• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.27-36
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• 2018

In this paper, we design and implement a real time IoT messaging system that can collect location information of moving vehicles and pedestrians in real time using MQTT protocol and provides location based information service in administrative area. We implemented MQTT based IoT device for vehicle location information collection and communication and MQTT based smartphone application for pedestrian location information service. IoT clients can send messages to the server in administrative units by using the MQTT Topic which is equal to administrative names. The SLIMS (Seoul Location based IoT Messaging System) implemented in this study is able to analyze the real time traffic volume of pedestrians and vehicles by tracking clients. It also can deliver messages to clients based on coordinate range. SLIMS can be used as a real-time location-based information service for large-scale IoT devices such as real-time flow population and vehicle traffic analysis and location-based message delivery.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.453-456
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• 2016

Recently, IoT technologies attract much attenction in medical area. Previous medical IoT had focused mainly on chronological diseases or fitness for particular users. Contrarily, medical use of the IoT technologies is now extended for medical institutes and hospitals to care intensively in-house patients, which requires typically more strict and reliable data delivery and security, authentication and authorization. This study defines scenario of the medical IoT for the intensive care and proposes an architecture of the medical IoT services. We implement a testbed using commerical sensors and Arduino board together with a Web-based platform. Experiment results on the testbed show that our approach can be feasible for the medical system in terms of latency and accuracy in medical data delivery.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.224-227
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• 2020

현 식품 공급망은 중앙 집중화되어 있고, 투명하지 않으며 복잡한 시스템으로 인해 많은 문제점이 존재한다. 판매자는 싼값에 팔고 소비자는 비싼 값에 구매하는 문제가 지속적으로 대두되고 있으며 유통 과정에서 생기는 문제에 대한 책임 추적이 어렵다. 본 논문에서는 각 유통 단계에서 생성되는 IoT 센서 데이터를 블록체인 기술에 적용하며 이를 활용하는 방안에 대해 제안한다. 제안 모델을 통해 유동 과정과 데이터에 대한 신뢰성을 확보하고 제품의 원산지, 배송 과정, 보관 상태를 비롯한 유통 정보들을 추적할 수 있다.

• Journal of Korea Port Economic Association
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• v.36 no.2
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• pp.1-18
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• 2020

The Internet of things (IoT) has been applied to a variety of industrial uses such as public service sectors, medical industries, automotive industries, and so on. Led by smart cities, this is typical. However, from a logistics perspective, the level of application is insufficient. This study examines the applicability of IoT-related technology in a container terminal, an object of the present invention, to derive an applicable plan. Analytic network process (ANP) analysis reveals the following results for IoT applications in container terminals: operating systems (26.7%), safety/environmental/security systems (26.4%), equipment maintenance systems (25.3%), and facility maintenance systems (21.6 %). The second ANP analysis reveals the following results: Economy (40.2%), productivity (21.1%), service level (19.5%), and utilizing technology level (19.2%). The application or standard of evaluation is important when applying IoT technology to container terminals; however, it is not concentrated in a certain area. It is desirable to build each container system with linkage and efficiency from a macroscopic view.

• Management & Information Systems Review
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• v.36 no.1
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• pp.273-290
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• 2017

Internet of Things (IoT) is considered to be the next wave of Information Technology transformation after the Internet has changed the process of doing business. Since the domain of IoT ranging from the sensor technology to service to the users is wide, the structure of the research domain is not delineated clearly. To do that we suggest to use the Technology Stack Model proposed by Porter et al.(2014) to measure the maturity level of IoT in organizations. Based on the Stack Model, for the general understandings of IoT, we do keyword analyses on the academic papers whose major research issue is IoT. It is found that the current status of IoT application from the perspectives of cloud and big data analytics is not active, meaning that the real value of IoT has not been realized. We also examine the cases which deal with the part of cloud process which is crucial for value accrual. Based on these findings, we suggest the future direction of IoT research. We also propose that IT is to value chain what IoT is to the Stack Model to derive value in organizations.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.235-237
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• 2018

최근 IoT 센서 즉, 사물 인터넷 기반 기술에 대한 연구가 많이 진행되고 있으며, 다양한 제품들이 출시되고 있다. 대표적으로 홈 IoT 제품으로 가정에서 인터넷과 스마트폰 어플리케이션을 이용하여 가스 밸브, 보일러, 전등 등을 제어하는 것을 볼 수 있다. 하지만, 농업분야에서는 농작물 생산지의 환경 정보를 수집하고, 그에 맞춰 온습도 등을 제어하기 위해 관리자 혹은 생산자가 수동적으로 처리해야만 하는 단점이 존재하였다. 본 논문에서는 비닐하우스와 축산농가 등에서 사용할 수 있는 IoT 센서 기반 무인 관리 어플리케이션을 설계하고자 한다. 사용자가 비닐하우스 혹은 축산농가에 들어가지 않아도 사용자가 스마트폰 어플리케이션을 통해 모니터링 하면서 온습도를 조절하고, 센서의 고장 유무를 파악하여 교체시기를 알려 주는 등의 기능을 포함 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.79-82
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• 2017

IoT devices are interconnected in global network with different functionalities and manage the data transfer in cloud computing. IoT devices can be used anytime, anywhere with any device with different applications and protocols. Same devices but different applications according to end user requirements such as sensors and Wi-Fi devices, reusability of these applications can enhance the development process. However, large number of variations in cloud computing make it difficult the features selection in application because of compatibility issues of devices. In this paper we have proposed multi-Software Product Lines (multi-SPLs) approach to manage the variabilities and commonalities of IoT applications and protocols. Feature modeling is used to manage the commonalities and variabilities of SPL. We proposed that multi-SPLs feature model is more appropriate for modeling of IoT applications and protocols.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4177-4190
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• 2015

Current research on Internet of Things (IoT) has primarily addressed the means to enhancing smart resource allocation, automatic network operation, and secure service provisioning. In particular, providing satisfactory security service in IoT systems is indispensable to its mission critical applications. However, limited resources prevent full security coverage at all times. Therefore, these limited resources must be deployed intelligently by considering differences in priorities of targets that require security coverage. In this study, we have developed a new application of Cognitive Radio (CR) technology for IoT systems and provide an appropriate security solution that will enable IoT to be more affordable and applicable than it is currently. To resolve the security-related resource allocation problem, game theory is a suitable and effective tool. Based on the Blotto game model, we propose a new strategic power allocation scheme to ensure secure CR communications. A simulation shows that our proposed scheme can effectively respond to current system conditions and perform more effectively than other existing schemes in dynamically changeable IoT environments.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.101-103
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• 2023

With the recent advances in communication technology and Internet of Things (IoT) infrastructure, home automation systems have emerged as a new paradigm for providing users with convenient smart home services. The IoT ecosystem has merged digital systems with the physical world, dramatically changing the way people live and work. However, at the same time, security remains one of the most significant research issues in IoT, as the deployment and application of high-availability systems come with various security risks that cause serious threats to users. Among them, the security issues arising from the interaction among devices/applications should not be underestimated. Attackers can exploit interactions among devices/applications to hack into the user's home. In this paper, we present a survey of research on detecting various types of interactions among devices/applications in IoT.