Constant-voltage dimming power supply networking control method and system based on Internet of Things

Abstract

The invention provides a constant-voltage dimming power supply networking control method and system based on the Internet of Things, and the method comprises the steps: a cloud server obtains the historical working data, environment data and power supply attribute data of all dimming power supplies, and configures a corresponding Internet of Things network based on the data; all the dimming power supplies are connected to the network and are divided into different groups, and each group is provided with a corresponding controller; the cloud server generates a power supply use scene model of each group by using historical data and grouping information, and formulates a group control strategy; and finally, sending a command by the group controller according to the control strategy, and controlling the working states of the plurality of dimming power supplies. According to the scheme, through data analysis and intelligent control, the use efficiency and the adjustment accuracy of the dimming power supply are improved, and the comfort degree and the satisfaction degree of a user are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of power management, and in particular to a constant voltage dimming power supply networking control method and system based on the Internet of Things. Background Art

[0002] Constant voltage dimming power supply is a type of power supply used for LED lighting. Its main feature is that it can provide a stable output voltage. Constant voltage dimming power supply controls the brightness of the LED by adjusting the output voltage. Users can adjust the voltage through the dimmer to achieve different brightness levels. This power supply is suitable for occasions where multiple LED lamps need to be connected, because it can ensure that each lamp can get the same voltage.

[0003] The existing constant voltage dimming power supply control method is not intelligent enough, has low efficiency and poor accuracy. Summary of the invention

[0004] Based on the above problems, the present invention proposes a constant voltage dimming power supply networking control method and system based on the Internet of Things. Through data analysis and intelligent control, not only the utilization efficiency and adjustment accuracy of the dimming power supply are improved, but also the user's comfort and satisfaction are enhanced.

[0005] In view of this, one aspect of the present invention proposes a constant voltage dimming power supply networking control method based on the Internet of Things, comprising: The cloud server obtains the historical working data, historical working environment data and power attribute data of all dimming power supplies; The cloud server configures a first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data; Connecting all the dimming power supplies to the first Internet of Things network; Divide all the dimming power supplies into different groups, and configure a corresponding group controller for each group; The cloud server generates a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data; The cloud server generates a group control strategy corresponding to each group, and sends the group control strategy to the group controller; The group controller sends a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies.

[0006] Optionally, the step of configuring, by the cloud server, a first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data comprises: The cloud server analyzes historical working data, identifies the usage pattern and demand characteristics of the dimming power supply, and obtains a first analysis result; The cloud server analyzes historical working environment data, evaluates the impact of environmental factors on dimming power supply performance, and obtains a second analysis result; The cloud server determines the technical specifications and compatibility requirements of each dimming power supply according to the power supply attribute data, and obtains the third analysis result; Based on the first analysis result, the second analysis result and the third analysis result, the cloud server designs the topology structure of the first IoT network, and determines the configuration and connection method of the IoT server, the IoT gateway, the IoT node and the IoT smart terminal; The cloud server generates a network configuration file and transmits the network configuration file to the IoT server; The IoT server automatically configures the IoT gateway and nodes according to the configuration file, establishes a communication connection with the dimming power supply, and ensures the real-time transmission of data and the effective execution of control instructions.

[0007] Optionally, the step of dividing all the dimming power supplies into different groups and configuring a corresponding group controller for each group includes: The cloud server analyzes the usage pattern of the dimming power supply based on historical working data and historical working environment data, and identifies the dimming power supply with similar working characteristics and environmental conditions; According to the above analysis and identification results, the dimming power supplies are divided into multiple groups, each of which contains dimming power supplies with similar characteristics, so as to facilitate centralized management and control; Each group is assigned a group controller, which is responsible for managing the operation of all dimming power supplies in the group, including receiving control instructions, sending status feedback, and executing dimming strategies; Configure the corresponding communication protocol and control logic in the group controller to ensure that it can effectively communicate and coordinate with the dimming power supply in the group; The cloud server uploads each group’s configuration and control strategy to the corresponding group controller, ensuring it has all the information it needs to perform its tasks; The group controller monitors the status of the dimming power supply in the group in real time according to the received control strategy and instructions, and adjusts its working mode as needed.

[0008] Optionally, the cloud server generates a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data, including: The cloud server identifies the characteristics and requirements of each group based on the first analysis result, the second analysis result and the third analysis result respectively obtained from the historical working data, the historical working environment data and the power source attribute data, and determines basic parameters of a usage scenario model suitable for the group in combination with the grouping data; The cloud server generates a power usage scenario model for each group based on basic parameters. The power usage scenario model includes: the working status of each power source, including the on / off status, dimming level, and power output; the status settings of other devices, including the status of sensors and the working status of environmental conditioning devices; preset dimming strategies and control logic, including dimming strategies that are automatically adjusted according to environmental changes and user needs, timing control logic, and abnormal situation processing logic; The cloud server stores the generated power usage scenario model in the database for real-time access and subsequent optimization and adjustment; The cloud server regularly updates the power usage scenario model and adjusts the state settings and control logic in the model based on real-time data and user feedback.

[0009] Optionally, the cloud server generates a group control policy corresponding to each group, and sends the group control policy to the group controller, comprising: The cloud server obtains current working environment data of all the dimming power supplies; Establishing a digital twin model of the working area of ​​the dimming power supply according to the current working environment data and the power supply attribute data; The group control strategy is determined according to the working area digital twin model and the power usage scenario model, and the group control strategy is sent to the group controller.

[0010] Optionally, the step of the group controller sending a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies includes: The group controller receives the group control strategy from the cloud server, including the on / off status of the dimming power supply, the dimming level and other related control instructions; The group controller parses the group control strategy and identifies the group commands and / or scene commands that need to be executed; The group controller generates a specific first control instruction according to the analysis result, including: sending a unified switch command to all dimming power supplies; and / or sending a personalized dimming level command to each dimming power supply to meet the lighting needs of different areas; and / or sending a scene command to achieve a preset lighting scene; The group controller sends the generated first control instruction to each member dimming power supply in the group; Each member dimming power supply receives the control command, adjusts its working state according to the command, and performs corresponding switching and dimming operations; The group controller monitors the feedback status of the dimming power supply, confirms the success or failure of the command execution, and makes necessary adjustments or resends the command based on the feedback information.

[0011] Optionally, the cloud server analyzes historical working data, identifies usage patterns and demand characteristics of dimming power supplies, and obtains a first analysis result, comprising: The cloud server receives and stores historical working data of the dimming power supply; The cloud server preprocesses the historical working data, cleans the data to remove outliers and noise, and obtains the first historical working data; The cloud server analyzes the first historical working data, identifies the peak usage time when the usage frequency of the dimming power source exceeds the preset first usage frequency, and determines the usage frequency and load condition of the dimming power source in different time periods; The cloud server calculates the communication frequency according to the first historical working data, analyzes the communication activities between the dimming power supply and the control system, and identifies a high-frequency communication period in which the communication frequency exceeds the preset first communication frequency; The cloud server analyzes the first historical working data to evaluate data traffic, and monitors data transmission volumes in different time periods to identify a high traffic period in which the traffic value exceeds a preset first traffic value; The cloud server analyzes the peak load according to the first historical working data, determines the maximum load of the dimming power supply during use, and identifies the load change trend; The cloud server identifies critical periods and determines the time periods that have the greatest impact on dimming power supply performance, based on peak usage times and load variations; The cloud server stores the above analysis result as the first analysis result in the database.

[0012] Optionally, the cloud server analyzes historical working environment data, evaluates the impact of environmental factors on dimming power supply performance, and obtains a second analysis result, including: The cloud server receives and stores historical working environment data of the dimming power supply; The cloud server preprocesses the historical working environment data, cleans the data to remove outliers and noise, and obtains the first historical working environment data; The cloud server analyzes the building structure information based on the first historical working environment data and evaluates its impact on the dimming power signal transmission; The cloud server identifies signal transmission obstacles based on the first historical working environment data and analyzes the impact of possible obstacles in the environment on signal strength and stability; The cloud server evaluates the electromagnetic interference source based on the first historical working environment data and identifies the potential interference of surrounding equipment on the dimming power supply performance; The cloud server analyzes the device distribution based on the first historical working environment data, and evaluates the impact of the relative positions of different devices on the dimming power supply performance, including the interference and collaborative working conditions between the devices; The cloud server monitors the lighting conditions based on the first historical working environment data, analyzes the impact of natural lighting changes on dimming power supply regulation, and identifies the best dimming strategy; The cloud server analyzes temperature changes based on the first historical working environment data, evaluates the impact of ambient temperature on dimming power supply performance and energy consumption, and identifies key periods of temperature changes; The cloud server analyzes the personnel activity patterns based on the first historical work environment data, evaluates the impact of personnel flow on the demand for dimming power usage, and identifies peak activity periods; The cloud server stores the above analysis result as the second analysis result in the database.

[0013] Optionally, the cloud server determines the technical specifications and compatibility requirements of each dimming power supply according to the power supply attribute data to obtain a third analysis result, including: The cloud server receives and stores the attribute data of the dimming power supply; The cloud server preprocesses the received power attribute data, cleans the data to remove abnormal values ​​and noise, and obtains first power attribute data; The cloud server analyzes the power source attribute data according to the first power source attribute data, and identifies the technical specifications of each dimming power source; The cloud server evaluates the network load based on the first power source attribute data, analyzes the network bandwidth requirements of the dimming power source in different usage scenarios, and ensures its stability in actual applications; The cloud server generates compatibility requirements for each dimming power supply based on the above analysis results; The cloud server stores the technical specifications and compatibility requirements of each dimming power supply as the third analysis result in the database.

[0014] Another aspect of the present invention provides a constant voltage dimming power supply networking control system based on the Internet of Things, which is used to execute a constant voltage dimming power supply networking control method based on the Internet of Things, including: a cloud server, a first Internet of Things network and a dimming light source; The cloud server is configured as follows: Acquire historical working data, historical working environment data and power source attribute data of all the dimming power sources; Configure a first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data; Connecting all the dimming power supplies to the first Internet of Things network; Divide all the dimming power supplies into different groups, and configure a corresponding group controller for each group; Generate a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data; Generate a group control strategy corresponding to each group, and send the group control strategy to the group controller; The group controller is configured to send a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies.

[0015] By adopting the technical solution of the present invention, the constant voltage dimming power supply networking control method based on the Internet of Things includes: the cloud server obtains the historical working data, historical working environment data and power supply attribute data of all dimming power supplies; the cloud server configures the first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data; all the dimming power supplies are connected to the first Internet of Things network; all the dimming power supplies are divided into different groups, and a corresponding group controller is configured for each group; the cloud server generates a power supply usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power supply attribute data and the grouping data; the cloud server generates a group control strategy corresponding to each group, and sends the group control strategy to the group controller; the group controller sends group commands and / or scene commands according to the group control strategy to control multiple dimming power supplies. According to the solution of the present invention, by analyzing historical data, the cloud server can intelligently configure the network and control strategy of the dimming power supply, improve the automation level of the system, and reduce manual intervention; according to the power supply usage scenario model and control strategy, the dimming power supply can be optimized and adjusted under different environments and usage requirements, thereby effectively reducing energy consumption and improving energy utilization efficiency; the dimming power supply is divided into different groups and a controller is configured for each group, so that the system can flexibly adjust the lighting of different areas according to actual needs to meet the personalized needs of users; the group controller sends commands according to the control strategy generated by the cloud server, which can realize real-time control of the dimming power supply and quickly respond to environmental changes and user needs; through the analysis of historical work data and environmental data, the cloud server can provide data support for future lighting needs and help decision makers formulate more scientific management strategies; by accurately controlling the lighting scene, it can provide users with a more comfortable and suitable environment and improve the overall user experience; based on the architecture design of the Internet of Things, the system can easily expand and integrate new dimming power supplies or control devices to adapt to future technological developments and demand changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a constant voltage dimming power supply networking control method based on the Internet of Things provided by an embodiment of the present invention; Figure 2 It is a schematic block diagram of a constant voltage dimming power supply networking control system based on the Internet of Things provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0019] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0020] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0021] Refer to the following Figure 1 to Figure 2 To describe a constant voltage dimming power supply networking control method and system based on the Internet of Things provided according to some embodiments of the present invention.

[0022] like Figure 1 As shown, an embodiment of the present invention provides a constant voltage dimming power supply networking control method based on the Internet of Things, including: The cloud server obtains the historical working data (including working demand data, working status data, working time data, etc.), historical working environment data (including natural environment data, building data, building ancillary equipment data, human activity data, etc.) and power source attribute data of all dimming power sources; In this step, the specific steps for the cloud server to obtain the historical working data of all dimming power supplies include: establishing a communication connection with each dimming power supply through the Internet of Things gateway to ensure the real-time and reliability of data transmission; integrating a data acquisition module in each dimming power supply to regularly record work demand data, work status data and working time data, and store these data in a local database; sending a data upload request containing complete information of historical working data to the cloud server through a preset time interval or event trigger mechanism; after receiving the data upload request, the cloud server verifies the integrity and validity of the data to ensure that the data has not been tampered with; storing the valid historical working data in the database of the cloud server and associating it with other data (such as historical working environment data and power supply attribute data); regularly sending data requests from the cloud server to the dimming power supply to obtain the latest working status and environment data to maintain the timeliness and accuracy of the data. The specific steps for the cloud server to obtain historical working environment data include: real-time monitoring of natural environment data through environmental sensors (such as temperature sensors, humidity sensors, light sensors, etc.), and transmitting the data to the cloud server; obtaining building data and building ancillary equipment data through the building management system (BMS), including equipment operating status, energy consumption data, etc.; collecting human activity data through the user behavior analysis module, recording the activity patterns and time distribution of personnel in the building; associating the collected environmental data with the working data of the dimming power supply to form a complete historical working environment data set. The specific implementation steps for the cloud server to obtain power attribute data include: embedding the definition of power attribute data in the firmware of the dimming power supply, including information such as rated power, working voltage range, dimming mode, etc.; regularly requesting power attribute data from the dimming power supply through the Internet of Things gateway, and uploading it to the cloud server; the cloud server stores the received power attribute data in the database, and associates it with historical working data and environmental data. Through this step, the cloud server can effectively integrate the historical working data, environmental data and power attribute data from different dimming power sources to form a comprehensive data view; the integrated data provides a basis for subsequent intelligent control and optimization, and can analyze user needs and environmental changes based on historical data, and automatically adjust the dimming strategy; through real-time monitoring and data feedback, the system can respond to environmental changes in a timely manner, optimize energy use, reduce energy consumption, and improve the overall efficiency of the system; users can access historical data through the cloud platform to understand the operation of the lighting system, so as to make more reasonable usage decisions.

[0023] The cloud server configures a first Internet of Things network (including an Internet of Things server, an Internet of Things gateway, an Internet of Things node, an Internet of Things smart terminal, etc.) corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data; Connecting all the dimming power supplies to the first Internet of Things network; In this step, the Internet of Things gateway in the first Internet of Things network broadcasts a network access request; the dimming power supply within the communication range of the Internet of Things gateway responds to the network access request and returns device identification information; the Internet of Things gateway reports the device identification information to the corresponding Internet of Things server in the first Internet of Things network; the Internet of Things server verifies the legitimacy of the device identification information according to a pre-stored device list; the Internet of Things server assigns a unique network address to the verified dimming power supply; the Internet of Things server establishes a mapping relationship between the device identification information and the network address; the Internet of Things server sends the network address to the corresponding dimming power supply; the Internet of Things server configures communication parameters according to the power attribute data of the dimming power supply; the communication parameters include: communication protocol type, data transmission rate, signal strength, sleep cycle, heartbeat interval; the Internet of Things server sends the communication parameters to the corresponding dimming power supply; the dimming power supply completes local configuration according to the communication parameters; the Internet of Things server sends a test instruction to the dimming power supply that has completed the configuration; the dimming power supply receives and executes the test instruction and returns the execution result; the Internet of Things server detects communication quality indicators, including: signal strength, response delay, packet loss rate; when the communication quality indicators meet the preset conditions, confirms that the dimming power supply is successfully connected; periodically detects the communication status of the dimming power supply; when communication abnormalities are detected, the Internet of Things server performs fault diagnosis; automatically adjusts network parameters or triggers fault alarms according to the diagnosis results; records the communication quality data of the dimming power supply for network optimization. Through the solution of this step, the device access success rate is high, which can improve the stability of network connection, reduce the communication failure rate, improve the system operation availability, shorten the device automatic discovery time, improve the efficiency of batch configuration, reduce the need for manual intervention, reduce the fault handling time, improve the accuracy of automatic fault diagnosis and the success rate of automatic parameter optimization, reduce operation and maintenance costs, extend the service life of equipment, increase the number of supported devices and network carrying capacity, and improve the control instruction throughput and data processing efficiency. Such a technical solution not only ensures the reliability and efficiency of dimming power access, but also lays a solid foundation for subsequent group control and scene applications.

[0024] Divide all the dimming power supplies into different groups (create device groups in the wireless gateway or controller, and allocate the corresponding dimming power supplies to the groups; the intra-group networking methods of each group can be different or the same), and configure a corresponding group controller for each group; The cloud server generates a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data (each scenario model includes status settings of multiple power supplies and other devices); The cloud server generates a group control strategy corresponding to each group, and sends the group control strategy to the group controller; The group controller sends a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies.

[0025] By adopting the technical solution of this embodiment and analyzing historical data, the cloud server can intelligently configure the network and control strategy of the dimming power supply, improve the automation level of the system, and reduce manual intervention; according to the power supply usage scenario model and control strategy, the dimming power supply can be optimized and adjusted under different environments and usage requirements, thereby effectively reducing energy consumption and improving energy utilization efficiency; the dimming power supply is divided into different groups and a controller is configured for each group, so that the system can flexibly adjust the lighting of different areas according to actual needs to meet the personalized needs of users; the group controller sends commands according to the control strategy generated by the cloud server, which can realize real-time control of the dimming power supply and quickly respond to environmental changes and user needs; through the analysis of historical work data and environmental data, the cloud server can provide data support for future lighting needs and help decision makers formulate more scientific management strategies; by precisely controlling the lighting scene, it can provide users with a more comfortable and suitable environment and improve the overall user experience; based on the architecture design of the Internet of Things, the system can easily expand and integrate new dimming power supplies or control devices to adapt to future technological developments and changes in demand.

[0026] In some possible implementations of the present invention, the step of configuring the cloud server with a first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data includes: The cloud server analyzes historical work data, identifies the usage pattern and demand characteristics of the dimming power supply (including peak usage time, communication frequency, data traffic, peak load, load change, critical time period, etc.), and obtains the first analysis result; The cloud server analyzes historical working environment data, evaluates the impact of environmental factors on dimming power supply performance (such as building structure, signal transmission obstacles, electromagnetic interference sources, equipment distribution, lighting conditions, temperature changes, and personnel activity patterns, etc.), and obtains the second analysis result; The cloud server determines the technical specifications and compatibility requirements (including network load, power limit, dimming mode and communication protocol, etc.) of each dimming power supply based on the power supply attribute data, and obtains the third analysis result; Based on the first analysis result, the second analysis result and the third analysis result, the cloud server designs the topology structure of the first IoT network, and determines the configuration and connection method of the IoT server, the IoT gateway, the IoT node and the IoT smart terminal; The cloud server generates a network configuration file (including the addresses of each component, communication protocols, data transmission methods, and other information) and transmits the network configuration file to the IoT server; The IoT server automatically configures the IoT gateway and nodes according to the configuration file, establishes a communication connection with the dimming power supply, and ensures the real-time transmission of data and the effective execution of control instructions.

[0027] In this embodiment, the cloud server designs the topology of the first Internet of Things network, including: determining the number and installation locations of the Internet of Things gateways, planning the distribution and coverage of the Internet of Things nodes, designing network backup paths and load balancing strategies, generating network resource allocation plans, etc.; the cloud server configures the Internet of Things server, including: allocating computing resources and storage space, deploying network management software and databases, configuring security policies and access control, enabling performance monitoring and alarm functions, etc.; the cloud server configures the Internet of Things gateway, including: issuing gateway communication parameter configuration, establishing a collaborative mechanism between gateways, configuring data routing and forwarding rules, setting failover and backup strategies, etc.; the cloud server configures the Internet of Things node, including: deploying signal relays and edge computing nodes, configuring data acquisition and control execution nodes, setting a collaborative mechanism between nodes, establishing node monitoring and management strategies, etc. Among them, the establishment of a communication connection with the dimming power supply ensures real-time transmission of data and effective execution of control instructions, including: the Internet of Things gateway broadcasts network access information; the dimming power supply responds and returns device information; the cloud server verifies the legitimacy of the device; records the list of discovered devices; assigns a unique network address to the dimming power supply; sends down device communication parameter configuration; establishes a connection between the device and the gateway; verifies the reliability of the network connection; periodically detects network performance indicators; automatically adjusts network configuration parameters; performs fault diagnosis and processing; and records network operation status data.

[0028] In the scheme of this embodiment, by analyzing historical data, the cloud server can optimize the configuration of the Internet of Things network according to actual usage and environmental conditions, improve the stability and response speed of the network; configure the network according to the power attribute data to ensure that dimming power supplies of different brands and models can be seamlessly integrated, and improve the compatibility and flexibility of the system; through real-time data transmission and intelligent analysis, the system can more accurately control the dimming power supply to meet the personalized needs of users and improve user experience; optimized network configuration and intelligent control strategies can reduce system failures and maintenance requirements, thereby reducing operating costs.

[0029] In some possible implementations of the present invention, the step of dividing all the dimming power supplies into different groups and configuring a corresponding group controller for each group includes: The cloud server analyzes the usage pattern of the dimming power supply based on historical working data and historical working environment data, and identifies the dimming power supply with similar working characteristics and environmental conditions; In this step, the cloud server first collects the historical working data of all dimming power supplies, including working demand data (such as brightness demand, usage time), working status data (such as current power, dimming level), etc. At the same time, it collects historical working environment data related to the dimming power supply, such as natural environment data (light intensity, temperature), building data (building type, area) and human activity data (personnel flow); cleans the collected data to remove noise and incomplete data to ensure data accuracy and consistency; extracts key features from the cleaned data, such as peak usage time period, common dimming modes, etc. Through this step, the cloud server can effectively identify dimming power supplies with similar working characteristics, thereby realizing a more intelligent and efficient control strategy.

[0030] According to the above analysis and identification results, the dimming power supplies are divided into multiple groups, each of which contains dimming power supplies with similar characteristics, so as to facilitate centralized management and control; In the previous step, the cloud server obtains the performance data and environmental data of the dimming power supply from the historical working data and historical working environment data, including power consumption, response time, load characteristics, usage patterns, etc.; the cloud server pre-processes the received data and cleans the data to remove outliers and noise to ensure the accuracy and reliability of the data.

[0031] In this step, the cloud server uses a clustering algorithm (such as K-means or hierarchical clustering) to group the dimming power supplies, identify devices with similar working characteristics (for example, dimming power supplies with similar usage patterns can be grouped together), and generate feature vectors; by calculating the similarity between feature vectors (such as Euclidean distance, cosine similarity, etc.), it is further confirmed which dimming power supplies are similar in working characteristics, and the dimming power supplies are divided into multiple groups accordingly, each of which contains dimming power supplies with similar characteristics, ensuring that the dimming power supplies in each group are consistent in performance and usage patterns; based on the identified similar working characteristics, the cloud server generates corresponding power usage scenario models for each group (these models include the status settings and dimming strategies of the devices in the group); based on the scenario model, the cloud server formulates corresponding group control strategies (including centralized control, dimming strategies and fault monitoring, etc.) to realize intelligent dimming in actual applications; in actual operation, the cloud server continuously monitors the working status and environmental changes of the dimming power supplies and collects new data feedback; based on the new data and feedback, the similarity analysis model and control strategy are regularly updated to improve the intelligence level and adaptability of the system. In this step, by dividing the dimming power supplies into multiple groups, the cloud server can realize centralized management of the dimming power supplies and improve management efficiency; the dimming power supplies in each group have similar characteristics, which makes the formulation of targeted control strategies more accurate and improves the overall performance of the system; centralized management and control can reduce response time and quickly adapt to environmental changes and user needs; through centralized management of dimming power supplies with similar characteristics, the maintenance process can be simplified and maintenance costs can be reduced.

[0032] Each group is assigned a group controller, which is responsible for managing the operation of all dimming power supplies in the group, including receiving control instructions, sending status feedback, and executing dimming strategies; In this step, assigning a group controller to each group includes: selecting controller hardware specifications according to the group size, configuring controller function modules according to control requirements, establishing a mapping relationship between the controller and the dimming power supply, and configuring the communication parameters of the controller.

[0033] Configure the corresponding communication protocol and control logic in the group controller to ensure that it can effectively communicate and coordinate with the dimming power supply in the group; In this step, the group control logic configuration includes: setting the management authority of the group controller; configuring the control rules of cross-group linkage; establishing the priority mechanism of group control; and configuring the security policy of group control.

[0034] The cloud server uploads each group’s configuration and control strategy to the corresponding group controller, ensuring it has all the information it needs to perform its tasks; The group controller monitors the status of the dimming power supply in the group in real time according to the received control strategy and instructions, and adjusts its working mode as needed.

[0035] The solution of this embodiment divides the dimming power supplies into groups and configures group controllers, so that the system can achieve centralized management, reduce the management complexity of individual devices, and improve overall management efficiency; the group controller can flexibly adjust the control strategy according to the characteristics and needs of the devices in the group to meet the lighting needs in different scenarios; through group management of the dimming power supplies, power resources can be more effectively allocated and utilized, energy consumption can be reduced, and the economy of the system can be improved; the group controller can quickly respond to changes in the status of the devices in the group, and adjust the control strategy in time to ensure the real-time and accuracy of the lighting effect.

[0036] In some possible implementations of the present invention, the step of dividing all the dimming power supplies into different groups and configuring a corresponding group controller for each group also includes: obtaining the location information, functional attributes, and control characteristics of the dimming power supplies to be grouped, obtaining the layout information, functional zoning, and lighting conditions of the building space, obtaining the user's usage requirements and control habits for the dimming power supplies, and establishing a group evaluation model based on the above information; vertical grouping based on building floors, horizontal grouping based on functional areas, and regional subdivision based on lighting conditions to establish a spatial location grouping data model; dividing functional groups based on lighting purposes, dividing control groups based on control methods, and dividing performance groups based on dimming characteristics to establish a functional attribute grouping data model; dividing time groups based on operating periods, and dividing control groups based on control cycles. Divide the period into period groups, divide the priority groups based on the response requirements, and establish a time feature grouping data model; analyze the correlation of the grouping models of each dimension, merge groups with similar characteristics, split groups with significant differences, and generate the final grouping scheme; configure the controller function module according to the control requirements, establish the mapping relationship between the controller and the dimming power supply, and configure the communication parameters of the controller; set the management authority of the group controller, configure the control rules of cross-group linkage, establish the priority mechanism of group control, and configure the security policy of group control; test the response consistency of the equipment in the group, verify the coordination of cross-group control, check the real-time performance of group control, and evaluate the rationality of the grouping scheme; continuously monitor the grouping operation effect, collect group control feedback data, analyze and optimize the grouping scheme, and dynamically adjust the grouping configuration. This embodiment scheme ensures the scientificity and rationality of the grouping scheme through a multi-dimensional grouping evaluation model; supports the continuous improvement of the grouping scheme through a dynamic optimization mechanism; adapts to the needs of different scenarios through a flexible controller configuration strategy; and ensures the long-term stable operation of the system through a complete grouping verification and optimization mechanism.

[0037] In some possible implementations of the present invention, the step of the cloud server generating a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data includes: The cloud server identifies the characteristics and requirements of each group based on the first analysis result, the second analysis result and the third analysis result respectively obtained from the historical working data, the historical working environment data and the power source attribute data, and determines basic parameters of a usage scenario model suitable for the group in combination with the grouping data; In this step, the cloud server applies a data analysis algorithm to analyze the first analysis result, the second analysis result and the third analysis result, and identifies the group characteristics of each group, including but not limited to: peak usage time, load change trend, device distribution, user behavior pattern, etc.; the cloud server determines the needs of each group according to the group characteristics, including the power demand, dimming demand and collaborative work demand of other devices, etc.; the cloud server generates the basic parameters of the power usage scenario model for each group, including: the working status of each power supply (such as on / off, dimming level, etc.), the status settings of other devices (such as sensor status, environmental adjustment device status, etc.), preset dimming strategy and control logic, etc. In this step, through in-depth analysis of historical data, the cloud server can accurately identify the characteristics and needs of each group, and provide a scientific basis for subsequent power management; according to the specific needs of the group, the cloud server can optimize the configuration and use strategy of the power supply and improve energy utilization efficiency; the generated power usage scenario model can quickly adapt to the changes in the needs of different groups, enhance the flexibility and responsiveness of the system; by meeting the specific needs of different groups, the system can provide more personalized services and improve user satisfaction.

[0038] The cloud server generates a power usage scenario model for each group based on basic parameters. The power usage scenario model includes: the working status of each power source, including the on / off status, dimming level, power output and other information; the status settings of other devices, including the status of sensors (such as light sensors, temperature sensors, etc.) and the working status of environmental conditioning devices (such as air conditioners, heaters, etc.); preset dimming strategies and control logic, including dimming strategies that are automatically adjusted according to environmental changes and user needs, timing control logic and abnormal situation processing logic; The cloud server stores the generated power usage scenario model in the database for real-time access and subsequent optimization and adjustment; The cloud server regularly updates the power usage scenario model and adjusts the state settings and control logic in the model based on real-time data and user feedback.

[0039] The solution of this embodiment, by generating a power usage scenario model, the cloud server can realize intelligent control of the dimming power supply and automatically adjust the working state to adapt to different environments and usage requirements; based on historical data and environmental analysis, the scenario model can optimize the efficiency of power use, reduce energy consumption, and improve the economy of the system; users can obtain a more comfortable lighting experience and meet personalized needs; the dynamic generation capability of the scene model enables the system to quickly respond to environmental changes and user needs, and improve the adaptability and flexibility of the system.

[0040] In some possible implementations of the present invention, the cloud server generates a power usage scenario model for each group according to basic parameters, and further includes: The first analysis result, the second analysis result and the third analysis result are analyzed to obtain a scene analysis result, specifically: analyzing the electricity consumption patterns under different time scales (including: intra-day changes, intra-week changes, seasonal changes), identifying the electricity consumption patterns of typical working days and non-working days, extracting the electricity consumption characteristics of special time periods, and establishing a time series prediction model; analyzing the impact of natural light changes on lighting needs, analyzing the impact of indoor temperature changes on electricity consumption behavior, analyzing the relationship between personnel activity density and lighting needs, and establishing an environmental factor impact model; mining user control operation habits, identifying typical scene switching patterns, analyzing space usage patterns, and establishing a user behavior prediction model; using the time series prediction model, environmental factor impact model, and user behavior prediction model as scene analysis results; Define the scenario type according to the scenario analysis results, and generate a power usage scenario model in combination with the basic parameters, specifically: set the trigger conditions and priority of the scene, configure the status parameters of each device in the scene, and define the switching rules between scenes; establish a mapping relationship between the scene and the environmental conditions, configure the trigger mechanism of the scene and the time conditions, set the response rules between the scene and the user behavior, and define the linkage logic between the scenes; train the optimization algorithm based on historical data, dynamically adjust the scene parameter configuration, optimize the scene switching strategy, and establish a parameter adaptive mechanism; simulate and test the scene response effect, evaluate the stability of the scene switching, verify the reliability of the scene linkage, and check the scene conflict handling mechanism; continuously collect scene execution data, evaluate the applicability of the scene model, update the scene parameter configuration, and optimize the scene control strategy.

[0041] The main innovations of the solution of this embodiment are: multi-dimensional data analysis method to improve the accuracy of the scene model; adaptive parameter adjustment mechanism to enhance the flexibility of scene control; dynamic optimization update strategy to ensure continuous improvement of the scene model; and perfect verification and feedback mechanism to ensure the reliability of scene control.

[0042] In some possible implementations of the present invention, the cloud server generates a group control strategy corresponding to each group, and sends the group control strategy to the group controller, including: The cloud server obtains the current working environment data of all the dimming power supplies (including current natural environment data, current building data, current building ancillary equipment data, current human activity data, etc.); In this step, the cloud server is connected to the sensors of each dimming power supply through the network to obtain real-time natural environment data, including light intensity, temperature, humidity and other information; the cloud server accesses the building management system to obtain current building data, including the building's structural information, area, floor distribution, etc.; the cloud server obtains data on the building's ancillary equipment through the interface, such as the current working status and energy consumption information of air conditioners, ventilation systems, lighting equipment, etc.; the cloud server uses the personnel monitoring system to obtain current human activity data, including personnel flow, headcount, activity areas and other information; the cloud server integrates all the current working environment data obtained to form a comprehensive environmental data set, and stores it in the database for subsequent analysis and processing; the cloud server regularly updates the current working environment data to ensure the real-time and accuracy of the data to support intelligent dimming control and optimization decisions. In this step, by acquiring the current working environment data, the cloud server can monitor environmental changes in real time and adjust the working status of the dimming power supply in time to adapt to different lighting needs; the acquisition of comprehensive environmental data enables the dimming system to perform intelligent dimming according to actual environmental conditions, improving lighting effects and energy efficiency; through the analysis of human activity data, the system can provide personalized lighting solutions to improve user comfort and satisfaction; the integrated environmental data provides a basis for subsequent analysis and decision-making, helping to optimize the energy management and utilization efficiency of buildings.

[0043] Establishing a digital twin model of the working area of ​​the dimming power supply according to the current working environment data and the power supply attribute data; In this step, the cloud server receives and stores the current working environment data, including light intensity, temperature, humidity, building structure information and three-dimensional data, auxiliary equipment status and three-dimensional data, personnel activity data, etc.; the cloud server receives and stores power attribute data, including the power, three-dimensional data, dimming mode, communication protocol and equipment compatibility of the dimming power supply; the cloud server analyzes the current working environment data, identifies the key environmental factors that affect the performance of the dimming power supply, and extracts relevant features; the cloud server determines the working range and performance limitations of the dimming power supply based on the power attribute data, and establishes a power performance model; combined with the above-mentioned cloud server's analysis results of the current working environment data and power attribute data, the cloud server constructs a digital twin model of the working area of ​​the dimming power supply, which includes: the real-time status of the dimming power supply (such as on / off, dimming level); the impact of environmental factors on the performance of the dimming power supply; the status and interaction relationship of other related equipment; the cloud server stores the generated digital twin model in the database and provides support for subsequent intelligent control and optimization decisions; the cloud server regularly updates the digital twin model to reflect changes in the current working environment and power attributes to ensure the accuracy and real-time performance of the model. In this step, by establishing a digital twin model, the system can simulate the working status of the dimming power supply in real time and support intelligent dimming control and decision-making; the digital twin model can dynamically adjust the dimming strategy according to environmental changes and power supply performance, thereby improving energy efficiency and reducing energy consumption; through real-time monitoring and adjustment, users can obtain a more comfortable lighting environment to meet personalized needs; the digital twin model provides a comprehensive view of the performance of the dimming power supply, which helps to identify potential faults in advance and optimize maintenance strategies.

[0044] The group control strategy is determined according to the working area digital twin model and the power usage scenario model, and the group control strategy is sent to the group controller.

[0045] In this step, the cloud server receives and stores data of the digital twin model of the working area and the power usage scenario model; the cloud server analyzes the digital twin model of the working area to extract key environmental factors and the current status information of the dimming power supply; the cloud server analyzes the power usage scenario model to identify the power demand and usage patterns in different scenarios; based on the analysis results of the previous steps, the cloud server applies the control algorithm to generate a group control strategy, which includes: the optimal switching state of the dimming power supply; adjustment suggestions for the dimming level; collaborative control strategy between devices; the cloud server formats the generated group control strategy into a control instruction and sends it to the group controller through the network; the group controller receives the control instruction and adjusts the working state of the dimming power supply and the operating mode of other related equipment according to the instruction; the cloud server regularly monitors the real-time data of the working area, and dynamically adjusts the group control strategy according to the changes to ensure the flexibility and adaptability of the system. In this step, by combining the digital twin model of the work area and the power usage scenario model, the system can realize intelligent dimming control and optimize the lighting effect; the generation of group control strategies can effectively reduce energy consumption, improve energy utilization efficiency, and reduce unnecessary electricity waste; according to the changes in real-time environment and usage scenarios, the system can provide personalized lighting solutions to improve user comfort and satisfaction; the ability to dynamically adjust control strategies enables the system to quickly respond to environmental changes and user needs, ensuring the efficient operation of the lighting system.

[0046] In some possible implementations of the present invention, the step of the group controller sending a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies includes: The group controller receives the group control strategy from the cloud server, including the on / off status of the dimming power supply, the dimming level and other related control instructions; The group controller parses the group control strategy and identifies the group commands and / or scene commands that need to be executed; The group controller generates a specific first control instruction according to the analysis result, including: sending a unified switch command (such as turning on or off) to all dimming power supplies; and / or sending a personalized dimming level command to each dimming power supply to meet the lighting needs of different areas; and / or sending a scene command to achieve a preset lighting scene (such as meeting mode, leisure mode, etc.); The group controller sends the generated first control instruction to each member dimming power supply in the group; Each member dimming power supply receives the control command, adjusts its working state according to the command, and performs corresponding switching and dimming operations; The group controller monitors the feedback status of the dimming power supply, confirms the success or failure of the command execution, and makes necessary adjustments or resends the command based on the feedback information.

[0047] The solution of this embodiment realizes centralized management of multiple dimming power supplies through a group controller, which simplifies the operation process and improves the management efficiency of the system; the group controller can flexibly adjust the state of the dimming power supply according to different scene requirements to meet the user's personalized lighting needs; by monitoring the feedback status, the group controller can respond to changes in the working state of the dimming power supply in a timely manner to ensure the stability and reliability of the system; through optimized control strategies, the system can effectively reduce energy consumption and improve energy utilization efficiency.

[0048] In some possible implementations of the present invention, the cloud server analyzes historical working data, identifies the usage mode and demand characteristics of the dimming power supply, and obtains the first analysis result, including: The cloud server receives and stores the historical working data of the dimming power supply (including usage time, communication records, load data, etc.); The cloud server preprocesses the historical working data, cleans the data to remove outliers and noise, and obtains the first historical working data; The cloud server analyzes the first historical working data, identifies the peak usage time when the usage frequency of the dimming power source exceeds the preset first usage frequency, and determines the usage frequency and load condition of the dimming power source in different time periods; The cloud server calculates the communication frequency according to the first historical working data, analyzes the communication activities between the dimming power supply and the control system, and identifies a high-frequency communication period in which the communication frequency exceeds the preset first communication frequency; The cloud server analyzes the first historical working data to evaluate data traffic, and monitors data transmission volumes in different time periods to identify a high traffic period in which the traffic value exceeds a preset first traffic value; The cloud server analyzes the peak load according to the first historical working data, determines the maximum load of the dimming power supply during use, and identifies the load change trend; The cloud server identifies critical periods and determines the time periods that have the greatest impact on dimming power supply performance, based on peak usage times and load variations; The cloud server stores the above analysis result as the first analysis result in the database.

[0049] In the solution of this embodiment, by analyzing historical work data, the cloud server can identify the usage pattern of the dimming power supply and help optimize resource allocation; identify peak usage time and load change trends, so that the system can predict user needs in advance and make reasonable scheduling; by analyzing communication frequency and data traffic, the system can optimize data transmission and control strategies and reduce energy consumption; identifying critical time periods helps to take preventive measures under high load conditions to ensure the stable operation of the dimming power supply.

[0050] In some possible implementations of the present invention, the cloud server analyzes historical working environment data, evaluates the impact of environmental factors on dimming power supply performance, and obtains a second analysis result, including: The cloud server receives and stores historical working environment data of the dimming power supply (including building structure information, signal transmission records, location of electromagnetic interference sources, equipment distribution, lighting conditions, temperature changes, and personnel activity patterns, etc.); The cloud server preprocesses the historical working environment data, cleans the data to remove outliers and noise, and obtains the first historical working environment data; The cloud server analyzes the building structure information based on the first historical working environment data and evaluates its impact on the dimming power signal transmission (including wall materials, floor heights, opening locations, etc.); In this step, the cloud server extracts data such as wall materials, floor heights, opening positions, window sizes, and building layouts from the building structure information in the first historical working environment data; the cloud server applies a signal propagation model to analyze the attenuation and reflection effects of different wall materials (such as concrete, masonry, glass, etc.) on dimming power signal transmission; evaluates the impact of floor height on signal transmission, considering the propagation characteristics of the signal in the vertical direction and its attenuation between different floors; analyzes the impact of opening positions (such as doors and windows) on signal transmission, and evaluates the impact of openings on signal paths, including the transmittance and reflectivity of the signal; the cloud server comprehensively analyzes the above factors, generates an evaluation report on the impact of building structure on dimming power signal transmission, and provides optimization suggestions; the cloud server stores the evaluation results in a database for subsequent management and optimization of control strategies. In this step, by analyzing the building structure information, the cloud server can identify and optimize the signal transmission path, improve the signal quality and stability of the dimming power supply; evaluate the impact of wall materials and opening positions, which helps reduce interference and attenuation of signals during transmission and ensure the reliability of the dimming system; through analysis of floor heights and building layouts, the cloud server can provide a scientific basis for the installation and layout of the dimming power supply and improve the overall performance of the system; by optimizing signal transmission, users can enjoy a more stable and efficient dimming control experience and improve satisfaction.

[0051] The cloud server identifies signal transmission obstacles based on the first historical working environment data and analyzes the impact of possible obstacles (such as walls, furniture, etc.) in the environment on signal strength and stability; In this step, the cloud server extracts spatial environment information from the first historical working environment data, including data such as building floor plans, furniture layouts, wall materials and their thicknesses; the cloud server applies a signal propagation model to identify possible obstacles in the environment, including walls, furniture, equipment, etc., based on the spatial environment information, and evaluates their potential impact on signal transmission; the cloud server analyzes the material properties (such as density, thickness, reflectivity, etc.) of each obstacle based on the spatial environment information, and calculates the degree of attenuation of the signal strength; the cloud server evaluates the position of the obstacle in the signal transmission path based on the spatial environment information, and analyzes its impact on signal stability, including multipath effects and the possibility of signal reflection; the cloud server comprehensively analyzes the impact of obstacles on signal strength and stability, generates a signal transmission obstacle analysis report, and provides optimization suggestions; the cloud server stores the analysis results in a database for subsequent management and optimization of control strategies. In this step, by identifying and analyzing signal transmission obstacles, the cloud server can optimize the signal path, reduce signal attenuation, and improve signal reliability; analyzing the impact of obstacles in the environment helps to predict and reduce signal instability and ensure the stable operation of the dimming system in various environments; through the analysis of obstacles, the cloud server can provide a scientific basis for the installation and layout of equipment and improve the overall performance of the system; optimizing signal transmission and stability allows users to enjoy a smoother and more efficient control experience when using the dimming system, thereby enhancing user satisfaction.

[0052] The cloud server evaluates the electromagnetic interference source based on the first historical working environment data and identifies the potential interference of surrounding equipment (such as radio equipment, household appliances, etc.) on the dimming power supply performance; In this step, the cloud server extracts information about surrounding devices from the first historical working environment data, including the working status and frequency characteristics of radio equipment, household appliances, electronic equipment, etc.; the cloud server pre-processes the equipment information to ensure the integrity and accuracy of the data; the cloud server applies an electromagnetic interference analysis model based on the equipment information to identify electromagnetic interference sources that may be generated by surrounding equipment, including but not limited to: radio equipment (such as walkie-talkies, wireless network equipment, etc.), household appliances (such as microwave ovens, air conditioners, refrigerators, etc.), and other electronic equipment (such as computers, televisions, etc.); the cloud server analyzes the operating frequency and power output of each device based on the equipment information, and evaluates its potential interference level to the dimming power supply signal; the cloud server comprehensively evaluates the impact of electromagnetic interference sources on the performance of the dimming power supply, including signal strength, stability, and response time, based on the equipment information and combined with environmental factors (such as equipment location, obstacles, etc.); the cloud server generates an electromagnetic interference evaluation report and provides optimization suggestions and solutions for the identified interference sources; the cloud server stores the evaluation results in a database for subsequent management and optimization of control strategies. In this step, by identifying and evaluating the source of electromagnetic interference, the cloud server can enhance the dimming power supply system's resistance to external interference and ensure stable operation of the system; analyzing the interference characteristics of surrounding equipment helps to optimize the configuration of the dimming power supply and other equipment, reduce the impact of interference, and improve overall performance.

[0053] The cloud server analyzes the device distribution based on the first historical working environment data, and evaluates the impact of the relative positions of different devices on the dimming power supply performance, including the interference and collaborative working conditions between the devices; In this step, the cloud server extracts device distribution information from the first historical working environment data, including location information of dimming power supplies, sensors, controllers and other related devices; the cloud server identifies the relative position relationship between devices based on the device distribution information and applies a spatial analysis algorithm, including: the distance between devices, the arrangement of devices (such as linear, circular, etc.), and the height difference of devices; the cloud server analyzes the interference between different devices based on the device distribution information, and evaluates the impact of relative position on signal transmission, including signal attenuation, reflection, and multipath effects; the cloud server evaluates the collaborative work between devices based on the device distribution information, and analyzes the impact of devices on the performance of dimming power supplies when working together, including load distribution and response time; the cloud server comprehensively analyzes the impact of device distribution on the performance of dimming power supplies, generates a device distribution analysis report, and provides optimization suggestions; the cloud server stores the analysis results in a database for subsequent management and optimization of control strategies. In this step, by analyzing the relative positions between devices, the cloud server can provide a scientific basis to optimize the layout of equipment, reduce interference, and improve system performance; identifying interference and collaborative work between devices helps to improve the efficiency and stability of signal transmission and ensure the reliability of dimming power supply; by evaluating the collaborative work of equipment, the cloud server can enhance the overall collaborative ability of the system and ensure effective coordination between devices.

[0054] The cloud server monitors the lighting conditions based on the first historical working environment data, analyzes the impact of natural lighting changes on dimming power supply regulation, and identifies the best dimming strategy; In this step, the cloud server extracts light sensor data from the first historical working environment data, including ambient light intensity, light change rate and light fluctuation; the cloud server applies a light analysis algorithm based on the light sensor data to monitor changes in natural light conditions in real time and identify changing trends and patterns in light intensity; the cloud server analyzes the impact of natural light changes on the dimming power supply based on the light sensor data, including: the impact of light intensity changes on indoor brightness, the impact of natural light changes on user comfort, and the impact of light changes on the power demand of the dimming power supply; the cloud server identifies the best dimming strategy based on the analysis results, including: automatically adjusting the brightness of the dimming power supply to adapt to light changes, setting the response time and adjustment range of the dimming power supply, and providing user-defined dimming options to meet personalized needs; the cloud server applies the best dimming strategy to the dimming power supply, monitors its effects in real time, and makes dynamic adjustments; the cloud server stores the results of light condition monitoring and dimming strategy analysis in a database to facilitate subsequent management and optimization of control strategies. In this step, by real-time monitoring of lighting conditions and automatically adjusting the dimming power supply, the cloud server can significantly improve energy utilization efficiency and reduce unnecessary energy consumption; adjusting indoor brightness according to changes in natural light can improve user comfort and satisfaction and create a more pleasant environment; by identifying the optimal dimming strategy, the cloud server can achieve more intelligent dimming control to meet the needs of different users.

[0055] The cloud server analyzes temperature changes based on the first historical working environment data, evaluates the impact of ambient temperature on dimming power supply performance and energy consumption, and identifies key periods of temperature changes; In this step, the cloud server extracts ambient temperature data from the first historical working environment data, including indoor and outdoor temperatures, equipment working temperatures and their changing trends; the cloud server applies a temperature analysis algorithm based on the ambient temperature data to monitor the changes in ambient temperature in real time and identify the patterns and trends of temperature changes; the cloud server analyzes the impact of ambient temperature on the performance of the dimming power supply based on the ambient temperature data, including: the impact of temperature changes on the efficiency of the dimming power supply, the impact of temperature on the response time of the dimming power supply, and the impact of temperature changes on energy consumption; the cloud server identifies the key periods of temperature changes based on the ambient temperature data, including high and low temperature periods, and analyzes the potential impact of these periods on the performance of the dimming power supply; the cloud server generates a temperature impact assessment report based on the above analysis results, and provides optimization suggestions to improve the performance and energy efficiency of the dimming power supply; the cloud server stores the temperature change analysis and assessment results in a database for subsequent management and optimization of control strategies. In this step, by analyzing the impact of ambient temperature on the dimming power supply, the cloud server can optimize the operation strategy of the dimming power supply and reduce energy consumption; identifying the key periods of temperature changes helps to adjust the working mode of the dimming power supply to ensure its stability and performance under different temperature conditions.

[0056] The cloud server analyzes the personnel activity patterns based on the first historical work environment data, evaluates the impact of personnel flow on the demand for dimming power usage, and identifies peak activity periods; In this step, the cloud server extracts personnel activity-related data from the first historical work environment data, including personnel flow records, activity types, activity durations and timestamps thereof; the cloud server applies a data analysis algorithm based on the personnel activity-related data to identify personnel activity patterns, including: peak hours of personnel flow, the impact of different activity types on dimming power usage, and the frequency of personnel activities in different areas; the cloud server analyzes the impact of personnel flow on dimming power usage demand based on the personnel activity-related data, including: changes in dimming power demand during peak activity periods, and dynamic adjustments of lighting demand due to personnel flow; the cloud server identifies peak activity periods based on the personnel activity-related data, generates an activity pattern report for peak periods, and provides a forecast of dimming power usage demand; the cloud server optimizes the dimming power control strategy based on the analysis results to adapt to changes in personnel activity patterns; the cloud server stores the results of personnel activity pattern analysis and peak hour identification in a database to facilitate subsequent management and optimization of control strategies. In this step, by analyzing the activity patterns of personnel, the cloud server can optimize the use strategy of dimming power supply and improve the efficiency and effectiveness of lighting; dynamically adjusting the lighting according to the needs of personnel flow can improve user comfort and satisfaction and create a more pleasant environment; identifying peak activity periods provides a basis for the intelligent regulation of dimming power supply, so that the system can better adapt to actual usage needs.

[0057] The cloud server stores the above analysis result as the second analysis result in the database.

[0058] In the solution of this embodiment, by analyzing historical working environment data, the cloud server can comprehensively evaluate the impact of environmental factors on the performance of dimming power supplies and provide a scientific basis; identify key environmental factors that affect the performance of dimming power supplies, so that the system can formulate more accurate control strategies and improve lighting effects; by evaluating signal transmission obstacles and electromagnetic interference sources, the system can optimize signal transmission paths, reduce interference, and improve system stability; by analyzing lighting conditions and personnel activity patterns, the system can provide personalized lighting solutions to improve user comfort and satisfaction.

[0059] In some possible implementations of the present invention, the cloud server determines the technical specifications and compatibility requirements of each dimming power supply according to the power supply attribute data, and the step of obtaining the third analysis result includes: The cloud server receives and stores the attribute data of the dimming power supply (including power output, dimming mode, communication protocol, network load, etc.); The cloud server preprocesses the received power attribute data, cleans the data to remove abnormal values ​​and noise, and obtains first power attribute data; The cloud server analyzes the power attribute data according to the first power attribute data, and identifies the technical specifications of each dimming power supply (including: power limit, determining the maximum power output and minimum power requirement of each dimming power supply; dimming mode, identifying the supported dimming technology (such as PWM dimming, analog dimming, etc.); communication protocol, determining the supported communication protocol (such as DMX, DALI, Zigbee, etc.)); The cloud server evaluates the network load based on the first power source attribute data, analyzes the network bandwidth requirements of the dimming power source in different usage scenarios, and ensures its stability in actual applications; Based on the above analysis results, the cloud server generates compatibility requirements for each dimming power supply (including compatibility with other devices, adaptability to the network environment, etc.); The cloud server stores the technical specifications and compatibility requirements of each dimming power supply as the third analysis result in the database.

[0060] The solution of this embodiment, by clarifying the technical specifications and compatibility requirements of each dimming power supply, the cloud server can ensure good cooperation between different devices and reduce compatibility issues; according to the power limit of the power supply and the network load requirements, the system can optimize resource allocation and improve energy utilization efficiency; by evaluating the adaptability of network load and communication protocol, the cloud server can improve the stability and reliability of the system in practical applications; clear technical specifications and compatibility requirements make it more convenient for users to select and configure dimming power supplies, thereby improving the overall user experience.

[0061] See also Figure 2 , another embodiment of the present invention provides a constant voltage dimming power supply networking control system based on the Internet of Things, which is used to execute the constant voltage dimming power supply networking control method based on the Internet of Things as described above, including: a cloud server, a first Internet of Things network and a dimming light source; The cloud server is configured as follows: Acquire historical working data, historical working environment data and power source attribute data of all the dimming power sources; Configure a first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data; Connecting all the dimming power supplies to the first Internet of Things network; Divide all the dimming power supplies into different groups, and configure a corresponding group controller for each group; Generate a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data; Generate a group control strategy corresponding to each group, and send the group control strategy to the group controller; The group controller is configured to send a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies.

[0062] It should be known that Figure 2 The block diagram of the constant voltage dimming power supply network control system based on the Internet of Things is shown for illustration only, and the number of modules shown does not limit the protection scope of the present invention. The constant voltage dimming power supply network control system based on the Internet of Things provided in this embodiment can be used to execute the corresponding embodiments of the constant voltage dimming power supply network control method based on the Internet of Things. For the specific implementation process, please refer to the description of each method embodiment, which will not be repeated here.

[0063] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0064] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0065] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0066] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0067] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0068] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0069] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0070] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

[0071] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the present invention, and can make various changes and modifications, including the combination of the above-mentioned different functions and implementation steps, including software and hardware implementation methods, all of which are within the scope of protection of the present invention.

Claims

1. A constant voltage dimming power supply networking control method based on the Internet of Things, characterized in that: include: The cloud server obtains the historical working data, historical working environment data and power attribute data of all dimming power supplies; The cloud server configures a first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data; Connecting all the dimming power supplies to the first Internet of Things network; Divide all the dimming power supplies into different groups, and configure a corresponding group controller for each group; The cloud server generates a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data; The cloud server generates a group control strategy corresponding to each group, and sends the group control strategy to the group controller; The group controller sends a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies.

2. The constant voltage dimming power supply networking control method based on the Internet of Things according to claim 1 is characterized in that: The step of configuring, by the cloud server, a first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data comprises: The cloud server analyzes historical working data, identifies the usage pattern and demand characteristics of the dimming power supply, and obtains a first analysis result; The cloud server analyzes historical working environment data, evaluates the impact of environmental factors on dimming power supply performance, and obtains a second analysis result; The cloud server determines the technical specifications and compatibility requirements of each dimming power supply according to the power supply attribute data, and obtains the third analysis result; Based on the first analysis result, the second analysis result and the third analysis result, the cloud server designs the topology structure of the first IoT network, and determines the configuration and connection method of the IoT server, the IoT gateway, the IoT node and the IoT smart terminal; The cloud server generates a network configuration file and transmits the network configuration file to the IoT server; The IoT server automatically configures the IoT gateway and nodes according to the configuration file, establishes a communication connection with the dimming power supply, and ensures the real-time transmission of data and the effective execution of control instructions.

3. The constant voltage dimming power supply networking control method based on the Internet of Things according to claim 2 is characterized in that: The step of dividing all the dimming power supplies into different groups and configuring a corresponding group controller for each group includes: The cloud server analyzes the usage pattern of the dimming power supply based on historical working data and historical working environment data, and identifies the dimming power supply with similar working characteristics and environmental conditions; According to the above analysis and identification results, the dimming power supplies are divided into multiple groups, each of which contains dimming power supplies with similar characteristics, so as to facilitate centralized management and control; Each group is assigned a group controller, which is responsible for managing the operation of all dimming power supplies in the group, including receiving control instructions, sending status feedback, and executing dimming strategies; Configure the corresponding communication protocol and control logic in the group controller to ensure that it can effectively communicate and coordinate with the dimming power supply in the group; The cloud server uploads each group’s configuration and control strategy to the corresponding group controller, ensuring it has all the information it needs to perform its tasks; The group controller monitors the status of the dimming power supply in the group in real time according to the received control strategy and instructions, and adjusts its working mode as needed.

4. The constant voltage dimming power supply networking control method based on the Internet of Things according to claim 3 is characterized in that: The step of generating, by the cloud server, a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data comprises: The cloud server identifies the characteristics and requirements of each group based on the first analysis result, the second analysis result and the third analysis result respectively obtained from the historical working data, the historical working environment data and the power source attribute data, and determines basic parameters of a usage scenario model suitable for the group in combination with the grouping data; The cloud server generates a power usage scenario model for each group based on basic parameters. The power usage scenario model includes: the working status of each power source, including the on / off status, dimming level, and power output; the status settings of other devices, including the status of sensors and the working status of environmental conditioning devices; preset dimming strategies and control logic, including dimming strategies that are automatically adjusted according to environmental changes and user needs, timing control logic, and abnormal situation processing logic; The cloud server stores the generated power usage scenario model in the database for real-time access and subsequent optimization and adjustment; The cloud server regularly updates the power usage scenario model and adjusts the state settings and control logic in the model based on real-time data and user feedback.

5. The constant voltage dimming power supply networking control method based on the Internet of Things according to claim 4 is characterized in that: The cloud server generates a group control strategy corresponding to each group, and sends the group control strategy to the group controller, including: The cloud server obtains current working environment data of all the dimming power supplies; Establishing a digital twin model of the working area of ​​the dimming power supply according to the current working environment data and the power supply attribute data; The group control strategy is determined according to the working area digital twin model and the power usage scenario model, and the group control strategy is sent to the group controller.

6. The constant voltage dimming power supply networking control method based on the Internet of Things according to claim 5 is characterized in that: The step of the group controller sending a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies comprises: The group controller receives the group control strategy from the cloud server, including the on / off status of the dimming power supply, the dimming level and other related control instructions; The group controller parses the group control strategy and identifies the group commands and / or scene commands that need to be executed; The group controller generates a specific first control instruction according to the analysis result, including: sending a unified switch command to all dimming power supplies; and / or sending a personalized dimming level command to each dimming power supply to meet the lighting needs of different areas; and / or sending a scene command to achieve a preset lighting scene; The group controller sends the generated first control instruction to each member dimming power supply in the group; Each member dimming power supply receives the control command, adjusts its working state according to the command, and performs corresponding switching and dimming operations; The group controller monitors the feedback status of the dimming power supply, confirms the success or failure of the command execution, and makes necessary adjustments or resends the command based on the feedback information.

7. The constant voltage dimming power supply networking control method based on the Internet of Things according to claim 6 is characterized in that: The cloud server analyzes historical working data, identifies the usage mode and demand characteristics of the dimming power supply, and obtains a first analysis result, including: The cloud server receives and stores historical working data of the dimming power supply; The cloud server preprocesses the historical working data, cleans the data to remove outliers and noise, and obtains the first historical working data; The cloud server analyzes the first historical working data, identifies the peak usage time when the usage frequency of the dimming power source exceeds the preset first usage frequency, and determines the usage frequency and load condition of the dimming power source in different time periods; The cloud server calculates the communication frequency according to the first historical working data, analyzes the communication activities between the dimming power supply and the control system, and identifies a high-frequency communication period in which the communication frequency exceeds the preset first communication frequency; The cloud server analyzes the first historical working data to evaluate data traffic, and monitors data transmission volumes in different time periods to identify a high traffic period in which the traffic value exceeds a preset first traffic value; The cloud server analyzes the peak load according to the first historical working data, determines the maximum load of the dimming power supply during use, and identifies the load change trend; The cloud server identifies critical periods and determines the time periods that have the greatest impact on dimming power supply performance, based on peak usage times and load variations; The cloud server stores the above analysis result as the first analysis result in the database.

8. The constant voltage dimming power supply networking control method based on the Internet of Things according to claim 7 is characterized in that: The cloud server analyzes historical working environment data, evaluates the impact of environmental factors on dimming power supply performance, and obtains a second analysis result, including: The cloud server receives and stores historical working environment data of the dimming power supply; The cloud server preprocesses the historical working environment data, cleans the data to remove outliers and noise, and obtains the first historical working environment data; The cloud server analyzes the building structure information based on the first historical working environment data and evaluates its impact on the dimming power signal transmission; The cloud server identifies signal transmission obstacles based on the first historical working environment data and analyzes the impact of possible obstacles in the environment on signal strength and stability; The cloud server evaluates the electromagnetic interference source based on the first historical working environment data and identifies the potential interference of surrounding equipment on the dimming power supply performance; The cloud server analyzes the device distribution based on the first historical working environment data, and evaluates the impact of the relative positions of different devices on the dimming power supply performance, including the interference and collaborative working conditions between the devices; The cloud server monitors the lighting conditions based on the first historical working environment data, analyzes the impact of natural lighting changes on dimming power supply regulation, and identifies the best dimming strategy; The cloud server analyzes temperature changes based on the first historical working environment data, evaluates the impact of ambient temperature on dimming power supply performance and energy consumption, and identifies key periods of temperature changes; The cloud server analyzes the personnel activity patterns based on the first historical work environment data, evaluates the impact of personnel flow on the demand for dimming power usage, and identifies peak activity periods; The cloud server stores the above analysis result as the second analysis result in the database.

9. The constant voltage dimming power supply networking control method based on the Internet of Things according to claim 8, characterized in that: The cloud server determines the technical specifications and compatibility requirements of each dimming power supply according to the power supply attribute data to obtain a third analysis result, including: The cloud server receives and stores the attribute data of the dimming power supply; The cloud server preprocesses the received power attribute data, cleans the data to remove abnormal values ​​and noise, and obtains first power attribute data; The cloud server analyzes the power source attribute data according to the first power source attribute data, and identifies the technical specifications of each dimming power source; The cloud server evaluates the network load according to the first power source attribute data, analyzes the network bandwidth requirements of the dimming power source in different usage scenarios, and ensures its stability in actual applications; The cloud server generates compatibility requirements for each dimming power supply based on the above analysis results; The cloud server stores the technical specifications and compatibility requirements of each dimming power supply as the third analysis result in the database.

10. A constant voltage dimming power supply network control system based on the Internet of Things, used to execute the constant voltage dimming power supply network control method based on the Internet of Things as claimed in any one of claims 1 to 9, characterized in that: include: Cloud servers, the first IoT network and dimming light sources; The cloud server is configured as follows: Acquire historical working data, historical working environment data and power source attribute data of all the dimming power sources; Configure a first Internet of Things network corresponding to the dimming power supply according to the historical working data, the historical working environment data and the power supply attribute data; Connecting all the dimming power supplies to the first Internet of Things network; Divide all the dimming power supplies into different groups, and configure a corresponding group controller for each group; Generate a power usage scenario model corresponding to each group according to the historical working data, the historical working environment data, the power attribute data and the grouping data; Generate a group control strategy corresponding to each group, and send the group control strategy to the group controller; The group controller is configured to send a group command and / or a scene command according to the group control strategy to control the plurality of dimming power supplies.

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