• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.850-852
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• 2014

Recently, the development of Machine to Machine (M2M) communication has been largely accomplished in a variety of fields including smart home. In M2M communication, the role of sensor node is only limited to gather data and send them to upper application layers. In this research, the limited role of the sensor node in traditional M2M communication is improved in order for the devices to make inference, which makes it possible to provide basic context-aware services within sensor node level. Therefore, implementation of rule-based inference system on microcontroller for smart home is proposed.

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.7-13
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• 2021

Machine vision is a technology that helps the computer as if a person recognizes and determines things. In recent years, as advanced technologies such as optical systems, artificial intelligence and big data advanced in conventional machine vision system became more accurate quality inspection and it increases the manufacturing efficiency. In machine vision systems using deep learning, the image quality of the input image is very important. However, most images obtained in the industrial field for quality inspection typically contain noise. This noise is a major factor in the performance of the machine vision system. Therefore, in order to improve the performance of the machine vision system, it is necessary to eliminate the noise of the image. There are lots of research being done to remove noise from the image. In this paper, we propose an autoencoder based machine vision system to eliminate noise in the image. Through experiment proposed model showed better performance compared to the basic autoencoder model in denoising and image reconstruction capability for MNIST and fashion MNIST data sets.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.1
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• pp.85-109
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• 2023

Laundry has traditionally been regarded as one of the most demanding household chores, but the introduction of smart washing machines is changing this perception. Although smart washing machines have been on the market for several years and consumers' perceptions of washing machines have changed, little is known about consumers' perceptions of smart washing machines. The purpose of this study is to determine what users expect from smart washing machines. We conducted two focus group interviews with sixteen participants who had used smart home appliances to acquire qualitative data. Stimuli created by the interviewees were applied in the focus group interviews to collect more insightful data. We analyzed the data using the three-step method and QSR NVivo. Analysis revealed ten categories of predictive expectations, including seven utilitarian attributes (i.e., smart functionality, smart user interface, reliability, controllability, interactivity, functional value, and economic value) and three hedonic attributes (i.e., fashionable value, psychological value, and social value). The results of this study have implications for the development of smart washing machines that would satisfy consumers by taking user expectations into account.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.523-529
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• 2009

Smart sensor is known as intelligent sensor, it is different with other conventional sensors in the case of intelligent system embedded on it. Smart sensor has many benefits e.g. low-cost in usage, self-decision and self-diagnosis abilities. This sensor consists of perception element(sensing element), signal processing and technology of communication. In this work, a bridge and structure of smart sensor has been investigated to be capable to condition monitoring routine. This investigation involves low power consumption, software programming, fast data acquisition ability, and authoritativeness warranty. Moreover, this work also develops smart sensor to be capable to perform high sampling rate, high resolution of ADC, high memory capacity, and good communication for data transfer. The result shows that the developed smart sensor is promising to be applied to various industrial fields.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.22-27
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• 2004

A new method that estimates the sensing ability of HH smart sensor is proposed. The new signal processing method have been developed that can distinguish among different materials relatively. The HH smart sensor was developed far recognition of materials. The HH smart sensor was made for experiment. Then, it was estimated the ability to recognize objects according to acceleration value. The sensing ability of HH smart sensor has been estimated with the $R_{SAI}$ method. Experiments and analysis were executed to estimate the ability to recognize objects according to acceleration value changing. Dynamic characteristics of HH smart sensor were evaluated relatively through a new $R_{SAI}$ method that uses the power spectrum density. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.285-286
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• 2021

With the recent development of Internet of Things (IoT) technology, smartization technology is expanding to the fields of agriculture, livestock, and fisheries, and smartization is in progress. In this smart technology, the most important thing is how to measure the data in the field and transmit it to the management system. Currently, the sensors used in the construction of smart farms and other livestock houses and farms are measuring and monitoring smart farms and other environmental conditions through various sensors such as temperature, humidity, CO gas, CO2, hydrogen, and O2. The communication method between these sensors and the HMI (Human Machine Interface) module that controls and manages the smart farm is still mainly using the RS-485-based modbus-RTU method. In this paper, we intend to design the MCU module for HMI so that various sensor modules can be connected to manage data through the RS-485-based Modbus method so that the sensor data required for smart farm construction can be managed by the HMI module.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.480-497
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• 2012

As a new business concept, machine-to-machine (M2M) communications are born from original telemetry technology with the intrinsic features of automatic data transmissions and measurement from remote sources typically by cable or radio. M2M includes a number of technologies that need to be combined in a compatible manner to enable its deployment over a broad market of consumer electronics. In order to provide better understanding for this emerging concept, the correlations among M2M, wireless sensor networks, cyber-physical systems (CPS), and internet of things are first analyzed in this paper. Then, the basic M2M architecture is introduced and the key elements of the architecture are presented. Furthermore, the progress of global M2M standardization is reviewed, and some representative applications (i.e., smart home, smart grid and health care) are given to show that the M2M technologies are gradually utilized to benefit people's life. Finally, a novel M2M system integrating intelligent road with unmanned vehicle is proposed in the form of CPS, and an example of cyber-transportation systems for improving road safety and efficiency are introduced.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.90-96
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• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.207-210
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• 2014

Damage is increasing by (Smishing) hacking attack Smishing you use a smart phone after entering 2013. Takeover of personal information and direct financial damage in collaboration with graphics sewing machine hacking attack has occurred. Monetary damage that leads to Internet payment service (ISP) and secure payment system in conjunction with graphics sewing machine hacking attack on a smartphone has occurred. In this paper, I will study analysis in the laboratory examples of actual infringement vinegar sewing machine hacking attack. It is a major power security measures to prevent damage to the secure payment system that a case analysis and practical principle technical nest sewing machine hacking attack, using Smishing. In this paper, I will be to research to be able to through a smart phone, to the online payment safer and more convenient.