• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.1-12
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• 2016

Internet of Things (IoTs) technologies have been computerized information generated from a variety of objects and humans, and have been applied to various fields by connecting via the Internet. In order to compensate for the marginal characteristics of IoT smart devices, such as low-power, limited processing and capacities, combining IoT and cloud computing technologies is now established itself as one of the paradigms. In this paper, we look at the definition, features and services of IoT and cloud computing technology, and we investigate and analyze the conversing needs of IoT and could computing, existing conversion paradigms, convergence cases, and platforms. In results, there are challenges to be solved, even though the cloud technologies complement a number of restrictions of IoT and offer various advantages such as scalability, interoperability, reliability, efficiency, availability, security, ease of access, ease of use, and reduced cost of deployment. We analyze the new research issues of convergence paradigm, and finally suggest a research challenges for convergence.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.259-265
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• 2018

As the supply method of products has become diverse and complex, problems such as manipulation of origin and product trace have occurred in the existing supply chain system. In order to deal with these issues, various Blockchain based studies have been actively carried in the SW industry and academy. However, there is a lack of comprehensive survey research on the applied Blockchain techniques, so that it hardly understand the pros and cons of the technologies. In this study, we intensively investigated the diverse studies from the Industrial and academic area based on the several criteria such as the goals, use of key Blockchain technologies, and IoT technologies.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.129-138
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• 2017

This paper is concerned with an Internet of Things (IoT)-based unmanned home-delivery box system, in which the system is developed with a prototype using a weight sensor, shock sensor, the Arduino and Raspberry-Pi of open-source hardware platforms. The developed system provides several functions such as a safe storage means, prevention of delivery-theft, and remote control of the home-delivery box, etc. Specifically, the system recognizes the arrival of goods by detecting the weight of deliveries and sends the arrived message of deliveries to the recipient' smartphone, and also controls (i.e., open and close) the locker of the unmanned home-delivery box system remotely with the smartphone. Furthermore, the developed system provides automatically a warning alarm around the unmanned home-delivery box when an external shock is applied to the home-delivery box, and sends a message on the shock to the recipient' smartphone. The major functions of the developed home-delivery box system have been verified in a realistic environment, and confirmed to work well. With the application of the developed home-delivery box system to the homes and offices where recipients are always not to stay, it is expected to significantly improve the safety of delivered goods as well as to effectively prevent the delivery operatives posing as a crime.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.2047-2053
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• 2015

Our research proposese an IoT Broker (gateway) platform which considers the both sides of a service developer and a user. The platform associates the devices around us with virtual-entities and infers the owner of the devices through the ontology scheme. These functionalities can make the service developer easily design a new service. For the user, the service can be automatically installed and deployed under this platform. We also make it possible for the IoT broker to be plugged-in by integrating various communication platforms and protocols into that platform. Our expreriment with the AllJoyn plug-in on Node-RED substantiated that various service flows can be easily deployed and work on our platform.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1238-1249
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• 2020

Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.1-7
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• 2017

As the network environment develops and speeds up, a lot of smart devices is developed, and a high-speed smart society can be realized while allowing people to interact with objects. As the number of things Internet has surged, a wide range of new security risks and problems have emerged for devices, platforms and operating systems, communications, and connected systems. Due to the physical characteristics of IoT devices, they are smaller in size than conventional systems, and operate with low power, low cost, and relatively low specifications. Therefore, it is difficult to apply the existing security solution used in the existing system. In addition, IoT devices are connected to the network at all times, it is important to ensure that personal privacy exposure, such as eavesdropping, data tampering, privacy breach, information leakage, unauthorized access, Significant security issues can arise, including confidentiality and threats to facilities. In this paper, we investigate cases of security threats and cases of network of IoT, analyze vulnerabilities, and suggest ways to minimize property damage by Internet of things.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.157-166
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• 2019

oneM2M has been adopted to national and global smart city platforms leveraging its benefits, oneM2M platform assures interoperability to devices and services with standard APIs. Existing access control mechanisms in the standard should be extended to easily distribute smart city data. Compared to the as-is standard, this paper proposes a new access control method with minimum human interventions during data distribution between data sellers and buyers. The proposal has been implemented as the new data marketplace APIs to oneM2M platform and used for data marketplace portal interworking. This also has been demonstrated with smart city PoC service.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.27-36
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• 2020

In this paper, we propose a method to derive valuable but hidden infromation from the data which is the core foundation in the 4th Industrial Revolution to pursue knowledge-based service fusion. The hyper-connected societies characterized by IoT inevitably produce big data, and with the data in order to derive optimal services for trouble situations it is first processed by discovering valuable information. A data-centric IoT platform is a platform to collect, store, manage, and integrate the data from variable devices, which is actually a type of middleware platforms. Its purpose is to provide suitable solutions for challenged problems after processing and analyzing the data, that depends on efficient and accurate algorithms performing the work of data analysis. To this end, we propose specially designed structures to store IoT data without losing the semantics and provide algorithms to discover the useful information with several definitions and proofs to show the soundness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1049-1065
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• 2023

Recently, with the development of IoT, AI, and mobile terminals, medical information platforms are expanding. The medical information platform can determine a patient's emergency situation, and medical staff can easily access patient information through a mobile terminal. However, in the existing platform, emergency situation decision is delayed, and faster and stronger authentication is required in emergency situations. Therefore, we propose an edge computing-based medical information platform for automatic authentication using patient situations. We design an edge computing-based medical information platform architecture capable of rapid transmission of biometric data of IoT and quick emergency situation decision, and implement the platform data flow in emergency situations. Relying on this platform, we propose the automatic authentication using patient situations. The automatic authentication protects patient information through patient-centered authentication by using the patient's situation as an authentication factor, and enables quick authentication by automatically proceeding with mobile terminal authentication after user authentication in emergencies without user intervention. We compared the proposed platform with existing platforms to show that it can make quick and stable emergency decisions. In addition, comparing the automatic authentication with existing authentication showed that it is fast and protects medical information centered on patient situations in emergency situations.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1105-1112
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• 2022

Field data monitoring systems such as renewable energy generation and smart farm integrated control are developing from PC and server to mobile first, and various wireless communication and application services have emerged with the development of IoT technology. Low-power wide-area networks are services optimized for low-power, low-capacity, and low-speed data transmission, and data collected in the field is transmitted to designated storage servers or cloud-based data platforms, enabling data monitoring. In this paper, we implement an IoT repeater that collects field data with a single device and transmits it to a wireless carrier cloud data flat using a low-power wide-area network, and a monitoring app using it. Using this, the system configuration is simpler, the cost of deployment and operation is lower, and effective data accumulation is possible.