• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3029-3045
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• 2017

The main processes of a cognitive radio system include spectrum sensing, spectrum decision, spectrum sharing, and spectrum conversion. Experimental results show that these stages introduce a time delay that affects the spectrum sensing accuracy, reducing its efficiency. To reduce the time delay, the frequency spectrum prediction was proposed to alleviate the burden on the spectrum sensing. In this paper, the deep recurrent neural network (DRNN) was proposed to predict the spectrum of multiple time slots, since the existing methods only predict the spectrum of one time slot. The continuous state of a channel is divided into a many time slots, forming a time series of the channel state. Since there are more hidden layers in the DRNN than in the RNN, the DRNN has fading memory in its bottom layer as well as in the past input. In addition, the extended Kalman filter was used to train the DRNN, which overcomes the problem of slow convergence and the vanishing gradient of the gradient descent method. The spectrum prediction based on the DRNN was verified with a WiFi signal, and the error of the prediction was analyzed. The simulation results proved that the multiple slot spectrum prediction improved the spectrum efficiency and reduced the energy consumption of spectrum sensing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.285-290
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• 2016

In rural area, our farmers confront decreasing benefits owing to imported crops and increased cost. Recently, the government encourage the 6th Industry that merges farming, rural resources, and information and communication technology. Therefor the government makes an investment in supplying 'smart greenhouse' in which a farmer monitor growing crops and environment information to control growing condition. The objective of this study is developing an Moving Monitor and Control System for crops in green House. This system includes a movable sensing unit, a controlling unit, and a server PC unit. The movable sensing unit contains high resolution IP camera, temperature and humidity sensor and WiFi repeater. It rolls on a rail hanging beneath the ceiling of a green house. The controlling unit contains embedded PC, PLC module, WiFi router, and BLDC motor to drive the movable sensing unit. And the server PC unit contains a integrated farm management software and home pages and databases in which the images of crops and environment informations. The movable sensing unit moves widely in a green house and gathers lots of information. The server saves these informations and provides them to customers with the direct commercing web page. This system will help farmers to control house environment and sales their crops in online market. Eventually It will be helpful for farmers to increase their benefits.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2730-2736
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• 2010

Recently, various networks have been introduced in the car of the internal and external sides. These have been integrated by one HMI(Human Machine Interface) to control devices of each network and provide information service. The existing vehicle navigation system, providing GPS based vehicle positioning service, has been included to these integrated networks as a default option. The GPS has been used to the most universal device to provide position information by using satellites' signal. But It is impossible to provide the position information when the GPS can't receive the satellites' signal in the area of tunnel, urban canyon, or forest canopy. Thus, this paper propose and implement the method of measuring vehicle position by using the sensing data of internal CAN network and external Wi-Fi network of the integrated car navigation circumstances when the GPS doesn't work normally. The results obtained by implementation shows the proposed method works well by map matching.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.321-326
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• 2021

Wireless communication is a core technology constituting the Internet of Things (IoT), but there is no suitable educational equipment to learn various wireless communication technologies used in the Internet of Things through practice. This paper deals with the development of advanced education and training equipment that can perform various IoT wireless communication practices. It uses an Arduino mega board as a device to control various sensors. As wireless network technologies to send and receive the sensing date wirelessly, it makes use of RFID/NFC and Bluetooth among WPAN technologies, WiFi among WLAN technologies and LoRa and 2.4GHz wireless transceiver among WWAN technologies. In addition, GPS, infrared communication, I2C communication, and SPI communication are organized so that various IoT wireless communication technologies can be learned through practice. In addition, since the educational equipment developed in this paper is equipped with two devices, it is designed to perform transmission and reception experiments for wireless network technology within the equipment.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.47-53
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• 2015

In this paper, we propose a novel tangible interface system whose system does not use the expensive hardware is introduced. This proposed tangible interface is used on the table top capacitive multi touch-screen. The tangible interface apparatus which is called smart puck has sanguine arduino compatible board. The board has a Cds photo-sensing sensor and the EPP8266 WiFi module. The Cds sensor decodes the photometric PWM signals from the system and sends corresponding information to the system via TCP/IP. The system has a server called MT-Server to communicate with the smart pucks. The tangible interface shows reliable operation with fast response that is compatible to the expensive traditional devices in the market.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.69-70
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• 2013

Through shipbuilding industry and IT convergence, high effiency of production facilities and process will be achieved. Using LTE based communicator, variable sensing data obtained from shipyard cabe be transmitted to central server. This agent system can be applied to total monitoring, sail test, and accident prevention, etc.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.215-226
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• 2015

Normally, aero photography using UAV uses about 430 MHz bandwidth radio frequency (RF) modem and navigates and remotely controls through the connection between UAV and ground control system. When using the exhausting method, it has communication range of 1-2 km with frequent cross line and since wireless communication sends information using radio wave as a carrier, it has 10 mW of signal strength limitation which gave restraints on life my distance communication. The purpose of research is to use communication technologies such as long-term evolution (LTE) of smart camera, Bluetooth, Wi-Fi and other communication modules and cameras that can transfer data to design and develop automatic shooting system that acquires images to UAV at the necessary locations. We conclude that the android based UAV filming and communication module system can not only film images with just one smart camera but also connects UAV system and ground control system together and also able to obtain real-time 3D location information and 3D position information using UAV system, GPS, a gyroscope, an accelerometer, and magnetic measuring sensor which will allow us to use real-time position of the UAV and correction work through aerial triangulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.740-746
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• 2013

Machine to machine (M2M) communication is a converged ICT(Information and Communications Technology) platform which can utilize communications services among people and things anytime, any place in realtime. The M2M platform consists of three components; M2M area networks sensing and generating data of things by various sensors and devices; public networks transporting those data; and M2M applications utilizing the aggregated data. There exist however two practical obstacles to realize the M2M communications in terms of interoperability between the WCDMA-based public network and the local networks based on W-Fi or ZigBee; one is the cost problem required to access the public network, and the other is the lack of a cost-effective modem or gateway to connect two different networks. In this paper, we proposed and implemented a novel M2M platform based on PWW (Person Area Network) which can resolve those two issues by using a proposed gateway connecting the local network and smartphones as application devices without access the WCDMA-based public network. We have shown that the proposed platform is very practical to adopt to the real environment by actual testing with the own developed smartphone applications.

• Journal of the Korean Society of Safety
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• v.32 no.1
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• pp.21-26
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• 2017

An IoT-based particulate matter (PM2.5) sensing device (PSD) is developed. The PSD consists of a PM2.5 sensor, signal processing circuit, and wi-fi enabled-microprocessor along with temperature and humidity sensors. The PSD estimates PM2.5 density by measuring light scattered by PM2.5. To gauge performance of the PSD, PM2.5 density of open air was measured with the PSD and compared with that of the collocated-government-certified measuring station. Measurements were taken at a sampling frequency of 100 Hz and moving-averaged to remove measurement noise. When compared to the result of the measuring station, average percentile error of PM2.5 density from the PSD is found to be 31%. A correlation coefficient is found to be 0.72 which indicates a strong correlation. Instantaneous variation, however, may far exceed average errors, leading to a conclusion that the PSD is more suitable for estimating average trend of PM2.5 density variations than estimating instantaneous PM2.5 density.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.897-908
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• 2018

In this paper, we propose a security framework for a cluster drones network using the MAVLink (Micro Air Vehicle Link) application protocol based on FANET (Flying Ad-hoc Network), which is composed of ad-hoc networks with multiple drones for IoT services such as remote sensing or disaster monitoring. Here, the drones belonging to the cluster construct a FANET network acting as WTRP (Wireless Token Ring Protocol) MAC protocol. Under this network environment, we propose an efficient algorithm applying the Lightweight Encryption Algorithm (LEA) to the CTR (Counter) operation mode of WPA2 (WiFi Protected Access 2) to encrypt the transmitted data through the MAVLink application. And we study how to apply LEA based on CBC (Cipher Block Chaining) operation mode used in WPA2 for message security tag generation. In addition, a modified Diffie-Hellman key exchange method is approached to generate a new key used for encryption and security tag generation. The proposed method and similar methods are compared and analyzed in terms of efficiency.