US-20260129735-A1 - LIGHTING CONTROL SYSTEM AND METHOD FOR AMUSEMENT DEVICE

US20260129735A1US 20260129735 A1US20260129735 A1US 20260129735A1US-20260129735-A1

Abstract

The present disclosure provides a lighting control system and a method for amusement device, relating to the technical field of smart homes. The lighting control system for amusement device includes a cloud server, an Internet of Things module of the amusement device, and a user terminal. The Internet of Things module includes a smart lighting device and a gateway device which are paired to connect, wherein the gateway device and the user terminal are both communicatively connected to the cloud server.

Inventors

YongFeng Lu
Sijin CHEN

Assignees

GuangZhou DreamFuns Amusement Technology Co., Ltd

Dates

Publication Date: 20260507
Application Date: 20241224
Priority Date: 20241107

Claims (15)

1 . A lighting control system for amusement device, comprising a cloud server, an Internet of Things module of the amusement device, and a user terminal, wherein the Internet of Things module comprises a smart lighting device and a gateway device which are paired to connect, and the gateway device and the user terminal are both communicatively connected to the cloud server; the user terminal is configured to send lighting control commands to the cloud server; the cloud server is configured to receive the lighting control commands and issue a corresponding first lighting adjustment strategy to the gateway device; the smart lighting device is configured to acquire the first lighting adjustment strategy forwarded by the gateway device and perform a lighting adjustment of the amusement device based on the first lighting adjustment strategy; and the gateway device is further configured to upload real-time environment data of the amusement device to the cloud server; the cloud server is further configured to receive the real-time environment data, generate a second lighting adjustment strategy matching user habits according to the real-time environment data and a trained lighting adjustment model, and send the second lighting adjustment strategy to the gateway device, wherein the lighting adjustment model is trained based on historical environment data and historical user usage data, and the historical user usage data comprises offline adjustment data of the smart lighting device uploaded by the gateway device and remote adjustment data corresponding to historical lighting control commands sent by the user terminal; and the smart lighting device is further configured to acquire the second lighting adjustment strategy forwarded by the gateway device and perform lighting adjustment of the amusement device based on the second lighting adjustment strategy.
2 . The lighting control system for the amusement device according to claim 1 , wherein the cloud server is further configured to perform a data preprocessing and a feature extraction on the real-time environment data to obtain current time features and current environment features; input the current time features and the current environment features into the lighting adjustment model to obtain a predicted lighting adjustment strategy output by the lighting adjustment model; and determine the second lighting adjustment strategy based on the predicted lighting adjustment strategy, wherein the data preprocessing comprises data cleaning and data standardization; and the lighting adjustment model uses supervised learning algorithms to predict user-preferred lighting settings, unsupervised learning algorithms to identify user usage patterns, and time series analysis to predict user usage times.
3 . The lighting control system for the amusement device according to claim 2 , wherein the cloud server is further configured to optimize a lighting usage time and a lighting brightness in the predicted lighting adjustment strategy based on preset energy consumption setting parameters to obtain the second lighting adjustment strategy.
4 . The lighting control system for the amusement device according to claim 1 , wherein the cloud server is further configured to periodically collect the historical environment data and the historical user usage data and update the lighting adjustment model based on the historical environment data and the historical user usage data, wherein the historical user usage data comprises one or more of switch-on/off times, lighting brightness adjustment records, lighting color adjustment records, scene mode selection records, and user manual adjustment frequencies.
5 . The lighting control system for the amusement device according to claim 1 , wherein the lighting control commands comprise one or more of lighting scene information, lighting brightness information, and lighting color information, wherein the lighting scene information comprises a reading mode, a leisure mode, or a sleep mode.
6 . The lighting control system for the amusement device according to claim 1 , wherein the user terminal is further configured to send device management commands to the cloud server; the cloud server is further configured to receive the device management commands and perform a target management of the smart lighting device based on the device management commands; and the target management comprises one or more of device registration, status monitoring, and fault diagnosis.
7 . The lighting control system for the amusement device according to claim 1 , wherein the smart lighting device interacts data with the gateway device through a preset communication protocol, and the gateway device is communicatively connected to the cloud server via Wi-Fi or a wired network; and the communication protocol comprises Wi-Fi or Bluetooth.
8 . A lighting control method for amusement device, applicable to the lighting control system for the amusement device according to claim 1 , wherein the lighting control method for amusement device comprises: the user terminal sending the lighting control commands to the cloud server; the cloud server receiving the lighting control commands and issuing the corresponding first lighting adjustment strategy to the gateway device; the smart lighting device acquiring the first lighting adjustment strategy forwarded by the gateway device and performing the lighting adjustment of the amusement device based on the first lighting adjustment strategy; the gateway device uploading the real-time environment data of the amusement device to the cloud server; the cloud server receiving the real-time environment data, generating a second lighting adjustment strategy matching user habits according to the real-time environment data and a trained lighting adjustment model, and sending the second lighting adjustment strategy to the gateway device, wherein the lighting adjustment model is trained based on the historical environment data and the historical user usage data, and the historical user usage data comprises the offline adjustment data of the smart lighting device uploaded by the gateway device and the remote adjustment data corresponding to historical lighting control commands sent by the user terminal; and the smart lighting device acquiring the second lighting adjustment strategy forwarded by the gateway device and performing the lighting adjustment of the amusement device based on the second lighting adjustment strategy.
9 . The lighting control method for the amusement device according to claim 8 , wherein the step of generating a second lighting adjustment strategy matching user habits according to the real-time environment data and a trained lighting adjustment model comprises: performing a data preprocessing and a feature extraction on the real-time environment data to obtain current time features and current environment features, wherein the data preprocessing comprises data cleaning and data standardization; inputting the current time features and the current environment features into the lighting adjustment model to obtain a predicted lighting adjustment strategy output by the lighting adjustment model, wherein the lighting adjustment model uses supervised learning algorithms to predict user-preferred lighting settings, unsupervised learning algorithms to identify user usage patterns, and time series analysis to predict user usage times; and determining the second lighting adjustment strategy based on the predicted lighting adjustment strategy.
10 . The lighting control method for the amusement device according to claim 9 , wherein the step of determining the second lighting adjustment strategy based on the predicted lighting adjustment strategy comprises: optimizing the lighting usage time and the lighting brightness in the predicted lighting adjustment strategy based on the preset energy consumption setting parameters to obtain the second lighting adjustment strategy.
11 . The lighting control system for the amusement device according to claim 2 , wherein the smart lighting device interacts data with the gateway device through a preset communication protocol, and the gateway device is communicatively connected to the cloud server via Wi-Fi or a wired network; and the communication protocol comprises Wi-Fi or Bluetooth.
12 . The lighting control system for the amusement device according to claim 3 , wherein the smart lighting device interacts data with the gateway device through a preset communication protocol, and the gateway device is communicatively connected to the cloud server via Wi-Fi or a wired network; and the communication protocol comprises Wi-Fi or Bluetooth.
13 . The lighting control system for the amusement device according to claim 4 , wherein the smart lighting device interacts data with the gateway device through a preset communication protocol, and the gateway device is communicatively connected to the cloud server via Wi-Fi or a wired network; and the communication protocol comprises Wi-Fi or Bluetooth.
14 . The lighting control system for the amusement device according to claim 5 , wherein the smart lighting device interacts data with the gateway device through a preset communication protocol, and the gateway device is communicatively connected to the cloud server via Wi-Fi or a wired network; and the communication protocol comprises Wi-Fi or Bluetooth.
15 . The lighting control system for the amusement device according to claim 6 , wherein the smart lighting device interacts data with the gateway device through a preset communication protocol, and the gateway device is communicatively connected to the cloud server via Wi-Fi or a wired network; and the communication protocol comprises Wi-Fi or Bluetooth.

Description

CROSS-REFERENCES TO RELATED APPLICATIONS The present disclosure claims priority to Chinese Patent Application No. 2024115859806, entitled “LIGHTING CONTROL SYSTEM AND METHOD FOR AMUSEMENT DEVICE” filed on Nov. 7, 2024 with the China Patent Office, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD The present disclosure relates to the technical field of smart homes, and specifically, to a lighting control system and a method for amusement device. BACKGROUND ART With the development of Internet of Things (IoT) technology, applications in fields such as smart homes and smart buildings are becoming increasingly widespread. Lighting control is one of the important application scenarios, and the traditional lighting control systems for amusement device typically rely on local hardware devices and preset programs, which lack flexibility and intelligence. This leads to poor player experience. SUMMARY The objective of the present disclosure is to provide a lighting control system and a method for amusement device to achieve efficient, flexible, and intelligent lighting control, thereby improving the player experience of amusement device. In a first aspect, the present disclosure provides a lighting control system for amusement device, including a cloud server, an Internet of Things module of the amusement device, and a user terminal. The Internet of Things module includes a smart lighting device and a gateway device which are paired to connect, wherein the gateway device and the user terminal are both communicatively connected to the cloud server. The user terminal is configured to send lighting control commands to the cloud server. The cloud server is configured to receive the lighting control commands and issue a corresponding first lighting adjustment strategy to the gateway device. The smart lighting device is configured to acquire the first lighting adjustment strategy forwarded by the gateway device and perform lighting adjustment of the amusement device based on the first lighting adjustment strategy. The gateway device is further configured to upload real-time environment data of the amusement device to the cloud server. The cloud server is further configured to receive the real-time environment data, generate a second lighting adjustment strategy matching user habits according to the real-time environment data and a trained lighting adjustment model, and send the second lighting adjustment strategy to the gateway device, wherein the lighting adjustment model is trained based on historical environment data and historical user usage data, and the historical user usage data includes offline adjustment data of the smart lighting device uploaded by the gateway device and remote adjustment data corresponding to historical lighting control commands sent by the user terminal; and the smart lighting device is further configured to acquire the second lighting adjustment strategy forwarded by the gateway device and perform lighting adjustment of the amusement device based on the second lighting adjustment strategy. Further, the cloud server is also configured to perform data preprocessing and feature extraction on the real-time environment data to obtain current time features and current environment features, input the current time features and the current environment features into the lighting adjustment model to obtain a predicted lighting adjustment strategy output by the lighting adjustment model, and determine the second lighting adjustment strategy based on the predicted lighting adjustment strategy. The data preprocessing includes data cleaning and data standardization. The lighting adjustment model uses supervised learning algorithms to predict user-preferred lighting settings, unsupervised learning algorithms to identify user usage patterns, and time series analysis to predict user usage times. Further, the cloud server is further configured to optimize the lighting usage time and the lighting brightness in the predicted lighting adjustment strategy based on preset energy consumption setting parameters to obtain the second lighting adjustment strategy. Further, the cloud server is further configured to periodically collect historical environment data and historical user usage data and update the lighting adjustment model based on the historical environment data and historical user usage data. The historical user usage data includes one or more of switch-on/off times, lighting brightness adjustment records, lighting color adjustment records, scene mode selection records, and user manual adjustment frequencies. Further, the lighting control commands include one or more of lighting scene information, lighting brightness information, and lighting color information, wherein the lighting scene information includes a reading mode, a leisure mode, or a sleep mode. Further, the user terminal is further configured to send device management commands to the cloud server. The cloud server