• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.370-378
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• 2018

Recent advances in network infrastructures, sensors, and IoT devices have accelerated the research and development of monitoring and interaction technologies designed for people, buildings, and environments. In particular, there has been an increasing demand for monitoring technologies for vulnerable people such as the infirm, disabled, and children. In this paper, we propose an efficient hospital room management system based on IoT care robots. The status of hospital rooms can be monitored and controlled more efficiently and intuitively by utilizing IoT devices and a cloud platform. We demonstrated the feasibility of the proposed system through the implementation of a prototype based on ARTIK IoT devices and the ARTIK Cloud platform. We found that the proposed system requires approximately 600 ms and 130 ms to collect sensor data and respond to alerts, respectively, which demonstrates it can operate in real-time.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.909-917
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• 2018

Recently, the Internet of Thing (IoT) technology is expanding explosively in the number of devices and applications in many application areas. In IoT systems, sensors and actuators are connected to the Internet and cooperate to do some applications by exchanging information. In this paper an IoT smart home system is developed to monitor and control home devices easily. Our system consists of sensor devices, IoT gateways, and an IoT server. Sensor devices developed using Rfduino sense the physical world and transmit their data using BLE to the IoT server thru the IoT gateway. We implemented the IoT gateway using Raspberry Pi and the IoT server using ARTIK cloud. We installed our system and made a test in our lab, which showed that our system can be installed and managed easily and extended its functionality in an easy way. By taking advantage of the rule mechanism and action messages of ARTIK cloud, we implemented the control of device parameters easily by sending action messages to the ARTIK cloud.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.513-514
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• 2018

Recently, IoT(Internet of Things) technology is being actively used to develop smart products and services. This paper proposes the architecture and major functionalities of IoT outdoor exercise equipment using ARTIK IoT Platform. It provides an exerciser with date&time, weather information, the amount of exercise. The amount of exercise and a user's ID are sent to a service server by LTE-M modem and the server provides the exercise history by web or smartphone app. As additional functionalities, a fine dust alarm light and an emergency alarm button are embedded. The proposed system has been exhibited on CHINA SPORT SHOW 2018 held on Shanghai, China.

• Journal of IKEEE
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• v.22 no.3
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• pp.664-671
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• 2018

Generally, conventional solar tracking systems employ irradiance sensors to track a sun position, which enables the system to generate maximum solar energy. The usage of irradiance sensors increases system costs and deteriorates the performance of systems from sensor malfunctions. In this paper, a new solar tracking system without irradiance sensors has been proposed in which the controller capable of controlling and monitoring remotely is based on Artik platform. The proposed system tracks the sun position by comparing the amount of currents from several solar panels, resulting in removing irradiance sensors. In order to verify the performance of the proposed solar tracking method, the 12[V]-20[W] prototype system is built and implemented. Since the proposed system has remote monitoring functions through the employment of Artik as the IoT platform, more advantages in installation, maintenance and expanded functionality can be obtained compared to the conventional solar tracking system.

• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.47-53
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• 2017

In this paper, we present open hardware platforms for Internet of Things (IoTs) emphasizing their strengths and weaknesses. We introduce six representative platforms, Raspberry PI, Arduino, Garileo, Edison, Beagle board and Artik. We define important performance issues for open hardware platforms for IoTs and analyze recent platforms according to the performance issues. We present recent research project using open hardware platforms introduced in this paper. We believe that this paper provide wise view and necessary information for open hardware platforms for Internet of Things (IoT).

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.584-587
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• 2018

사물인터넷(Internet of Things; IoT)이 차세대 성장동력으로 부상하면서 선진국을 비롯한 많은 단체들이 IoT 육성을 위한 전략을 세우고 있다. 특히 플랫폼(platform)은 IoT의 중요요소기술로 여겨지면서 IoT 플랫폼 보안에 대한 관심은 나날이 높아지고 있다. 현재 국내 IoT 플랫폼('ARTIK', 'Thingplug', 'IoTMakers')들은 oneM2M과 같은 국제표준기술을 기반으로 플랫폼의 다양한 기능을 제공해줌으로서 사용자가 IoT 생태계(ecosystem)에 보다 쉽게 접근할 수 있도록 독려하고 있다. 이렇듯 IoT 플랫폼 기술이 빠른 속도로 성장하고 있는 반면, 국내 IoT 플랫폼들의 보안에 대한 분석이나 연구사례가 거의 없다. 따라서 본 논문에서는 현재 상용화하고 있는 국내 IoT 플랫폼들을 대상으로 보안분석을 수행하고 보안이슈와 보완방안을 시사한다.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.428-442
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• 2022

A reliable automatic passenger counting (APC) system is a key point in transportation related to the efficient scheduling and management of transport routes. In this study, we introduce a lightweight head detection network using deep learning applicable to an embedded system. Currently, object detection algorithms using deep learning have been found to be successful. However, these algorithms essentially need a graphics processing unit (GPU) to make them performable in real-time. So, we modify a Tiny-YOLOv3 network using certain techniques to speed up the proposed network and to make it more accurate in a non-GPU environment. Finally, we introduce an APC system, which is performable in real-time on embedded systems, using the proposed head detection algorithm. We implement and test the proposed APC system on a Samsung ARTIK 710 board. The experimental results on three public head datasets reflect the detection accuracy and efficiency of the proposed head detection network against Tiny-YOLOv3. Moreover, to test the proposed APC system, we measured the accuracy and recognition speed by repeating 50 instances of entering and 50 instances of exiting. These experimental results showed 99% accuracy and a 0.041-second recognition speed despite the fact that only the CPU was used.