• Title/Summary/Keyword: On-Device AI

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Development of AI Image Analysis Emergency Door Opening and Closing System linked Wired/Wireless Counting (유무선 카운팅 연동형 AI 영상분석 비상문 개폐 시스템 개발)

  • Cheol-soo, Kang;Ji-yun, Hong;Bong-hyun, Kim
    • Journal of Digital Policy
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    • v.1 no.2
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    • pp.1-8
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    • 2022
  • In case of a dangerous situation, the roof, which serves as an emergency exit, must be open in case of fire according to the Fire Act. However, when the roof door is opened, it has become a place of various incidents and accidents such as illegal entry, crime, and suicide. As a result, it is a reality to close the roof door in terms of facility management to prevent crime, various incidents, and accidents. Accordingly, the government is pushing to legislate regulations on housing construction standards, etc. that mandate the installation of electronic automatic opening and closing devices on rooftop doors. Therefore, in this paper, an intelligent emergency door opening/closing device system is proposed. To this end, an intelligent emergency door opening and closing system was developed by linking wired and wireless access counting and AI image analysis. Finally, it is possible to build a wireless communication-based integrated management platform that provides remote control and history management in a centralized method of device status real-time monitoring and event alarm.

Top 10 Key Standardization Trends and Perspectives on Artificial Intelligence in Medicine (의료 인공지능 10대 표준화 동향 및 전망)

  • Jeon, J.H.;Lee, K.C.
    • Electronics and Telecommunications Trends
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    • v.35 no.2
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    • pp.1-16
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    • 2020
  • "Artificial Intelligence+" is a key strategic direction that has garnered the attention of several global medical device manufacturers and internet companies. Large hospitals are actively involved in different types of medical AI research and cooperation projects. Medical AI is expected to create numerous opportunities and advancements in areas such as medical imaging, computer aided diagnostics and clinical decision support, new drug development, personal healthcare, pathology analysis, and genetic disease prediction. On the contrary, some studies on the limitations and problems in current conditions such as lack of clinical validation, difficulty in performance comparison, lack of interoperability, adversarial attacks, and computational manipulations are being published. Overall, the medical AI field is in a paradigm shift. Regarding international standardization, the work on the top 10 standardization issues is witnessing rapid progress and the competition for standard development has become fierce.

Research on the development of demand for medical and bio technology using big data (빅데이터 활용 의학·바이오 부문 사업화 가능 기술 연구)

  • Lee, Bongmun.;Nam, Gayoung;Kang, Byeong Chul;Kim, CheeYong
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.345-352
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    • 2022
  • Conducting AI-based fusion business due to the increment of ICT fusion medical device has been expanded. In addition, AI-based medical devices help change existing medical system on treatment into the paradigm of customized treatment such as preliminary diagnosis and prevention. It will be generally promoted to the change of medical device industry. Although the current demand forecasting of medical biotechnology commercialization is based on the method of Delphi and AHP, there is a problem that it is difficult to have a generalization due to fluctuation results according to a pool of participants. Therefore, the purpose of the paper is to predict demand forecasting for identifying promising technology based on building up big data in medical biotechnology. The development method is to employ candidate technologies of keywords extracted from SCOPUS and to use word2vec for drawing analysis indicator, technological distance similarity, and recommended technological similarity of top-level items in order to achieve a reasonable result. In addition, the method builds up academic big data for 5 years (2016-2020) in order to commercialize technology excavation on demand perspective. Lastly, the paper employs global data studies in order to develop domestic and international demand for technology excavation in the medical biotechnology field.

A 0.9-V human body communication receiver using a dummy electrode and clock phase inversion scheme

  • Oh, Kwang-Il;Kim, Sung-Eun;Kang, Taewook;Kim, Hyuk;Lim, In-Gi;Park, Mi-Jeong;Lee, Jae-Jin;Park, Hyung-Il
    • ETRI Journal
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    • v.44 no.5
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    • pp.859-874
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    • 2022
  • This paper presents a low-power and lightweight human body communication (HBC) receiver with an embedded dummy electrode for improved signal acquisition. The clock data recovery (CDR) circuit in the receiver operates with a low supply voltage and utilizes a clock phase inversion scheme. The receiver is equipped with a main electrode and dummy electrode that strengthen the capacitive-coupled signal at the receiver frontend. The receiver CDR circuit exploits a clock inversion scheme to allow 0.9-V operation while achieving a shorter lock time than at 3.3-V operation. In experiments, a receiver chip fabricated using 130-nm complementary metal-oxide-semiconductor technology was demonstrated to successfully receive the transmitted signal when the transmitter and receiver are placed separately on each hand of the user while consuming only 4.98 mW at a 0.9-V supply voltage.

Development of a Smart Device Utilization Education Program for Senior Citizens

  • Ahra CHO;Chan-Woo YOO
    • Fourth Industrial Review
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    • v.4 no.1
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    • pp.19-27
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    • 2024
  • Purpose: This study is based on the results of the National Information Society Agency's the Report on the Digital Divide in 2022. This study sought to develop digital literacy education programs for senior citizens, a digitally disadvantaged group, and to utilize smart devices to enhance their digital capabilities. Research design, data and methodology: Based on Gagné's nine events of instruction, a total of 7-session educational programs using smart devices were developed, and teaching-learning goals were set at a level that older learners can realistically perform. In preparation for the era of digital transformation, AI utilization methods are introduced and utilized in some sessions of the educational program. Results: Among a total of 7 sessions of the educational program, 5 sessions using KakaoTalk and Naver App, and 2 sessions using other apps were developed. There are a total of three sessions using AI. Conclusions: This study presented a digital literacy education program that combined AI, addressing the insufficiency of AI-based education programs targeting senior citizens. It is expected that this educational program will be able to improve the digital literacy skills and provide a basis for fulfilling their responsibilities as digital citizens by suggesting a direction for AI utilization education for senior citizens.

Retrieval Method using Device Characteristics and Device Usage Characteristics in Multi-Device Environment (다중 기기 환경에서 기기 특성과 기기 사용 특성을 활용한 검색 기법)

  • Kwon, Joon Hee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.17 no.3
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    • pp.17-26
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    • 2021
  • Internet of Things is an infrastructure of the interconnected devices. In Internet of Things environment, many smart devices are used in daily life. It requires a new retrieval method using multiple devices. We propose an information retrieval method using both device characteristics and device usage characteristics in multi-device environments. Firstly, information retrieval is performed using a general purpose device. And then, it is performed using dedicated devices. Our method uses both characteristics of the devices and usage characteristics of them. Moreover, it considers queries on the general purpose device. This paper proposes a new retrieval method and describes algorithms. Then, it presents smart home scenarios. Performance evaluation is performed using the scenarios. The evaluation results show higher precision and efficiency than previous researches. The proposed method gets information more accurately and quickly in IOT multiple device environments.

Energy-Aware Data-Preprocessing Scheme for Efficient Audio Deep Learning in Solar-Powered IoT Edge Computing Environments (태양 에너지 수집형 IoT 엣지 컴퓨팅 환경에서 효율적인 오디오 딥러닝을 위한 에너지 적응형 데이터 전처리 기법)

  • Yeontae Yoo;Dong Kun Noh
    • IEMEK Journal of Embedded Systems and Applications
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    • v.18 no.4
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    • pp.159-164
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    • 2023
  • Solar energy harvesting IoT devices prioritize maximizing the utilization of collected energy due to the periodic recharging nature of solar energy, rather than minimizing energy consumption. Meanwhile, research on edge AI, which performs machine learning near the data source instead of the cloud, is actively conducted for reasons such as data confidentiality and privacy, response time, and cost. One such research area involves performing various audio AI applications using audio data collected from multiple IoT devices in an IoT edge computing environment. However, in most studies, IoT devices only perform sensing data transmission to the edge server, and all processes, including data preprocessing, are performed on the edge server. In this case, it not only leads to overload issues on the edge server but also causes network congestion by transmitting unnecessary data for learning. On the other way, if data preprocessing is delegated to each IoT device to address this issue, it leads to another problem of increased blackout time due to energy shortages in the devices. In this paper, we aim to alleviate the problem of increased blackout time in devices while mitigating issues in server-centric edge AI environments by determining where the data preprocessed based on the energy state of each IoT device. In the proposed method, IoT devices only perform the preprocessing process, which includes sound discrimination and noise removal, and transmit to the server if there is more energy available than the energy threshold required for the basic operation of the device.

Threat Detection Algorithm for Wearable Device User based on PPG Signal Processing (웨어러블 디바이스 착용자의 신변 보호를 위한 PPG 신호 처리 및 위협 감지 알고리즘 개발)

  • Sohee Yoo;Gyuwon Hwang;Jaehyun Yoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2024.05a
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    • pp.648-649
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    • 2024
  • 웨어러블 디바이스 착용자의 PPG 신호 데이터로 위협 상황을 감지하는 알고리즘을 개발한다. 본 논문에서는 외부 환경에 예민한 PPG 센서에 최적화된 전처리 알고리즘을 제안하고 긍정 및 부정 영상 시청 실험을 통해 얻은 PPG 신호 데이터를 이용하여 위험 상황과 안전한 상황을 구분하는 정확도 96.87%의 1D-CNN 모델을 개발한다.

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Two-way Interactive Algorithms Based on Speech and Motion Recognition with Generative AI Technology (생성형 AI 기술을 적용한 음성 및 모션 인식 기반 양방향 대화형 알고리즘)

  • Dae-Sung Jang;Jong-Chan Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.2
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    • pp.397-402
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    • 2024
  • Speech recognition and motion recognition technologies are applied and used in various smart devices, but they are composed of simple command recognition forms and are used as simple functions. Apart from simple functions for recognition data, professional command execution capabilities are required based on data learned in various fields. Research is being conducted on a system platform that provides optimal data to users using Generative AI, which is currently competing around the world, and can interact through voice recognition and motion recognition. The main technical processes designed for this study were designed using technologies such as voice and motion recognition functions, application of AI technology, and two-way communication. In this paper, two-way communication between a device and a user can be achieved by various input methods through voice recognition and motion recognition technology applied with AI technology.

Decrease of Gate Leakage Current by Employing AI Sacrificial Layer in the DLC-coated Si-tip FEA Fabrication (DLC-coated Si-tip FEA 제조에 있어서 Al 희생층을 이용한 게이트 누설 전류의 감소)

  • Ju, Byeong-Kwon;Lee, Sangjo;Kim, Hoon;Lee, Yun-Hi;Oh, Myung-Hwan
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.48 no.8
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    • pp.577-579
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    • 1999
  • DLC film remaining on device surface could be removed by eliminating AI sacrificial layer as a final step of lift-off process in the fabrication of DLC-coated Si-tip FEA. The field emission properties(I-V curves, hysteresis, and current fluctuation etc.) of the processed device were analyzed and the process was employed to 1.76 inch-sized FEA panel fabrication in order to evaluate its FED applicability.

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