• International Journal of Advanced Culture Technology
• /
• v.9 no.1
• /
• pp.28-39
• /
• 2021

In the new era of IoT, a deeper and richer understanding of consumer characteristics is required to accelerate the acceptance and popularization of different types of smart home services (e.g., hedonic or utilitarian smart home services). In the current research, self-regulation systems are considered one of the consumer characteristics. Therefore, this research examines the role of consumers' regulatory focus (promotion focus vs. prevention focus) in their responses to smart home services, particularly when they are not familiar with the services. Specifically, this research examines whether consumers' attitudes toward utilitarian/hedonic smart home services differ according to their regulatory focus, particularly when they are not familiar with the services. The results indicate that consumers who are not familiar with smart home services have more favorable attitudes toward hedonic smart home services when they are promotion-focused (vs. prevention-focused). In contrast, there is no significant difference in their attitudes toward utilitarian smart home services between promotion- and prevention-focused consumers. Our findings imply that regulatory focus may be an effective marketing and segmentation tool in promoting new smart home services and facilitating low-familiarity consumers' receptiveness to the services.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.2
• /
• pp.892-905
• /
• 2018

In smart home environment, certificate based signature technology is being studied by communication with Internet of Things(IoT) device. However, block - chain technology has attracted much attention because of the problems such as single - point error and management overhead of the trust server. Among them, Keyless Signature Infrastructure(KSI) provides integrity by configuring user authentication and global timestamp of distributed server into block chain by using hash-based one-time key. In this paper, we provide confidentiality by applying group key and key management based on multi - solution chain. In addition, we propose a smart home environment that can reduce the storage space by using Extended Merkle Tree and secure and efficient KSI-based authentication and communication with enhanced security strength.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.6
• /
• pp.2781-2798
• /
• 2019

Thanks to internet, as one of indispensable parts of our lives, many devices that we use in our daily lives like TV, air conditioner, refrigerator, washing machine, can be monitored and controlled remotely by becoming more intelligent via Internet of Things (IoT) technology. Smart Home applications as one of the elements of smart cities, are individually the most demanded application without question. In this study, Smart Energy Management (SEM) system, based on NodeMCU and Android, has been designed for SEM, which is a part of the smart home application. With this system, household energy consumption can be monitored in real time, as well as having the ability to record the data comprising of operation times and energy consumption information for each device. Additionally, it is ensured to meet the energy needs on a maximized level possible, during the hours when the energy costs are lower owing to the SEM system. The Android interface provides the users with the opportunity to monitor and change their electricity consumption habits in order to optimize the energy efficiency, along with the opportunity to draw up of a daily and weekly schedule.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.1
• /
• pp.135-141
• /
• 2018

In this paper, we describe design and implementation of optimal smart home control system. Recent developments in technologies such as sensors and communication have enabled the Internet of Things to control a wide range of objects, such as light bulbs, socket-outlet, or clothing. Many businesses rely on the launch of collaborative services between them. However, traditional IoT systems often support a single protocol, although data is transmitted across multiple protocols for end-to-end devices. In addition, depending on the manufacturer of the Internet of things, there is a dedicated application and it has a high degree of complexity in registering and controlling different IoT devices for the internet of things. ARIoT system, special marking points and edge extraction techniques are used to detect objects, but there are relatively low deviations depending on the sampling data. The proposed system implements an IoT gateway of object based on OneM2M to compensate for existing problems. It supports diverse protocols of end to end devices and supported them with a single application. In addition, devices were learned by using deep learning in the artificial intelligence field and improved object recognition of existing systems by inference and detection, reducing the deviation of recognition rates.

• Telecommunications review
• /
• v.24 no.5
• /
• pp.677-691
• /
• 2014

Connectivity is becoming more important keywords recently. For example, many devices are going to be connected to the internet. It is usually called as the IoT(internet of things). Many IoT devices can be evolved as a part of giant system of the world wide web. It is a great opportunity for us, because many new services can have emerged through this paradigm. In this paper, we propose a device virtualization framework for smart home service. The proposed framework connects the many home appliances devices and the internet using a dynamic protocol conversion. After our protocol conversion for device virtualization, our framework provides a RESTful API to access the resources of device through the internet. Therefore, the proposed framework can provide a variety of services, so it also can be developed into the ecosystem for smart home service. The current framework version only supports UPnP enabled devices of the home, but it can easily be extended to many other home middleware solutions. To verify the feasibility of the framework, we have implemented several service scenarios.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.14 no.5
• /
• pp.277-286
• /
• 2019

In this paper, we propose an efficient hyperplane generation technique to classify human activity from combination of events and sequence information obtained from multiple-event sensors. By generating hyperplane efficiently, our machine learning algorithm classify with less memory and run time than the LSVM (Linear Support Vector Machine) for embedded system. Because the fact that light weight and high speed algorithm is one of the most critical issue in the IoT, the study can be applied to smart home to predict human activity and provide related services. Our approach is based on reducing numbers of hyperplanes and utilizing robust string comparing algorithm. The proposed method results in reduction of memory consumption compared to the conventional ML (Machine Learning) algorithms; 252 times to LSVM and 34,033 times to LSTM (Long Short-Term Memory), although accuracy is decreased slightly. Thus our method showed outstanding performance on accuracy per hyperplane; 240 times to LSVM and 30,520 times to LSTM. The binarized image is then divided into groups, where each groups are converted to binary number, in order to reduce the number of comparison done in runtime process. The binary numbers are then converted to string. The test data is evaluated by converting to string and measuring similarity between hyperplanes using Levenshtein algorithm, which is a robust dynamic string comparing algorithm. This technique reduces runtime and enables the proposed algorithm to become 27% faster than LSVM, and 90% faster than LSTM.

• Journal of Internet Computing and Services
• /
• v.23 no.5
• /
• pp.69-78
• /
• 2022

As the use of Internet of Things (IoT) devices has expanded, digital forensics coverage of the National Police Agency has expanded to smart home areas. Accordingly, most of the existing studies conducted to acquire smart home platform data were mainly conducted to analyze local data of mobile devices and analyze network perspectives. However, meaningful data for evidence analysis is mainly stored on cloud storage on smart home platforms. Therefore, in this paper, we study how to acquire stored in the cloud in a Hey Home Air environment by extracting accessToken of user accounts through a cookie database of browsers such as Microsoft Edge, Google Chrome, Mozilia Firefox, and Opera, which are recorded on a PC when users use the Hey Home app-based "Hey Home Square" service. In this paper, the it was configured with smart temperature and humidity sensors, smart door sensors, and smart motion sensors, and artifacts such as temperature and humidity data by date and place, device list used, and motion detection records were collected. Information such as temperature and humidity at the time of the incident can be seen from the results of the artifact analysis and can be used in the forensic investigation process. In addition, the cloud data acquisition method using OpenAPI proposed in this paper excludes the possibility of modulation during the data collection process and uses the API method, so it follows the principle of integrity and reproducibility, which are the principles of digital forensics.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.10
• /
• pp.499-508
• /
• 2016

According to spreading K-pop globally, the market size related to K-pop stars is increasingly growing at home and abroad. Recently, services and products having direct interaction with the star are emerging. This research aims to propose a new service using a smart, connected social robotic figure that can support interaction between fans and K-pop stars. For this study, we begin by exploring literature about K-pop culture. Also, we investigate cases that connect between fans and stars and then build the development directions for a new service. Based on these development directions, we extract feasible technology and its interaction elements through analysing the cases of social robots. Finally, we propose the social robotic figure service in this research. This service proposed in this study can create and enhance diverse bidirectional communication between fans and stars through employing a user-customized, smart, connected figure based on a IoT platform. This research contributes to approaches for sustainable advance of K-pop through applying IoT technology.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.11a
• /
• pp.1137-1140
• /
• 2017

본 연구에서는 Java기반 Android App과 라즈베리파이 보드를 기반으로 Wi-fi 통신을 통해 스마트폰과 라즈베리파이를 연동하여 집안의 커튼, 전구, 카메라 등과 같은 기기들을 제어하는 시스템을 구현하는 방법을 제시하였다. 기존의 가정의 전구와 커튼과 같은 전자기기들을 스마트폰을 통하여 자택에서 편안하게 제어할 수 있으며 향후 지어지는 신축 아파트들이나 병원과 같은 시설에서 이러한 IoT 기술이 접목될 가능성이 있기 때문에 라즈베리파이와 하드웨어를 연동하여 가정기기를 제어하는 시스템을 구현하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.787-790
• /
• 2015

스마트폰의 등장을 시작으로 사물과 인터넷의 결합이 급속히 진행되면서 다양하고 새로운 시장이 형성 되고 있다. 특히 모바일 네트워크가 확산되면서 소비자의 스마트 홈 시장에 대한 관심이 높아졌으며 다양한 기업들이 스마트 홈 시장에 진입하고 있다. 본 논문에서는 다양한 스마트 홈 기술을 소개한다. OneM2M, AllJoyn의 플랫폼 구조와 보안 표준을 살펴보고 IoTivity, Homekit, Thread의 특징을 분석하여 스마트 홈 기술의 동향을 분석한다.