• Convergence Security Journal
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• v.20 no.2
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• pp.91-99
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• 2020

The purpose of this study is to present the application of Information and Communication Technology(ICT) during the 4th Industrial Revolution for the efficient implementation of government emergency preparedness policies. Brainstorming by experts categorized the government's emergency preparedness policies into 4 types and 12 detailed tasks. Classification results were used by AHP(Analytic Hierarchy Process) to analyze relative importance and priorities. The AHP survey found that strengthening crisis management responsiveness was the most important detailed task. Artificial Intelligence(AI), Internet of Things(IoT), Unmanned Autonomy System, Virtual Reality(VR), and Augmented Reality(AR) were presented as major information and communication technology(ICT) for the efficient execution of detailed tasks.

• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.31-36
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• 2015

Recently, the necessity of Internet of Things in conjunction between devices is increasing. However, there are increasing security threats while applying various communication technologies in the Internet of Things. In this paper, we propose a security countermeasures to minimize damage to the security of a variety of security technologies used in the Internet of Things in order to improve the efficiency of the Internet of Things. The proposed method defined the environment to minimize security damage between home devices such as TV, washing machine, refrigerator, boiler and medical devices such as Analyzers, blood glucose meters, blood pressure monitors that are used in daily life. In addition, a variety of technologies(Zigbee, Wi-Fi, NFC, RFID, etc.) that are used in the Internet of Things may be under integrated management.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.295-298
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• 2014

In recently, a climatic change(such as subtropical climate and frequent unusual high temperature) and the open-trade policies of agricultural & livestock products are increasing the outbreak risk of highly pathogenic avian influenza(HPAI) and foot and mouth disease(FMD), and accordingly the socio-economic damage and impacts are also increasing due to the cases such as damage from the last 5 times of FMD outbreak(3,800 billion won), from 10 years public control cost of Pine Wilt Disease (PWD)(238.3 billion won), and from the increased invasive pests of exotic plant like isoptera. Therefore, the establishment of new operation strategy of IoT(Internet of Things) based satellite early warning system(SEWS) for plants and animals as a subsystem of national disaster response and management system is being required, where the forensic technology & measures should be applied as a government policy to estimate the post compensation and to carry out the legal responsibility.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.99-105
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• 2018

As the Internet of Thing(IoT) technology recently has become a big issue, many researches have been carried out to link the Internet of things with the home network system. Various home network systems are being implemented to connect many devices used in the home with the Internet and to control and operate the devices using a smart phone. However, existing protocols that operate on the Internet are not suitable for a limited environment such as low power, low capacity, and low performance. Therefore, the Internet Engineering Task Force (IETF) Working Group proposed the CoAP/6LoWPAN technology as a suitable protocol for internetworking IoT devices with the Internet in a limited environment and adopting it as a standard. In this paper, a smart home network system is implemented to control and operate various IoT devices in a home using CoAP/6LoWPAN in mobile environment. The performance of HTTP and CoAP such as data transmission time, data transmission rate is analyzed.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.15-21
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• 2021

This paper conducted a feasibility study by applying an Internet of Things and Artificial intelligence-based management system for the elderly living alone in an aging society. The number of single-person families over the age of 50 is expected to increase, and problems such as health, safety, and loneliness may occur due to aging. Therefore, by establishing an IoT-based care system for the elderly living alone, a stable service was developed through securing a rapid response system for the elderly living alone and automatically reporting 119. The participants of the demonstration test were subjects under the jurisdiction of the "Seongnam Senior Complex," and the data collection rate between the IoT sensor and the emergency safety gateway was high. During the demonstration period, as a result of evaluating the satisfaction of the IoT-based care system for the elderly living alone, 90 points were achieved. We are currently in the COVID-19 situation. Therefore, the number of elderly living alone is continuously increasing, and the number of people who cannot benefit from care services will continue to occur. Also, even if the COVID-19 situation is over, the epidemic will happen again. So the care system is essential. The elderly care system developed in this way will provide safety management services based on artificial intelligence-based activity pattern analysis, improving the quality of in-house safety services.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.1
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• pp.105-115
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• 2021

In this paper, we surveyed the service system disclosed by the government and self-governing province to analyze the status of IoT data service. Survey conditions were focused on data generated from objects such as sensors, OpenAPI that can utilize the generated data and data having a data update cycle of less than 1 month. As a result of the survey, the ratio of IoT data to data released by the government, self-governing province and the private sector was only 1.2%. Therefore, in order to increase the utilization with the development of IoT technology, a dedicated organization that can manage the IoT data service is needed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2546-2553
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• 2015

Falling can happen to anyone, anywhere at anytime and especially it is one of the risk factor that can lead causes of death of persons aged 65 and over. Recently, the study of fall detection mechanisms as a smart healthcare service based on the IoT(Internet of Things) are being actively investigated. In this paper, we implement a fall detection system using arduino as a smart sensor communicates with a smart device. When transmitting the information of the acceleration on a sensor smart sensor with a BLE(Bluetooth Low Energy), the smart device processing and analyzing this information. and determines a fall situation. A fall detection system based on the Internet of Things which using smart sensor and smart device, has the advantage of being able to overcome the mobility and portability constraints.

• Journal of KIBIM
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• v.13 no.3
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• pp.12-20
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• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1379-1386
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• 2017

As the Internet of Things evolves, various IoT services are provided. IFTTT is an abbreviation for If This Then That and refers to a service that links different web-based services. This paper proposes a system that generates and manages rules that combine the possibility of IFTTT service and the real-time event processing according to the concept of IoT service. Conventional database-based data processing methods are burdened to process a lot of data of IoT devices coming in real-time. The IoT device's data can be classified into formal data such as the amount of power, temperature value and position information, and informal data such as video or image data. Thus, this system classifies the data stream of IoT devices coming in real-time using the CEP engine Esper into a file signature table, classifies the formal/informal data, and shows the condition of the device data defined by the user and the service to be provided by applying the service.