• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.17-26
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• 2019

The Constrained Application Protocol (CoAP) is a specialized web transfer protocol proposed by the IETF for use in IoT environments. CoAP was designed as a lightweight machine-to-machine protocol for resource constrained environments. Due to the strength of low overhead, the number of CoAP devices is expected to rise rapidly. When CoAP runs over UDP for wireless sensor networks, CoAP needs to support congestion control mechanisms. Since the default CoAP defines a minimal mechanism for congestion control, several schemes to improve the mechanism have been proposed. To keep CoAP lightweight, the majority of the schemes have been focused mainly on how to measure RTT accurately and how to set RTO adaptively according to network conditions, but other approaches such as rate-based congestion control were proposed more recently. In this paper, we survey the literature on congestion control for CoAP and discuss the future research directions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.211-212
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• 2021

Recently, as interest in health increases, the wearable market that can collect various biometric information is expanding. In addition, telemedicine and healthcare services through these bio-signals are expected to become common. In this paper, we introduce a service that can store bio-signals collected through IoT equipment in a database and monitor them in real time through the web. By implementing a system for collecting and storing biometric data and real-time monitoring, it can be utilized for various health management diagnosis.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.53-61
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• 2020

Recently, as the uncontact service is activated in earnest due to the Corona 19 virus, the necessity of system development to provide non-face-to-face contact remote medical service has increased. In this study, we propose a smart healthcare system, Rm_She(Remote Medical Smart Healthcare System). Rm_She can collect and manage various vital signs information by connecting various healthcare products that detect bio-signals based on IoT to one application. The health check app (HC_app) is used to connect vital sign measurement devices to a wireless LAN and receive vital sign values from the HC_app. Then, the vital signs are output to the user on the smartphone, and the corresponding information is transmitted to the healthcare management server. The healthcare server receives the measured values and stores them in a database, and the stored measured values are provided as a web service so that medical staff can remotely monitor them in real time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.728-738
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• 2016

We are currently able to share not only the information from humans but also the data from connected things on the Internet. We are getting close to IoT era because of progress of Information Communication Technology. Therefore, the ways of data transfer are offered between things to things. One of typical way is the HTTP protocol. However, The field of Internet of Things platforms requires more fast and more stable communication protocol to handle massive data. The system supporting HTTP protocol, there is a problem of transmission efficiency in a relatively large header compared to data. also HTTP protocol system overload situations and the problem of data compatibility happens due to each standard of many organizations. Thus, To solve these problems, I suggest the data collection solution based on MQTT protocol for the operation of the stable IoT platforms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.237-244
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• 2018

The Smart Factory level of manufacturing factories of SMEs now lacks a system for grasping the accurate inventory amount associated with inventory movements in managing warehouses at the basic level. Also, it is difficult to manage accurate materials for loss of data due to worker manual work and production method due to experience. In order to solve this problem, in this paper, automatic acquisition of inventory to minimize manual work to grasp workers' Inventory and improve automation is done. In the smart warehouse management system using the IoT-based autonomous mobile module, the autonomous mobile module acquires the data of the inventory storage while moving through the line. In order to grasp the material of the Inventory storage, The Camera module recognizes the name of the inventory storage. And Then, If output matches, the data measured by the sensor is transferred to the server. This data can be processed, saved in a database, and real-time inventory quantity and location can be grasped in a web-based monitoring environment for administrators. The Real-time Automatic Inventory (RAIC) systems is reduce manual tasks and expect the effects of automated inventory management systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.152-158
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• 2016

In this paper, we implemented the full stack platform design with MongoDB database of open source platform Raspberry PI 3 model. We experimented the triggering of event driven with acceleration sensor data logging with wireless communication. we captured the image of USB Camera(MS LifeCam cinema) with 28 frames per second under the Linux version of Raspbian Jessie and extended the functionality of wireless communication function with Bluetooth technology for the purpose of making Android Mobile devices interface. And therefore we implemented the functions of the full stack platform for recognizing the event triggering characteristics of detecting the acceleration sensor action and gathering the temperature and humidity sensor data under IoT environment. Especially we used MEAN Stack for developing the performance of full stack platform because the MEAN Stack is more akin to working with MongoDB than what we know of as a database. Afterwards, we would enhance the performance of full stack platform for IoT clouding functionalities and more feasible web design with MongoDB.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.8
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• pp.845-854
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• 2019

In IoT environment, an intelligent agent is an autonomous entity with computing power that interacts with various things for specific purposes without human intervention. Recently, as the development of Internet technology has increased the size of resources and services that intelligent agents can utilize, an environment where intelligent agents can collaborate with each other is needed. To effectively support these changes, a method is needed to provide workspaces where intelligent agents can form various groups and collaborate on them. In this paper, we present TSpace which is an Ethereum-based group workspace for effective collaboration among intelligent agents. In TSpace, intelligent agents in IoT environment can use group service based on the Ethereum blockchain through the developed CoAP/RESTful web service. TSpace also introduces a new mechanism for managing Ethereum wallets of agents accessing group services and for creating Ethereum transactions using them.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.107-115
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• 2019

Effective construction safety management systems are desperately required for reducing damage caused by increasing safety accidents in construction sites. Safety accidents in construction sites can effectively protect if proactive measures are taken to prevent unauthorized worker access the expected hazardous area. In this study, we have developed a IoT(Internet of Things)-based dangerous zone alarming system for safety management in construction sites, which can be operated at low cost in large-scale sites as well as small and medium-sized construction sites. The development system utilizes a Zigbee-based beacon technology and cellular mobile communication technology to detect when authorized workers, unauthorized field workers or outsiders approaches hazardous zones. If somebody approaches the dangerous zones the system notifies immediately to the safety manager with a danger warning signal. It is expected that this system can effectively prevent safety accidents when applied to construction sites.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.613-621
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• 2019

Recently, with the development of the Internet of Things (IoT) and cloud computing technologies, security threats have increased as malicious codes infect IoT devices, and new malware spreads ransomware to cloud servers. In this study, we propose a threat-detection technique that checks obfuscated script patterns to compensate for the shortcomings of conventional signature-based and behavior-based detection methods. Proposed is a malicious code-detection technique that is based on malicious script-pattern analysis that can detect zero-day attacks while maintaining the existing detection rate by registering and checking derived distribution patterns after analyzing the types of malicious scripts distributed through websites. To verify the performance of the proposed technique, a prototype system was developed to collect a total of 390 malicious websites and experiment with 10 major malicious script-distribution patterns derived from analysis. The technique showed an average detection rate of about 86% of all items, while maintaining the existing detection speed based on the detection rule and also detecting zero-day attacks.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.151-156
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• 2021

Low-end IoT devices do not have enough computation and memory resources for DNN learning and inference. Integer quantization of real-type neural network models can reduce model size, hardware computational burden, and power consumption. This paper describes the design and implementation of a web-based quantization platform for CNN deep learning accelerator chips. In the web service platform, we implemented visualization of the model through a convenient UI, analysis of each step of inference, and detailed editing of the model. Additionally, a data augmentation function and a management function of files that store models and inference intermediate results are provided. The implemented functions were verified using three YOLO models.