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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/81902

    Title: 基於機器學習的LED照明調控機制:以智慧農場為實施例;LED Dimming Control Mechanism Based on Machine Learning:A Practical Case in Smart Farms
    Authors: 鄧博謙;Teng, Po-Chien
    Contributors: 通訊工程學系
    Keywords: 機器學習;物聯網;machine learing;IoT
    Date: 2019-12-20
    Issue Date: 2020-01-07 14:32:51 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 隨著當代用電量的需求逐漸地提高,能源消耗過度的議題與提升能源使用效
    同時減少家用照明設備的能源消耗以及優化光源供應的目的。;With the increasing demand of electricity consumption, the issue of excessive energy
    consumption and the study of improving energy e ciency have been receive more atten-
    tion. However, relying solely on human resources for energy management and allocation
    will signi cantly reduce the e ciency of energy use and the immediacy of decision-making.
    In recent years, in view of the rapid development of Internet of things technology, indus-
    try, government, academic and industrial sectors have begun to apply IoT technology
    in people′s life, such as smart farms, smart homes and smart meters,etc. Monitoring
    environmental changes and impacts through IoT technology can not only e ectively use
    energy, but also reduce the cost of energy management. Therefore, the combination of
    Internet of things technology and energy management has become one of the important
    solutions to improve energy e ciency . In this paper, we design a smart dimming system
    that combines IoT technology for the energy management scenario of smart farms. This
    system consists of three subsystems, namely the IoT device end, the user end and the
    cloud. In order to increase the e ciency of farm management and enhance the accuracy
    of light regulation and energy e ciency, this system simultaneously introduces and inte-
    grates four functional modules, including low-power communication technology , energy
    monitoring device, cloud integrated service platform and neural network algorithm.
    In this thesis design of three subsystems, rst of all, the Internet of things devices
    through a variety of heterogeneous sensors (such as: colour sensor, the temperature and
    humidity sensors, electronic meter, etc.) after sensing changes in the environment on the
    farm, gateway will upload sensing data to the cloud platform by low power communication
    transmission technology MQTT for graphical representations and data storage, and it
    can receive by the end user and the cloud control switch and adjust the LED brightness ;
    Furthermore, in the cloud-end, we choose the Azure cloud platform developed by Microsoft
    and build Node-RED platform in the virtual machine as the development tool of the
    system, which connect three subsystems. Finally, in the user -end, users can access the
    required information, control and manage IoT devices remotely through the graphical
    interface designed in Node-RED platform, thus realizing the bidirectional transmission
    architecture of the IoT and vertically integrated services. In addition, GRNN neural
    network is introduced in this paper to help calculate the optimal allocation strategy of
    light and sunlight complementing each other. Through GRNN neural network, the system
    will judge whether the light source needs to be adjusted in the current environment, and
    calculate the best PWM dimming value for certain regions, so as to achieve the balance
    among the immediacy of dimming, energy consumption and stability of the light source
    supply. Finally, through the system design of this paper, we expect to provide users
    with integrated services based on the Internet of things technology to remotely monitor
    and manage the situation in the farm at any time and anywhere, and make timely and
    accurate complementary dimming according to the change of external light source, so as
    to optimize the brightness supply with the lowest energy consumption cost. In the future
    research, this paper is expected to combine the system designed in this paper with the
    application of energy management system (HEMS) in the smart home environment, so as
    to achieve the purpose of simultaneously reducing the energy consumption of household
    lighting equipment and optimizing the supply of light source.
    Appears in Collections:[通訊工程研究所] 博碩士論文

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