• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.78-88
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• 2023

Medication safety and medicine delivery challenge the well-being of the elderly and the management of the elderly center. With the outbreak of COVID-19, the elderly in the care center were challenged by the inconvenience of the medication restocking. The purpose of this paper accentuates the importance of the design and development of an UAV-based Smart Medicine Case (UAV-SMC) to improve the performance of medication management and medicine delivery in the elderly center. The researchers came up with the design of UAV-SMC in the light of the UAV and IoT technology to improve the performance of both Medication Practice Management (MPM) and Low Inventory Detection and Delivery (LIDD). Based on the result, with UAV-SMC, the performance of both MPM and LIDD was significantly improved. The UAV-SMC improves the efficacy of medication management in the elderly center by 26.97 to 149.83 seconds for each medication practice and 9.03 mins for each time of medicine delivery in Subang Jaya Malaysia. This paper only investigates the adoption of UAV-SMC in the content of elderly center rather than other industries. The authors consider integrating the UAV-SMC with the e-pharmacy system in the future. In conclusion, the UAV-SMC has significantly improved the medication management and guard the safety of elderly and caretaker in the elderly in the post-pandemic times.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.55-70
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• 2016

Recently, development of indoor positioning system and IoT such as beacon makes it possible to collect and analyze each customer's shopping behavior in off-line shopping malls. In this study, we propose a realtime brand recommendation scheme based on each customer's brand visiting history for off-line shopping mall with indoor positioning system. The proposed scheme, which apply collaborative filtering to off-line shopping mall, is composed of training and apply process. The training process is designed to make the base brand network (BBN) using historical transaction data. Then, the scheme yields recommended brands for shopping customers based on their behaviors and BBN in the apply process. In order to verify the performance of the proposed scheme, simulation was conducted using purchase history data from a department store in Korea. Then, the results was compared to the previous scheme. Experimental results showd that the proposed scheme performs brand recommendation effectively in off-line shopping mall.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.17-22
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• 2013

Heterogeneous radios are used in disaster management agencies for a variety of reasons though the radio must have the same radio frequency and protocol for voice communication. For this reason, the variety of heterogeneous radio voice connection methods have been studied but these are simple analog voice line cross connection or partial networked based on digitalization. In this paper, we suggest the method of voice packet transmission method based on All-IP per radio through IP network using SIP/RTP for scalability and openness and developed a prototype of the proposed method was verified.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.31-37
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• 2017

Recently Drone technology is emerging as an alternative new way of distribution systems services. Amazon, Google which are global network chain distribution companies are developing an idea of Drone based delivery service and applied for patent for Drone distribution systems in USA. In this paper, we investigate a way to adopt Drone system to Air Cargo logistics, in particular, drone system based on combination of Light ID and RFID technology in the management procedure in stock warehouse. Also we explain the expected impact of Drone systems to customs declaration process. In this paper, we address the investigated limitations of Drone by the Korean Aviation Act as well as suggest the directions of future research for application of Drone to Air logistics industry with investigated limitations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.959-979
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• 2024

Rice pest identification is essential in modern agriculture for the health of rice crops. As global rice consumption rises, yields and quality must be maintained. Various methodologies were employed to identify pests, encompassing sensor-based technologies, deep learning, and remote sensing models. Visual inspection by professionals and farmers remains essential, but integrating technology such as satellites, IoT-based sensors, and drones enhances efficiency and accuracy. A computer vision system processes images to detect pests automatically. It gives real-time data for proactive and targeted pest management. With this motive in mind, this research provides a novel farmland fertility algorithm with a deep learning-based automated rice pest detection and classification (FFADL-ARPDC) technique. The FFADL-ARPDC approach classifies rice pests from rice plant images. Before processing, FFADL-ARPDC removes noise and enhances contrast using bilateral filtering (BF). Additionally, rice crop images are processed using the NASNetLarge deep learning architecture to extract image features. The FFA is used for hyperparameter tweaking to optimise the model performance of the NASNetLarge, which aids in enhancing classification performance. Using an Elman recurrent neural network (ERNN), the model accurately categorises 14 types of pests. The FFADL-ARPDC approach is thoroughly evaluated using a benchmark dataset available in the public repository. With an accuracy of 97.58, the FFADL-ARPDC model exceeds existing pest detection methods.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.212-220
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• 2024

A recently the advancement of society, AI technology has made significant strides, especially in the fields of computer vision and voice recognition. This study introduces a system that leverages these technologies to recognize users through a camera and relay commands within a vehicle based on voice commands. The system uses the YOLO (You Only Look Once) machine learning algorithm, widely used for object and entity recognition, to identify specific users. For voice command recognition, a machine learning model based on spectrogram voice analysis is employed to identify specific commands. This design aims to enhance security and convenience by preventing unauthorized access to vehicles and IoT devices by anyone other than registered users. We converts camera input data into YOLO system inputs to determine if it is a person, Additionally, it collects voice data through a microphone embedded in the device or computer, converting it into time-domain spectrogram data to be used as input for the voice recognition machine learning system. The input camera image data and voice data undergo inference tasks through pre-trained models, enabling the recognition of simple commands within a limited space based on the inference results. This study demonstrates the feasibility of constructing a device management system within a confined space that enhances security and user convenience through a simple real-time system model. Finally our work aims to provide practical solutions in various application fields, such as smart homes and autonomous vehicles.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.5
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• pp.25-30
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• 2024

Train derailment accidents have been increasing over the past five years. The causes of these railroad derailments were found to be mainly defective track switches that change train tracks, use of old parts, and poor maintenance issues. In this paper, to solve these problems, an intelligent sensor-based automatic railway risk prediction algorithm and hypothesis were established and computer simulation experiments were performed. In particular, research on RFID technology and IoT sensor technology was conducted on a WEB basis. In addition, in this paper, in order to prevent country of origin counterfeiting accidents, a blockchain-based computer simulation to prevent forgery of railway parts was performed using open source.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1439-1446
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• 2017

Steady exercise or walking exercise is helpful for the treatment of chronic diseases or cancers. In this paper, I presented a smart poster to enable the patients to exercise while moving between the smart posters, dynamically, in order to provide better exercise effect to them. It can be a new form of exercise prescription that combines exercise with walking using smart posters. The personalized exercise prescription is downloaded from the management server in real time when the patient approaches, and induces the patient's exercise and walking. In addition, the smart poster helps patient to move to other posters in order to induce more walking exercise. To achieve this, I proposed a transfer protocol that autonomously exchanges session information between smart posters in this paper. Moreover, the smart poster based on Raspberry was implemented to verify validity of this protocol, and an experiment was conducted to measure the request and response time between smart posters in the implemented environment. In the experiment, when the other poster sent the message requesting the exercise session 100 times and received the response message, the 95 percentage of received messages had the response time within 0.05 seconds.

• Journal of Institute of Convergence Technology
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• v.6 no.2
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• pp.41-46
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• 2016

Based on Regional Industry Development Plan in 2014, machinery part industry and medical instrument industry has been designated as core industries of Chung-buk area. Machinery part industry plays an important role in economic growth of chung-buk area and it has been faced with signigicant changes - such as SMART factory and IoT(Internet of things). Also, medical instrument industry with 3D printing technology grows rapidly in Chung-buk area. It is believed that medical instrument could be next cash-cow items for Chung-buk area. In this paper, we survey, analyze and summarize the current machinery part industry and medical instrument industry focused on Chunk-buk Area.