Amusement ride light control system and method

Abstract

The application provides a kind of amusement equipment light control system and method, it is related to smart home technical field, the amusement equipment light control system includes cloud server, the internet of things module of amusement equipment and user terminal, internet of things module includes the smart lamp and gateway equipment of matching connection, gateway equipment and user terminal are all connected with cloud server communication;Through the combination of cloud technology and internet of things hardware, the amusement equipment light control system can realize remote and local control to smart lamp, and can realize intelligent linkage with the sense of player, provide the intelligent light adjustment experience that is matched with the use habit of user, realize personalized light adjustment;User can adjust the light setting of amusement equipment at any time and anywhere according to actual demand, improve the convenience and flexibility of amusement equipment use.Therefore, the application realizes efficient, flexible and intelligent light control, improves the player experience of amusement equipment.

Description

Technical Field

[0001] The present invention relates to the field of smart home technology, and in particular to a lighting control system and method for amusement equipment. Background Art

[0002] With the development of the Internet of Things (IoT), its applications in smart homes, smart buildings, and other fields are becoming increasingly widespread. Lighting control is a key application scenario. Traditional amusement ride lighting control systems typically rely on local hardware devices and preset programs, lacking flexibility and intelligence, resulting in a poor player experience. Summary of the Invention

[0003] The object of the present invention is to provide a lighting control system and method for amusement equipment, so as to achieve efficient, flexible and intelligent lighting control and improve the player experience of the amusement equipment.

[0004] In a first aspect, the present invention provides an amusement equipment lighting control system, comprising a cloud server, an Internet of Things module for the amusement equipment, and a user terminal, wherein the Internet of Things module comprises paired smart lamps and a gateway device, and both the gateway device and the user terminal are communicatively connected to the cloud server;

[0005] The user terminal is used to send a lighting control command to the cloud server; the cloud server is used to receive the lighting control command and send a corresponding first lighting adjustment strategy to the gateway device; the smart lamp is used to obtain the first lighting adjustment strategy forwarded by the gateway device and adjust the lighting of the amusement device based on the first lighting adjustment strategy;

[0006] The gateway device is also used to upload real-time environmental data of the amusement equipment to the cloud server; the cloud server is also used to receive the real-time environmental data, and generate a second lighting adjustment strategy that matches the user's usage habits based on the real-time environmental data and the 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 environmental data and historical user usage data, and the historical user usage data includes offline adjustment data of the smart lamps uploaded by the gateway device and remote adjustment data corresponding to historical lighting control commands sent by the user terminal; the smart lamps are also used to obtain the second lighting adjustment strategy forwarded by the gateway device, and perform lighting adjustment of the amusement equipment based on the second lighting adjustment strategy.

[0007] Furthermore, the cloud server is also used to perform data preprocessing and feature extraction on the real-time environmental data to obtain current time features and current environmental features, input the current time features and current environmental features into the lighting adjustment model, obtain the 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, data preprocessing includes data cleaning and data standardization; the lighting adjustment model uses a supervised learning algorithm to predict the user's preferred lighting settings, uses an unsupervised learning algorithm to identify the user's usage pattern, and uses time series analysis to predict the user's usage time.

[0008] Furthermore, the cloud server is also used to optimize the light usage time and light brightness in the predicted light adjustment strategy based on the preset energy consumption setting parameters to obtain a second light adjustment strategy.

[0009] Furthermore, the cloud server is also used to regularly collect historical environmental data and historical user usage data, and update the lighting adjustment model based on the historical environmental data and historical user usage data; wherein the historical user usage data includes one or more of the light switching time, light brightness adjustment records, light color adjustment records, scene mode selection records and user manual adjustment frequency.

[0010] Furthermore, the lighting control command includes one or more of lighting scene information, lighting brightness information, and lighting color information, and the lighting scene information includes a reading mode, a leisure mode, or a sleep mode.

[0011] Furthermore, the user terminal is also used to send device management commands to the cloud server; the cloud server is also used to receive device management commands and perform target management of smart lamps based on the device management commands; wherein the target management includes one or more of device registration, status monitoring and fault diagnosis.

[0012] Furthermore, the smart lamps exchange data with the gateway device through a preset communication protocol, and the gateway device communicates with the cloud server through Wi-Fi or a wired network; wherein the communication protocol includes Wi-Fi or Bluetooth.

[0013] In a second aspect, the present invention further provides a method for controlling lighting of an amusement device, which is applied to the amusement device lighting control system of the first aspect; the method for controlling lighting of an amusement device comprises:

[0014] The user terminal sends lighting control commands to the cloud server;

[0015] The cloud server receives the lighting control command and sends the corresponding first lighting adjustment strategy to the gateway device;

[0016] The smart lamp obtains the first lighting adjustment strategy forwarded by the gateway device, and adjusts the lighting of the amusement equipment based on the first lighting adjustment strategy;

[0017] The gateway device uploads the real-time environmental data of the amusement equipment to the cloud server;

[0018] The cloud server receives real-time environmental data, generates a second lighting adjustment strategy that matches the user's usage habits based on the real-time environmental data and the trained lighting adjustment model, and sends the second lighting adjustment strategy to the gateway device. The lighting adjustment model is trained based on historical environmental data and historical user usage data. The historical user usage data includes offline adjustment data for smart lamps uploaded by the gateway device and remote adjustment data corresponding to historical lighting control commands sent by the user terminal.

[0019] The smart lamp obtains the second lighting adjustment strategy forwarded by the gateway device, and adjusts the lighting of the amusement equipment based on the second lighting adjustment strategy.

[0020] Furthermore, based on the real-time environmental data and the trained lighting adjustment model, a second lighting adjustment strategy that matches the user's usage habits is generated, including:

[0021] Perform data preprocessing and feature extraction on real-time environmental data to obtain current time features and current environmental features; data preprocessing includes data cleaning and data standardization;

[0022] Input the current time characteristics and current environment characteristics into the lighting adjustment model to obtain the predicted lighting adjustment strategy output by the lighting adjustment model. The lighting adjustment model uses a supervised learning algorithm to predict the user's preferred lighting settings, an unsupervised learning algorithm to identify the user's usage patterns, and time series analysis to predict the user's usage time.

[0023] Based on the predicted lighting adjustment strategy, a second lighting adjustment strategy is determined.

[0024] Furthermore, based on the predicted lighting adjustment strategy, determining a second lighting adjustment strategy includes:

[0025] The light usage time and light brightness in the predicted light adjustment strategy are optimized based on the preset energy consumption setting parameters to obtain a second light adjustment strategy.

[0026] The amusement equipment lighting control system and method provided by the present invention include a cloud server, an Internet of Things (IoT) module for the amusement equipment, and a user terminal. The IoT module includes paired smart lamps and a gateway device, and both the gateway device and the user terminal are communicatively connected to the cloud server. The user terminal is configured to send a lighting control command to the cloud server. The cloud server is configured to receive the lighting control command and issue a corresponding first lighting adjustment policy to the gateway device. The smart lamp is configured to obtain the first lighting adjustment policy forwarded by the gateway device and adjust the lighting of the amusement equipment based on the first lighting adjustment policy. The gateway device is further configured to upload real-time environmental data of the amusement equipment to the cloud server. The cloud server is further configured to receive the real-time environmental data and, based on the real-time environmental data and a trained lighting adjustment model, generate a second lighting adjustment policy that matches the user's usage habits and send the second lighting adjustment policy to the gateway device. The lighting adjustment model is trained based on historical environmental data and historical user usage data. The historical user usage data includes offline adjustment data for the smart lamp uploaded by the gateway device and remote adjustment data corresponding to historical lighting control commands sent by the user terminal. The smart lamp is further configured to obtain the second lighting adjustment policy forwarded by the gateway device and adjust the lighting of the amusement equipment based on the second lighting adjustment policy.

[0027] By combining cloud technology with IoT hardware, this amusement equipment lighting control system not only enables remote and localized control of smart lighting fixtures, but also intelligently interacts with the player's senses, providing an intelligent lighting adjustment experience that matches the user's usage habits and enables personalized lighting adjustment. Users can adjust the lighting settings of the amusement equipment anytime and anywhere according to their actual needs, improving the convenience and flexibility of amusement equipment use. Therefore, the amusement equipment lighting control system and method provided by the present invention achieve efficient, flexible, and intelligent lighting control, improving the player experience of amusement equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0029] Figure 1 A schematic structural diagram of a lighting control system for an amusement device provided by an embodiment of the present invention;

[0030] Figure 2 A schematic diagram of the system architecture of an amusement equipment lighting control system provided by an embodiment of the present invention;

[0031] Figure 3 A schematic flow chart of a method for controlling lighting of an amusement device provided by an embodiment of the present invention;

[0032] Figure 4 A flowchart of another method for controlling lighting of an amusement device provided by an embodiment of the present invention.

[0033] Icons: 110-cloud server; 120-IoT module; 121-gateway device; 122-smart lamp; 130-user terminal. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] Existing lighting control systems currently have shortcomings in remote control, energy management, and system integration. For example, existing lighting control systems lack intelligent integration with the player's sensory system and are unable to provide personalized lighting adjustment solutions, resulting in a poor player experience. In response to this, embodiments of the present invention provide an amusement equipment lighting control system and method that utilizes network cloud technology and IoT hardware to perform data processing and device management through the cloud, enabling more efficient, flexible, and intelligent lighting control. This, to a certain extent, addresses existing issues such as insufficient intelligence, inconvenient remote control, and imperfect energy management.

[0036] The embodiment of the present invention provides a lighting control system for an amusement device, such as Figure 1 As shown, the amusement equipment lighting control system includes a cloud server 110, an IoT module 120 for the amusement equipment, and a user terminal 130. The IoT module 120 includes paired smart lamps 122 and a gateway device 121. Both the gateway device 121 and the user terminal 130 are in communication with the cloud server 110. The cloud server 110 is primarily responsible for data processing and command issuance; the IoT module 120 is primarily responsible for receiving and executing control commands; and the user terminal 130 is primarily responsible for sending control commands and receiving device status information.

[0037] The amusement equipment lighting control system can provide remote control functions for the amusement equipment: the user terminal 130 is used to send lighting control commands to the cloud server 110; the cloud server 110 is used to receive the lighting control commands and send the corresponding first lighting adjustment strategy to the gateway device 121; the smart lamp 122 is used to obtain the first lighting adjustment strategy forwarded by the gateway device 121, and adjust the lighting of the amusement equipment based on the first lighting adjustment strategy.

[0038] The cloud server 110 can convert the lighting control command from the user terminal 130 into a corresponding first lighting adjustment policy, thereby controlling the lighting adjustment of the smart lamp 122. Optionally, the lighting control command can include one or more of lighting scene information, lighting brightness information, and lighting color information. The lighting scene information can include reading mode, leisure mode, or sleep mode. This allows users to remotely control the lighting scene, lighting brightness, and lighting color of the amusement device.

[0039] The amusement equipment lighting control system can also provide an intelligent lighting adjustment experience: the gateway device 121 is also used to upload real-time environmental data of the amusement equipment to the cloud server 110; the cloud server 110 is also used to receive real-time environmental data, and generate a second lighting adjustment strategy that matches the user's usage habits based on the real-time environmental data and the trained lighting adjustment model, and send the second lighting adjustment strategy to the gateway device 121; wherein, the lighting adjustment model is trained based on historical environmental data and historical user usage data, and the historical user usage data includes offline adjustment data of the smart lamps uploaded by the gateway device 121 and remote adjustment data corresponding to historical lighting control commands sent by the user terminal 130; the smart lamps 122 are also used to obtain the second lighting adjustment strategy forwarded by the gateway device 121, and perform lighting adjustment of the amusement equipment based on the second lighting adjustment strategy.

[0040] The cloud server 110 can obtain historical environmental data and historical user usage data, and analyze user usage habits through machine learning algorithms to generate a lighting adjustment model, and use the lighting adjustment model in combination with real-time environmental data to automatically generate a lighting control strategy. For example, soft warm lights are automatically turned on at dusk, and the lights are dimmed when the ambient light is dark. Among them, the environmental data (historical environmental data / real-time environmental data) may include one or more of light intensity, temperature, humidity and air pressure, and the historical user usage data may include one or more of light switching time, light brightness adjustment records, light color adjustment records, scene mode selection records and user manual adjustment frequency. The above-mentioned offline adjustment data refers to the user's direct setting or adjustment of the corresponding adjustment data of the smart lamps on the amusement equipment. When training the lighting adjustment model, cross-validation can be used to evaluate the model performance, and the model can be optimized through hyperparameter tuning.

[0041] By combining cloud technology with IoT hardware, this amusement ride lighting control system enables both remote and localized control of smart lighting fixtures, while also intelligently interacting with players' senses. This system provides an intelligent lighting adjustment experience tailored to user habits, enabling personalized lighting adjustments. Users can adjust the ride's lighting settings anytime, anywhere, based on their actual needs, enhancing the ride's convenience and flexibility. Consequently, this amusement ride lighting control system achieves efficient, flexible, and intelligent lighting control, enhancing the player experience.

[0042] Optionally, the user terminal 130 may be a smart phone, a tablet computer, or other mobile devices.

[0043] Optionally, the smart lamp 122 can exchange data with the gateway device 121 via a preset communication protocol, and the gateway device 121 can communicate with the cloud server 110 via Wi-Fi or a wired network; wherein the communication protocol includes Wi-Fi or Bluetooth. The gateway device 121 can communicate with the cloud server 110 and the user terminal 130 via Wi-Fi or Bluetooth communication protocol.

[0044] In some possible embodiments, the cloud server 110 is further configured to perform data preprocessing and feature extraction on real-time environmental data to obtain current time features and current environmental features, input the current time features and current environmental features into a lighting adjustment model, obtain a predicted lighting adjustment strategy output by the lighting adjustment model, and determine a second lighting adjustment strategy based on the predicted lighting adjustment strategy; wherein, data preprocessing includes data cleaning and data standardization; the lighting adjustment model uses a supervised learning algorithm to predict the user's preferred lighting settings, uses an unsupervised learning algorithm to identify the user's usage patterns, and uses time series analysis to predict the user's usage time.

[0045] Specifically, data cleaning is used to remove outliers and noisy data, and data standardization is used to unify data of different dimensions to the same scale. During feature extraction, time features such as hours, days of the week, and months can be extracted from the timestamp; data such as light intensity, temperature, humidity, and air pressure can be combined into composite features as environmental features. Supervised learning algorithms can include random forests or gradient boosting trees; unsupervised learning algorithms can use K-means clustering algorithms; and time series analysis can use ARIMA (AutoRegressive Integrated Moving Average) models. By combining multiple algorithms such as supervised learning algorithms, unsupervised learning algorithms, and time series analysis, accurate predictions of lighting adjustment strategies can be achieved.

[0046] In a possible implementation, the predicted lighting adjustment strategy may be directly used as the second lighting adjustment strategy.

[0047] In another possible implementation, the predicted lighting adjustment strategy can be optimized based on the user's energy consumption requirements to obtain a second lighting adjustment strategy. Based on this, the aforementioned amusement ride lighting control system also has an energy consumption management function: the cloud server 110 is further configured to optimize the light usage time and light brightness in the predicted lighting adjustment strategy based on preset energy consumption setting parameters to obtain the second lighting adjustment strategy. The energy consumption setting parameters are user-preset parameters, such as those generated by the user selecting whether to enable energy-saving mode. By optimizing light usage time and light brightness, energy consumption can be reduced, achieving energy savings.

[0048] Optionally, the cloud server 110 is further configured to regularly collect historical environmental data and historical user usage data, and to update the lighting adjustment model based on the historical environmental data and historical user usage data. The historical user usage data includes one or more of the following: light on / off times, light brightness adjustment records, light color adjustment records, scene mode selection records, and user manual adjustment frequency. By regularly updating the lighting adjustment model, changes in user preferences for amusement device lighting can be promptly identified, further enhancing the player experience of the amusement device.

[0049] Optionally, the user terminal 130 is further configured to send device management commands to the cloud server 110. The cloud server 110 is further configured to receive the device management commands and perform targeted management of the smart lighting based on the device management commands. Target management includes one or more of device registration, status monitoring, and fault diagnosis. In this way, the cloud server 110 can manage the amusement equipment based on user operations, including device registration, status monitoring, and fault diagnosis. The user terminal 130 can obtain device status information from the cloud server 110, such as device registration information, status monitoring information, and fault diagnosis information.

[0050] In one possible implementation, Figure 2As shown, gateway device 121 can be a local data acquisition terminal switchboard. This local data acquisition terminal switchboard can aggregate environmental data collected by various environmental sensors and upload it to cloud server 110. Environmental sensors can include ambient light sensors, temperature and humidity sensors, and air pressure sensors. The aforementioned smart lighting fixture 122 can include multiple data execution extensions, such as data execution extension 1 and data execution extension 2. The lighting adjustment policy issued by cloud server 110 can include sub-policies corresponding to each data execution extension. The local data acquisition terminal switchboard can obtain the lighting adjustment policy issued by cloud server 110 and issue each sub-policy to the corresponding data execution extension to achieve an intelligent lighting adjustment experience. Each data execution extension can implement functions such as light brightness control, light style control, machine parameter control, and historical data query. The cloud server 110 can issue lighting adjustment policies to control the light brightness of each data execution extension, thereby achieving energy consumption management.

[0051] For ease of understanding, the above-mentioned amusement equipment lighting control system is introduced in detail below.

[0052] The above-mentioned amusement equipment lighting control system mainly includes the following parts:

[0053] 1. Cloud Server:

[0054] (1) Responsible for the storage, processing and analysis of data, as well as the issuance of user control commands.

[0055] (2) The cloud server communicates with the user control terminal (i.e., user terminal, such as a smartphone, tablet computer, etc.) through an open API interface.

[0056] (3) Using big data analysis technology, the cloud server can recommend intelligent lighting adjustment strategies based on user usage habits and environmental data.

[0057] 2. IoT hardware module (i.e. IoT module):

[0058] (1) Includes smart lamps and gateway devices connected to cloud servers.

[0059] (2) Smart lamps exchange data with gateway devices through communication protocols such as Wi-Fi or Bluetooth.

[0060] (3) The gateway device is responsible for receiving control commands from the cloud server and forwarding them to the corresponding smart lamps.

[0061] 3. User control terminal module:

[0062] (1) Users can remotely control the smart lights of amusement equipment through an application (i.e., APP) installed on a smartphone or other mobile device.

[0063] (2) The APP communicates with the cloud server, and the user's control commands are forwarded to the IoT hardware module through the cloud server to realize the control of the lights.

[0064] The function implementation of the above-mentioned amusement equipment lighting control system may include the following steps:

[0065] Step 1: System initialization

[0066] The user downloads and installs the APP on the user terminal, registers an account and logs in. Scan the QR code of the gateway device or enter the device identification code through the APP to bind the gateway device to the user account.

[0067] Step 2: Connect smart lamps to the gateway device

[0068] Users follow the app's instructions to pair the smart lamps with the gateway device. The smart lamps establish a communication connection with the gateway device using a specified communication protocol.

[0069] Step 3: Cloud Configuration and Management

[0070] The gateway device connects to the internet via Wi-Fi or a wired network, establishing a stable communication link with the cloud server. The cloud server manages the amusement equipment based on user operations, including registration, status monitoring, and fault diagnosis.

[0071] Step 4: Lighting control and management

[0072] Users can use the app to select lighting scenes (such as reading mode, leisure mode, or sleep mode) or set the lighting brightness and color. The app sends the user's control commands to the cloud server, which performs the corresponding logical processing and sends the control commands to the corresponding gateway device, which ultimately forwards the commands to the smart lamp for execution.

[0073] Step 5: Intelligent Adjustment

[0074] The cloud server regularly collects user usage data and environmental sensor data (such as light intensity, temperature, humidity, and time information), analyzes user usage habits through machine learning algorithms, and automatically adjusts the lighting control strategy. For example, it automatically turns on soft warm lights at dusk and dims the lights of amusement equipment when the ambient light is low.

[0075] Through this solution, the amusement ride lighting control system enables remote and local control of smart lamps, providing a more intelligent lighting adjustment experience. Users can adjust lighting settings anytime and anywhere according to their needs, improving convenience and flexibility. Furthermore, cloud servers can perform big data analysis to provide personalized lighting control strategies, enhancing the user experience. Furthermore, this amusement ride lighting control system also features energy management, reducing energy consumption by optimizing lighting usage time and brightness.

[0076] In summary, the amusement equipment lighting control system provided by the embodiment of the present invention realizes intelligent control of amusement equipment lighting by combining cloud technology with Internet of Things hardware, which not only improves the user experience, but also has efficient energy consumption management functions, and has broad application prospects and market value.

[0077] The embodiment of the present invention also provides a method for controlling the lighting of an amusement device, which is applied to the above-mentioned amusement device lighting control system. The method for controlling the lighting of an amusement device can realize the remote control function of the amusement device, see Figure 3 The flowchart of a method for controlling lighting of an amusement device is shown in FIG. 1 , and the method for controlling lighting of an amusement device includes:

[0078] In step S310, the user terminal sends a lighting control command to the cloud server.

[0079] In step S320 , the cloud server receives the lighting control command and sends a corresponding first lighting adjustment strategy to the gateway device.

[0080] In step S330, the smart lamp obtains the first lighting adjustment strategy forwarded by the gateway device, and adjusts the lighting of the amusement equipment based on the first lighting adjustment strategy.

[0081] The above-mentioned amusement equipment lighting control method can also realize intelligent lighting adjustment experience, see Figure 4 FIG. 1 is a flow chart of another method for controlling lighting of an amusement device, wherein the method for controlling lighting of an amusement device comprises:

[0082] In step S410 , the gateway device uploads the real-time environmental data of the amusement device to the cloud server.

[0083] In step S420, the cloud server receives the real-time environmental data, generates a second lighting adjustment strategy that matches the user's usage habits based on the real-time environmental data and the trained lighting adjustment model, and sends the second lighting adjustment strategy to the gateway device.

[0084] The light adjustment model is trained based on historical environment data and historical user use data, and the historical user use data includes offline adjustment data of the smart lamp uploaded by the gateway device and remote adjustment data corresponding to the historical light control command sent by the user terminal.

[0085] In some possible embodiments, the step S420 can include: performing data preprocessing and feature extraction on the real-time environment data to obtain current time features and current environment features; the data preprocessing includes data cleaning and data standardization; inputting the current time features and the current environment features into the light adjustment model to obtain a predicted light adjustment strategy output by the light adjustment model; the light adjustment model uses a supervised learning algorithm to predict a light setting preferred by the user, uses an unsupervised learning algorithm to identify a use mode of the user, and uses time series analysis to predict a use time of the user; and determining a second light adjustment strategy based on the predicted light adjustment strategy.

[0086] In a possible implementation, the predicted light adjustment strategy can be optimized based on the energy consumption demand of the user to obtain the second light adjustment strategy. Based on this, the light use time and the light brightness in the predicted light adjustment strategy can be optimized based on preset energy consumption setting parameters to obtain the second light adjustment strategy.

[0087] The step S430 includes: acquiring, by the smart lamp, the second light adjustment strategy forwarded by the gateway device, and adjusting the light of the amusement device based on the second light adjustment strategy.

[0088] In this way, by combining the cloud technology and the Internet of Things hardware, the amusement device light control method can realize remote and localized control of the smart lamp, and can also realize intelligent linkage with the player's senses, provide an intelligent light adjustment experience that matches the user's use habits, and realize personalized light adjustment; the user can adjust the light setting of the amusement device at any time and anywhere according to actual needs, and improve the convenience and flexibility of the use of the amusement device. Therefore, the amusement device light control method realizes efficient, flexible and intelligent light control, and improves the player experience of the amusement device.

[0089] The amusement device light control method provided in this embodiment has the same implementation principle and technical effects as the amusement device light control system embodiments described above. For brevity, the part of the amusement device light control method embodiments not mentioned can refer to the corresponding content in the amusement device light control system embodiments described above.

[0090] The term "and / or", used in the context of the present application, should not be interpreted as limited to a logical "both" or "at least one of operation. It should be understood that the term "and / or" as used in the context of this application encompasses both the logical "both" and "at least one of operations. For example, the expression "A and / or B" can mean A alone, B alone, or A and B together. Similarly, the expression "at least one of A and B" can mean A alone, B alone, or A and B together.

[0091] In all the examples shown and described herein, any specific numerical values should be interpreted as merely exemplary and not as a limitation, and thus other examples of the exemplary embodiments can have different values.

[0092] It should be noted that similar reference numerals and characters refer to similar items throughout the drawings, and once an item is defined in one drawing, it is not necessary for it to be further defined and explained in subsequent drawings.

[0093] In addition, in the description of the embodiments of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connection", and "connecting" should be understood as broad terms, for example, can be fixed connection, can be detachable connection, or integral connection; can be mechanical connection, can be electrical connection; can be direct connection, can be indirect connection through an intermediate medium, and can be internal communication of two elements. For those skilled in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0094] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", "third" are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent substitutions for part or all of the technical features; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A lighting control system for an amusement ride, characterized in that: It includes a cloud server, an Internet of Things module for amusement equipment, and a user terminal. The Internet of Things module includes a paired smart lamp and a gateway device. Both the gateway device and the user terminal are in communication with the cloud server. The user terminal is used to send a lighting control command to the cloud server; The cloud server is used to receive the lighting control command and send the corresponding first lighting adjustment strategy to the gateway device; the smart lamp is used to obtain the first lighting adjustment strategy forwarded by the gateway device and adjust the lighting of the amusement device based on the first lighting adjustment strategy; The gateway device is further configured to upload real-time environmental data of the amusement device to the cloud server; the cloud server is further configured to receive the real-time environmental data, generate a second lighting adjustment strategy that matches the user's usage habits based on the real-time environmental data and the 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 environmental data and historical user usage data, and the historical user usage data includes offline adjustment data of the smart lamp uploaded by the gateway device and remote adjustment data corresponding to historical lighting control commands sent by the user terminal; the smart lamp is further configured to obtain 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; The cloud server is further configured to perform data preprocessing and feature extraction on the real-time environmental data to obtain current time features and current environmental features, input the current time features and current environmental features into the light adjustment model to obtain a predicted light adjustment strategy output by the light adjustment model, and determine the second light adjustment strategy based on the predicted light adjustment strategy; wherein the data preprocessing includes data cleaning and data standardization; the light adjustment model uses a supervised learning algorithm to predict the user's preferred light settings, uses an unsupervised learning algorithm to identify the user's usage patterns, and uses time series analysis to predict the user's usage time.

2. The amusement equipment lighting control system according to claim 1, characterized in that: The cloud server is further configured to optimize the light usage time and light brightness in the predicted light adjustment strategy based on preset energy consumption setting parameters to obtain the second light adjustment strategy.

3. The amusement equipment lighting control system according to claim 1, characterized in that: The cloud server is also used to regularly collect the historical environmental data and the historical user usage data, and update the lighting adjustment model based on the historical environmental data and the historical user usage data; wherein the historical user usage data includes one or more of light switching time, light brightness adjustment records, light color adjustment records, scene mode selection records and user manual adjustment frequency.

4. The amusement equipment lighting control system according to claim 1, characterized in that: The light control command includes one or more of light scene information, light brightness information, and light color information, and the light scene information includes a reading mode, a leisure mode, or a sleep mode.

5. The amusement equipment lighting control system according to claim 1, characterized in that: The user terminal is further used to send device management commands to the cloud server; the cloud server is further used to receive the device management commands and perform target management on the smart lamp based on the device management commands; wherein the target management includes one or more of device registration, status monitoring and fault diagnosis.

6. The amusement equipment lighting control system according to any one of claims 1 to 5, characterized in that: The smart lamp exchanges data with the gateway device via a preset communication protocol, and the gateway device is connected to the cloud server via Wi-Fi or a wired network; wherein the communication protocol includes Wi-Fi or Bluetooth.

7. A method for controlling lighting of an amusement device, characterized in that: An amusement equipment lighting control system applied to any one of claims 1-6; The amusement equipment lighting control method includes: The user terminal sends a lighting control command to the cloud server; The cloud server receives the lighting control command and sends a corresponding first lighting adjustment strategy to the gateway device; The smart lamp obtains the first light adjustment strategy forwarded by the gateway device, and adjusts the light of the amusement equipment based on the first light adjustment strategy; The gateway device uploads the real-time environmental data of the amusement device to the cloud server; The cloud server receives the real-time environmental data, generates a second lighting adjustment strategy that matches the user's usage habits based on the real-time environmental data and the trained lighting adjustment model, and sends the second lighting adjustment strategy to the gateway device; wherein the lighting adjustment model is trained based on historical environmental data and historical user usage data, and the historical user usage data includes offline adjustment data of the smart lamp uploaded by the gateway device and remote adjustment data corresponding to historical lighting control commands sent by the user terminal; The smart lamp obtains the second light adjustment strategy forwarded by the gateway device, and performs light adjustment of the amusement equipment based on the second light adjustment strategy.

8. The amusement equipment lighting control method according to claim 7, characterized in that: Generating a second lighting adjustment strategy that matches the user's usage habits based on the real-time environmental data and the trained lighting adjustment model includes: Performing data preprocessing and feature extraction on the real-time environmental data to obtain current time features and current environmental features; wherein the data preprocessing includes data cleaning and data standardization; Inputting the current time characteristics and the current environment characteristics into the light adjustment model to obtain a predicted light adjustment strategy output by the light adjustment model; wherein the light adjustment model uses a supervised learning algorithm to predict the user's preferred light settings, uses an unsupervised learning algorithm to identify the user's usage pattern, and uses time series analysis to predict the user's usage time; Based on the predicted light adjustment strategy, the second light adjustment strategy is determined.

9. The amusement equipment lighting control method according to claim 8, characterized in that: The determining the second lighting adjustment strategy based on the predicted lighting adjustment strategy includes: The light usage time and light brightness in the predicted light adjustment strategy are optimized based on the preset energy consumption setting parameters to obtain the second light adjustment strategy.

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