• Journal of the Korean Dietetic Association
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• v.30 no.1
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• pp.61-73
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• 2024

This report was prepared to introduce the developed Internet of Things (IoT)-based Smart Food Safety Management System (iMEAL) for children's foodservices registered in the Center for Children's Foodservice Management and report the results of hygiene monitoring through microbial analysis of two foods simulated and distributed based on this system. The program consisted of three menu screens: a foodservice management and meal inspection function, a refrigerator/freezer monitoring function, and a sanitary/safety inspection log function. Data such as cooking temperature, refrigerator and freezer temperature, salinity, and chlorine concentration were collected using IoT sensors or terminals, and hygiene safety inspection diary results (recorded by cooks) were transmitted to the Internet and stored. The APCs (3.78±0.07 log CFU/g) and E. coli (not detected) in stir-fried pork teriyaki sauce and the heating process met cooking standards. Similarly, the APCs (4.05±0.05 log CFU/g) and E. coli (not detected) in cucumber/chomuchim, which was not heated, also met cooking standards. APCs increased over time when cooked food was left for 1 hour, 1.5 hours, or 2 hours but remained acceptedable. Based on hygiene monitoring results of these two foods, using the i-MEAL system resulted in the safe production and distribution of children's food.

• Journal of Platform Technology
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• v.11 no.6
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• pp.79-88
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• 2023

Recently, industrial accidents have continued to increase due to the industrialization, and worker safety management is recognized as essential to reduce losses due to hazardous factors at work places. To manage the safety of workers, it is required to apply customized safety management artificial intelligence technology that takes into account the characteristics of industrial sites, and a service for real-time risk detection and response to workers depending on the situation based on safety accident types and risk analysis for each task and process. The proposed safety management service consists of worker devices to acquire sensor data, edge devices to collect from IoT-based sensors, and a voice chatbot to support workers' disaster response. The voice chatbot plays a major role in interacting with workers at disaster sites to respond to risks. This paper focuses on real-time risk response using an IoT-based system and voice chatbot on a server for work safety according to the worker's situation. A Scenario-based voice chatbot is used to process responses at the edge level to provide safety management services.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.69-75
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• 2022

Fire-alarm systems are safety equipment that facilitate rapid evacuation and early suppression in case of fire. It is highly desirable that fire-alarm systems have low false-alarm rates and are thus reliable. Until now, researchers have attempted to improve detector performance by applying new technologies such as IoT. To this end, IoT-based fire-detection systems have been developed. However, due to scarcity of large-scale operational data, researchers have barely studied malfunctioning in fire-alarm systems or attempted to reduce false-alarm rates in these systems. In this study, we analyzed false-alarm rates of smoke/temperature detectors and unwanted fire-alarm signal patterns at K institution, where Korea's largest IoT-based fire-detection system operates. After analyzing the fire alarm occurrences at the institution for five years, we inferred that the IoT-based fire-detection system showed lower false-alarm rates compared to the automatic fire-detection equipment. We analyzed the detection pattern by dividing it into two parts: normal operation and unwanted fire alarms. When a specific signal pattern was filtered out, the false-alarm rate was reduced to 66.9% in the smoke detector and to 46.9% in the temperature detector.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.40-41
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• 2021

Recently, particulate matter(PM) caused by internal factors such as industrialization and urbanization as well as external factors such as Asian dust is a serious problem in Korea. In particular, while the emission due to construction appears to be very serious among the internal factors, it is necessary to manage PM in consideration of the characteristics of construction sites. Accordingly, in this study, a PM management system suitable for construction sites was developed to reduce civil complaints caused by PM and to minimize damage to field workers and nearby residents by supporting the fine dust management system of the state and local governments. The factors to be considered when measuring PM due to the specificity of construction sites were considered, and the system components were developed based on the considerations. As a result, an IoT based construction site PM monitoring system (CPMS) that integrates each component was established.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.24-30
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• 2020

As the number of internet-connected appliances and the variety of IoT services are rapidly increasing, it is hard to protect IT assets with traditional network security techniques. Most traditional network log analysis systems use rule based mechanisms to reduce the raw logs. But using predefined rules can't detect new attack patterns. So, there is a need for a mechanism to reduce congested raw logs and detect new attack patterns. This paper suggests enterprise security management for IoT services using graph and network measures. We model an event network based on a graph of interconnected logs between network devices and IoT gateways. And we suggest a network clustering algorithm that estimates the attack probability of log clusters and detects new attack patterns.

• Journal of Information Technology Applications and Management
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• v.27 no.3
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• pp.19-36
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• 2020

The Internet of things (IoT) is a system of interrelated computed devices, digital machines and any physical objects which are provided with unique identifiers and the potential to transmit data to people or machine (M2M) without requiring human interaction. IoT devices can be used to monitor and control the electrical and electronic systems used in different fields like smart home, smart city, smart healthcare and etc. In this study we introduce four imaginary IoT devices as a learning support assistants according to students' dominant learning styles measured by Honey and Mumford Learning Styles: Activists, Reflectors, Theorists and Pragmatists. This research emphasizes the association between students' strong learning styles and a preference to appropriate IoT devices with specific characteristics. Moreover, different levels of IoT devices' architecture are clearly explained in this study where all the artificial devices are designed based on this structure. Data analysis of experiment were measured by the use of chi square test for association and research results showed the statistical significance of the estimated model and the impacts of each category over the model where we finally got accurate estimates for our research variables. This study revealed the importance of considering the students' dominant learning styles before inventing a new IoT device.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.189-194
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• 2020

Recently, various clustering techniques have been studied to efficiently handle data generated by heterogeneous IoT devices. However, existing clustering techniques are not suitable for mobile IoT devices because they focus on statically dividing networks. This paper proposes a probabilistic deep learning-based dynamic clustering model for collecting and analyzing information on IoT devices using edge networks. The proposed model establishes a subnet by applying the frequency of the attribute values collected probabilistically to deep learning. The established subnets are used to group information extracted from seeds into hierarchical structures and improve the speed and accuracy of dynamic clustering for IoT devices. The performance evaluation results showed that the proposed model had an average 13.8 percent improvement in data processing time compared to the existing model, and the server's overhead was 10.5 percent lower on average than the existing model. The accuracy of extracting IoT information from servers has improved by 8.7% on average from previous models.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.29-36
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• 2019

With the rapid development of 5G technology, more and more network functions are interconnected and more popular. In order to effectively manage emerging network concepts, it allows any device object in the real world to be connected anywhere and at any time through the integration of device object recognition, interaction and raw data collection technologies. In addition, IP Multimedia Subsystem (IMS) is an architecture framework for transmitting IP-based information to the device object which can be represented as end user. Therefore, the Internet of Things and IP Multimedia Subsystem (IoT-IMS) communication platform can provide a convenient and fast way for user or device objects to deploy new application services effectively. In particular, in order to collect and manage the device information from IoT effectively in the IoT-IMS communication platform, an IoT Information Gateway (IIG) is proposed. Through the IoT Application Service (AS) scenario, the collected device information can be easily observed and managed in a unified way.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.981-984
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• 2015

IoT is network evolved one more step than Mobile or Internet based on the existing wire communication and can interconnect all people, things, and virtual space at any time, anywhere. In particular, Internet of Things technology is expected to be converged on medical service such as elderly home care, chronic disease management, and treatment, and then it also contributes to savings and service quality of in the medical field and leads the paradigm or innovation of healthcare industry. In this study, we analyzed the IoT technology and application cases of medical service based on the IoT at home and abroad.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.47-57
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• 2015

Recently, Internet of Things (IoT) have become popular for research and development in many areas. IoT makes a new intelligent network between things, between things and persons, and between persons themselves. Social network service technology is in its infancy, but, it has many benefits. Adjacent users in a social network tend to trust each other more than random pairs of users in the network. In this paper, we propose recommendation technique using social network in Internet of Things environment. We study previous researches about information recommendation, IoT, and social IoT. We proposed SIoT_P(Social IoT Prediction) using social relationships and item-based collaborative filtering. Also, we proposed SR(Social Relationship) using four social relationships (Ownership Object Relationship, Co-Location Object Relationship, Social Object Relationship, Parental Object Relationship). We describe a recommendation scenario using our proposed method.