• Journal of IKEEE
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• v.25 no.4
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• pp.598-606
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• 2021

In this paper, we presents a new service binding and resource management model for context based services in mobile edge computing (MEC) networks. The proposed control is composed of two layers: MEC service bindng control layer (MCL) and user context control layer (UCL). The MCL manages service binding construction, resource allocation, and service policy construction from a system point of view; and the UCL manages real-time service adaptation using meta-objects. Through simulations, we confirmed that the proposed control offers enhanced throughput and content transfer time when it is compared to the legacy computing and control models. The proposed control model can be employed as a key component for the context based various internet-of-things (IoT) services in MEC environments.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.202-204
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• 2021

다양한 IoT 기기로 구성된 모바일 IoT 환경에서는 IoT에서 수집된 데이터가 다른 IoT의 학습 데이터로 사용되는 순환 구조로 이루어져 있다. 따라서 해당 환경에서 데이터는 공유되는 자원이며 매우 중요한 요소이다. 특히 IoT 기기가 밀집된 지역에서는 많은 트래픽이 발생하기 때문에 전송지연 및 데이터 손실로 인한 시스템 성능이 저하되는 문제가 발생한다. 따라서 본 논문에서는 안전한 데이터 통신을 위한 블록체인 기반의 시스템 구조를 제안한다. 해당 시스템은 블록체인을 사용하여 IoT 기기의 이동성과 밀집도를 판별하고, 트래픽 밀집 구역이 발생하였을 경우 UAV를 활용하여 통신이 원활하게 이루어질 수 있도록 한다.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.267-269
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• 2018

This paper is a study to solve the malfunction of Fire Detection System and to react swiftly in case of fire. if a fire occurs because of malfunction of the fire receiver, it may not be possible to respond appropriately. in order to solve this problem, Fire Detection System using IoT, the manager studied the method of confirming the fire occurrence with mobile phone Application. We propose a wireless Fire Detection System by building a server and a client using a micom and a mobile phone application. This is to reduce the damage caused by the fire.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.347-350
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• 2018

In order for an IoT system to automatically make the house temperature pleasant for the user, the system needs to predict the optimal start-up time of air-conditioner or heater to get to the temperature that the user has set. Predicting the optimal start-up time is important because it prevents extra fee from the unnecessary operation of the air-conditioner and heater. This paper introduces an ANN(Artificial Neural Network) and an IoT system that predicts the cooling and heating time in households using air-conditioner and heater. Many variables such as house structure, house size, and external weather condition affect the cooling and heating. Out of the many variables, measurable variables such as house temperature, house humidity, outdoor temperature, outdoor humidity, wind speed, wind direction, and wind chill was used to create training data for constructing the model. After constructing the ANN model, an IoT system that uses the model was developed. The IoT system comprises of a main system powered by Raspberry Pi 3 and a mobile application powered by Android. The mobile's GPS sensor and an developed feature used to predict user's return.

• Journal of Internet of Things and Convergence
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• v.7 no.3
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• pp.1-8
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• 2021

With the rapid increase in the use of IoT and mobile devices, cyber criminals targeting IoT devices are also on the rise. Among IoT devices, when using a wireless access point (AP), problems such as packets being exposed to the outside due to their own security vulnerabilities or easily infected with malicious codes such as bots, causing DDoS attack traffic, are being discovered. Therefore, in this study, in order to actively respond to cyber attacks targeting IoT devices that are rapidly increasing in recent years, we proposed a method to collect traces of intrusion incidents artifacts from IoT devices, and to improve the validity of intrusion analysis data. Specifically, we presented a method to acquire and analyze digital forensics artifacts in the compromised system after identifying the causes of vulnerabilities by reproducing the behavior of the sample IoT malware. Accordingly, it is expected that it will be possible to establish a system that can efficiently detect intrusion incidents on targeting large-scale IoT devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2119-2124
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• 2016

The Internet of things (IoT) needs to be an event-driven approach for efficient related time response and processing. The growth of mobile devices in Internet of Things (IoT) leads to a number of intelligent buildings related IoT applications. For instance, home automation controlling system uses client system such web apps on smartphone or web service to access the home server by sending control commands. The gateway based RESTful technology responsible for handling clients'requests attests an internet latency in case a large number of clients' requests submit toward the gateway increases. In this paper, we propose the design tasks of the IoT gateway for handling concurrency events. The gateway based event-driven architecture is designed for building IoT gateway using node.js on one side and communication protocol based message-oriented middleware known as XMPP to handle communications of intelligent building control devices connected to the gateway through a centralized hub.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

• Journal of Integrative Natural Science
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• v.11 no.3
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• pp.148-153
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• 2018

In this paper, we propose a hybrid-recognition system to obtain the state information and control the Internet of Things (IoT) based smart devices using two recognitions. First, we use a facial recognition for checking the owner of the mobile devices, i.e., smartphones, tablet PCs, and so on, and obtaining the state information of the IoT based smart devices, i.e., smart cars, smart appliance, and so on, and then we use a fingerprint recognition to control them. Further, in the conventional system, the message of the state and control information between the mobile devices and smart devices is only exchanged through the cellar mobile network. Thus, we also propose a direct communication to reduce the total transmission time. In addition, we develop a testbed of the proposed system using smartphones, desktop computers, and Arduino vehicle as one of the smart devices. We evaluate the total transmission time between the conventional and direct communications and show that the direct communication with the proposed system has better performance.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.212-217
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• 2020

We studied on the design of a sprinkler control system that communicates with the administrator's mobile through a wireless communication network and a sprinkler unit that sprays water on the vegetation area. This sprinkler control system consists of a communication module that receives an operation signal for the operation of the sprinkler unit from the administrator's mobile, and a control module that controls the sprinkler unit according to the operation signal received through the communication module. It is also designed to control sprinkler units by measuring temperature, humidity, light intensities, vibration and field images in the vegetation area in real time through sensors and camera for each of them and comparing them with established limit criteria. The sprinkler allows the administrator to control the sprinkler more easily because the administrator operates the sprinkler through the mobile from a distance, and emergency situations occur and can respond quickly.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1252-1256
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• 2016

Internet of Things(IoT)-devices are now expanding inter-connecting networking technologies to invent healthcare monitoring system especially for assessing physiological conditions of the chronically-ill patients those with cardiovascular diseases. Hence, IoT system is expected to be utilized for home healthcare by dedicating the original usage of IoT devices to collect the biomedical data such as electrocardiogram(ECG) and photoplethysmography(PPG) signal. The aim of this work is to implement health monitoring system by integrating IoT devices with Raspberry-pi components to measure and analyze ECG and the multi-channel PPG signals. The acquired data and fiducial features from our system can be transmitted to mobile devices via wireless networking technology to support the concept of tele-monitoring services based on IoT devices.