• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.143-158
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• 2017

Smart Home Appliance which makes people to operate machines in the home by remote control is service or technology to provide convenience. It is close to home, so it has privacy problem and security problem. If Smart Home Applications is attacked, Scale of damage is anticipated. In case of products from overseas country, various vulnerability has been announced every year. Therefore, It is necessary to identify and to analysis threats of Smart Home Appliance using systematically method for using safe Smart home appliance service. In this paper, we present check list for identifying and analyzing threats using Threat Modeling and then we analyzed the Domestic Smart Home Appliance using check list which we present.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.4
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• pp.480-485
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• 2010

In this paper, we developed mobile robot platform called Ecobot for the application system of friendly environment smart home appliance. Ecobot fulfills the purposes of monitoring of the healthy environment and guidance in the application system of friendly smart environment home appliance, home network formed by Zigbee network. For the healthy environment, the system contains monitoring sensor. Moreover, it continuously keeps the healthy environment by controlling the smart home appliances linkng with Zigbee network. And also using the URG-04LX laser distance sensor, it monitors indoor environment through autonomous moving and collision avoidance.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.83-89
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• 2010

If an appliance perceives the location or health condition of a resident in the smart home, it can provide more intelligent service actively. That is, while the conventional appliance is operated by manual input of a resident, the location-based human adaptive appliance detects the resident's information such as location, activity pattern, or health condition by itself and provides the most suitable living condition for the resident autonomously. This paper presents the real-time location-based metabolic rate estimation method that measures the amount of physical activity (metabolic rate) for location-based human adaptive air-conditioner. And, the feasibility of the algorithm is evaluated experimentally on a test bed using the pyroelectric infrared sensor-based indoor location aware system (PILAS) that is a non-terminal-based location-aware system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.67-74
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• 2011

With the rapid increase of recent smart phone diffusion, the convergences of home network environments and intelligent home appliances such as digital TV, internet refrigerator, DVD, digital video, communication appliance using a smart phone are highly focussed and become the recent trends in IT industry. In this paper, we design and implement home appliance control system based on the smart phone(Android) network environments. Through several experiments using Android smart phone, we confirmed that the proposed system can control and monitor indoor home appliances conveniently anywhere and anytime from outdoor.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.414-424
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• 2015

In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.1
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• pp.85-109
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• 2023

Laundry has traditionally been regarded as one of the most demanding household chores, but the introduction of smart washing machines is changing this perception. Although smart washing machines have been on the market for several years and consumers' perceptions of washing machines have changed, little is known about consumers' perceptions of smart washing machines. The purpose of this study is to determine what users expect from smart washing machines. We conducted two focus group interviews with sixteen participants who had used smart home appliances to acquire qualitative data. Stimuli created by the interviewees were applied in the focus group interviews to collect more insightful data. We analyzed the data using the three-step method and QSR NVivo. Analysis revealed ten categories of predictive expectations, including seven utilitarian attributes (i.e., smart functionality, smart user interface, reliability, controllability, interactivity, functional value, and economic value) and three hedonic attributes (i.e., fashionable value, psychological value, and social value). The results of this study have implications for the development of smart washing machines that would satisfy consumers by taking user expectations into account.

• Proceedings of the Korea Society of Design Studies Conference
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• 2005.05a
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• pp.266-267
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• 2005

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.486-494
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• 2014

Intelligent homes consist of ubiquitous sensors, home networks, and a context-aware computing system. These homes are expected to offer many services such as intelligent air-conditioning, lighting control, health monitoring, and home security. In order to realize these services, many researchers have worked on various research topics including smart sensors with low power consumption, home network protocols, resident and location detection, context-awareness, and scenario and service control. This paper presents the real-time metabolic rate estimation method that is based on measured heart rate for human adaptive appliance (air-conditioner, lighting etc.). This estimation results can provide valuable information to control smart appliances so that they can adjust themselves according to the status of residents. The heart rate based method has been experimentally compared with the location-based method on a test bed.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.213-219
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• 2015

Real-time energy monitoring systems is a demand-response system which is reported to be effective in saving energy up to 12%. Real-time energy monitoring system is commonly composed of smart-plugs which sense how much electrical power is consumed and IHD(In-Home Display device) which displays power consumption patterns. Even though the monitoring system is effective, users should themselves match which smart plus is connected to which appliance. In order to make the matching work to be automatic, the monitoring system need to have appliance identification algorithm, and some works have made under the name of NILM(Non-Intrusive Load Monitoring). This paper proposed an algorithm which utilizes multiple classifiers to improve accuracy of appliance identification. The algorithm proposes to understand each classifiers performance, that is, when a classifier make a result how much the result is reliable, and utilize it in choosing the final result among result candidates from many classifiers. By using the proposed algorithm this paper make 4.5% of improved accuracy with respect to using single best classifier, and 2.9% of improved accuracy with respect to other method using multiple classifiers, so called CDM(Commitee Decision Mechanism) method.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.127-137
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• 2018

As the next generation technology, leading 4th industrial revolution has been progressed, the goods and services converged by the technology are being released in a market. The smart appliances among them attracts users' attentions as a key promising industry. Thus, this study investigates the factors that influence switching intention to smart appliances based on Push-Pull-Mooring framework. We collected 217 survey responses and formed structural equation modeling with AMOS 22.0. The results show that functional deprivation, money deprivation, alternative attractiveness had an effect on the switching intention to smart appliances. In addition, low switching cost is related to the relationship between external variables and switching intention. The results expect to provide useful information to the smart appliance-related companies.