry adopts IoT technology for improving the effectiveness.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.155-164
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• 2023

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.