• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.310-316
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• 2022

The smart tourism service provides services such as travel planning and tour guides to tourists using key technologies of the 4th industrial revolution, such as the Internet of Things, communication infrastructure, big data, artificial intelligence, AR/VR, and drones. We are developing smart tourism services such as recommended travel products, my travel itinerary, tourism information, and chatbots for tourists through the smart tourism app. In this paper, we develop a smart tourism service system that provides real-time location-based tourism information and weather information to tourists. The smart tourism service system consists of a smart tourism app, a smart tourism information system, and an IoT data collection device. The smart tourism information system receives weather information from the IoT data collection device installed in the tourist destination. The location-based smart tourism service is provided as a smart tourism app in the smart tourism information system according to the Beacon's UUID in the IoT data collection device. The smart tourism information system stores the Beacon's UUIDs received from tourists and provides a safe hiking service for tourists.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.39-47
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• 2023

The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1135-1142
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• 2017

In this paper, we propose IoT based smart CCTV security service to prevent crime in blind spot and prevent unexpected fire or danger. In the proposed method, a RC (Radio Control) car is made using Raspberry pie, and a camera and various modules are installed in an RC car. It was then implemented using Raspbian O / S, Apache Web Server, Shell script, Python, PHP, HTML, CSS, Javascript. The RC car provides a security service that informs the manager of the situation by judging the risk of the scene with modules such as video, voice and temperature. Experimental results show that the transmission time of video and audio information is less than 0.1 second. In addition, real-time status transmission was possible in AVG, emergency, and manual mode. It is expected that the proposed method will be applied to the development of smart city by applying it to unmanned vehicles, drones and the like.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.232-237
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• 2016

As a possible standardization of wireless local area network (WLAN), IEEE 802.11 LRLP is under discussion in order to support long range and low power (LRLP) communication for internet of things (IoT) including drones and many other IoT devices. In this paper, an efficient adaptive resource unit allocation scheme for uplink multiuser transmission in IEEE 802.11 LRLP networks is proposed. In the proposed scheme, which adopts OFDMA random access based transmission scheme of IEEE 802.11ax, in order to enhance the efficiency of the slotted OFDMA random access, access point (AP) traces the history of the sizes of successfully transmitted uplink data, and adjusts the sizes of resource units for the next uplink multiuser transmission adaptively. Our simulation results corroborate that the proposed scheme significantly improves the system throughput.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.145-153
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• 2023

This study emphasizes the essential need in the military for effective measurement and monitoring of soldiers' physical fitness, health, and exercise capabilities to enhance both their overall fitness and combat effectiveness. The effective assessment of physical fitness is considered a core element of management, aligning with principles of modern management. Particularly, preparing soldiers with robust physical fitness is deemed crucial for adapting to dynamic changes on the battlefield. In this research, the RFM (Recency, Frequency, Monetary) customer analysis and clustering methods, validated in e-commerce, are introduced as a basis for applying an AI-driven customer analysis approach to assess military personnel fitness. To achieve this, the study explores the incorporation of the RSC (Reveal, Sustainable, Control) analysis model. This model aims to effectively categorize and monitor military personnel fitness. The application of the RFM technique in the RSC analysis model quantifies and models military fitness, fostering continuous improvement and seeking strategies to enhance the effectiveness of fitness management. Through these methods, the study develops an AI customer analysis technique applied to the RSC clustering analysis method for improving and sustaining military personnel fitness.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.133-144
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• 2019

Although deep learning-based visual image recognition technology has evolved rapidly, most of the commonly used methods focus solely on recognition accuracy. However, the demand for low latency and low power consuming image recognition with an acceptable accuracy is rising for practical applications in edge devices. For example, most Internet of Things (IoT) devices have a low computing power requiring more pragmatic use of these technologies; in addition, drones or smartphones have limited battery capacity again requiring practical applications that take this into consideration. Furthermore, some people do not prefer that central servers process their private images, as is required by high performance serverbased recognition technologies. To address these demands, the object and scene recognition technologies for mobile/embedded devices that enable optimized neural networks to operate in mobile and embedded environments are gaining attention. In this report, we briefly summarize the recent trends and issues of object and scene recognition technologies for mobile and embedded devices.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.83-92
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• 2018

This paper uses the Apollonius Circle technique to estimate the position of a target that generates a specific signal by using a drone, which is rapidly becoming a rapidly expanding industry. The existing direction finding method is performed through the vehicle on the ground or installed the antenna at a high position to detect the position of the target. However, the conventional direction finding method is difficult to configure the reception environment of the LOS signal, It is difficult. However, the direction finding using the drone is easy to construct and measure the LOS signal receiving environment using the drone flying at high altitude. In this study, we use the 3D 800MHz Path-Loss Model to reconstruct the signal by using the measurement data of the ground direction finding, reconstruct the signal by using the 3-D 800MHz Path-Loss Model, and use the Apollonius Circle method to estimate the position of the target. A simulation was performed to estimate the position of the target. Simulation was performed to determine the target position estimation performance by configuring the ground direction finding and the dron direction finding.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.121-127
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• 2020

The small tracking radar targets the target in a real-time, fast-moving, fast-moving target against aircraft with a large RCS that is maneuvering at low speed and a small RCS aircraft maneuvering at high speed (fighters, drones, helicopters, etc.) It is a pulsed radar that detects and tracks. Performing a performance test on a tracking radar in a real environment is expensive, and it is difficult to quantitatively measure performance in a real environment. Describes the composition of the laboratory environment's comprehensive performance test facility and the main requirements and implementation of each configuration.Anechoic chambers to simulate the room environment, simulation target generator to simulate the signal of the room target, target It is composed of a horn antenna driving device to simulate the movement of a vehicle and a Flight Motion Simulatior (FMS) to simulate the flight environment of a tracking radar, and each design and implementation has been described.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.167-172
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• 2017

Mobile nodes are used for prolonging the life-time of the entire wireless sensor networks and many studies that use drones to collected data have been actively conducted with the development of drone related technology. In case of associating a drone and tactical wireless sensor networks, real-time feature and efficiency are improved. The previous studies so focus on reducing drone's flight distance that the energy consumption of sensor nodes is unbalanced. This unbalanced energy consumption accelerates the network partition and increases drone's flight distance. In this paper, we proposed a new selection scheme considered drone's flight distance and nodes' life-time to solve this problem when rendezvous nodes that collect data from their cluster and directly communicate with a drone are selected.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.49-54
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• 2022

Immersive contents is content that provides a realistic experience by maximizing the user's five senses, and includes virtual reality, augmented reality, and mixed reality. In order to provide a sense of reality to users in immersive content, it is necessary to provide realistic visual images, hearing, and touch. However, due to the rapid change in the environment for developing immersive content, experts in training human resources are having difficulties in designing the curriculum. In this study, we propose a series of educational courses that use drones to acquire and process real-world measurement data and apply the derived data to VR, AR, and MR to help experts in training immersive content develop talent. The design of training process composes through demand survey and analysis of companies, students, and local communities. This study can be a useful resource for education experts who want to train immersive contents manpower.