Method and system for constructing data model of lighting equipment

Abstract

The invention relates to a data model construction method and system for lighting equipment. Internet of Things equipment is managed through an Internet of Things equipment management platform. The Internet of Things equipment comprises a signal concentrator and an equipment terminal, and can monitor whether communication channels between the signal concentrator and the equipment terminal and between the signal concentrator and the server are smooth or not. The communication speed of the communication connection between the equipment terminal and the signal concentrator can be determined by using an information transmission rate formula, the communication speed of the communication connection between the signal concentrator and the server can also be determined, and the authenticity of real-time information can be determined based on the comparison between the actual communication speed and the theoretical communication speed. When the difference between the actual communication speed and the theoretical communication speed is large, it can be determined that the authenticity of the real-time information flow obtained by the lighting equipment digital twin system is low. When the actual communication speed is not greatly different from the theoretical communication speed, it can be determined that the authenticity of the real-time information flow obtained by the lighting equipment digital twin system is high.

Description

Technical Field

[0001] This application relates to the technical field of the Internet of Things, and particularly to a method and system for constructing a data model of lighting equipment. Background Art

[0002] Digital twin system technology is a newly emerging digital platform technology. A digital twin system can monitor a physical system in multiple dimensions, such as the digital twin system of a subway system, a building BIM platform, etc. The urban lighting system has multi-dimensional characteristics, such as the energy dimension of electrical supply, the three-dimensional space dimension of spatial distribution, the information dimension of device cluster communication, etc. The operation status monitoring scheme of the urban lighting system is suitable for introducing a digital twin system. At present, the authenticity of real-time information transmitted by the digital twin system is a difficult point restricting the development of digital twin system technology. Since the digital twin system is a system based on a complex Internet of Things cluster. When there are loopholes in the communication of Internet of Things devices, it is difficult for the digital twin system to receive real-time information, and thus it is impossible to update the monitoring content of the digital twin system. Therefore, it is necessary to propose a method and system for constructing a data model of lighting equipment to address the defect of low authenticity of real-time information in the traditional digital twin system of lighting equipment. Summary of the Invention

[0003] Based on this, it is necessary to propose a method and system for constructing a data model of lighting equipment to address the defect of low authenticity of real-time information in the traditional digital twin system of lighting equipment.

[0004] This application provides a method for constructing a data model of lighting equipment, including:

[0005] Establish an Internet of Things device management platform; the Internet of Things devices include signal concentrators and device terminals; the device terminals are communicatively connected to the signal concentrators, and the signal concentrators are used to send information to the Internet of Things device management platform;

[0006] Select all information flows of a signal concentrator;

[0007] Based on the information transmission rate formula, determine the theoretical time delay of all information flows of the signal concentrator;

[0008] Judge whether the difference between the actual time delay of all information flows of the signal concentrator and the theoretical time delay of all information flows of the signal concentrator is within the error range;

[0009] If the difference between the actual time delay of all information flows of the signal concentrator and the theoretical time delay of all information flows of the signal concentrator is within the error range, then return to selecting all information flows of a signal concentrator until all signal concentrators are selected;

[0010] If the difference between the actual time delays of all information flows of the signal concentrator and the theoretical time delays of all information flows of the signal concentrator is not within the error range, a warning message is issued, and all information flows of the selected signal concentrator are returned until all signal concentrators are selected.

[0011] This application provides a data model construction system for lighting equipment, including:

[0012] A server for executing the data model construction method for lighting equipment mentioned above;

[0013] A signal concentrator communicatively connected to the server;

[0014] A device terminal communicatively connected to the signal concentrator.

[0015] This application relates to a data model construction method and system for lighting equipment, which manages Internet of Things devices through an Internet of Things device management platform. The Internet of Things devices include signal concentrators and device terminals, and can monitor whether the communication channels between the signal concentrators and the device terminals and between the signal concentrators and the servers themselves are smooth. Using the information transmission rate formula, the communication speed of the communication connection between the device terminal and the signal concentrator can be determined, and the communication speed of the communication connection between the signal concentrator and the server itself can also be determined. Based on the comparison between the actual communication speed and the theoretical communication speed, the authenticity of real-time information can be determined. Specifically, the server itself has an Internet of Things device management platform, and based on the Internet of Things device management platform, the communication quality monitoring of Internet of Things devices can be realized, and the authenticity of the real-time information flow obtained by the lighting equipment digital twin system can be determined. When the actual communication speed differs greatly from the theoretical communication speed, it can be determined that the authenticity of the real-time information flow obtained by the lighting equipment digital twin system is low. When the actual communication speed differs little from the theoretical communication speed, it can be determined that the authenticity of the real-time information flow obtained by the lighting equipment digital twin system is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 FIG. is a flowchart of a data model construction method for lighting equipment provided by an embodiment of this application.

[0017] Figure 2 FIG. is a structural connection diagram of a data model construction system for lighting equipment provided by an embodiment of this application.

[0018] REFERENCE SIGNS:

[0019] 100 - Server; 200 - Signal concentrator; 300 - Device terminal. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions and advantages of the present application more comprehensible, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely used to explain the present application and are not intended to limit the present application.

[0021] The present application provides a method for constructing a data model of a lighting device.

[0022] As Figure 1 shown, in an embodiment of the present application, a method for constructing a data model of a lighting device includes:

[0023] S100, establish an Internet of Things device management platform.

[0024] Specifically, the Internet of Things devices include a signal concentrator and device terminals. The device terminals are communicatively connected to the signal concentrator, and the signal concentrator is used to send information to the Internet of Things device management platform;

[0025] S200, select all information flows of a signal concentrator.

[0026] S300, based on the information transmission rate formula, determine the theoretical time delay of all information flows of the signal concentrator.

[0027] S400, determine whether the difference between the actual time delay of all information flows of the signal concentrator and the theoretical time delay of all information flows of the signal concentrator is within the error range.

[0028] Specifically:

[0029] S410, select a signal concentrator.

[0030] S420, receive all information flows of the signal concentrator.

[0031] It is worth mentioning that

[0032] wherein, T i为第i个 is the time when the signal concentrator executes the information flow transmission process, and L ij is the information transmission time between the i-th signal concentrator and the j-th device terminal.

[0033] S430, determine the actual time delay of all information flows between the signal concentrator and the device terminals.

[0034] S440, return to the step of selecting a signal concentrator until all signal concentrators have been selected.

[0035] S450, determine the actual time delay of all information flows between the server itself and all signal concentrators based on the actual time delay of all information flows between each signal concentrator and the device terminal.

[0036]

[0037] Among them, T 和 is the sum of the times of all T i .

[0038] S500, if the difference between the actual time delay and the theoretical time delay of all information flows of the signal concentrator is within the error range, return all information flows of the selected signal concentrator until all signal concentrators are selected.

[0039] S600, if the difference between the actual time delay and the theoretical time delay of all information flows of the signal concentrator is not within the error range, send a warning message and return all information flows of the selected signal concentrator until all signal concentrators are selected.

[0040] Specifically, when the communication between all signal concentrators and the device terminal is normal, it can be judged whether the communication between the signal concentrator and the Internet of Things device management platform is normal by the communication speed between all signal concentrators and the Internet of Things device management platform.

[0041] This embodiment relates to a method for constructing a data model of lighting equipment, which manages Internet of Things devices through an Internet of Things device management platform. The Internet of Things devices include signal concentrators and device terminals, and can monitor whether the communication channels between the signal concentrators and the device terminals and between the signal concentrators and the server itself are smooth. The information transmission rate formula can be used to determine the communication speed of the communication connection between the device terminal and the signal concentrator, and can also determine the communication speed of the communication connection between the signal concentrator and the server itself. Based on the comparison between the actual communication speed and the theoretical communication speed, the authenticity of real-time information can be determined. Specifically, the server itself has an Internet of Things device management platform, and the communication quality of the Internet of Things devices can be monitored based on the Internet of Things device management platform, so as to determine the authenticity of the real-time information flow obtained by the lighting equipment digital twin system. When the difference between the actual communication speed and the theoretical communication speed is large, it can be determined that the authenticity of the real-time information flow obtained by the lighting equipment digital twin system is low. When the difference between the actual communication speed and the theoretical communication speed is small, it can be determined that the authenticity of the real-time information flow obtained by the lighting equipment digital twin system is high.

[0042] In an embodiment of the present application, S100 includes:

[0043] S111, receive the IP address of the signal concentrator.

[0044] S112. Establish a network connection with the signal concentrator based on the IP address of the signal concentrator.

[0045] S113. Send a test data packet to the signal concentrator.

[0046] S114. Determine the data transmission rate parameter and data delay parameter of the signal concentrator.

[0047] Specifically, the processes of S111 to S114 are actually the processes for the signal concentrator to perform network access. Log in to the management interface of the signal concentrator through the Web interface or dedicated software. The management interface of this signal concentrator is the Internet of Things device management platform. In the management interface, configure network parameters such as the IP address, subnet mask, and default gateway of the signal concentrator according to the network environment. These parameters must match the network where it is located to ensure that the signal concentrator can communicate normally.

[0048] S113 is to perform a network connectivity test to verify whether the signal concentrator has successfully accessed the network. This can be achieved by attempting to access the management interface of the signal concentrator from other devices or sending data to the signal concentrator. Test performance indicators such as the data transmission rate and delay of the signal concentrator to ensure that it meets the actual application requirements.

[0049] In an embodiment of the present application, S100 further includes:

[0050] S121. Receive the IP data table sent by the signal concentrator.

[0051] Specifically, the IP data table includes the IPs of all device terminals.

[0052] In the process of networking the signal concentrator and device terminals, the IPs of the device terminals are required. The IPs of the device terminals can also be used for the management of the Internet of Things device management platform.

[0053] S122. Select the IP of a device terminal.

[0054] S123. Send an instruction to enable the Ping program to the signal concentrator.

[0055] S124. Receive the data transmission rate parameter and data delay parameter corresponding to the IP of the device terminal.

[0056] S125. Return the selected IP of a device terminal until all device terminals have been selected.

[0057] Specifically, the Ping program is one of the most commonly used tools for measuring network latency. It calculates the round-trip time (RTT) by sending a small data packet to the target host and waiting for a response.

[0058] For example, executing the program "ping 114.114.114.114 -c3" will send three test data packets (ICMP packets), send the ICMP packets to the specified device terminal IP address, and display the time of each request and the average round-trip time.

[0059] Based on the time of each request and the average round-trip time, the data transmission rate parameter and data delay parameter corresponding to the IP of the device terminal can be determined.

[0060] The data transmission rate parameter and data delay parameter of the signal concentrator, and the data transmission rate parameter and data delay parameter corresponding to the IP of the device terminal. These parameters are the actual time delays of all information flows of the signal concentrator in the test environment. Through the test environment, it can be determined whether the communication link between the device terminal and the signal concentrator and the communication link for the signal concentrator to send information to the Internet of Things device management platform are normal.

[0061] In an embodiment of the present application, after S100, it includes:

[0062] S131, based on the IP data table, call the processor data processing rate and maximum computing power of each device terminal.

[0063] Specifically, the processor data processing rate of the device terminal is mainly related to the number of cores and threads of the processor, the clock frequency, and the cache size.

[0064] When the processor data processing rate of the device terminal cannot be retrieved, software such as PassMark PerformanceTest and Geekbench can be used to test the processor data processing rate. They can simulate various application scenarios and evaluate the performance of the processor by running a series of complex computing tasks.

[0065] The computing power of the device terminal refers to the ability of the device to perform a certain operation. In most cases, the computing power mainly refers to the ability of multiplication and addition operations.

[0066] Taking the GPU as an example, the computing power can be estimated by calculating the number of ALUs (Arithmetic Logic Units) it contains. For example, the GT7600 in Imagination's PowerVR GPU Series7XT contains 6 USCs (Unified Shading Clusters), and each USC contains 192 FP32 cores or 384 FP16 cores. Calculate its theoretical peak computing power according to the clock frequency of the processor.

[0067] Taking GT7600 as an example, if its clock frequency is 1 GHz, then its FP32 computing power is 2304 GFLOP / s. If the clock frequency is 650 MHz, the computing power is 1497 GFLOP / s.

[0068] Actually, in this embodiment, the maximum computing power of the device terminal can be the combined computing power of the signal concentrator and a single device terminal, or the combined computing power of the signal concentrator and all secondary device terminals.

[0069] The combined computing power can be tested for the processor data processing rate using software such as PassMark PerformanceTest and Geekbench. They can simulate various application scenarios and evaluate the performance of the processor by running a series of complex computing tasks.

[0070] S132, call the transmission bandwidth parameters of each signal concentrator.

[0071] Specifically, the transmission bandwidth of the signal concentrator is actually the minimum combined transmission bandwidth from the server to the signal concentrator and from the signal concentrator to a single device terminal.

[0072] S133, based on the processor data processing rate of each device terminal and the transmission bandwidth parameters of each signal concentrator, establish an information transmission rate formula.

[0073] In an embodiment of the present application, the information transmission rate formula is:

[0074]

[0075] K(f ij )CPU ij ≤G ij (Formula 4)

[0076] Wherein, L ij is the information transmission time between the i-th signal concentrator and the j-th device terminal, K(f ij ) is the data volume between the i-th signal concentrator and the j-th device terminal, R ij is the transmission bandwidth among the i-th signal concentrator, the j-th device terminal, and the server, CPU ij is the processor data processing rate of the i-th signal concentrator and the j-th device terminal, and G ij is the maximum computing power of the i-th signal concentrator and the j-th device terminal.

[0077] Actually, the information transmission time L between the signal concentrator and the device terminal ij includes two parts. One part is the data volume K(f ij)Computing time of the signal concentrator and the device terminal Another part is the data volume K(f ij )The transmission time of data from the server to the signal concentrator and from the signal concentrator to a single device terminal

[0078] In an embodiment of the present application, after S133, it includes obtaining the error range of the theoretical time delay of all information flows of the signal concentrator.

[0079] The obtaining of the error range of the theoretical time delay of all information flows of the signal concentrator includes:[[]]

[0080] S141, obtaining the first error range of the theoretical time delay of all information flows between a single signal concentrator and the device terminal.

[0081] Specifically, obtaining the first error range includes:[[]]

[0082]

[0083] T Δi =T 2i -T 1i i ∈ [1, N], i is a real integer (Formula 7)

[0084] Among them, T 1i is the minimum theoretical time delay of all information flows between the i-th signal concentrator and the first to the n-th device terminals, T 2i is the maximum theoretical time delay of all information flows between the i-th signal concentrator and the first to the n-th device terminals, and TΔi is the first error range.

[0085] More specifically:[[]]

[0086]

[0087] L Δij =L 2ij -L 1ij (Formula 10)

[0088] Among them, L 1ij is the minimum theoretical time delay of all information flows between the i-th signal concentrator and the j-th device terminal, L 2ij is the maximum theoretical time delay of all information flows between the i-th signal concentrator and the j-th device terminal, and LΔij is the secondary error range between the i-th signal concentrator and the j-th device terminal.

[0089] S142, obtaining the second error range of the theoretical time delay of all information flows between the signal concentrator and the server.

[0090] Specifically, obtaining the second error range includes:

[0091]

[0092] T Δ = T4 - T3 (Formula 13)

[0093] where T3 is the minimum theoretical time delay of all information flows between the signal concentrator and the server, T4 is the maximum theoretical time delay of all information flows between the signal concentrator and the server, and T Δ is the second error range.

[0094] S143. Define the working state of the communication fault between the signal concentrator and the device terminal as that the difference between the actual time delay and the theoretical time delay of the information flow between the signal concentrator and the device terminal exceeds the first error range.

[0095] S144. Define the working state of the communication fault between the signal concentrator and the server as that the difference between the actual time delay and the theoretical time delay of the information flow between the signal concentrator and the server exceeds the second error range.

[0096] Specifically, during the actual working process, since the data volume K(f ij ) will change and the combined computing power of the data in the data volume K(f ij ) for the device terminal is different, the minimum theoretical time delay T3 of all information flows between the signal concentrator and the server and the maximum theoretical time delay T4 of all information flows between the signal concentrator and the server will fluctuate.

[0097] By calculating the floating of the secondary error range L Δij , the size of the secondary error range in the normal state can be determined. Based on the difference calculation between the actual value and the theoretical value L ij of the i-th signal concentrator and the j-th device terminal, it can be determined whether the difference is within the secondary error range L Δij . Furthermore, it can be determined whether the communication between the i-th signal concentrator and the j-th device terminal is normal, and finally the authenticity of the real-time information flow obtained by the lighting device digital twin system in this communication link can be determined.

[0098] By calculating the floating of the first error range T Δi , the size of the first error range in the normal state can be determined. Based on the actual values of all information flows between the i-th signal concentrator and the first to the n-th device terminals and the theoretical values T i of all information flows between the i-th signal concentrator and the first to the n-th device terminalsBy calculating the difference, it can be determined whether the difference is within the first error range T Δi Therein, it can be further determined whether the communication of all information flows between the i-th signal concentrator and the first to the n-th device terminals is normal, and finally determine the authenticity of the real-time information flow obtained by the lighting device digital twin system at the communication node of the signal concentrator.

[0099] By calculating the floating of the second error range T Δ the size of the second error range under normal conditions can be determined. Based on the actual values of all information flows between the signal concentrator and the server and the theoretical value T 和 of all information flows between the signal concentrator and the server, by calculating the difference, it can be determined whether the difference is within the second error range T Δ内 Therein, it can be further determined whether the communication of all information flows between the signal concentrator and the server is normal, and finally determine the authenticity of the real-time information flow of the lighting device digital twin system itself.

[0100] This application provides a data model construction system for lighting devices.

[0101] As Figure 2 shown, in an embodiment of this application, a data model construction system for lighting devices includes a server 100, a signal concentrator 200, and a device terminal 300.

[0102] The server 100 is used to execute the data model construction method for lighting devices mentioned in any of the foregoing embodiments.

[0103] The signal concentrator 200 is communicatively connected to the server 100.

[0104] The device terminal 300 is communicatively connected to the signal concentrator 200.

[0105] This embodiment relates to a data model construction system for lighting equipment. The server 100 manages the signal concentrator 200 and the device terminal 300 through the Internet of Things device management platform. The Internet of Things devices include the signal concentrator 200 and the device terminal 300, which can monitor whether the communication channels between the signal concentrator 200 and the device terminal 300, and between the signal concentrator 200 and the server 100 itself are smooth. The server 100 can determine the communication speed of the communication connection between the device terminal 300 and the signal concentrator 200 using the information transmission rate formula, and can also determine the communication speed of the communication connection between the signal concentrator 200 and the server 100 itself. Based on the comparison between the actual communication speed and the theoretical communication speed, the authenticity of real-time information can be determined. Specifically, the server 100 itself has an Internet of Things device management platform. By implementing the communication quality monitoring of Internet of Things devices based on the Internet of Things device management platform, the authenticity of the real-time information flow obtained by the lighting equipment digital twin system can be determined. When the difference between the actual communication speed and the theoretical communication speed is large, it can be determined that the authenticity of the real-time information flow obtained by the lighting equipment digital twin system is low. When the difference between the actual communication speed and the theoretical communication speed is small, it can be determined that the authenticity of the real-time information flow obtained by the lighting equipment digital twin system is high.

[0106] The technical features of the above-described embodiments can be combined arbitrarily, and there is no limitation on the execution order of the method steps. For the sake of brevity of description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0107] The above-described embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for constructing a data model of a lighting device, characterized in that, Including: Establish an Internet of Things device management platform; the Internet of Things devices include signal concentrators and device terminals; The device terminals are communicatively connected to the signal concentrators, and the signal concentrators are used to send information to the Internet of Things device management platform; Select all information flows of a signal concentrator; Based on the information transmission rate formula, determine the theoretical time delay of all information flows of the signal concentrator; Judge whether the difference between the actual time delay of all information flows of the signal concentrator and the theoretical time delay of all information flows of the signal concentrator is within the error range; If the difference between the actual time delay of all information flows of the signal concentrator and the theoretical time delay of all information flows of the signal concentrator is within the error range, return to select all information flows of a signal concentrator until all signal concentrators are selected; If the difference between the actual time delay of all information flows of the signal concentrator and the theoretical time delay of all information flows of the signal concentrator is not within the error range, issue a warning message, return to select all information flows of a signal concentrator until all signal concentrators are selected.

2. The method for constructing a data model of the lighting device according to claim 1, characterized in that, The establishment of the Internet of Things device management platform includes: Receive the IP address of the signal concentrator; Based on the IP address of the signal concentrator, establish a network connection with the signal concentrator; Send a test data packet to the signal concentrator; Determine the data transmission rate parameter and data delay parameter of the signal concentrator.

3. The method for constructing a data model of the lighting device according to claim 2, wherein The establishment of the Internet of Things device management platform further includes: Receive the IP data table sent by the signal concentrator; the IP data table includes the IPs of all device terminals; Select the IP of a device terminal; Send an instruction to enable the Ping program to the signal concentrator; Receive the data transmission rate parameter and data delay parameter corresponding to the IP of the device terminal; Return to select the IP of a device terminal until all device terminals are selected.

4. The method for constructing a data model of the lighting device according to claim 3, wherein After the establishment of the Internet of Things device management platform, it includes: Based on the IP data table, call the processor data processing rate and maximum computing power of each device terminal; Call the parameter of the transmission bandwidth of each signal concentrator; Based on the processor data processing rate of each device terminal and the parameter of the transmission bandwidth of each signal concentrator, establish an information transmission rate formula.

5. The method for constructing a data model of a lighting device according to claim 4, wherein: The information transmission rate formula is: K(f ij )CPU ij ≤G ij Among them, L ij is the information transmission time between the i-th signal concentrator and the j-th device terminal, K(f ij ) is the data volume between the i-th signal concentrator and the j-th device terminal, R ij is the transmission bandwidth among the i-th signal concentrator, the j-th device terminal and the server, CPU ij is the processor data processing rate of the i-th signal concentrator and the j-th device terminal, G ij is the maximum computing power of the i-th signal concentrator and the j-th device terminal.

6. The method for constructing a data model of the lighting device according to claim 5, characterized in that, After establishing the information transmission rate formula based on the processor data processing rate of each device terminal and the parameter of the transmission bandwidth of each signal concentrator, the method further includes: Obtain the error range of the theoretical time delay of all information flows of the signal concentrator; The obtaining of the error range of the theoretical time delay of all information flows of the signal concentrator includes: Obtain the first error range of the theoretical time delay of all information flows between a single signal concentrator and a device terminal; Obtain the second error range of the theoretical time delay of all information flows between the signal concentrator and the server; Define the working state of the communication failure between the signal concentrator and the device terminal as that the difference between the actual time delay of the information flow between the signal concentrator and the device terminal and the theoretical time delay of the information flow between the signal concentrator and the device terminal exceeds the first error range; Define the working state of the communication failure between the signal concentrator and the server as that the difference between the actual time delay of the information flow between the signal concentrator and the server and the theoretical time delay of the information flow between the signal concentrator and the server exceeds the second error range.

7. The method for constructing a data model of the lighting device according to claim 6, wherein The obtaining of the first error range of the theoretical time delay of all information flows between a single signal concentrator and a device terminal includes: Calculating the first error range according to the following formula: i is a real integer i is a real integer T Δi = T 2i - T 1i i ∈ [1, N], i is a real integer Among them, T 1i is the minimum theoretical time delay of all information flows between the i-th signal concentrator and the first to the n-th device terminals, and T 2i is the maximum theoretical time delay of all information flows between the i-th signal concentrator and the first to the n-th device terminals, and T Δi is the first error range.

8. The method for constructing a data model of the lighting device according to claim 7, characterized in that, The obtaining of the second error range of the theoretical time delay of all information flows between the signal concentrator and the server includes: Calculating the second error range according to the following formula: T Δ = T4 - T3 Among them, T3 is the minimum theoretical time delay of all information flows between the signal concentrator and the server, T4 is the maximum theoretical time delay of all information flows between the signal concentrator and the server, and T Δ is the second error range.

9. The method for constructing a data model of the lighting device according to claim 8, characterized in that The judging whether the difference between the actual time delay of all information flows of the signal concentrator and the theoretical time delay of all information flows of the signal concentrator is within the error range includes: Select a signal concentrator; Receive all information flows of the signal concentrator; Determine the actual time delay of all information flows between the signal concentrator and the device terminal; Return to the step of selecting a signal concentrator until all signal concentrators are selected; Based on the actual time delay of all information flows between each signal concentrator and the device terminal, determine the actual time delay of all information flows between the server itself and all signal concentrators.

10. A data model construction system for a lighting device, characterized in that, It includes: A server for executing the data model construction method of the lighting device according to any one of claims 1 to 9; A signal concentrator communicatively connected to the server; A device terminal communicatively connected to the signal concentrator.

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