• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.17-27
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• 2024

Overfishing, climate change, and competitive fishing have led to a continuous decline in fishery production. To address these issues, the Total Allowable Catch (TAC) system has been established, which sets annual catch quotas for individual fish species and allows fishing only within those limits. As part of the TAC system, land-based investigators measure the length and height of fish species at auction markets to calculate the weight and TAC depletion. However, the accuracy of the acquired data varies depending on the skill level of the land-based investigators, and the labor-intensive nature of the work makes it unsustainable. To address these issues, this paper proposes a fish species recognition and length measurement system that automatically measures the length, height, and weight of eight TAC-managed fish species using the camera of a smart pad that can measure the distance to the water surface. This system can help to automate the current labor-intensive work, minimize data loss, and facilitate the establishment of the TAC system.

• Smart Media Journal
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• v.13 no.1
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• pp.18-23
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• 2024

Power efficiency management in smart farms is important due to its link to climate change. As climate change negatively impacts agriculture, future agriculture is expected to utilize smart farms to minimize climate impacts, but smart farms' power consumption may exacerbate the climate crisis due to the current electricity production system. Therefore, it is essential to efficiently manage and optimize the power usage of smart farms. In this study, we propose a system that monitors the power usage of smart farm equipment in real time and predicts the power usage one hour later using GRU. CT sensors are installed to collect power usage data, which are analyzed to detect and prevent abnormal patterns, and combined with IoT technology to efficiently manage and monitor the overall power usage. This helps to optimize power usage, improve energy efficiency, and reduce carbon emissions. The system is expected to improve not only the energy management of smart farms, but also the overall efficiency of energy use.

• Journal of Drive and Control
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• v.21 no.2
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• pp.53-64
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• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.763-770
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• 2024

Currently, land-based fish farms utilizing seawater have introduced and are utilizing various equipment such as real-time water quality monitoring systems, facility automation systems, and automated dissolved oxygen supply devices. Furthermore, data collected from various equipment in these fish farms produce structured and unstructured big data related to water quality environment, facility operations, and workplace visual information. The big data generated in the operational environment of fish farms aims to improve operational and production efficiency through the development and application of various methods. This study aims to develop a system for effectively analyzing and visualizing big data produced from land-based fish farms. It proposes a data visualization process suitable for use in a fish farm big data analysis system, develops big data visualization tools, and compares the results. Additionally, it presents intuitive visualization models for exploring and comparing big data with time-series characteristics.

• Journal of the Korean association of regional geographers
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• v.15 no.3
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• pp.369-392
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• 2009

Recently international movements of labour as well as those of goods and other production elements such as capitals and technology have been increased rapidly under the process of glocalization. The huge amount of immigrant workers' in-flows makes increasing influences on regional economy in South Korea. This paper examines such impacts of immigrant workers on local labor markets, productivity. and industrial composition and innovation on the basis of analysis of empirical data and review of existing literature on the subject. Despite a problem of simplification, some reasoning can be listed as follows: First of all, the inflow of immigrant workers has an effect of job displacement among domestic simple workers, with duel effects on the status of native workers; secondly, Immigrant workers give a positive effect on local productivity, but only with low level of wage and of purchasing power; thirdly, the in-flow of immigrant workers seems to prevent existing industries from transformation towards new ones and/or from automation and innovation of production facilities, while there seems no clear relationship with foreign direct investments of local firms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.49-55
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• 2017

Most motor cases adopt deep drawing products, which are excellent in waterproof functions, concentricity, right angle, and quality. In addition, the blower motor and seat motor, which are installed in the car interior and do not require waterproof function, adopts a multi-forming manufacturing method. The deep drawing process requires an expensive transfer press that can digest approximately 12 processes, such as drawing, trimming and piercing. On the other hand, products can be produced with low investment because the multi-forming method is composed of one multi-forming machine or one multi-forming machine and one press. The multi-forming machine is a high-priced facility that is mostly imported and a bending / shearing process multi-foaming machine, which was developed by domestic small and medium-sized enterprises, is not enough to reduce the production cost. An integral multi - forming machine is used as a limited working method for thin material and small products. A large product and thick material has a high shear load. A large product and thick material has a high shear load and uses a single crank press. After blanking, the worker manually feeds the material to a multi-forming machine. When the bending operation is performed in the multi-forming machine, it is transferred to the press again to calibrate the dimensions. This variance in work processes has resulted in lower cost competitiveness due to the lower productivity, quality issues, and excessive operator input. The aim of this study was to establish a stable and cost - effective production system through bending / shearing process separation and facility automation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.702-708
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• 2018

3D printing technology is attracting increasing attention as a key technology of the fourth industrial revolution that can change the production paradigm of existing industries. The introduction of construction 3D printing technology has been slower than other industries because of the characteristics of the construction field. On the other hand construction automation using 3D printing is required to reduce the production population, as well as improve productivity and safety. In this study, a construction 3D printing work breakdown structure and link method to a standard estimation system were developed as a preliminary preparation for introducing 3D printing to construction. Based on expert consultation on construction and 3D printing, a hypothetical scenario was developed based on existing construction 3D printing technology. According to the scenario, 16 kinds of works required for 3D printing construction work were derived. The existing work breakdown structure and standard estimation system were analyzed, and the 3D printing work was linked. 3D printing works that were the same as the existing breakdown structure were found, and non-existent works were added to the similar breakdown structure. These results are expected to be helpful for future 3D printing construction management and cost estimation. The actual standard estimation system through 3D printing work will need to be calculated.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• Journal of the Korea Institute of Building Construction
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• v.23 no.2
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• pp.175-185
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• 2023

Upon analyzing labor productivity in the construction industry across OECD countries, it was found that in 2019, labor productivity per employee in the South Korean construction industry was lower than that of major developed countries when adjusted for purchasing power parity(PPP). Specifically, when benchmarked against other countries at a base of 100, South Korea scored 76.9 in the United States, 88.4 in Japan, and 85.1 in the OECD average. Notably, South Korea ranked 25th in labor productivity per employee in the construction industry among 35 OECD countries in 2019, indicating a low standing. A comparative analysis of the construction market size and labor productivity in the construction industry across OECD countries revealed that larger construction markets did not necessarily correlate with higher labor productivity. To enhance labor productivity in the construction industry, this study proposed the active implementation of smart construction technology at construction sites and the promotion of on-site assembly work using off-site construction(OSC) technology, rather than traditional on-site labor. Moreover, it was recommended that the development of modular construction methods and technologies be expanded. In the future, if off-site production methods and modules are further developed through advanced robotics and factory automation, labor productivity is anticipated to increase due to the restructuring of production methods, such as manufacturing.