• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2093-2099
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• 2015

To prevent damage to the cargo, monitoring and remote management for reefer containers is necessary. The currently used remote monitoring service is the Power Cable Transmission(PCT) system, which is recommended by the International Maritime Organization(IMO). However, this system is not widely used because it requires a separate PCT infrastructure and is susceptible to data loss problems. To solve this problem, this study introduces the "IoT-based reefer container management system", The proposed system which is attached to reefer container collects and transmits data on the temperature, status and location of reefer container to middleware using RS-232 communication and WCDMA/GSM communication. Middleware is store the data received in the database and provide information to user in real time through the web and mobile program. At this time, users able to change setting temperature in real time from a distant place through the web program. This study tested by transit about shipment of strawberries to monitor and analyze and check the system's overall effectiveness.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.707-714
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• 2013

IoT, which can be regarded as an enhanced version of M2M communication technology, was proposed to realize intelligent thing to thing communications by utilizing Internet connectivity. Things in IoT are generally heterogeneous and resource constrained. Also such things are connected with each other over LLN(low power and lossy Network). Confidentiality, mutual authentication and message origin authentication are required to make a secure service in IoT. Security protocols used in traditional IP Networks cannot be directly adopted to resource constrained devices in IoT. Under the respect, a IETF standard group proposes to use lightweight version of DTLS protocol for supporting security services in IoT environments. However, the protocol can not cover up all of very constrained devices. To solve the problem, we propose a scheme which tends to support mutual authentication and session key agreement between devices that contain only a single crypto primitive module such as hash function or cipher function because of resource constrained property. The proposed scheme enhances performance by pre-computing a session key and is able to defend various attacks.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.1-7
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• 2022

Machine learning (ML) algorithms have been intended to seamlessly collaborate for enabling intelligent networking in terms of massive service differentiation, prediction, and provides high-accuracy recommendation systems. Mobile edge computing (MEC) servers are located close to the edge networks to overcome the responsibility for massive requests from user devices and perform local service offloading. Moreover, there are required lightweight methods for handling real-time Internet of Things (IoT) communication perspectives, especially for ultra-reliable low-latency communication (URLLC) and optimal resource utilization. To overcome the abovementioned issues, this paper proposed an intelligent scheme for traffic steering based on the integration of MEC and lightweight ML, namely support vector machine (SVM) for effectively routing for lightweight and resource constraint networks. The scheme provides dynamic resource handling for the real-time IoT user systems based on the awareness of obvious network statues. The system evaluations were conducted by utillizing computer software simulations, and the proposed approach is remarkably outperformed the conventional schemes in terms of significant QoS metrics, including communication latency, reliability, and communication throughput.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1109-1116
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• 2018

The purpose of this study is to solve the loss of personal belongings by utilizing monitoring function of IoT platform. The beacon to combined with personal belongings are registered with the application server, the trigger processing function according to the occurrence of the lost event is performed intelligently through the device, the app, the IoT network, and the application server.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.37-53
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• 2024

This study selected bicycle road hazard detection factors for mobile IoT sensor device operation and developed service application plans. Twelve bicycle road hazard detection factors were derived through a focused group interview, and a fuzzy AHP-based importance analysis was conducted on 30 road and transportation experts. As a result, 'damage to pavement' (1st overall) and 'environmental obstacle' (2nd) with low visibility but a high risk of accidents were selected the most. The factors in terms of facility management, such as 'disconnected route occurrence' (4th), 'artificial obstacle' (5th), 'effective width' (6th), and 'poor drainage' (7th), were selected as the upper and middle areas. Factors that are not direct accident-inducing factors, such as 'loss of road markings' (11th) and 'free space width' (12th), were selected the least. Based on this, a plan was presented to apply the bicycle road hazard detection service and a service operation strategy according to real-time performance. Nevertheless, follow-up studies, such as human behavioral analysis based on bicycle operators, analysis according to the bicycle road type, service demonstration, and pilot operation, will be needed to develop safe bicycle road management is expected.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.1-7
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• 2021

Recently, technological differentiation(sensor, AI) of products using IoT technology to satisfy consumer needs in the mature market for smart home appliances has received a lot of positive responses. However, air conditioner products are in the early stages of convergence technology. Therefore, air conditioner products are fields that require ICT technologies for information production, collection, processing, storage, and service development beyond IoT. In this paper, we collect and store contactless bio-signal using IR-UWB radar technology. The blowing direction of the air conditioning is controlled according to bio-signal and user's sleep is monitored to provide an optimal sleep environment. In addition, we propose a service algorithm that can provide comfort with changes in the optimal conditions of air conditioning and emotional lighting depending on the discomfort index environment. Through this study, we developed an intelligent smart air conditioning service platform with ICT technology of bio-signal, discomfort index, and emotional lighting.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1107-1112
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• 2016

This study is the Smart Office features that take advantage of KEPCO eIoT(: energy Internet of Thing) platform, and it's Network configuration is composed of sensing device, gateway, platform, and the service server. The key features are parts for processing protocol data between the gateway and the device using LoRa(: Long Range) technology, Intelligent applications and public safety data connected to the PS-LTE(: Public Safety-Long-Term Evolution) system. And the resource tree provided Smart Office for the service, which commonly used in the application server and the device.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.1-8
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• 2021

With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.