• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1223-1230
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• 2021

Recently, energy resource management is a major concern around the world. Energy management activities minimize environmental impacts of the energy production. This paper presents design and prototyping of a home electric energy monitoring system that provides residential consumers with real time information about their electricity use. The developed system is composed of an in-house sensing system and a server system. The in-home sensing system is a set of wireless smart plug which have an AC power socket, a relay to switch the socket ON/OFF, a CT sensor to sense current of load appliance and a Kmote. The Kmote is a wireless communication interface based on TinyOS. Each sensing node sends its detection signal to a home gateway via wireless link. The home gateway stores the received signals into a remote database. The server system is composed of a database server and a web server, which provides web-based monitoring system to residential consumers. We analyzed and presented energy consumption data from electrical appliances for 3 months in home. The experimental results show the promising possibilities to estimate the energy consumption patterns and the current status.

• Smart Media Journal
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• v.11 no.8
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• pp.55-64
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• 2022

In the recent education market, Edutech technology, in which various digital technologies are grafted into the education, is being actively applied due to the 4th industrial revolution and the development of ICT. In particular, realistic experiential learning contents that can provide realistic and immersive learning in a virtual space are in the spotlight and are being expanded to each field. However, in the field of Korean medicine education, the introduction of ICT is delayed due to the nature of Korean medicine, difficulties in apprenticeship education, quantitative education, and the absence of an objective evaluation system. Therefore, in this study, we propose a digital technology application for acupuncture and acupuncture points, where practice is particularly important in Korean medicine. Various methods of acupuncture and acupoints education using AR, MR, IoT and Touch-Display Table will provide an opportunity to change the paradigm of Korean medicine education and further contribute to the globalization of Korean medicine.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.296-299
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• 2022

The rapid urban expansion and the increase in natural disasters due to the increase of population after industrialization and climate change are causing numerous urban management problems. The IP based hyper-connectivity caused by the initiation of the 4th industrial revolution enables a variety of technologies and services that produce vast amounts of data and solve urban management problems based on this. Especially, the quality of life is improved by providing the necessary information for life that are produced through a sensor network on wired and wireless communication. In this study, we intend to propose the method of optimal communcation network composition for innovative and futuristic city management technology through the case of K-water Smart Village Communication System

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.67-77
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• 2023

This study represents an innovative research conducted in the smart farm environment, developing a deep learning-based disease and pest detection model and applying it to the Intelligent Internet of Things (IoT) platform to explore new possibilities in the implementation of digital agricultural environments. The core of the research was the integration of the latest ImageNet models such as Pseudo-Labeling, RegNet, EfficientNet, and preprocessing methods to detect various diseases and pests in complex agricultural environments with high accuracy. To this end, ensemble learning techniques were applied to maximize the accuracy and stability of the model, and the model was evaluated using various performance indicators such as mean Average Precision (mAP), precision, recall, accuracy, and box loss. Additionally, the SHAP framework was utilized to gain a deeper understanding of the model's prediction criteria, making the decision-making process more transparent. This analysis provided significant insights into how the model considers various variables to detect diseases and pests.

• Convergence Security Journal
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• v.24 no.1
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• pp.11-20
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• 2024

Recently, smart buildings that can efficiently manage energy using ICT technology and operate and control through the building automation system by collecting data from a large number of IoT sensors in real time are attracting attention. However, as data management is carried out through an open environment, the safety of smart buildings is threatened by the security vulnerability of the existing building automation protocol. Therefore, in this paper, we analyze the major data link technology of BACnet, which is used universally, and propose OWE-based efficient BACnet/SC that can ensure the reliability of data in a wireless environment. The proposed protocol enables safe communication even in an open network by applying OWE and provides the same level of security as BACnet/SC in a TLS environment. As a result, it reduces the connection process twice and reduces the average time required by 40%, enabling more efficient communication than before.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.208-209
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• 2023

IT(Information Technology) 기술이 고도화됨에 따라 금융 분야에서는 스마트 컨트랙트에 기반하여 자산을 거래할 수 있는 DeFi(Decentralized Finance)가 발전하고 있다. 또한, 다양한 IoT(Internet of Things) 기기들로 구성된 융합환경이 상호 연결되며 IoBE(Internet of Blended Environment)가 조성되고 있다. IoBE의 구성요소 중 의료융합환경인 디지털 헬스케어는 스마트 의료 기기를 통해 진료서비스를 제공한다. 최근에는 디지털 헬스케어 내 자산 거래 수단으로 DeFi를 활용하기 위한 연구가 진행되고 있다. 그러나, 디지털 헬스케어 서비스에 DeFi가 활용될 수 있음에 따라 DeFi 내 보안 위협이 전파될 수 있다. 전파된 보안 위협은 DeFi에서의 디지털 화폐 탈취뿐만 아니라, 디지털 헬스케어 내민감 정보 탈취, 서비스 거부 공격 등 복합 위협으로 이어질 수 있다. 따라서, 본 논문에서는 DeFi의 취약점을 분석하고 이를 기반으로 디지털 헬스케어에서 발생 가능한 공격 시나리오를 도출한다.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.890-891
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• 2015

With South Korea entering aging society, the problem of the elderly living alone is aggravating due to increasing health risks associated with social isolation. This should be counteracted by providing them with supports conducive to the recovery of social relationship and effective management of daily activities, such as health checkups, homecare services, chore services, and contents building for information service. This paper presents a human care system implementing miniaturization and portability for the elderly and other care recipients by integrating various contents into recipients' situation perception, direct experience, and sensor modules as a smartphone application in Internet of Things environment to facilitate their health status monitoring.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1023-1032
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• 2017

When a cryptographic device such as smart card performs an encryption for a plain text, an attacker can extract the secret key in it using side channel information. Especially, many researches found some weaknesses for side channel attack on the lightweight block cipher LEA designed to apply in IoT environments. In this paper, we survey several masking countermeasures to defeat the side channel attack and propose a novel masking conversion method. Even though the proposed Arithmetic-to-Boolean masking conversion method requires storage memory of 256 bytes, it can improve the LEA encryption speed up to 17 percentage compared to the case adopted the previous masking method.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.641-644
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• 2021

Wearable devices and IoT are being utilized in various fields, where all systems are developing in the direction of multi-functionality, low power consumption, and high speed. In this paper, we propose a DC -DC Step-down C onverter for IoT smart devices. The proposed DC -DC Step-down converter is composed of a control block of the power supply stage. It also consists of an overheat protection circuit, under-voltage protection circuit, an overvoltage protection circuit, a soft start circuit, a reference voltage circuit, a lamp generator, an error amplifier, and a hysteresis comparator. The proposed DC-DC converter was designed and fabricated using a Magnachip / Hynix 180nm CMOS process, 1-poly 6-metal, the measured results showed a good match with the simulation results.