• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1949-1954
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• 2016

Smart grid technology can be called grid techniques to improve the efficiency of the electric power by exchanging bidirectional information of electric power with real-time between electric power suppliers and consumers. Recently, the solar power generation system is being applied actively. However the solar power system has several problems leading to reduce overall electricity generation, because the difficult of the diagnosis and the solar power system failure such as PV(PhotoVoltaics) and inverter. In order to build an efficient smart grid, a stable electric power energy requirements capture and management and early fault detection is essentially required in solar power generation system. In this paper, it is designed to monitor the operating status of the solar power monitoring system from a remote location through a RS-485 or TCP/IP communication module to monitoring the output of solar power energy and abnormal phenomenon, to developing the measurement module and to transfer measured data.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.808-817
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• 2016

Recently, the wearable computing technology with bio-sensors has been rapidly developed and utilized in various areas such as personal health, care-giving for senior citizens who live alone, and sports activities. In particular, the wearable computing equipment to measure vital signs by means of digital yarns and bio sensors is noticeable. The wearable computing devices help users monitor and manage their health in their daily lives through the customized healthcare service. In this paper, we suggest a system for monitoring and analyzing vital signs utilizing smart healthcare clothing with bio-sensors. Vital signs that can be continuously acquired from the clothing is well-known as unstructured data. The amount of data is huge, and they are perceived as the big data. Vital sings are stored by Hadoop Distributed File System(HDFS), and one can build data warehouse for analyzing them in HDFS. We provide health monitoring system based on vital sings that are acquired by biosensors in smart healthcare clothing. We implemented a big data platform which provides health monitoring service to visualize and monitor clinical information and physical activities performed by the users.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2235-2239
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• 2003

The aim of this research is to study and develop enabling technologies for home healthcare device with ubiquitous network. The motivation of this paper is to enable healthcare in home, to development the device for smart home health care. To achieve the aim, we must develop the prototype platform based on home gateways, distributed context user interface based on UPnP and support for information sharing with high speed power line communication and mobile infra-structures. And IPv6 is the base technology of this platform. In this paper, we concern that physical health, mental health and medical emergencies is all of home healthcare. With the smart device, we evaluate the connectivity, automatic information extraction and private data exchange and event driven message. The result of this paper is demonstration of smart device for ubiquitous communication in a healthcare application such as patient monitoring device and several information services. In conclusion, home healthcare will support more healthy and easy living for a human.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.619-628
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• 2012

The ZigBee network has been considered to monitor electricity usage of home appliances in the smart grid network. ZigBee, however, may suffer from a coexistence problem with wireless local area network (WLAN). In this paper, to resolve the coexistence problem between ZigBee network and WLAN, we propose a new protocol constructing a cognitive smart grid network for supporting monitoring of home appliances. In the proposed protocol, home appliances first estimates the transmission timing and channel information of WLAN by reading request to send/clear to send (RTS/CTS) frames of WLAN. Next, based on the estimated information, home appliances transmit a data at the same time as WLAN transmission. To manage the interference between WLAN and smart grid network, we propose a cognitive beamforming algorithm. The beamforming algorithm is designed to guaranteeing zero interference to WLAN while satisfying a required rate for smart metering. We also propose an energy efficient rate adaptation algorithm. By slowing down the transmission rate while satisfying an imperceptible impact of quality of service (QoS) of the receiver, the home appliance can significantly save transmit power. Numerical results show that the proposed multiple antenna technique provides reliable communications for smart metering with reduced power comparing to the simple transmission technique.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.162-175
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• 2018

Currently, electricity consumption and feedback mechanisms are being widely researched in Internet of Things (IoT) areas to realise power consumption monitoring and management through the remote control of appliances. This paper aims to develop a smart electricity utilisation IoT platform with a deep belief network for electricity utilisation feature modelling. In the end node of electricity utilisation, a smart monitoring and control module is developed for automatically operating air conditioners with a gateway, which connects and controls the appliances through an embedded ZigBee solution. To collect electricity consumption data, a programmable smart IoT gateway is developed to connect an IoT cloud server of smart electricity utilisation via the Internet and report the operational parameters and working states. The cloud platform manages the behaviour planning functions of the energy-saving strategies based on the power consumption features analysed by a deep belief network algorithm, which enables the automatic classification of the electricity utilisation situation. Besides increasing the user's comfort and improving the user's experience, the established feature models provide reliable information and effective control suggestions for power reduction by refining the air conditioner operation habits of each house. In addition, several data visualisation technologies are utilised to present the power consumption datasets intuitively.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.207-210
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• 2005

Ubiquitous computing is one of the key technology areas in the "Project on Development of Ubiquitous computing and network technology" promoted by the Ministry of Science and Technology as a frontier business of the $21^{st}$ century in Korea, which is based on the new concept merging physical space and computer-based cyber space. With recent advances in Micro Electro Mechanical System (MEMS) technology, low cost and low-power consumption wireless micro sensor nodes have been available. Using these smart sensor nodes, there are many activities to monitor real world, for example, habitat monitoring, earthquake monitoring and so on. In this paper, we introduce web-based real environment monitoring system incorporating wireless sensor nodes. It collects sensing data produced by some wireless sensor nodes and stores them into a database system to analyze. Our environment monitoring system is composed of a networked camera and environmental sensor nodes, which are called Mica2 and developed by University of California at Berkeley. We have modified and ported network protocols over TinyOS and developed a monitoring application program using the MTS310 and MTS420 sensors that are able to observe temperature, relative humidity, light and accelerator. The sensed data can be accessed user-friendly because our environment monitoring system supports web-based user interface. Moreover, in this system, we can setup threshold values so the system supports a function to inform some anomalous events to administrators. Especially, the system shows two useful pre-processed data as a kind of practical uses: a discomfort index and a septicity index. To make both index values, the system restores related data from the database system and calculates them according to each equation relatively. We can do enormous works using wireless sensor technologies, but just environment monitoring. In this paper, we show just one of the plentiful applications using sensor technologies.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.30-33
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• 2015

In this paper, we proceeded a study on the Hybrid RF based development of the smart phone Application skin disease monitoring using CMOS camera. we proposed an image transfer technology which can use the CMOS camera and we developed the smart phone application which can be possible to use a remote monitoring for skin disease. Image transfer technology using Hybrid RF communication applied for WiFi using CMOS camera. We implemented the function which can use a remote monitoring using Wi-Fi. These suggestion can be a good example for endoscopic applications using hybrid RF based smart phone application of skin disease monitoring using CMOS camera.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3544-3564
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• 2022

With the development of the NB-IoT (Narrow band Internet of Things) and smart cities, coupled with the emergence of smart smoke sensors, new requirements and issues have been introduced to study on the deployment of sensors in large spaces. Previous research mainly focuses on the optimization of wireless sensors in some monitoring environments, including three-dimensional terrain or underwater space. There are relatively few studies on the optimization deployment problem of smart smoke sensors, and leaving large spaces with obstacles such as libraries out of consideration. This paper mainly studies the deployment issue of smart smoke sensors in large spaces by considering the fire probability of fire areas and the obstacles in a monitoring area. To cope with the problems of coverage blind areas and coverage redundancy when sensors are deployed randomly in large spaces, we proposed an optimized deployment strategy of smart smoke sensors based on the PSO (Particle Swarm Optimization) algorithm. The deployment problem is transformed into a multi-objective optimization problem with many constraints of fire probability and barriers, while minimizing the deployment cost and maximizing the coverage accuracy. In this regard, we describe the structure model in large space and a coverage model firstly, then a mathematical model containing two objective functions is established. Finally, a deployment strategy based on PSO algorithm is designed, and the performance of the deployment strategy is verified by a number of simulation experiments. The obtained experimental and numerical results demonstrates that our proposed strategy can obtain better performance than uniform deployment strategies in terms of all the objectives concerned, further demonstrates the effectiveness of our strategy. Additionally, the strategy we proposed also provides theoretical guidance and a practical basis for fire emergency management and other departments to better deploy smart smoke sensors in a large space.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.733-739
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• 2019

Water level measurement is highly demanding in IoT monitoring areas such as smart factory, smart farm, and smart fish farm. However, existing water level indicators are limited to be used in industrial fields as commercial products due to the high cost of sensors and the complexity of algorithms used. In order to solve these problems, our paper proposed methods using an infrared distance sensor as well as a hall sensor for the water level measurement, both of which are contactless smart sensors. Data errors caused by the inaccuracy of existing sensors were decreased by applying new simple structures so that versatility is enhanced. The performance of our method was validated using experiments based on simulations. We expect that our new water depth indicator can be extended to a general-purpose water level monitoring system based on IoT technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2213-2231
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• 2013

Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.