• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.499-500
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• 2022

차량용 블랙박스의 대중화와 '스마트 국민 제보' 애플리케이션 도입에 따른 영향으로 교통법규 위반 공익신고 건수가 급증하면서 대응해야 할 담당 경찰 인력이 부족한 상황이다. 이러한 인력 부족 문제를 해결하기 위해서 인공지능(AI) 알고리즘을 활용하여 신고된 영상의 위법 여부를 자동으로 분석할 필요가 있다. 본 논문에서는 공익신고의 대부분을 차지하고 있는 진로변경 위반 영상 분석을 위한 객체 인식 방법에 대한 연구 내용을 기술한다. 이 연구에서는 딥러닝 알고리즘과 컴퓨터 비전 알고리즘을 통해 진로변경 위반 분석에 필요한 차량과 실선 객체를 인식하여 진로변경 위반 영상 분석에 활용할 수 있도록 한다.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.243-255
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• 2021

The purpose of this study is to investigate the effect of software education based on physical computing on the CT ability of elementary school students. To this end, previous studies related to physical computing software education and software education in the 2015 revised curriculum were analyzed. In addition, COBL was selected among many physical computing tools on the market in consideration of the level and characteristics of learners in the school to conduct the study, and 'Professor Lee Jae-ho's AI Maker Coding with COBL' was used as the textbook. This study was conducted for 10 sessions on 135 students in 6 classes in 6th grade of H Elementary School located in Pyeongtaek, Gyeong gi-do. The results of this study are as follows. First, it was confirmed that physical computing software education linked to real life was effective in improving the CT ability of elementary school students. Second, the change in competency of CT ability by sector improved evenly from 8 to 30 points in the pre-score and post-score of computing thinking ability. Third, in this study, it was confirmed that 87% of students were very positive as a result of a survey of satisfaction with classes after real-life physical computing software education. We hope that follow-up studies will help select various regions across cities and rural areas, and prove that real-life physical computing software education for various learner members, including large and small schools, will help elementary school students improve their CT ability.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.53-56
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• 2019

본 논문에서는 화력을 이용하는 대형 파워 플랜트 설비의 미세먼지 발생량을 저감시키고 능동적으로 제어 할 수 있는 효율적인 시스템을 제안한다. 이 시스템은 기존의 고정형으로 설계된 집진기 방식의 고정부하량 한계점과 극복하고 초미세먼지 PM2.5, 미세먼지 PM10의 발생량에 따라 IoT센서 감지에 의해 지능형 알고리즘으로 효율적으로 저감 제어 처리량을 극대화하고, 미세먼지 발생량을 최소화한다. 또한 이 시스템의 차별성은 기존의 집진기에서 잡혀지지 않는 초미세먼지를 새로운 형태의 물질인 FAA(Fine-dust Adsorption Agent)를 통해 연료 연소 시 발생되는 초미세먼지 미세입자 자체를 크게 만들어 기존 설비 집진기 필터에 포집되게 하는 혁신적인 방식이다. 이번 연구를 통해 350도~1000도 열원에서 작용할 수 있는 화학물질 FAA 용액(Agent)을 개발 하였으며 지능형 AI 분사장치를 통해 연료에 첨가되어 연소 시 미세먼지를 20배~50배까지 볼륨을 확대시켜 기존 집진필터에 포집될 수 있게 동작된다. 이때, 기존 설계된 집진기의 한계(부하)용량에 상관없이 미세먼지 발생량을 상황인식 반응형 알고리즘(AI제어) 통해 분사량을 능동적으로 조절하여 미세먼지 발생량을 저감하는 진보적 혁신성을 지닌다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.27-36
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• 2022

In this paper, to improve the conditions of the fish processing site, we propose a method to predict the cutting point of fish according to the target weight using AI machine vision. The proposed method performs image-based preprocessing by first photographing the top and front views of the input fish. Then, RANSAC(RANdom SAmple Consensus) is used to extract the fish contour line, and then 3D external information of the fish is obtained using 3D modeling. Next, machine learning is performed on the extracted three-dimensional feature information and measured weight information to generate a neural network model. Subsequently, the fish is cut at the cutting point predicted by the proposed technique, and then the weight of the cut piece is measured. We compared the measured weight with the target weight and evaluated the performance using evaluation methods such as MAE(Mean Absolute Error) and MRE(Mean Relative Error). The obtained results indicate that an average error rate of less than 3% was achieved in comparison to the target weight. The proposed technique is expected to contribute greatly to the development of the fishery industry in the future by being linked to the automation system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1525-1530
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• 2021

By applying AI-based efficient inventory management and logistics optimization technology using the smart factory's production plan and manufacturing data, the company's productivity improvement and customer satisfaction can be expected to increase. In this paper, we proposed a system that collects data from the factory's production process, stores it in the cloud, and uses the manufacturing data stored there to apply AI-based supply chain optimization technology later. While the existing system supported approximately 10 to 20 data types, the proposed system is designed and developed to support more than 100 data types. In addition, in the case of the collection cycle, data can be collected 1-2 times per second, and data collection in TB units is possible. Therefore This system is designed to be applied to the existing factory of past in addition to the smart factory.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.347-354
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• 2022

Since the era of the 4th industrial revolution has been ripe, the use of artificial intelligence(AI) based on massive data is beginning to be actively applied in various fields. However, as the process of analyzing forest species is carried out manually, many errors are occurring. Therefore, in this paper, about 60,000 pieces of AI learning data were automatically analyzed for pine, larch, conifer, and broadleaf trees of aerial photographs and pseudo images in the metropolitan area, and an AI model was developed to distinguish tree species. Through this, it is expected to increase in work efficiency by using the tree species division image as basic data when producing forest change detection and forest field topics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.23-28
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• 2024

This study focuses on investigating and exploring solutions to problems related to the increase in the elderly population in modern society where aging is rapidly progressing. With the advent of an aging society the elderly population requires more attention and support. In response companies are attempting to provide elder care services using AI and robotic technology. These services can assist seniors not only with health management and daily life care but also with emotional health aspects. This paper analyzes various elder-related technologies available in the current market investigates their pros and cons and potential for development. The paper concludes that companies need to develop and provide more AI and robot-based elder care services to solve aging problems. Such services can alleviate social and emotional issues in an aging society enhancing the quality of life for seniors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.133-139
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• 2024

In response to the challenges posed by a super-aged society, local authorities are conducting educational programs on smartphone usage tailored for the elderly. However, obstacles such as the limitations of one-to-many education and suboptimal learning outcomes for the elderly have hindered the efficacy of smartphone education. This study suggests an educational service intended for direct application in offline settings, considering the identified problems. Through the utilization of generative AI, the proposed app identifies specific challenges encountered by users during actual smartphone use, offering personalized exercises to facilitate customized and repetitive learning experiences for individual users. When integrated with existing local government education initiatives, this app is anticipated to enhance the efficiency of smartphone education by providing personalized, one-on-one training that is efficient in terms of time and content.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.17-22
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• 2024

Recently, as the ICT field has been used in various environments, it has become possible to analyze pests by crops, use robots when harvesting crops, and predict by big data by utilizing ICT technologies in a sustainable agricultural environment. However, in a sustainable agricultural environment, efforts to solve resource depletion, agricultural population decline, poverty increase, and environmental destruction are constantly being demanded. This paper proposes an artificial intelligence-based big data processing analysis method to reduce the production cost and increase the efficiency of crops based on a sustainable agricultural environment. The proposed technique strengthens the security and reliability of data by processing big data of crops combined with AI, and enables better decision-making and business value extraction. It can lead to innovative changes in various industries and fields and promote the development of data-oriented business models. During the experiment, the proposed technique gave an accurate answer to only a small amount of data, and at a farm site where it is difficult to tag the correct answer one by one, the performance similar to that of learning with a large amount of correct answer data (with an error rate within 0.05) was found.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.23-29
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• 2023

For given the importance of elementary school students developing the ability to solve problems using artificial intelligence (AI), problem-solving abilities should be developed using AI along with education to develop problem-solving abilities. Such students need a form that allows them to understand the concepts and principles of AI and to be easily educated in a fun way to understand basic understanding of how AI works. To this end, this study planned an 8-hour AI convergence program and operated based on self-driving cars, demonstrating that it was effective in improving elementary school students' problem-solving abilities, creativity, and AI understanding. As a result of operating the camp, students' understanding of AI was 3.56 (standard deviation 0.85), 4.00 (standard deviation 0.71), and t-value was -5.412 (p<0.001), indicating statistically improved understanding of AI, and high satisfaction and interest of students. In the future, it will be necessary to develop an educational program that allows elementary school students to devise their own ideas and create products to which AI models can be applied.