• Title/Summary/Keyword: 인공지능기기

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Configuration and Application of a deep learning-based fall detection system (딥러닝 기반 낙상 감지 시스템의 구성과 적용)

  • Jong-Seok Woo;Lionel Kyenyeneye;Sang-Joong Jung;Wan-Young Chung
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.4
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    • pp.213-220
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    • 2023
  • Falling occurs unexpectedly during daily activities, causing many difficulties in life. The purpose of this study was to establish a system for fall detection of high-risk occupations and to verify their effectiveness by collecting data and applying it to predictive models. To this end, a wearable device was configured to detect fall by calculating acceleration signals and azimuths through acceleration sensors and gyro sensors. In addition, the study participants wore the device on their abdomen and measured necessary data from falls-related movements in the process of performing predetermined activities and transmitted it to the computer through a Bluetooth device present in the device. The collected data was processed through filtering, applied to fall detection prediction models based on deep learning algorithms which are 1D CNN, LSTM and CNN-LSTM, and evaluate the results.

The Analysis of Elementary School Teachers' Perception of Using Artificial Intelligence in Education (인공지능 활용 교육에 대한 초등교사 인식 분석)

  • Han, Hyeong-Jong;Kim, Keun-Jae;Kwon, Hye-Seong
    • Journal of Digital Convergence
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    • v.18 no.7
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    • pp.47-56
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    • 2020
  • The purpose of this study is to comprehensively analyze elementary school teachers' perceptions of the use of artificial intelligence in education. Recently, interest in the use of artificial intelligence has increased in the field of education. However, there is a lack of research on the perceptions of elementary school teachers using AI in education. Using descriptive statistics, multiple linear regression analysis, and semantic differential meaning scale, 69 elementary school teachers' perceptions of using AI in education were analyzed. As a results, artificial intelligence technology was perceived as most suitable method for assisting activities in class and for problem-based learning. Factors which influence the use of AI in education were learning contents, learning materials, and AI tools. AI in education had the features of personalized learning, promoting students' participation, and provoking students' interest. Further, instructional strategies or models that enable optimized educational operation should be developed.

A Dynamic state transition based on Augmented Reality using the 3-axis accelerometer sensor (3축 가속도 센서를 이용한 증강현실 기반의 동적 상태변환 알고리즘)

  • Jang, Yu-Na;Park, Sung-Jun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2010.07a
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    • pp.99-102
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    • 2010
  • 스마트폰의 도입으로 인하여 증강현실이 널리 알려짐에 따라 대중들의 관심은 이에 집중되고 있으며 휴대성으로 인하여 모바일 기기에서의 증강현실 연구가 하나의 흐름으로 자리 잡고 있다. 기존의 증강 현실 관련 응용 기술들이 많이 연구되고 있지만 실제 게임에서 사용되고 있는 인공 지능과 결합된 연구는 이루어지고 있지 않다. 본 논문에서는 스마트 폰의 기능중 하나인 3축 가속도 센서를 이용하여 증강 현실 환경에서 3D 에이전트의 상태를 동적으로 변환하는 인공 지능 알고리즘을 제안한다. 인공지능이 적용된 에이전트의 상태를 제어하기 위한 전통적인 방식으로서 사용자가 직접 입력해 주거나 이를 인식하는데 마커를 사용하여 해결하였다. 본 논문에서는 증강 현실 구현을 위해 마커리스 추적 기술을 사용하였고 3축 가속도 센서를 이용하여 동적으로 에이전트의 상태를 변환하도록 하였다.

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Using 3D image-based body shape Measurement to increase the accuracy of body shape Measurement (체형 측정의 정확도를 높이기 위한 3차원 영상 기반의 체형 측정 활용)

  • So, Ji Ho;Jeon, Young-Ju
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.4
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    • pp.803-806
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    • 2020
  • The body shape measurement method using 3D images has been widely used due to the recent development of 3D measurement cameras and algorithms. Existing 3D imaging devices are expensive devices, and there is a limit to their universalization. Due to the recent spread of inexpensive 3D cameras and the development of various measurement methods, various possibilities are being shown. It is expected to have a great impact on the medical device market that requires accurate data collection. Various medical device products using artificial intelligence are emerging, and accurate data collection is the most important to develop accurate artificial intelligence algorithms. Collection equipment using 3D cameras is expected to act as a major factor in the development of artificial intelligence algorithms using 3D images.

Categorization of Interaction Factors through Analysis of AI Agent Using Scenarios (인공지능 에이전트의 사용 시나리오 분석을 통한 인터랙션 속성 유형화)

  • Cheon, Soo-Gyeong;Yeoun, Myeong-Heum
    • Journal of the Korea Convergence Society
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    • v.11 no.11
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    • pp.63-74
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    • 2020
  • AI products are used 'AI assistants' as embedded in smart phones, speakers, appliances as agents. Studies on anthropomorphism, such as personality, voice with a weak AI are being conducted. Role and function of AI agents will expand from development of AI technology. Various attributes related to the agent, such as user type, usage environment, appearance of the agent will need to be considered. This study intends to categorize interaction factors related to agents from the user's perspective through analysis of concept videos which agents with strong AI. Framework for analysis was built on the basis of theoretical considerations for agents. Concept videos were collected from YouTube. They are analyzed according to perspectives on environment, user, agent. It was categorized into 8 attributes: viewpoint, space, shape, agent behavior, interlocking device, agent interface, usage status, and user interface. It can be used as reference when developing, predicting agents to be commercialized in the future.

Standardization Trends on Artificial Intelligence in Medicine (의료 인공지능 표준화 동향)

  • Jeon, J.H.;Lee, K.C.
    • Electronics and Telecommunications Trends
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    • v.34 no.5
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    • pp.113-126
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    • 2019
  • Based on the accumulation of medical big data, advances in medical artificial intelligence technology facilitate the timely treatment of disease through the reading the medical images and the increase of prediction speed and accuracy of diagnoses. In addition, these advances are expected to spark significant innovations in reducing medical costs and improving care quality. There are already approximately 40 FDA approved products in the US, and more than 10 products with K-FDA approval in Korea. Medical applications and services based on artificial intelligence are expected to spread rapidly in the future. Furthermore, the evolution of medical artificial intelligence technology is expanding the boundaries or limits of various related issues such as reference standards and specifications, ethical and clinical validation issues, and the harmonization of international regulatory systems.

Analysis of the utility of intelligent speakers in the Internet of Things environment (사물인터넷 환경에서 지능형 스피커의 활용성 분석)

  • Lee, Seong-Hoon;Lee, Dong-Woo
    • Journal of Internet of Things and Convergence
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    • v.8 no.3
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    • pp.41-46
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    • 2022
  • Smart home in the Internet of Things (IoT) environment aims to provide an optimal living environment for users by connecting all devices in the home. In such a smart home environment, artificial intelligence speakers are being used as a way to manage and control all devices. The existing speaker function is changing from simple music playback to the role of an interface that controls and manages all devices in the smart home space. This study dealt with the market status and usability analysis in the US and Korea, the leader in artificial intelligence speakers. The main target companies were Amazon, Google, and Apple in the US, as well as Kakao, SKT, and KT in Korea. In addition, based on the reaction results of domestic users to artificial intelligence speakers, the derivation of major problems and directions for improvement were described.

Ai-Based Cataract Detection Platform Develop (인공지능 기반의 백내장 검출 플랫폼 개발)

  • Park, Doyoung;Kim, Baek-Ki
    • Journal of Platform Technology
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    • v.10 no.1
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    • pp.20-28
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    • 2022
  • Artificial intelligence-based health data verification has become an essential element not only to help clinical research, but also to develop new treatments. Since the US Food and Drug Administration (FDA) approved the marketing of medical devices that detect mild abnormal diabetic retinopathy in adult diabetic patients using artificial intelligence in the field of medical diagnosis, tests using artificial intelligence have been increasing. In this study, an artificial intelligence model based on image classification was created using a Teachable Machine supported by Google, and a predictive model was completed through learning. This not only facilitates the early detection of cataracts among eye diseases occurring among patients with chronic diseases, but also serves as basic research for developing a digital personal health healthcare app for eye disease prevention as a healthcare program for eye health.