• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.139-143
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• 2019

Measurement of flow rate is required in various fields. Water meters are often used at home, and flow meters are used in water and sewage plants, petrochemical industries and so on.. A system is needed to monitor the flow rate in real time and notify immediately when flow rate is abnormal. Recently, with the development of the IoT it is possible to construct such devices at low cost. WeMos can be programmed with Arduino IDE as a mini wifii IoT module. The flow sensor can output a digital pulse proportional to the flow rate. In this paper, we developed the flow monitoring and warning system using WeMos and IoT technology. When the system operates, it calculates the flow rate, sends the value as JSON format to the server, monitors the flow rate as graph from the remote with the smartphone. We also implement the system to promptly send alert message to the smart phone using Pushbullet when the flow rate is abnormal.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.279-287
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• 2019

In this paper, we attempted to analyze the balance ability of the body by measuring changes in body motion and plantar pressure distribution. So we developed a program that can measure and analyze range of motion and center of body pressure using inertial measurement unit(IMU) and FSR(Force Sensing Resistor) sensor, we also produced a contents that can help improve the balance ability. The quantitative values of range of motion and center of body pressure measured by this program are visualized in real time so that the user can easily recognize the results. In addition, the contents were designed to be adjusted according to the direction of improving the balance ability by adjusting the difficulty level based on the measured balance information. This can be achieved by increasing the concentration and participation will by using visual feedback method that proceeds while watching moving objects according to the user's motion.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.143-149
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• 2019

Floating holograms are technologies that provide rich 3D stereoscopic images in a wide space such as advertisement, concert. In addition, It is possible to reduce the 3D glasses inconvenience, eye strain, and space distortion, and to enjoy 3D images with excellent realism and existence. Therefore, this paper implements a user gesture recognition system for manipulating a floating hologram characters that can be used in a small space devices. The proposed method detects face region using haar feature-based cascade classifier, and recognizes the user gestures using a user gesture-occurred position information that is acquired from the gesture difference image in real time. And Each classified gesture information is mapped to the character motion in floating hologram for manipulating a character action. In order to evaluate the performance of the proposed user gesture recognition system for manipulating a floating hologram character, we make the floating hologram display devise, and measures the recognition rate of each gesture repeatedly that includes body shaking, walking, hand shaking, and jumping. As a results, the average recognition rate was 88%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.149-162
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• 2021

This paper established a new smart factory based on manufacturing data for an introductory company focusing on the personalized cosmetics manufacturing industry. We build on an example of a system that collects, manages, and analyzes documents and data that were previously managed by CGMP-based analog for data-driven use. To this end, we have established a system that can collect all data in real time at the production site by introducing artificial intelligence smart factory platform LINK5 MOS and POP system, collecting PLC data, and introducing monitoring system and pin board. It also aims to create a new business cluster space based on this project.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.195-200
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• 2021

With the development of transportation and mobiles demand for tourism travel is increasing and related industries are also developing significantly. The combination of augmented reality and tourism contents one of the areas of digital media technology, is also actively being studied, and artificial intelligence is already combined with the tourism industry in various directions, enriching tourists' travel experiences. In this paper, we propose a system that scans miniature models produced by reducing tourist areas, finds the relevant tourist sites based on models learned using deep learning in advance, and provides relevant information and 3D models as AR services. Because model learning and object detection are carried out using YOLOv3 neural networks, one of various deep learning neural networks, object detection can be performed at a fast rate to provide real-time service.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.1-8
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• 2021

In this paper, we propose an approach that combines the technological advantages of P2P and cloud computing to support MMOGs that allowing a huge amount of users worldwide to share a real-time virtual environment. The proposed P2P system based on cloud computing can provide a greater level of scalability because their more resources are added to the infrastructure even when the amount of users grows rapidly. This system also relieves a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the peers. In this paper, we describe the concept and basic architecture of cloud computing-based P2P Systems for scalability of MMOGs. An efficient and effective provisioning of resources and mapping of load are mandatory to realize this architecture that scales in economical cost and quality of service to large communities of users. Simulation results show that by controlling the amount of cloud and user-provided resource, the proposed P2P system can reduce the bandwidth at the server while utilizing their enough bandwidth when the number of simultaneous users keeps growing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.51-62
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• 2022

This study suggests a design of predictive modeling for a hospital fall risk based on inpatients' posture. Inpatient's profile, medical history, and body measurement data along with basic information about a bed they use, were used to predict a fall risk and suggest an algorithm to determine the level of risk. Fall risk prediction is largely divided into two parts: a real-time fall risk evaluation and a qualitative fall risk exposure assessment, which is mostly based on the inpatient's profile. The former is carried out by recognizing an inpatient's posture in bed and extracting rule-based information to measure fall risk while the latter is conducted by medical staff who examines an inpatient's health status related to hospital fall risk and assesses the level of risk exposure. The inpatient fall risk is determined using a sigmoid function with recognized inpatient posture information, body measurement data and qualitative risk assessment results combined. The procedure and prediction model suggested in this study is expected to significantly contribute to tailored services for inpatients and help ensure hospital fall prevention and inpatient safety.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.17-22
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• 2022

In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.119-125
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• 2022

The power supply for the anti-aircraft radar homing sensor should allow the system to receive power quickly and stably without the influence of noise. For this purpose, DC-DC converters are widely used for reliable power conversion. Also, switching of DC-DC converters Frequency noise should not cause false alarms and ghosts that may affect the detection and tracking performance of the system, and it should have a check function that can monitor power in real time while the homing sensor is operating. In order to apply to anti-aircraft radar homing sensor, we developed a multi-output switching power supply with maximum output 𐩒𐩒𐩒 W, efficiency 80% or more (@100% load), output power by receiving 28VDC input, and power supply to achieve more than 80% efficiency. A DC-DC converter was applied to this large output, and the multi-output flyback method was applied to the rest of the low-power output.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.63-68
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• 2022

There are 395,789 people with hearing impairment in Korea, according to the 2021 Disability Statistics Annual Report by the Korea Institute for the Development of Disabled Persons. These people are experiencing a lot of inconvenience through hearing impairment, and many studies related to recognition and translation of Korean sign language are being conducted to solve this problem. In sign language recognition and translation research, collecting sign language data has many difficulties because few people use sign language professionally. In addition, most of the existed data is sign language data taken from the front of the speaker. To solve this problem, in this paper, we designed and developed a storage system that can collect sign language data based on multi-view points in real-time, rather than a single point, and store and manage it with high usability.