• Journal of Korea Trade
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• v.26 no.8
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• pp.1-20
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• 2022

Purpose - The paper aims to develop the theory of TAM and perceived risk through a more comprehensive and rigorous understanding of the influencing factors of the consumer's adoption of LG HomNet smart home from the perspective of trade-offs. Design/methodology - Based on the TAM and perceived risk theory, combined with the individual characteristics of consumers in the context of information technology as the external factors of the technology acceptance model, this paper constructs a theoretical model of the factors affecting the use intention of the consumer. It was empirically tested by using SEM, and survey data was collected from 458 respondents. Findings - The research results show that 9 hypotheses of the research model are supported and have reliable prediction accuracy. Consumers' perceived interest, perceived connectivity and perceived controllability have a significant positive impact on their intention to use. In addition, this paper also confirmed the mediating effect of perceived usefulness and perceived ease of use. Originality/value - Consumers are very concerned about gains and losses. Low-level performance risks, security risks, and financial risks will drive the consumer to have a stronger intention to use, and financial risks have the strongest impact. This research provides a useful implication and guidance for smart home equipment manufacturers and service providers in product and service innovation and marketing and promotion strategies.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.592-597
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• 2014

In this paper, we propose an adaptive transformation engine that provides smart devices with optimal user interfaces and media contents to their characteristics so as to conveniently control home networks remotely using smart devices in the wired and wireless home networks which various kinds of smart devices and home network devices are connected. The proposed engine dynamically transforms UI contents and transfers them using device profiles and UI transformation policies to make it suitable for smart devices. Moreover, the proposed engine offers suitable media contents for smart devices through capabilities of real-time media transcoding and streaming considering device and media profiles.

• 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 Institute of Control, Robotics and Systems
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• v.12 no.9
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• pp.905-911
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• 2006

Smart homes are expected to offer various intelligent services by recognizing the residents' life pattern, health, and feeling. One of the key issues for realizing the smart home is how to detect the locations of residents. Currently, the research effort is focused on two approaches: terminal-based and non-terminal-based method. The terminal-based method employs a type of device that should be carried by the resident while the non-terminal-based method has no such device. This paper presents a novel non-terminal-based approach using an array of pyroelectric infrared sensors (PIRs) that can detect residents. The feasibility of the system is evaluated experimentally on a test bed.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.271-272
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• 2018

4차 혁명을 맞으며 최대 키워드인 사물인터넷(IoT)이 부각되면서 다양한 분야의 산업에 IoT 제품들이 소비시장에 등장하고 있다. 사물인터넷(IoT) 기술은 최근 주택의 주거 공간 내에서 삶의 질을 높여주는 스마트홈(Smart Home)에 적용 확대되고 있다. 이에 본 연구는 국내 스마트홈(Smart Home) 기술현황을 분석하고자 하며, 그 분석 대상을 국내 주요 3개의 이동통신사의 스마트홈(Smart Home) 사물인터넷(IoT) 홈 서비스로 한다. 본 연구는 국내 주요이동통신사에서 제공하고 있는 사물인터넷(IoT) 홈서비스의 기술사례를 통해 안전성, 편리성, 절약성 3가지의 유형으로 나누어 분석하였다.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.111-125
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• 2004

In this paper, we applied user-centered context to Smart Home Applications. Current research activities on smart home have just focused on the infrastructure without considering user's contexts and implementation cost. We first realized the user-centered personalized services using ubi-UCAM (a Unified Context-aware Application Model), which exploited contexts from various kinds of smart sensors. We, then, verified its usefulness in the ubiquitous computing-enabled home environment. It can be extended to various application areas since it guarantees independence between sensors and services. Accordingly, it will play a key role in future smart home environment.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.312-314
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• 2005

We have implement indoor positioning system to supply orientation information, We have used ultrasound in indoor positioning system for distance and orientation measurements, then propose a set of methods to calculate orientation from an array of well placed ultrasonic sensors operating in the indoor positioning system, We have design and implement a indoor positioning system using a combination of hardware and software and demonstrate end-to-end functionality of the system, We have implement ZigBee based home automation system using location-aware System.

• Convergence Security Journal
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• v.22 no.2
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• pp.59-66
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• 2022

Recently, smart home technology has been developed with a great response due to the convenience of home automation. Smart home technology provides various services by connecting various Internet of Things (IoT) and sensors to a home network through wired/wireless networks. In addition, the smart home service easily and conveniently controls lighting, energy, environment, and door cameras through a wall pad. However, while it has become a social issue due to the recent hacking accident of wall pads, personal information leakage and privacy infringement are expected. Accordingly, it is necessary to prepare preventive and countermeasures against security vulnerability factors of wall pads. Therefore, this study expects that it can be used as basic data for future smart home application and response technology development by examining the weak causes and countermeasures related to wall pads.

• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.209-216
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• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.31 no.3
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• pp.81-100
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• 2013