• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.293-297
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• 2009

This paper describes a real-time reliable measurement and analysis system for ubiquitous healthcare based on IEEE802.15.4 standard. In order to obtain and monitor physiological body signals continuously, wearable pulse oximeter is designed in wrist that could used to measure oxygen saturation of a patient unobtrusively. The measured data was transferred to a central PC or server by using wireless sensor nodes via a wireless sensor network for storage and analysis purposes. LabVIEW server program was designed to monitor and process the measured photoplethysmogram(PPG) to accelerated plethysmogram(APG) by appling second order derivatives in server PC. These experimental results demonstrate that APG can precisely describe the features of an individual's PPG and be used as estimation of vascular elasticity for blood circulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.545-548
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• 2009

Recently, researches related to automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for $SpO_2$ sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, $SpO_2$ and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the $SpO_2$ and ECG signals. HRV(Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.90-96
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• 2019

Storage cabinet in a lab in these days measures various environmental factors in real-time with IoT sensors. Preexisting system collects sensor data, analyze a risk and then command other equipment. Such centralized control system tends to have an issue with of speed slowing down. It's because when there are more storage cabinets, there are more data to process. In order to solve this issue, this report addresses decentralized IoT sensor based lab safety control system. It can analyze internal state of storage cabinet to identify any hazardous situations and effectively control them. Such decentralized control system using sensor modules for internal environment of the cabinet storage and automated control algorithm based on administrator's log history can manage any hazardous situations by automated control of environment factors of inside a lab. It would allow users to deal with a hazard if it happens. Even better, it can prevent it to happen from the beginning.

• Journal of IKEEE
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• v.23 no.1
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• pp.322-325
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• 2019

The non-intrusive load monitoring(NILM) algorithm can infer the power usage of the individual electric devices by the total electric power consumption of the main line. To develop such an algorithm, power usage pattern data of individual devices as well as those of various combinations of these devices are required. In this paper, we propose a method to develop a power usage pattern data acquisition system for developing a NILM algorithm for a smart farm. The data acquisition system is capable of simultaneously measuring the power usage of individual electrical devices and the power usage according to various combinations of scenarios every second. The measured data can be remotely monitored from the outside of the smart farm through the LTE network, and the measured data is stored in an external server.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1369-1374
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• 2021

Recently, controversy has been raised over the security and safety of Chinese-made network equipment (Huawei 5G), apps (TikTok, etc.). In particular, according to the results of the Ministry of Defense investigation in 2020, malicious codes were found in CCTVs made in China that were delivered as military surveillance equipment used as a coast guard system, and specific information was remotely transmitted to a Chinese server. The safety issues of these Chinese security products can be questioned as being systematically led by the state rather than by companies or individuals. In this paper, we perform network and process level analysis of 360 Total Security(360 TS), a Chinese antivirus software. In addition, it compares and analyzes the domestic cloud-based vaccine V3 Lite product. Through this, the safety of Chinese security solutions is checked and information leakage and risks are suggested.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.23-30
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• 2020

In this study, the relationship between natural gas (NG) data and gas-related environmental elements was performed using machine learning algorithms to predict the level of gas leakage risk without directly measuring gas leakage data. The study was based on open data provided by the server using the IoT-based remote control Picarro gas sensor specification. The naturel gas leaks into the air, it is a big problem for air pollution, environment and the health. The proposed method is multivariate outlier removing method based Random Forest (RF) classification for predicting risk of NG leak. After, unsupervised k-means clustering, the experimental dataset has done imbalanced data. Therefore, we focusing our proposed models can predict medium and high risk so best. In this case, we compared the receiver operating characteristic (ROC) curve, accuracy, area under the ROC curve (AUC), and mean standard error (MSE) for each classification model. As a result of our experiments, the evaluation measurements include accuracy, area under the ROC curve (AUC), and MSE; 99.71%, 99.57%, and 0.0016 for MOL_RF respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1305-1310
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• 2019

Modern agriculture is changing from resource-oriented agriculture to technology-oriented agriculture. Agriculture, which combines science and technology, is recognized as a new growth engine, and governments, local governments, research institutes, and industry are working together to develop and disseminate various devices necessary for smart farms to build intelligent smart farms. Recently, research is being conducted to build a more intelligent agricultural environment by building a cloud platform. In this paper, we propose a plan to build an urban energy - independent smart farm that can utilize leisure time and agricultural activities by utilizing the rooftop of a city. Also, by using IT technology, various data of smart farm can be managed on remote server, and HMI module for controlling internal environment of smart farm can be developed to manage smart farm automatically or semi-automatically. The service model suggests a model that can manage the internal environment of the smart farm based on mobile.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.441-447
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• 2020

In a situation in which around 50 million metric tons of electrical and electronic products is generated globally per year, the total installed base of Internet of Things (IoT) devices is projected to amount to around 75 billion worldwide by 2025. However, there is very little research on identification schemes for end-of-life treatment (EoLT) of IoT devices. To address this issue, this paper proposes new identifiers including EoLT information such as recyclability rate (Rcyc) and recoverability rate (Rcov) of an IoT device, recycling rate (RCR) and recovery rate (RVR) of each part in the IoT device, etc. and implements them by using object identifier (OID), mobile radio frequency identification (RFID) and quick response (QR) code. The implemented OID and mobile RFID can be used with cooperation of a remote server via communication networks and the implemented QR code can be used simply with a smartphone app.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.539-544
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• 2020

The research is on progressing to operate digital door lock with the method to guarantee the security and safety in the meantime to use digital door lock conveniently using Internet of Things (IoT) standardizing various service providing technology using IoT in home network currently. In this study, compose home network interconnecting Raspberry-PI and web server reflection this trend and composed the system to control the door lock after connect Arduino substituting converter function. Making Raspberry-PI using dynamic IP address using existing open source easily maintain DNS information and possible to connect internet network in home network ethernet and finally, making the smartphone can control door lock remotely entering designated address after connect the internet. The connection between home network and Arduino is executed by Raspberry-PI and bluetooth pairing as 1:1 and make random user's access to be impossible. Especially, to make open/close the door lock with smartphone not by using password on the keypad or using RFID card is judged as the method increasing the security make random user's access to be impossible and also increased the usefulness making remote control to be possible.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.94-103
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• 2022

As a large amount of data generated by sensors or devices at the manufacturing site is transmitted to the server or client, problems arise in network processing time delay and storage resource cost increase. To solve this problem, considering the manufacturing site, where real-time responsiveness and non-disruptive processes are essential, QRC (Quotient Remainder Compression) and BL_beta compression algorithms that enable real-time and lossless compression were applied to actual manufacturing site sensor data for the first time. As a result of the experiment, BL_beta had a higher compression rate than QRC. As a result of experimenting with the same data by slightly adjusting the data size of QRC, the compression rate of the QRC algorithm with the adjusted data size was 35.48% and 20.3% higher than the existing QRC and BL_beta compression algorithms.