| 摘要(英) |
With the increasing demand of electricity consumption, the issue of excessive energy
consumption and the study of improving energy eciency have been receive more atten-
tion. However, relying solely on human resources for energy management and allocation
will signi cantly reduce the eciency 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 eciency . 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 eciency of farm management and enhance the accuracy
of light regulation and energy eciency, 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. |
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