• Agribusiness and Information Management
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• v.9 no.1
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• pp.1-6
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• 2017

Recent scandals of milk additives in several developing countries provoked controversy about quality issue of dairy products, grapping academic attention to the dairy supply chain. In this paper, we first focus on moral hazard problem of self-interested entities about the quality across the dairy supply chain, due to unobservable and unverifiable quality management efforts of all entities - including dairy producers, stations, and a final producer - and high inspection cost for the quality. Based on the identified moral hazard problem, we understand why the adoption of IoT-based tracking systems about quality produced from each entity is a must, different from RFID-based tracking systems.

• Journal of IKEEE
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• v.22 no.3
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• pp.664-671
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• 2018

Generally, conventional solar tracking systems employ irradiance sensors to track a sun position, which enables the system to generate maximum solar energy. The usage of irradiance sensors increases system costs and deteriorates the performance of systems from sensor malfunctions. In this paper, a new solar tracking system without irradiance sensors has been proposed in which the controller capable of controlling and monitoring remotely is based on Artik platform. The proposed system tracks the sun position by comparing the amount of currents from several solar panels, resulting in removing irradiance sensors. In order to verify the performance of the proposed solar tracking method, the 12[V]-20[W] prototype system is built and implemented. Since the proposed system has remote monitoring functions through the employment of Artik as the IoT platform, more advantages in installation, maintenance and expanded functionality can be obtained compared to the conventional solar tracking system.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.784-793
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• 2022

Grid-connected distributed power generation has been widely used in green energy generation. However, due to the distributed characteristics, distributed power generation is difficult to be dynamically allocated and monitored in the electrical control process. In order to solve this problem, this research combined the Internet of Things (IoT) with the automatic control system of electrical engineering to improve the control strategy of the power grid inverter according to the characteristics of the IoT system. In the research, a connection system of the power grid inverter and the IoT controller were designed, and the application effect was tested by simulation experiments. The results showed that the power grid inverter had strong tracking control ability for current and power control. Meanwhile, the electrical control system of the IoT could independently and dynamically control the three-phase current and power. The given value was reached within 50 ms after the step signal was input, which could protect the power grid from being affected by the current. The overall system could realize effective control, dynamic control and protective control.

• ETRI Journal
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• v.43 no.3
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• pp.459-470
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• 2021

This paper presents a low-cost prototype for monitoring online the maximum power produced by a domestic photovoltaic (PV) system using Internet of Things (IoT) technology. The most common tracking algorithms (P&O, InCond, HC, VSS InCond, and FL) were first simulated using MATLAB/Simulink and then implemented in a low-cost microcontroller (Arduino). The current, voltage, load current, load voltage, power at the maximum power point, duty cycle, module temperature, and in-plane solar irradiance are monitored. Using IoT technology, users can check in real time the change in power produced by their installation anywhere and anytime without additional effort or cost. The designed prototype is suitable for domestic PV applications, particularly at remote sites. It can also help users check online whether any abnormality has happened in their system based simply on the variation in the produced maximum power. Experimental results show that the system performs well. Moreover, the prototype is easy to implement, low in cost, saves time, and minimizes human effort. The developed monitoring system could be extended by integrating fault detection and diagnosis algorithms.

• Smart Media Journal
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• v.12 no.5
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• pp.73-80
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• 2023

Recently, intelligent control systems are developing rapidly in various application fields, and methods for utilizing technologies such as deep learning, IoT, and cloud computing for intelligent control systems are being studied. An important technology in an intelligent control system is recognizing and tracking objects in images. However, existing multi-object tracking technology has problems in accuracy and speed. In this paper, a real-time intelligent control system was implemented using YOLO v5 and YOLO v6 based on a one-shot architecture that increases the accuracy of object tracking and enables fast and accurate tracking even when objects overlap each other or when there are many objects belonging to the same class. The experiment was evaluated by comparing YOLO v5 and YOLO v6. As a result of the experiment, the YOLO v6 model shows performance suitable for the intelligent control system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.443-452
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• 2021

One of the key technologies in edge computing is that it always provides services close to the user by moving data between edge servers according to the user's movements. As such, the movement of data between edge servers is frequent. As IoT technology advances and usage areas expand, the data generated also increases, requiring technology to accurately track and process each data to properly manage the data present in the edge computing environment. Currently, cloud systems do not have data disposal technology based on tracking technology for data movement and distribution in their environment, so users cannot see where it is now, whether it is properly removed or not left in the cloud system if users request it to be deleted. In this paper, we propose a tracking data server to create and manage the movement and distribution of data for each edge server and data stored in the central cloud in an edge computing environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.6
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• pp.916-922
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• 2017

Security systems for inland cargo truck transportation are mostly limited to route tracking for safe and efficient transportation. With this route tracking system, the status of cargo trucks can be monitored easily within inland boundaries. In case of oil transportation by land, however, security systems ensuring transportation of a designated quantity of products have been subject to extensive research since thefts and substitution by a similar product in the transportation process have emerged as a social problem. Security devices installed in an oil tank truck must meet the explosion-proof performance standards and be applicable to varying types of trucks. Accordingly, a wireless electronic seal with RF communication functions is considered to be the most appropriate method, but e-seals on moving vehicles require such levels of performance and reliability that can overcome certain challenges including changing radio waves and topographical impediments. Considering these characteristics of oil tank trucks, this study proposes an stabilization method to enhance the RF communication performance of e-seals, based on radio simulation and experiment findings.

• Journal of the Society of Disaster Information
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• v.13 no.1
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• pp.106-117
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• 2017

This study is to present to be the efficient demonstration of the life protection systems which is developed for the prevention and prompt correspondence for social disaster. It is to suggest to be conducted prompt accident prevention and correspondence based on the type of accident and developing technology development of life protection systems for social disaster using convergence technology like directional speaker system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1659-1674
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• 2024

Conventional maritime communication struggles to provide high data rate services for Internet of Things (IoT) devices due to the variability of maritime environments, making it challenging to ensure consistent connectivity for onboard sensors and devices. To resolve this, we perform mathematical modeling of the maritime channel and compare it with real measurement data. Through the modeled channel, we verify the received beam gain at buoys on the ocean surface. Additionally, leveraging the modeled wave motions, we estimate future angles of the buoy to use the Extended Kalman Filter (EKF) for design beamforming strategies that adapt to the evolving maritime environment over time. We further validate the effectiveness of these strategies by assessing the results from an outage probability perspective. focuses on improving maritime communication by developing a dynamic model of the maritime channel and implementing a Kalman filter-based buoy motion tracking system. This system is designed to enable precise beamforming, a technique used to direct communication signals more accurately. By improving beamforming, the aim is to enhance the quality of communication links, even in challenging maritime conditions like rough seas and varying sea states. In our simulations that consider realistic wave motions, you've observed significant improvements in link quality due to the enhanced beamforming technique. These improvements are particularly notable in environments with high sea states, where communication challenges are typically more pronounced. The progress made in this area is not just a technical achievement; it has broad implications for the future of maritime communication technologies. This paper promises to revolutionize the way we approach communication in maritime environments, paving the way for more reliable and efficient information exchange on the seas.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1283-1292
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• 2022

At present, several artificial intelligence projects in the healthcare and medical field are competing with each other, and the interfaces between the systems lack unified specifications. Thus, this study presents an artificial intelligence platform for healthcare and medical fields which adopts the deep learning technology to provide algorithms, models and service support for the health and medical enterprise applications. The suggested platform can provide a large number of heterogeneous data processing, intelligent services, model managements, typical application scenarios, and other services for different types of business. In connection with the suggested platform application, we represents a medical service which is corresponding to the trusted and comprehensible tracking and analyzing patient behavior system for Health and Medical treatment using Internet of Behavior concept.