• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.12
• /
• pp.1612-1617
• /
• 2020

Recently, research to reduce the accident rate by actively adopting artificial intelligence technology in the field of disaster safety technology is spreading. In particular, it is important to quickly search the Rescue Requester in order to effectively perform rescue activities at the disaster site. However, it is difficult to search for Rescue Requester due to the nature of the disaster environment. In this paper, We intend to develop an artificial intelligence system that can be operated in a smart helmet for firefighters to search for a rescue requester. To this end, the optimal SoC was selected and developed as an embedded system, and by testing a general-purpose artificial intelligence S/W, the embedded system for future smart helmet research was verified to be suitable as an artificial intelligence S/W operating platform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.530-532
• /
• 2021

This paper deals with AI education service that enables developers who have completed basic programming education to program in C/C++ language in order to learn big data and artificial intelligence. In addition, a customized development environment configuration system according to the development environment and how the user implements and tests artificial intelligence are explained. And also it has a function to check the effect on artificial intelligence through manipulation of various internal parameters. It is expected that it will be possible to develop artificial intelligence education services without language restrictions through networks in the future.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.11a
• /
• pp.319-320
• /
• 2022

해무는 해면에 인접한 층에서 수증기가 응결하여 대기 중에 부유하는 현상으로 기상학적으로 수평 가시거리가 1km이하 일때로 정의되며 해무로 인해 항공기 이착륙 지연, 교통사고, 운항 통제, 인명 피해 등 사회적, 경제적 피해를 유발하고 있다. 본 연구에서는 기존의 해무 발생, 탐지, 예측과 관련한 연구를 비교 분석하여 향후 연구개발의 방향을 제시하고자 한다. 해무 발생, 예측과 관련하여 연구개발이 진행되어 왔으나 해무의 특성상 규칙성이 약하고 고정적인 측정법이나 이를 다루기 위한 네트워크가 부족하여 예측하기가 어렵다. 특히, 국내에서는 국립해양조사원과 기상청에서 해무 탐지 및 예측에 관한 연구개발 및 서비스가 진행되고 있으나 현업화가 이루어지지 않거나 특정지점에 대한 정보만 제공되고 있는 한계가 있다. 따라서, CCTV영상, 인공위성 영상, 시정계, 기상자료, 수치모형을 통해 수집된 정보를 통합하여 예측할 수 있는 인공지능기반의 해무 탐지 및 예측 기술개발이 진행되어야 할 것이다.

• Informatization Policy
• /
• v.23 no.1
• /
• pp.74-93
• /
• 2016

This paper proposes Korean national science and ICT policies in artificial intelligence (AI) field. After analyzing the AI trends in major countries as an initiative for global competitiveness, we suggest for new solutions for nutcracker threats and provide policy recommendations for strengthening competitiveness and commercialization in AI field of Korea. Korea's AI status was diagnosed in the order of governance, research and development (R&D), technology commercialization, law and legislation, and human resources strategy. In conclusion, it proposes improvement of governance, procession of long term future market initiative R&D, development of AI commercialization platforms, preparation of research friendly law and environment, and the nurturing of practical and converging human resources system.

• Broadcasting and Media Magazine
• /
• v.25 no.4
• /
• pp.35-45
• /
• 2020

역사적으로 전염병은 기존의 경제 질서를 완전히 바꾸는 촉매제였다. 전문가들은 코로나19가 디지털 플랫폼 경제를 획기적으로 확대하고 보호주의 중심의 글로벌 경제 질서를 획기적으로 재편할 것으로 내다봤다. 특히, 비대면 문화가 보편화됨에 따라 기존 산업에서 인공지능으로 이어지는 혁신 기술을 접목한 디지털 기반 산업으로 전환해야 할 필요성에 따라 ICT 기반 기업 간의 경쟁이 심화될 것으로 예상된다. 코로나19는 신기술로 막 뛰어든 스타트업 ICT 기업에게 새로운 기회가 될 수도 있고, 기존 ICT 기업이 입지를 강화해 글로벌기업으로 거듭날 수 있는 기회가 될 수도 있다. 그 기회의 중심에는 4차 산업 혁명을 이끌 인공지능 기술이 있다. 본 고에서는 포스트 코로나 시대를 위한 인공지능 기술의 동향과 발전 방향을 살펴보고, AR 및 VR과 같은 영상 미디어 기술의 역할에 대해서 살펴본다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.07a
• /
• pp.453-454
• /
• 2021

본 논문에서는 딥아이(DIY) 블록 프로그래밍과 라즈베리파이의 피지컬 컴퓨팅을 활용해 엑츄에이터와 센서를 제어하고 센서를 통해 수집한 데이터를 전처리해 인공지능에 활용함으로써 효율적인 인공지능 교육 방식을 제안한다. 해당 방식은 블록코딩 방식을 사용함으로써 문자코딩 대비 오타을 줄이고 문법 구애율을 낮춤으로써 프로그래밍 입문자의 구문적 어려움을 최소화하고 개념과 전략적 학습을 극대화한다. 블록프로그래밍 사용언어로 파이썬을 채택해 입문자의 편의를 도모하고 파일처리, 크롤링, csv데이터 추출을 통해 인공지능 교육에 활용한다.

• Informatization Policy
• /
• v.27 no.2
• /
• pp.3-19
• /
• 2020

Artificial intelligence(AI) and blockchain are developing as the core technology leading the Fourth Industrial Revolution. However, AI is still showing limitations in securing and verifying data and explaining the evidence for the results, and blockchain also has some drawbacks such as excessive energy consumption and lack of flexibility in data management. This study analyzed technological limitations of AI and blockchain and convergence trends to overcome them, and finally suggested ways to improve Korea's related policies. Specifically, in terms of R&D reinforcement, we proposed 1) mid- and long-term AI /blockchain convergence research at the national level and 2) blockchain-based AI data platform development. In terms of creating an innovative ecosystem, we also suggested 3) development of AI/blockchain convergence applications by industry, and 4) Start-up support for developing AI/blockchain convergence business models. Lastly, in terms of improving the legal system, we insisted that 5) widening the application of regulatory sandboxes and 6) improving regulations related to privacy protection is necessary.

• Journal of The Korean Association of Information Education
• /
• v.26 no.4
• /
• pp.273-284
• /
• 2022

The goal of this paper is to propose the use of machine learning platforms in education to train learners to recognize data biases. Learners can cultivate the ability to recognize when learners deal with AI data and systems when they want to prevent damage caused by data bias. Specifically, this paper presents a method of data bias education using MachineLearningforKids, focusing on the case of AI baseball referee. Learners take the steps of selecting a specific topic, reviewing prior research, inputting biased/unbiased data on a machine learning platform, composing test data, comparing the results of machine learning, and present implications. Learners can learn that AI data bias should be minimized and the impact of data collection and selection on society. This learning method has the significance of promoting the ease of problem-based self-directed learning, the possibility of combining with coding education, and the combination of humanities and social topics with artificial intelligence literacy.

• The Journal of Bigdata
• /
• v.2 no.2
• /
• pp.9-16
• /
• 2017

Global Platform Solution Company (aka Amazon, Google, MS, IBM) who has cloud platform, are driving AI and Big Data service on their cloud platform. It will dramatically change Enterprise business value chain and infrastructures in Supply Chain Management, Enterprise Resource Planning in Customer relationship Management. Enterprise are focusing the channel with customers and Business Partners and also changing their infrastructures to platform by integrating data. It will be Digital Transformation for decision support. AI and Deep learning technology are rapidly combined to their data driven platform, which supports mobile, social and big data. The collaboration of platform service with business partner and the customer will generate new ecosystem market and it will be the new way of enterprise revolution as a part of the 4th industrial revolution.

• Journal of the Korea Convergence Society
• /
• v.9 no.8
• /
• pp.127-133
• /
• 2018

The purpose of this study is to analyze the technology trend of artificial intelligent speaker(AI speaker) and to suggest direction of domestic AI speaker through the case study of AI speaker. As a research method, technical background was studied through literature, and then, case of AI speaker was investigated. As a result, It attempts to extend it to the visual interface. One of these attempts is attention to the built-in screen AI speaker. AI speakers should be a platform for humans and computers to interact with, not just convenience facilities. Based on the implications presented in this study, we hope to be able to use it as a reference for predicting the service development direction of domestic artificial intelligent speakers in the future.