• Management & Information Systems Review
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• v.34 no.3
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• pp.141-160
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• 2015

IoT(Internet of Things) has become a major issue as new type of convergence technology, expending existing of USNs(Ubiquitous Sensor Networks), NFC(Near Field Communication), and M2M(Machine to Machine). The IoT technology defines as a networking for things, which can establish intelligent links collaboratively for sensing networking and processing between each other without human intervention. The purpose of this study is to investigate to forecast the future distribution changes and orientation of contribution of distribution industry on IoT and to provide the implication of distribution changes. To become a global market leader, IoT requires much more development of core technology of IoT for distribution industry, new service creation and try to use a market-based demand side strategy to create markets. So, to become a global leader in distribution industry, this study results show that first of all establishment of standardization of IoT, privacy safeguards, security issues, stability and value were more important than others. The research findings suggest that the development goals of IoT should strive to boost the creation of a global leader in distribution industry and convenience to consider consumers' demands as the most important thing.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.215-225
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• 2024

With the rapid development of Internet of Things (IoT) and big data technology, a large amount of data will be generated during the operation of related industries. How to classify the generated data accurately has become the core of research on data mining and processing in IoT industry chain. This study constructs a classification model of IoT industry chain based on improved random forest algorithm and text analysis, aiming to achieve efficient and accurate classification of IoT industry chain big data by improving traditional algorithms. The accuracy, precision, recall, and AUC value size of the traditional Random Forest algorithm and the algorithm used in the paper are compared on different datasets. The experimental results show that the algorithm model used in this paper has better performance on different datasets, and the accuracy and recall performance on four datasets are better than the traditional algorithm, and the accuracy performance on two datasets, P-I Diabetes and Loan Default, is better than the random forest model, and its final data classification results are better. Through the construction of this model, we can accurately classify the massive data generated in the IoT industry chain, thus providing more research value for the data mining and processing technology of the IoT industry chain.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.1
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• pp.45-53
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• 2017

The Internet of Things (IoT) technology allows devices connected to the Internet to exchange information without human intervention, and to provide useful services to people. Currently, garbage trucks are regularly dispatched to collect garbage. In such a case, garbage may be less than half of the garbage collection capacity in some area, and garbage may be exceeded in another area so that garbage trucks can not collect all at once. In this paper, we have studied the method of estimating the amount of garbage to be collected and describe the development contents of the product and management system. The prediction of garbage volume was made possible by using IoT technology to measure the volume of garbage in real time. In addition, the measurement values are visibly displayed through the dashboard, so that the amount of garbage generated can be predicted and managed. This will allow IoT technology to help keep street hygiene.

• Convergence Security Journal
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• v.14 no.7
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• pp.45-51
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• 2014

The most important point in the QoS management system to ensure the quality of the IoT system design goal is quality measurement system and the quality evaluation system. This research study is a matrix model for the IoT based on key quality measures by diagnosis system structure and function. Developing for the quality metrics measured Internet of Things environment will provide the foundation for the Internet of Things quality measurement/analysis. IoT matrix system for quality evaluation is a method to describe the functional requirements and the quality requirements in a single unified table for quality estimation performed. Comprehensive functional requirements and quality requirements by assessing the association can improve the reliability and usability evaluation. When applying the proposed method IoT quality can be improved while reducing the QoS signaling, the processing, the basis for more efficient quality assurances as a whole.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.90-99
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• 2017

The service structure of the Mobius IoT platform, which has been developed on the basis of the oneM2M standard, connects servers and gateways directly to exchange data using HTTP or MQTT. Such structure may cause problems not to operate IoT services safely. In this paper, we propose an effective structure to manage sessions between gateways (or devices) and server using SIP safely and stably. In addition, we provide the way to implement the proposed method on Mobius IoT platform. To verify the operation of the proposed method, we actually implement the proposed method on Mobius IoT platform, and construct a testbed for a typical IoT application service environment with SIP servers. The results of the experiment show that the proposed method works normally, and it can contribute to the stable operation of IoT services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2396-2413
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• 2018

Trust management is one of the most challenging issues for the highly heterogeneous Internet of Things (IoT). In the context of the IoT, it is difficult to evaluate the node's trustworthiness in the same trust model when a node provides different services. Guaranteeing the availability of the trust management service is another significant challenge because of the dynamic nature of IoT environments. With these issues in mind, this paper propose a robust and adaptive trust management system for the IoT that is able to measure the trustworthiness of nodes based on feedbacks collected from participants in a specific context and ensure the availability of trust management services. The main contributions of our system are: 1) Proposing a partly decentralized trust management framework, which improves the resiliency of the trust mechanism; 2) Proposing an adaptive trust evaluation scheme and a three-dimensional context representation makes trust evaluation more accurate and specific; 3) Enhancing the adaptive trust evaluation scheme by incorporating a bad behavior factor in trust estimation, which efficiently distinguishes misleading feedbacks from On-Off attacks. Simulation results show the good performance of the proposed system and especially show effectiveness against On-Off attacks compared to other trust mechanisms.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1519-1530
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• 2020

As livestock farms grow in size, the number of breeding individuals increases, making it difficult to manage livestock. Livestock farms require an integrated management system such as a monitoring system, an access control system, and an abnormal behavior detection system to manage livestock houses. In this paper, a smart korean cattle livestock management system using IoT and AI technology was proposed for livestock management in livestock farms. The smart korean cattle farm management system consists of a monitoring and control system, a vehicle access management system, and an abnormal cattle behavior detection system. It is expected that this will help manage large-scale livestock houses, and additional research is needed to improve the performance of abnormal behavior detection in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.10
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• pp.259-268
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• 2018

Due to the development of cities and the increase of vehicles, effective control of parking space management service in cities is needed. However, the existing parking lot management system does not provide limited or convenient service in terms of space and time. In this paper, we propose distributed parking space management service based on large scale LPWA (Low-Power Wide-Area). The parking sensor collects parking space information from the parking lot and is transmitted over a low-power wide network. All parking data is processed and analyzed in the IoT cloud. Through a parking space management service system in all cities, users are given the temporal convenience of determining the parking space and the area efficiency of the parking space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• 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.