• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.1017-1023
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• 2015

The amount of smart phones has increased exponentially. Due to the periodic release of high-performance smart phones and upgraded operating system, new smart phones become out-dated over 1 or 2 years. In order to solve environmental constraints of these smart phones, virtualization technology using Thin-Client terminal has been developed. However, in the case of Virtual Machine(VM), the applications associated with sensors and a GPS device can not run because they are not included. In this paper, by implementing the device driver for Android running in a virtual machine in the x86-based systems, it is to provide Android virtualization capabilities such as using the latest smart phones in the virtual machine environment. It would like to propose a method that the virtual device driver receives sensors and GPS information from the old Android smart phones(Thin-Client) that actually work and run as if the real device exists.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.317-325
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• 2022

In this study, we propose a technological system designed to provide machine vision-based automatic inspection and autonomous operation services for an entire process related to product inspection in wire harness manufacturing. The smart factory paradigm is a valuable and necessary goal, small companies may encounter steep barriers to entry. Therefore, the best approach is to develop towards this approach gradually in stages starting with the relatively simple improvement to manufacturing processes, such as replacing manual quality assurance stages with machine vision-based inspection. In this study, we consider design issues of a system based on the proposed technology and describe an experimental implementation. In addition, we evaluated the implementation of the proposed technology. The test results show that the adoption of the proposed machine vision-based automatic inspection and operation service system for multi-wire harness production may be considered justified, and the effectiveness of the proposed technology was verified.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.12
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• pp.297-304
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• 2019

The technological advances such as communication, sensor, and artificial intelligence lead smart factory construction. Smart factory aims at efficient process control by utilizing data from the existing automation process and intelligence technology such as machine learning. As a result of constructing smart factory, productivity increases, but costs increase. Therefore, small companies try to make a step-by-step transition from existing process to smart factory. In this paper, we have proposed a remote control system that support data collection, monitoring, and control for manufacturing equipment to support the construction of CNC cutting machine based small-scale smart factory. We have proposed the structure and design of the proposed system and efficient sensing data transmission scheme. To check the feasibility, the system was implemented for CNC cutting machine and functionality verification was performed. For performance evaluation, the web page access time was measured. The results means that the implemented system is available level.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Journal of KIBIM
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• v.12 no.2
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• pp.1-11
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• 2022

Road traffic accidents (RTAs) are the leading cause of accidental death among children. RTA reduction is becoming an increasingly important social issue among children. Municipalities aim to resolve this issue by introducing "Smart Pedestrian Crosswalks" that help prevent traffic accidents near children's facilities. Nonetheless such facilities tend to be installed in relatively limited number of areas, such as the school zone. In order for budget allocation to be efficient and policy effects maximized, optimal location selection based on machine learning is needed. In this paper, we employ machine learning models to select the optimal locations for smart pedestrian crosswalks to reduce the RTAs of children. This study develops an optimal location index using variable importance measures. By using k-means clustering method, the authors classified the crosswalks into three types after the optimal location selection. This study has broadened the scope of research in relation to smart crosswalks and traffic safety. Also, the study serves as a unique contribution by integrating policy design decisions based on public and open data.

• Journal of the Korean Society of Safety
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• v.35 no.2
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• pp.94-99
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• 2020

Bikers can be subjected to injuries from unexpected accidents even if they wear basic helmets. A properly designed airbag can efficiently protect the critical areas of the human body. This study introduces a wearable smart airbag system using machine learning techniques to protect human neck and shoulders. When a bicycle accident happens, a microprocessor analyzes the biker's motion data to recognize if it is a critical accident by comparing with accident classification models. These models are trained by a variety of possible accidents through machine learning techniques, like k-means and SVM methods. When the microprocessor decides it is a critical accident, it issues an actuation signal for the gas inflater to inflate the airbag. A protype of the wearable smart airbag with the machine learning techniques is developed and its performance is tested using a human dummy mounted on a moving cart.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.457-465
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• 2019

This paper present developing methods of man-machine interface(MMI) system for smart temperature controller with android platform. This MMI system could communicate with mobile machine. Firstly we present electrical hardware design method of MMI system of smart temperature controller. Smart temperature controller is composed of dual processors. Secondly we develop operating software of MMI system using android development environment. And finally we present verification of MMI systems of smart temperature controller with android platform through field experiment. This MMI system with android platform has rapid development speed due to performance of android platform.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.129-137
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• 2018

Smart machines are one of the topics of our society recently. A smart machine should have a wiser or smarter function than the past. In the modern society, the environment of each family is being improved toward the direction of smart home. In this environment, smart speakers are now increasingly serving as interfaces for controlling various devices in the home, from devices that listen to conventional music. In this paper, we review the technology development trends of domestic and foreign smart speaker market, and describe the core technologies required. In Korea, while SKT and KT are dominant in the speaker market, major IT companies such as Amazon, Google and Apple are focusing on launching related products and technology development.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.31-40
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• 2018

We designed and implemented the attachable smart adapter for the general management of each company's agricultural machine regardless of whether it is equipped with a CAN (Controller Area Network) module. The smart adapter consists of a main board (Raspberry Pi3B), which operates agricultural machine's management software in Linux environment, and a self-developed interface board for power adjustment and status sensing. For the status monitoring, a sensing interface using a serial input was defined between the smart adapter and the sensors of the agricultural machine, and the state diagram of the agricultural machine was defined for diagnosis. We made a panel to simulate the sensors of the agricultural machine using the switch's on/off contact point, and confirmed the status monitoring and diagnostic functions by inputting each state of the farm machinery from the simulator panel.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.959-966
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• 2024

Recently, various IoT devices are being developed to suit the user's lifestyle in our daily lives. In this paper, a smart coffee machine using IoT technology was implemented through an application and an ESP-01 WiFi module. The implemented smart coffee machine is different from existing coffee machines with alarm functions in that it can manage the desired date and time with an application by combining IoT. The application uses Android Studio to input data and transmits appropriate information to the smart coffee machine. An Arduino-based circuit was configured to control the coffee machine and MP3 module so that coffee is extracted at the desired time and an alarm sound is heard through the speaker. The extracted coffee can be divided into three stages: hot, warm, and lukewarm depending on the temperature. Finally, the suitability of the implemented smart coffee machine was confirmed through an experiment on the change in coffee temperature according to the amount of water and time.