淡江大學機構典藏:Item 987654321/118717
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 62830/95882 (66%)
造訪人次 : 4042543      線上人數 : 1034
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/118717


    題名: Learning the classroom automation preferences with low user intervention
    作者: Chang, F.-C.;Huang, H.-C.;Chu, L.
    關鍵詞: smart classroom;Internet of Things;automation
    日期: 2020-04-30
    上傳時間: 2020-06-01 12:15:22 (UTC+8)
    摘要: With the affordable Internet of Things (IoT) devices, the number of smart classrooms are increasing. There are researches on how to incorporate the IoT technology into the pedagogy. We put the emphasis on classroom automation which enables the teacher to flexibly configure the smart devices without coding. It is achieved by a framework on top of the physical IoT network. In the framework, the automation process is modeled as a state transition engine. The teacher only needs to signal the engine to take a few system state snapshots as the preferences. Once the preference model is derived by the learning process, an event would trigger the engine to compute the suggested system states from this model. Then the automation process invokes the predefined actions to reach the target system states. The framework allows the engineer to provide the basic functions to configure the system, while keeping the user intervention low at providing the training data. In addition to describing the example applications of the framework, a simple use case is also simulated to demonstrate how to design a learning mechanism for this framework.
    DOI: 10.1109/LifeTech48969.2020.1570616823
    顯示於類別:[資訊創新與科技學系] 會議論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML206檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋