• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.99-106
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• 2017

In this paper, an energy harvesting and profiling system is designed for smart video devices in internet of things environments without dedicated power source. The energy harvesting module provides the harvested energy from solar panel to the smart video device. The energy profiling module measures the battery outflow current and the battery voltage of the smart video device and the consumed energy of processes, and calculate the harvested energy from the energy harvesting module to the smart video device and the total energy consumption of the smart video device. The accuracy of the harvested energy measured by the device energy profiling module is validated by comparing with the calculated energy using the regional solar radiation provided by Korea Meteorological Administration. Energy harvesting data from the designed energy harvesting and profiling system can be used to design the perpetual operation of smart video devices or Internet of Things sensors.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.256-264
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• 2023

Smart farm technology using IoT is one of the technologies that can increase productivity and improve the quality of agricultural products in agriculture, which is facing difficulties due to the decline in rural population, lack of rural manpower due to aging, and increase in diseases and pests due to climate change. . Smart farms using existing IoT simply monitor farms, implement smart plant growers, and have automatic greenhouse opening and closing systems. This paper implements a smart farm system based on MQTT, an industry standard protocol for the Internet of Things, and Node-RED, a representative development middleware for the Internet of Things. First, data is extracted from Arduino sensors, and data is collected and transmitted from IoT devices using the MQTT protocol. Then, Node-RED is used to process MQTT messages and store the sensing data in real time in MongoDB, a representative NoSQL, to store the data. Through this smart farm system, farm managers can use a computer or mobile phone to check sensing information on the smart farm in real time, anytime, anywhere, without restrictions on time and space.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.61-67
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• 2024

In order to monitor the growth environment of new varieties of crops, it is necessary to build the agricultural production infrastructure and strengthen the agricultural resource management system using popular smart sensor tag technology. In addition, the infrastructure for improving high-quality new varieties of crops using IoT technology and the monitoring system must be strengthened. In other words, widespread smart sensor (RFID UHF Sensor Tag) technology for environmental monitoring required for improving new crop varieties is desperately needed in the smart farm environment. Therefore, in this paper, we implemented an integrated sensor that can implement smart tag functions based on heterogeneous integrated sensors. In addition, we developed a technology that can manage crops in real time through the implemented smart integrated tag and smartphone linkage. For this purpose, an integrated antenna capable of RFID and Bluetooth communication was constructed. In addition, a communication method that allows information to be collected directly from the smartphone through the Bluetooth function was used.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.139-144
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• 2022

The smart cities are evolving constantly and are responsible for the current transformation of cities and countries into a completely connected network of information and technology This interconnected network of a huge number of smart devices is capable of exchanging complex information and provides tremendous support including enhanced quality of life within urban locations. Unfortunately this set-up is vulnerable to security attacks and requires the widespread ubiquitous network to authorize access through privacy and thus offer security in order to ensure civilian participation in a country. The smart network should benefit the individuals of the country by developing potential strategies to protect the smart cities and their participating entities from the unauthorized attacks. Trustworthy data sharing strategies based on the utilization of advanced technology features via smart communication network could solve some issues of privacy and security. This paper presents the challenges and issues related to protection and highlights the important aspects of securing the smart cities and its components. It also presents the role of cloud security for building a secure smart city.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.265-275
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• 2024

Smart factory is a remarkable development from traditional manufacturing systems to data-based smart manufacturing systems that can connect and process data continuously, collected from machines, production equipment to production and business processes, capable of supporting workers in making decisions or performing work automatically. Smart factory is the key and center of the fourth industrial revolution, combining improvements in traditional manufacturing activities with digital technology to help factories achieve greater efficiency, contributing to increased revenue and reduce operating costs for businesses. Besides, the importance of smart factories is to make production more quality, efficient, competitive and sustainable. Businesses in Vietnam are in the process of learning and applying smart factory models. However, the number of businesses applying the pine factory model is still limited due to many barriers and difficulties. Therefore, in this paper we conduct a survey to assess the needs and current situation of businesses in applying smart factories and propose some specific solutions to develop and promote application of smart factory model in Vietnamese businesses.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.388-393
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• 2024

The convergence of machine learning and smart farm is becoming more and more important. The purpose of this research is to quantitatively analyze machine learning and smart farm with bibliographic data from 2013 to 2023. This study analyzed the 251 articles, filtered from the Web of Science, with regard to the article publication trend, the article citation trend, the top 10 research area, and the top 10 keywords representing the articles. The quantitative analysis results reveal the four points: First, the number of article publications in machine learning and smart farm continued growing from 2016. Second, the article citations in machine learning and smart farm drastically increased since 2018. Third, Computer Science, Engineering, Agriculture, Telecommunications, Chemistry, Environmental Sciences Ecology, Material Science, Instruments Instrumentation, Science Technology Other Topics, and Physics are top 10 research areas. Fourth, it is 'machine learning', 'smart farming', 'internet of things', 'precision agriculture', 'deep learning', 'agriculture', 'big data', 'machine', 'smart' and 'smart agriculture' that are the top 10 keywords composing authors' keywords in the articles in machine learning and smart farm from 2013 to 2023.

• Convergence Security Journal
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• v.14 no.7
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• pp.65-73
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• 2014

Recently, the Internet of things has become issue as the new techniques the cloud computing and the grid computing etc. The Internet of Things is can grow even more that utilization of the range with the development of smart devices. and it has a lot of interest in several industries. In these circumstances, By analyzing the technologies and trends in the Internet of Things, I think you are ready to adapt to future IT field when needed. therefore, this paper are analyzed a various technologies and a case studies of the Internet of things, and it is expected to be used as the road map and material to build environment of the Internet of things in the future.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.1-7
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• 2021

An amazing growth in the field of Internet of Things (IoT) and Blockchain based smart cities from both industry and academia has been witnessed in the recent years. There are many smart applications such as intelligent transportation, smart banking, improving the life style of citizen, energy consumption and managing the waste in the city, handling home needs are supporting the Smart city concept. These applications are profoundly supported by the advanced technologies like Blockchain as well as IoT in the recent past. Smart cities can be supported by the Blockchain core concepts such as secure, transparent, decentralized and immutable nature. Still, Blockchain and IoT technologies implementation in smart cities are in their early stages and significant research efforts are desirable to integrate them. This review article explores the roles and responsibilities of Blockchain and IoT in building smart cities.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.273-278
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• 2022

Uncertainty is increasing around the world due to COVID-19 and Ukraine crisis. In this situation, each company is making countless efforts to survive. In Korea, smart factory projects targeting small and medium-sized businesses with difficulties have been continuously promoted. As for the smart factory business that has been promoted so far, the base expansion of the smart factory is also steadily increasing as the number of companies carrying out the project is increasing. It was also found that it contributed to productivity improvement and quality improvement. Despite these positive aspects, difficulties and operational problems are also appearing in the process of promoting smart factories. In this study, we investigated and analyzed operational problems and difficulties in the process of promoting smart factories. In addition, improvement plans for problems were presented according to the contents of this analysis, and improvement plans were presented by classifying them into introduction and supply companies, considering that the smart factory business is formed in the form of a consortium between introduction and supply companies.

• Smart Media Journal
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• v.13 no.1
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• pp.24-35
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• 2024

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.