• Title/Summary/Keyword: Appinventor

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Implementation of Mobile Multi-sensor System for Measuring an Environment (환경 측정을 위한 모바일 다기능 센서의 구현)

  • Ju, Ji-Dong;Kim, Jin-Seoung;Kang, Bong-Gu;Shim, Jeachang
    • Journal of Korea Multimedia Society
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    • v.17 no.8
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    • pp.1020-1024
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    • 2014
  • The environment information such as dust, temperature, humidity, illumination and gas are very important in daily life. We implemented multi-sensor system which made for measuring an environment by using Arduino, ZigBee, and Appinventor. We also designed a packet for transmitting environment data. The data are sent to the server via ZigBee and then it communicates to a smart phone via WI-Fi. In this study, we added divers sensors, designed a protocol which made for transfer several kinds of data and improve mobility for real time monitoring by using smart phones. The system was worked well and the data was transmitted correctly to the smart phone.

Design and Application of Artificial Intelligence Experience Education Class for Non-Majors (비전공자 대상 인공지능 체험교육 수업 설계 및 적용)

  • Su-Young Pi
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.529-538
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    • 2023
  • At the present time when the need for universal artificial intelligence education is expanding and job changes are being made, research and discussion on artificial intelligence liberal arts education for non-majors in universities who experience artificial intelligence as part of their job is insufficient. Although artificial intelligence education courses for non-majors are being operated, they are mainly operated as theory-oriented education on the concepts and principles of artificial intelligence. In order to understand the general concept of artificial intelligence for non-majors, it is necessary to proceed with experiential learning in parallel. Therefore, this study designs artificial intelligence experiential education learning contents of difficulty that can reduce the burden of artificial intelligence classes with interest in learning by considering the characteristics of non-majors. After, we will examine the learning effect of experiential education using App Inventor and the Orange artificial intelligence platform. As a result of analysis based on the learning-related data and survey data collected through the creation of AI-related projects by teams, positive changes in the perception of the need for AI education were found, and AI literacy skills improved. It is expected that it will serve as an opportunity for instructors to lay the groundwork for designing a learning model for artificial intelligence experiential education learning.