Urban lighting control method and system based on distributed illuminance and storage medium

Abstract

The invention discloses an urban lighting control method and system based on distributed illuminance and a storage medium. The method comprises the following steps: dividing a city preset illumination area, and collecting illuminance and meteorological data of each illumination sub-area; analyzing the illuminance data and generating an urban real-time illuminance field; comparing whether the illuminance of each illumination sub-region is lower than a preset illuminance threshold of the illuminance of the corresponding region or not to determine the illumination sub-regions to be regulated and controlled, and distinguishing adjacent or independent illumination sub-regions in the illumination sub-regions to be regulated and controlled; for each independent illumination sub-region, correspondingly generating a first regulation and control instruction to complete illumination intensity adjustment of the illumination sub-region; clustering is carried out on the adjacent illumination sub-regions, and a linkage region is determined; acquiring illuminance compensation values of adjacent areas in the linkage area by using an illuminance compensation neural network model; and obtaining a linkage area illuminance adjustment scheme by using a multi-objective optimization algorithm, and generating a second regulation and control instruction to complete linkage area illuminance adjustment and control. According to the invention, fine management of urban lighting can be realized.

Description

Technical Field

[0001] The present application relates to the technical field of urban lighting control, and in particular to a method, system and storage medium for urban lighting control based on distributed illuminance. Background Art

[0002] Smart city lighting management systems have developed rapidly in recent years. Through the application of intelligent control technology, it has not only improved the overall image of the city, but also effectively reduced energy consumption. Traditional urban lighting control methods mainly rely on manual intervention or simple time switches. With the advancement of information technology, intelligent lighting control systems based on sensor networks have gradually become a research hotspot. This type of system monitors the illuminance and other environmental parameters of various areas of the city in real time to achieve dynamic regulation of lighting equipment, thereby achieving energy saving and improving lighting quality.

[0003] In order to achieve more accurate lighting control, two main solutions are usually adopted in the existing technology: one is time switch control, and the other is illumination control based on central node sensors. Time switch control is to control the opening and closing of street lights through a preset schedule. This method is simple and easy to use, but it cannot adapt to the changes in natural light in different seasons and weather conditions. Another common method is to install sensors in the central area of ​​the city, and use the data collected by these sensors to determine the lighting status of the entire city, thereby achieving automated control to a certain extent.

[0004] However, both of the above methods have certain limitations. The timer switch control cannot flexibly respond to changes in natural light, which easily leads to a waste of lighting resources. The control strategy based on the central node sensor is difficult to accurately reflect the lighting conditions in a large area due to insufficient sensor deployment, which affects the precision of regulation. Therefore, how to achieve more efficient energy management and more accurate lighting control while ensuring the lighting effect has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] In order to respond to changes in light intensity in local areas, complete lighting regulation in a timely and accurate manner, avoid energy waste, and achieve refined management of urban lighting, the present application provides an urban lighting control method, system and storage medium based on distributed illuminance.

[0006] In a first aspect, the present application provides an urban lighting control method based on distributed illuminance, comprising: Divide the scope of urban lighting areas, deploy light intensity sensors and meteorological sensors in each divided lighting sub-area, and collect light intensity data and meteorological data of each lighting sub-area; Use big data analysis algorithms to analyze the collected illuminance data of each lighting sub-area and generate a real-time illuminance field for the city; Monitor the generated real-time urban illumination field, compare whether the illumination of each lighting sub-area is lower than the preset illumination threshold of the illumination of the corresponding area, and dynamically match and adjust the preset illumination threshold of the illumination of each area according to the climate data in different time periods; obtain the lighting sub-area whose illumination is lower than the preset illumination threshold of the illumination of the corresponding area, record it as the lighting sub-area to be regulated, and statistically distinguish the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be regulated; the illumination of each lighting sub-area refers to the average illumination; For each independent lighting sub-area, a first control instruction is correspondingly generated so that the lighting equipment in the lighting sub-area adjusts the illumination of the lighting sub-area to a preset illumination threshold of the illumination of the corresponding area according to the first control instruction; Adjacent lighting sub-areas are clustered, and adjacent lighting sub-areas belonging to the same category are regionally linked and recorded as linked areas; a light intensity compensation neural network model is used to obtain the light intensity compensation value of the adjacent areas in the linked area during the process of gradually adjusting the light intensity of each area in the linked area to the preset light intensity threshold of the corresponding area; a multi-objective optimization algorithm is used to obtain the light intensity adjustment plan of the linked area by combining the light intensity of each area in the linked area, the preset light intensity threshold of the corresponding area of ​​each area, and the compensation value of the adjacent areas in the linked area during the process of adjusting the light intensity of each area to the preset light intensity threshold of the corresponding area, so that the light intensity of each area in the linked area reaches the preset light intensity threshold of the corresponding area and the adjustment energy consumption is minimized; a second control instruction is generated according to the light intensity adjustment plan of the linked area so that the lighting equipment in the linked area completes the light intensity adjustment control of the linked area according to the second control instruction.

[0007] By adopting the above scheme, the lighting areas are divided and illuminance sensors are deployed to collect illuminance data, and a distributed illuminance field is constructed to accurately respond to the actual lighting needs of each area. The regional illuminance is dynamically adjusted by combining multimodal data such as different time periods and climate data to achieve the optimal regional illuminance standard and ensure user needs. At the same time, the impact of regional illuminance adjustment on the illuminance of adjacent areas is considered in combination with the geographical location and historical illuminance of the lighting equipment. The multi-objective optimization algorithm is used in combination with the illuminance compensation neural network model to obtain the illuminance compensation value, so as to minimize energy consumption while ensuring the lighting effect.

[0008] Preferably, it also includes: The camera device installed in each lighting sub-area to be regulated is used to collect and obtain the historical crowd density in the corresponding area in real time, and the regional unit with the largest crowd density in the corresponding area in the recent period of time is statistically obtained; For each independent lighting sub-area counted, a first control instruction is generated accordingly so that the lighting equipment in the lighting sub-area adjusts the illuminance of the lighting sub-area to the preset illuminance threshold of the corresponding area according to the first control instruction, and the lighting equipment at the location of the statistically obtained area unit is the adjustment object; According to the linkage area illumination adjustment plan, a second control instruction is generated correspondingly so that the lighting equipment in the linkage area completes the linkage area illumination adjustment control process according to the second control instruction, and the lighting equipment at the location of the area unit corresponding to each area of ​​the linkage area obtained by statistics is taken as the adjustment object.

[0009] By adopting the above solution, when adjusting the lighting equipment of independent lighting sub-areas and linkage areas to achieve optimal illumination, adjustments are focused on regional units with high pedestrian density, thereby avoiding energy waste caused by excessive lighting in areas with low pedestrian density and achieving reasonable allocation of lighting resources.

[0010] Preferably, before comparing whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, it also includes: determining whether the illuminance of the lighting sub-area was adjusted at the last moment; If not performed, then compare the illuminance of each lighting sub-area at the current moment with the illuminance of the lighting sub-area at the previous moment in advance; if the difference between the two is less than the preset difference, then continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; if the difference between the two is greater than the preset difference, then temporarily stop continuing to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; when it is determined that the illuminance at the next moment is still lower than the preset illuminance threshold of the corresponding area, continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; If so, continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be adjusted.

[0011] By adopting the above solution, taking into account the possibility that the real-time collected illuminance may be lower than the preset illuminance threshold of the regional illuminance due to sudden reasons such as voltage instability, in order to avoid such unnecessary adjustments, when it is determined that no illuminance adjustment was made at the previous moment, the illuminance at the previous moment is compared to decide whether to make real-time adjustments, thereby improving the stability and energy efficiency of the system.

[0012] Preferably, after using the illumination compensation neural network model to obtain the illumination compensation value of the adjacent area in the linkage area in the process of gradually adjusting the illumination of each area in the linkage area to the preset illumination threshold of the illumination of the corresponding area, using a multi-objective optimization algorithm, combined with the illumination of each area in the linkage area, the preset illumination threshold of the illumination of each area corresponding to the area, and the compensation value of the adjacent area in the linkage area in the process of adjusting the illumination of each area to the preset illumination threshold of the illumination of the corresponding area, before obtaining the illumination adjustment plan of the linkage area, it also includes: comparing whether the illumination compensation value of the adjacent area in the linkage area is less than the preset illumination compensation value, if so, setting the obtained illumination compensation value to 0; otherwise, retaining the currently obtained illumination compensation value.

[0013] By adopting the above solution, in the process of adjusting the illumination of the linked area, the illumination compensation values ​​of the adjacent areas are screened to ensure that actual compensation is performed only when the compensation value exceeds the preset value, thereby ensuring the best lighting effect for the area and achieving more refined and efficient lighting control.

[0014] Preferably, it also includes: According to the real-time illumination field of the city generated by monitoring, it is determined that the illumination of each lighting sub-area does not fall below the preset illumination threshold of the illumination of the corresponding area, and then the illumination of each lighting sub-area in the future is obtained by using the big data analysis algorithm for analysis and prediction, and the real-time illumination field of the city in the future is generated accordingly; Predict the meteorological data for a period of time in the future based on the meteorological data collected in real time, and determine the preset illumination threshold of the corresponding regional illumination for a period of time in the future by combining the predicted meteorological data with the information of the future time period; determine whether there is a lighting sub-area whose illumination is lower than the preset illumination threshold of the corresponding regional illumination for a period of time in the future based on the predicted real-time illumination field of the city for a period of time in the future; if so, determine the corresponding lighting sub-area to be regulated, continue to statistically distinguish the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be regulated, and complete the regional illumination adjustment control according to the statistical distinction results.

[0015] By adopting the above solution, in the process of adjusting the illumination of the linked area, the illumination compensation values ​​of the adjacent areas are screened to ensure that actual compensation is performed only when the compensation value exceeds the preset value, thereby ensuring the best lighting effect for the area and achieving more refined and efficient lighting control.

[0016] Preferably, it also includes: According to the real-time illumination field of the city generated by monitoring, it is determined that the illumination of each lighting sub-area does not fall below the preset illumination threshold of the illumination of the corresponding area, and then the illumination of each lighting sub-area in the future is obtained by using the big data analysis algorithm for analysis and prediction, and the real-time illumination field of the city in the future is generated accordingly; Predict the meteorological data for a period of time in the future based on the meteorological data collected in real time, and determine the preset illumination threshold of the corresponding regional illumination for a period of time in the future by combining the predicted meteorological data with the information of the future time period; determine whether there is a lighting sub-area whose illumination is lower than the preset illumination threshold of the corresponding regional illumination for a period of time in the future based on the predicted real-time illumination field of the city for a period of time in the future; if so, determine the corresponding lighting sub-area to be regulated, continue to statistically distinguish the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be regulated, and complete the regional illumination adjustment control according to the statistical distinction results.

[0017] By adopting the above solution, not only can unnecessary lighting adjustments be avoided and energy be saved when the current light intensity meets the demand, but also reasonable lighting control decisions can be made in advance through the prediction of future light intensity and analysis of meteorological data, further improving the intelligence level and energy efficiency of the system.

[0018] Preferably, it also includes: Determine whether a request information for a regional light intensity preset illumination threshold value set by a user is received; if received, compare the size of the regional light intensity preset illumination threshold value requested by the user with the regional light intensity safety illumination threshold value, if it is less than, ignore the user request, if it is greater than or equal to, replace the regional light intensity preset illumination threshold value corresponding to different time periods and climate data with the regional light intensity preset illumination threshold value set by the user; wherein, each area is set with a regional light intensity safety illumination threshold value.

[0019] By adopting the above solution, the function of users defining preset illumination thresholds for regional illumination is realized, which enhances the flexibility and personalized configuration capability of the system. At the same time, the regional illumination safety illumination threshold is introduced to ensure that even when the user sets a lower illumination threshold, basic safety lighting needs are met to avoid safety hazards caused by too low illumination.

[0020] Preferably, it also includes: When dividing the scope of urban lighting areas, the type of each lighting sub-area is determined according to the location of each lighting sub-area; according to the type corresponding to each lighting sub-area, a corresponding number of light intensity sensors of the corresponding type are set and evenly deployed in each divided lighting sub-area; wherein the types of lighting sub-areas include: commercial area type, residential area type and public facility area type, and each type is matched with a corresponding number of light intensity sensors.

[0021] By adopting the above solution, considering that different types of areas have different requirements for illumination, a reasonable configuration of the number of sensors can avoid waste of resources, improve the economy of the overall system, and achieve more fine-grained lighting control.

[0022] In a second aspect, the present application provides an urban lighting control system based on distributed illuminance, comprising: A lighting area data acquisition module is preset to divide the scope of urban lighting areas, deploy light intensity sensors and meteorological sensors in each divided lighting sub-area, and collect and obtain light intensity data and meteorological data of each lighting sub-area; A real-time illumination field acquisition module for preset lighting areas is used to analyze the collected illumination data of each lighting sub-area using a big data analysis algorithm to generate a real-time illumination field for the city; The module for determining the lighting sub-areas to be regulated is used to monitor the generated real-time urban illuminance field, compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, and dynamically match and adjust the preset illuminance threshold of each area according to the climate data in different time periods; obtain the lighting sub-areas whose illuminance is lower than the preset illuminance threshold of the corresponding area, record them as the lighting sub-areas to be regulated, and statistically distinguish the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be regulated; the illuminance of each lighting sub-area refers to the average illuminance; The lighting sub-area control module to be controlled is used to generate a first control instruction for each independent lighting sub-area so that the lighting equipment in the lighting sub-area adjusts the illumination of the lighting sub-area to a preset illumination threshold of the corresponding area according to the first control instruction; Adjacent lighting sub-areas are clustered, and adjacent lighting sub-areas belonging to the same category are regionally linked and recorded as linked areas; a light intensity compensation neural network model is used to obtain the light intensity compensation value of the adjacent areas in the linked area during the process of gradually adjusting the light intensity of each area in the linked area to the preset light intensity threshold of the corresponding area; a multi-objective optimization algorithm is used to obtain the light intensity adjustment plan of the linked area by combining the light intensity of each area in the linked area, the preset light intensity threshold of the corresponding area of ​​each area, and the compensation value of the adjacent areas in the linked area during the process of adjusting the light intensity of each area to the preset light intensity threshold of the corresponding area, so that the light intensity of each area in the linked area reaches the preset light intensity threshold of the corresponding area and the adjustment energy consumption is minimized; a second control instruction is generated according to the light intensity adjustment plan of the linked area so that the lighting equipment in the linked area completes the light intensity adjustment control of the linked area according to the second control instruction.

[0023] By adopting the above scheme, the illuminance and meteorological data of each lighting sub-area are collected in real time, and the big data analysis algorithm is used to generate the real-time urban illuminance field. The real-time illuminance field is monitored and combined with meteorological data and other data to complete the adjustment of the preset illuminance threshold of the optimal illuminance in each area, thereby realizing the comprehensive intelligent management of the urban lighting control system based on distributed illuminance. At the same time, the linkage control of adjacent areas is intelligently identified and processed, and the lowest energy consumption adjustment of illuminance in the linkage area is realized through the illuminance compensation neural network model and multi-objective optimization algorithm, thereby further improving the energy efficiency ratio of the system.

[0024] In a third aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method as described above.

[0025] In a fourth aspect, the present application provides a computer device, comprising a memory, a processor, and a program stored and executable on the memory, wherein the program implements the steps of the above method when executed by the processor.

[0026] In summary, this application has the following beneficial effects: 1. Divide the urban lighting range and widely deploy the illuminance sensor network to monitor the illuminance data of each lighting sub-area in real time, forming a high-precision distributed illuminance field, improving the accuracy and response speed of lighting control; dynamically adjust the preset illuminance threshold of each area in combination with different time periods and meteorological data to ensure that the lighting demand matches the actual lighting conditions, guarantee the urban lighting effect, and achieve energy-saving goals; consider the impact of the illuminance adjustment process of each adjacent lighting sub-area, introduce the illuminance compensation mechanism in combination with the neural network, and use the multi-objective optimization algorithm to optimize the illuminance adjustment plan of the linkage area, ensuring that the illuminance of each area in the linkage area meets the preset standard and the adjustment energy consumption is minimized, further improving energy efficiency; 2. Through real-time collection and statistics of historical crowd density in the lighting sub-area to be regulated, the regional units with high crowd density in the lighting sub-area are identified, and the lighting equipment of these regional units is adjusted first when adjusting the lighting equipment of independent lighting sub-areas and linkage areas, thus realizing the reasonable allocation of lighting resources; 3. Through the prediction of future illuminance and analysis of meteorological data, it is predicted that the illuminance needs to be adjusted in the future, and reasonable lighting control decisions can be made in advance, further improving the intelligence and energy efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a flow chart of the urban lighting control method based on distributed illuminance described in a specific embodiment; Figure 2 It is a schematic diagram of the structure of the urban lighting control system based on distributed illumination in a specific embodiment. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0029] like Figure 1 As shown, the embodiment of the present application discloses a method for controlling urban lighting based on distributed illuminance, and the specific steps include: S1. Divide the urban lighting area and collect the illuminance data and meteorological data in each divided lighting sub-area.

[0030] Specifically, the scope of urban lighting areas is divided, such as N preset lighting areas; a number of light intensity sensors, meteorological sensors, cameras and other equipment are deployed in each divided lighting sub-area, such as M light intensity sensors and P meteorological sensors.

[0031] The above deployed sensors are evenly distributed in each lighting sub-area. The deployed sensors and devices are used to collect and obtain the illuminance data and meteorological data of each lighting sub-area in a regular or real-time manner according to user needs; the illuminance data includes: location information, light field range, illuminance, time and elevation, etc.; the meteorological data includes: temperature, humidity and light intensity, etc.

[0032] In addition, considering that different types of areas (such as commercial areas, residential areas, and public facilities areas) have different requirements for lighting, a reasonable configuration of the number of sensors can avoid waste of resources and accurately complete regional lighting control. Therefore, when dividing the scope of urban lighting areas, the type of each lighting sub-area can be determined according to the location of each lighting sub-area; wherein the types of lighting sub-areas include: commercial area type, residential area type, and public facilities area type, etc.; according to the type corresponding to each lighting sub-area, a corresponding number of light intensity sensors matching the corresponding type is set, and evenly deployed in each divided lighting area; each type of lighting sub-area corresponds to a number of light intensity sensors matching it, such as: M1 light intensity sensors matching the commercial area type, M2 light intensity sensors matching the residential area type, and M3 light intensity sensors matching the public facilities area type.

[0033] S2. Use big data analysis algorithms to analyze the collected illuminance data of each lighting sub-area and generate a real-time urban illuminance field.

[0034] Specifically, first, the illuminance data of each lighting sub-area collected in real time is cleaned and preprocessed to remove abnormal data and noise data in the illuminance data, and interpolate the missing data; secondly, the location data and timestamp of each sensor are combined to align the spatiotemporal data, and then the illuminance distribution of each sensor at each location in each lighting sub-area is analyzed in real time, and the real-time illuminance field of the city is generated by integrating the illuminance distribution of all lighting sub-areas.

[0035] In addition, in order to further intuitively display the lighting conditions in various areas of the city and help decision makers better understand the current lighting distribution status, the illumination data of each sub-area is visualized as an illumination map; the illumination map is set as a dynamic, interactive visualization interface, which represents the illumination level of each area through different colors or brightness.

[0036] S3. Monitor the generated real-time urban illumination field, determine the lighting sub-areas to be regulated and perform statistical differentiation.

[0037] Specifically, the real-time urban illuminance field generated by monitoring is compared, the illuminance of each lighting sub-area is compared with the preset illuminance threshold of the corresponding area, and it is determined whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, and then the lighting sub-area to be regulated is determined, that is, the lighting sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area is obtained, and it is recorded as the lighting sub-area to be regulated.

[0038] The illuminance of each lighting sub-area refers to the illuminance value or average illuminance at a specific position in the lighting sub-area. In this embodiment, the average illuminance collected by multiple illuminance sensors in each lighting sub-area is used as the illuminance of the lighting sub-area.

[0039] The preset illumination threshold of the regional illumination corresponding to each lighting sub-area is dynamically matched and adjusted according to different time periods and meteorological data; for example, the preset illumination threshold of the illumination during the day is set higher, while it is relatively low at night; the preset illumination threshold of the illumination on foggy days is set higher, while it is relatively low on sunny days. For each time period and meteorological data, there is a corresponding optimal preset illumination threshold of illumination. Specifically, the optimal historical illumination preset illumination threshold is determined by combining the weighted results of user satisfaction feedback data and power consumption feedback data under different historical illumination conditions under the same historical time period and meteorological data. A training database is established based on the historical illumination preset illumination threshold, historical time period and meteorological data, and a neural network model is designed for training to obtain the preset illumination threshold of illumination that dynamically matches different time periods and meteorological data.

[0040] Taking into account that the illumination adjustments of adjacent lighting sub-areas will affect each other, the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be adjusted are statistically distinguished; wherein, the adjacent lighting sub-areas are clustered according to their positions, and the adjacent lighting sub-areas belonging to the same category are regionally linked and recorded as linked areas.

[0041] S4. Perform regional illumination adjustment control for the lighting sub-area to be regulated.

[0042] Specifically, for each independent lighting sub-area, a first control instruction is generated accordingly; the first control instruction includes: a first control start instruction and a first control end instruction; the first control start instruction is sent to the lighting equipment in the lighting sub-area, and the lighting equipment in the lighting sub-area that receives the first control start instruction starts to adjust its own light intensity, and uses the illuminance sensor in the lighting sub-area to monitor until the illuminance in the lighting sub-area reaches the preset illuminance threshold of the corresponding area, and then the first control stop instruction is sent to the lighting equipment in the lighting sub-area, and the lighting equipment in the lighting sub-area that receives the first control stop instruction stops adjusting its own light intensity, thereby completing the adjustment control of the illuminance of the lighting sub-area to the preset illuminance threshold of the corresponding area.

[0043] For each linkage area, before generating the corresponding second control instruction, the illumination compensation neural network model is used in advance to obtain the illumination compensation value of the adjacent area in the linkage area during the process of gradually adjusting the illumination of each area in the linkage area to the preset illumination threshold of the illumination of the corresponding area; the illumination compensation neural network model is iteratively trained and generated through the historical illumination of each area in the linkage area, the historical target illumination during the process of adjusting to the preset illumination threshold of the illumination of the corresponding area, and the historical illumination compensation value of each adjacent area in the linkage area during the process of adjusting the illumination of each area to the preset illumination threshold of the illumination of the corresponding area; wherein, each area in the linkage area refers to each lighting sub-area in the linkage area.

[0044] Specifically, the process of adjusting the current illuminance of each area to the preset illuminance threshold of the corresponding area illuminance can be divided into several adjustment steps, and the illuminance corresponding to each divided adjustment step is used as the target area illuminance. For each adjustment step, the current illuminance and the target illuminance are input into the illuminance compensation neural network model to obtain the illuminance compensation value for each adjacent area in the linkage area. Among them, the illuminance adjustment of the same area has different effects on the illuminance adjustment of the adjacent areas. In this embodiment, the illuminance of a single area is adjusted to the specified area unit position.

[0045] After obtaining the illumination compensation value of the adjacent area in the linkage area in the process of gradually adjusting the illumination of each area in the linkage area to the preset illumination threshold of the illumination of the corresponding area, a multi-objective optimization algorithm is used to combine the illumination of each area in the linkage area, the preset illumination threshold of the illumination of each area corresponding to the area, and the compensation value of the adjacent area in the linkage area in the process of adjusting the illumination of each area to the preset illumination threshold of the illumination of the corresponding area, to obtain the linkage area illumination adjustment plan so that the illumination of each area in the linkage area reaches the preset illumination threshold of the illumination of the corresponding area and the adjustment energy consumption is minimized.

[0046] For example, the current linkage area is A, B, and C, where the current illuminance of area A is A1, and the corresponding regional illuminance preset illuminance threshold is A2; where the target illuminance during the adjustment from A1 to A2 is Ax, Ax can be multiple values, and the compensation values ​​for the adjacent areas in the linkage area during the adjustment from A1 to A2 are Bx and Cx; similarly, the current illuminance of area B is B1, and the corresponding regional illuminance preset illuminance threshold is B2; where the transition target illuminance during the adjustment from B1 to B2 is By, By can be multiple values, and the compensation values ​​for the adjacent areas in the linkage area during the adjustment from B1 to B2 are Ay and Cy; similarly, the current illuminance of area C is C1, and the corresponding regional illuminance preset illuminance threshold is C2; where the transition target illuminance during the adjustment from C1 to C2 is Cz, Cz can be multiple values, and the compensation values ​​for the adjacent areas in the linkage area during the adjustment from C1 to C2 are Az and Bz; a multi-objective optimization algorithm is used to construct a multi-objective optimization function to obtain:

[0047] Wherein, P represents energy consumption, a represents the energy consumption conversion coefficient corresponding to the adjusted illuminance of area A from A1 to Ax, b represents the energy consumption conversion coefficient corresponding to the adjusted illuminance of area B from B1 to By, and c represents the energy consumption conversion coefficient corresponding to the adjusted illuminance of area C from C1 to Cz; Wherein, , as well as , , as well as is an unknown number, you can traverse the combination and substitute it, traverse the combination ( , , ) The corresponding illumination compensation neural network model can be used to obtain the corresponding Bx and Cx, Ay and Cy, and Az and Bz, and finally solve the optimal combination solution, which is used as the adjustment plan.

[0048] A second control instruction is generated in accordance with the linkage area illumination adjustment plan, wherein the second control instruction includes: a second control start instruction, a second control end instruction, and adjustment parameters corresponding to the optimal combination solution; the second control start instruction is sent to the lighting equipment in each lighting sub-area of ​​the linkage area, and the lighting equipment in each lighting sub-area that receives the second control start instruction starts to adjust its own light intensity, and uses the illumination sensor in the lighting sub-area to monitor until the illumination in the lighting sub-area reaches the illumination value of the area corresponding to the optimal combination solution. A second control stop instruction is sent to the lighting equipment in the lighting sub-area, and the lighting equipment in the lighting sub-area that receives the second control stop instruction stops adjusting its own light intensity, and completes the adjustment control of the illumination of the lighting sub-area to the preset illumination threshold of the illumination of the corresponding area, so that the lighting equipment in the linkage area completes the illumination adjustment control of the linkage area in accordance with the second control instruction.

[0049] In addition, considering that when the illumination adjustment of a certain area has a small impact on the illumination of the adjacent area, the current impact can be ignored, and the illumination of the adjacent area can be adjusted to the preset illumination threshold of the illumination of the corresponding area as much as possible; therefore, after using the illumination compensation neural network model to obtain the illumination compensation value of the adjacent area in the linkage area in the process of gradually adjusting the illumination of each area in the linkage area to the preset illumination threshold of the illumination of the corresponding area, a multi-objective optimization algorithm is used to combine the illumination of each area in the linkage area, the preset illumination threshold of the illumination of each area corresponding to the area, and the compensation value of the adjacent area in the linkage area in the process of adjusting the illumination of each area to the preset illumination threshold of the illumination of the corresponding area, before obtaining the illumination adjustment plan of the linkage area, it also includes: comparing whether the illumination compensation value of the adjacent area in the linkage area is less than the preset illumination compensation value, if less, setting the obtained illumination compensation value to 0; otherwise, retaining the currently obtained illumination compensation value.

[0050] In summary, through the distributed light sensor network, the light intensity and meteorological data of various areas of the city are monitored in real time to generate a real-time urban light intensity field; using big data analysis algorithms and multi-objective optimization algorithms, the light intensity of each area is dynamically adjusted to achieve precise control and energy-saving goals, thereby improving the level of refined management of lighting control, effectively coping with complex lighting environments, and ensuring lighting quality and user experience.

[0051] In a specific embodiment, when adjusting the lighting equipment of the independent lighting sub-areas and the linkage area, in order to ensure the reasonable allocation of lighting resources, the adjustment is focused on the area units with high pedestrian density, thereby avoiding energy waste caused by excessive lighting in areas with low pedestrian density; the method also includes: The camera device in each lighting sub-area to be regulated is used to collect and obtain the historical crowd density in the corresponding area in real time, and the regional unit with the largest crowd density in the corresponding area in the recent historical period is statistically obtained; the specific duration of the recent historical period can be set according to human needs.

[0052] For each independent lighting sub-area counted, a first control instruction is generated accordingly so that the lighting equipment in the lighting sub-area adjusts the illuminance of the lighting sub-area to the preset illuminance threshold of the corresponding area according to the first control instruction. In the process, the lighting equipment at the location of the statistically obtained area unit is the adjustment object; that is, the first control start instruction and the first control stop instruction are sent to the lighting equipment at the location of the area unit with the largest crowd density statistically obtained in the lighting sub-area, and the adjustment control of the illuminance of the lighting sub-area to the preset illuminance threshold of the corresponding area is completed accordingly.

[0053] In accordance with the linkage area illumination adjustment plan, a second control instruction is generated correspondingly so that the lighting equipment in the linkage area completes the linkage area illumination adjustment control according to the second control instruction. In the process, the lighting equipment at the location of the area unit corresponding to each area of ​​the linkage area obtained by statistics is the adjustment object; that is, the second control start instruction and the second control stop instruction are sent to the lighting equipment at the location of the area unit with the largest pedestrian density obtained by statistics in each lighting sub-area of ​​the linkage area, so as to complete the linkage area illumination adjustment control accordingly.

[0054] In addition, regarding how the lighting devices in the lighting sub-area that have received the first control start instruction start to adjust their own light intensity, it is possible to choose to make uniform adjustments based on the performance of each lighting device in the regional unit, and to increase the light intensity of the same value simultaneously, and when the maximum light intensity threshold of the corresponding lighting device is reached, reduce or do not adjust the light intensity of the corresponding lighting device until the illuminance in the lighting sub-area reaches the preset illuminance threshold of the corresponding regional illuminance. Similarly, regarding how the lighting devices in each lighting sub-area that have received the second control start instruction start to adjust their own light intensity, it is possible to choose to make uniform adjustments based on the performance of each lighting device in the regional unit corresponding to the corresponding lighting sub-area in the linkage area, and to increase the light intensity of the same value simultaneously, and when the maximum light intensity threshold of the corresponding lighting device is reached, reduce or do not adjust the light intensity of the corresponding lighting device until the illuminance in the lighting sub-area reaches the illuminance value of the corresponding regional illuminance of the optimal combination solution.

[0055] In a specific embodiment, considering that the illuminance of some lighting sub-areas is lower than the preset illuminance threshold of the corresponding area due to external sudden reasons such as unstable voltage of lighting equipment, in order to avoid unnecessary frequent adjustments caused by such reasons and further improve the stability and energy efficiency of lighting control, the method further includes: Before comparing whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, the method further includes: determining whether the illuminance of the lighting sub-area was adjusted at the last moment; If not, it indicates that the illuminance at the current moment is roughly the same as that at the previous moment, then the illuminance of each lighting sub-area at the current moment is compared with the illuminance of the lighting sub-area at the previous moment in advance; if the difference between the two is less than the preset difference, then continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; if the difference between the two is greater than the preset difference, it is highly likely that an emergency has occurred in the lighting equipment, and the operation is temporarily stopped. Continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; when it is determined that the illuminance at the next moment is still lower than the preset illuminance threshold of the corresponding area, that is, it is not an emergency, continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; If so, continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be adjusted.

[0056] In addition, comprehensive consideration is given to the fact that meteorological data generally will not change too quickly over a period of time; therefore, on the basis of judging the illuminance at each moment compared to the previous moment, the illuminance of the lighting sub-area is adjusted. If, for the first period of time starting from the current moment, the illuminance judgment result for the same lighting sub-area continues to be lower than the preset illuminance threshold of the corresponding area, it is determined that there is a fault in the control of the lighting equipment in the lighting sub-area, a prompt message is generated and the control is suspended.

[0057] In a specific embodiment, when the current illuminance meets the demand, there is no need to adjust the lighting. By predicting the future illuminance and analyzing the meteorological data, reasonable lighting control decisions can be made in advance, further improving the intelligence and energy efficiency of the system. The method also includes: Based on the real-time urban illumination field generated by monitoring, it is determined that the illumination of each lighting sub-area does not fall below the preset illumination threshold of the corresponding area, indicating that the current illumination meets the demand. The big data analysis algorithm is then used to analyze and predict the illumination of each lighting sub-area in the future, and the real-time illumination field of the city in the future is generated accordingly; the future period can be set manually.

[0058] Utilize big data analysis and prediction technology to predict weather data for a period of time in the future based on the real-time collected weather data; for example, use deep learning algorithms to predict weather data for a period of time in the future.

[0059] Combine the predicted meteorological data with the future time period information to determine the preset illumination threshold of the corresponding area in the future; based on the predicted real-time illumination field of the city in the future, determine whether there is a lighting sub-area whose illumination is lower than the preset illumination threshold of the corresponding area in the future; if so, The corresponding lighting sub-area to be regulated is determined; specifically, the moment when the illuminance of the lighting sub-area first appears to be lower than the preset illuminance threshold of the corresponding area within a period of time in the future is taken as the reference moment, and the lighting sub-area whose illuminance at the reference moment is lower than the preset illuminance threshold of the corresponding area is correspondingly determined to be the lighting sub-area to be regulated; continue to statistically distinguish the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be regulated, and complete the regional illuminance adjustment control according to the statistical distinction results.

[0060] In a specific embodiment, in order to realize the function of user-defined regional light illuminance preset illuminance threshold, the flexibility and personalized configuration capability of the system are enhanced, and the method further includes: Determine whether a request for a preset illumination threshold value of regional illumination set by a user is received; If received, compare the size of the regional light illumination preset threshold requested by the user with the regional light illumination safety threshold. If it is less than, ignore the user request. If it is greater than or equal to, replace the regional light illumination preset threshold that matches the climate data in different time periods with the regional light illumination preset threshold set by the user; wherein each area is set with a regional light illumination safety threshold.

[0061] like Figure 2 As shown, the embodiment of the present application discloses an urban lighting control system based on distributed illuminance, including: The preset lighting area data acquisition module 101 is used to divide the scope of the urban lighting area, deploy light intensity sensors and meteorological sensors in each divided lighting sub-area, and collect and obtain light intensity data and meteorological data of each lighting sub-area; A preset lighting area real-time illumination field acquisition module 102 is used to analyze the collected illumination data of each lighting sub-area using a big data analysis algorithm to generate a real-time illumination field of the city; The module 103 for determining the lighting sub-area to be regulated is used to monitor the generated real-time urban light illumination field, compare whether the light illumination of each lighting sub-area is lower than the preset light illumination threshold of the corresponding area, and dynamically match and adjust the preset light illumination threshold of each area according to the climate data in different time periods; obtain the lighting sub-area whose light illumination is lower than the preset light illumination threshold of the corresponding area, record it as the lighting sub-area to be regulated, and statistically distinguish the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be regulated; the light illumination of each lighting sub-area refers to the average light illumination; The lighting sub-area control module 104 to be controlled is used to generate a first control instruction for each independent lighting sub-area so that the lighting equipment in the lighting sub-area adjusts the illumination of the lighting sub-area to the preset illumination threshold of the corresponding area illumination according to the first control instruction; clustering is performed for adjacent lighting sub-areas, and the adjacent lighting sub-areas belonging to the same category are regionally linked, which are recorded as linkage areas; using the illumination compensation neural network model, the illumination compensation value of the adjacent area in the linkage area is obtained in the process of gradually adjusting the illumination of each area in the linkage area to the preset illumination threshold of the illumination of the corresponding area; using a multi-objective optimization algorithm, combined with the illumination of each area in the linkage area, the preset illumination threshold of the illumination of each area corresponding to the area, and the compensation value of the adjacent area in the linkage area in the process of adjusting the illumination of each area to the preset illumination threshold of the illumination of the corresponding area, to obtain the linkage area illumination adjustment plan so that the illumination of each area in the linkage area reaches the preset illumination threshold of the illumination of the corresponding area and the adjustment energy consumption is minimized; according to the linkage area illumination adjustment plan, a second control instruction is generated so that the lighting equipment in the linkage area completes the linkage area illumination adjustment control according to the second control instruction.

[0062] In a specific embodiment, the system has a preset lighting area data acquisition module 101, which is also used to use a camera installed in each lighting sub-area in the lighting sub-area to be regulated to acquire the historical crowd density in the corresponding area in real time, and to obtain the regional unit with the largest crowd density in the corresponding area in the recent period of time; The lighting sub-area control module 104 to be controlled is also used to generate a first control instruction for each independent lighting sub-area counted so that the lighting equipment in the lighting sub-area adjusts the illumination of the lighting sub-area to the preset illumination threshold of the corresponding area according to the first control instruction, and the lighting equipment at the location of the statistically obtained regional unit is the adjustment object; and generate a second control instruction according to the linkage area illumination adjustment scheme so that the lighting equipment in the linkage area completes the linkage area illumination adjustment control according to the second control instruction, and the lighting equipment at the location of the regional unit corresponding to each area of ​​the statistically obtained linkage area is the adjustment object.

[0063] In a specific embodiment, the system further includes: The pre-control module 105 of the lighting sub-area to be controlled is used to compare and determine, based on the real-time urban light illumination field generated by monitoring, whether the light illumination of each lighting sub-area is lower than the preset light illumination threshold of the corresponding area, and then use the big data analysis algorithm to analyze and predict the light illumination of each lighting sub-area in a future period of time, and generate the real-time light illumination field of the city in the future period of time accordingly; predict the meteorological data in the future period of time in advance based on the meteorological data collected in real time, and determine the preset light illumination threshold of the corresponding area in the future period of time by combining the predicted meteorological data with the future time period information; judge whether there is a lighting sub-area in the future period of time according to the predicted real-time light illumination field of the city below the preset light illumination threshold of the corresponding area; if so, determine the lighting sub-area to be controlled accordingly, continue to statistically distinguish the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be controlled, and complete the regional light illumination adjustment control according to the statistical distinction results.

[0064] In a specific embodiment, the module 103 for determining the lighting sub-area to be regulated in the system is also used to, before comparing whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the illuminance of the corresponding area, further include: determining whether the illuminance of the lighting sub-area was adjusted at the previous moment; if not, comparing the illuminance of each lighting sub-area at the current moment with the illuminance of the lighting sub-area at the previous moment in advance; if the difference between the two is less than the preset difference, continuing to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the illuminance of the corresponding area, obtaining a sub-area whose illuminance is lower than the preset illuminance threshold of the illuminance of the corresponding area, and recording it as the lighting sub-area to be regulated; if the difference between the two is greater than the preset difference, temporarily stopping the comparison. Compare each lighting sub-area to see if the illuminance is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; when it is determined that the illuminance is still lower than the preset illuminance threshold of the corresponding area at the next moment, continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; if so, continue to compare each lighting sub-area to see if the illuminance is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated.

[0065] In a specific embodiment, the lighting sub-area control module 104 to be controlled in the system is also used to use a light intensity compensation neural network model to obtain the light intensity compensation value of the adjacent area in the linkage area during the process of gradually adjusting the light intensity of each area in the linkage area to the preset light intensity threshold of the corresponding area. Then, a multi-objective optimization algorithm is used to combine the light intensity of each area in the linkage area, the preset light intensity threshold of the light intensity of each area corresponding to the area, and the compensation value of the adjacent area in the linkage area during the process of adjusting the light intensity of each area to the preset light intensity threshold of the corresponding area. Before obtaining the light intensity adjustment plan of the linkage area, it also includes: comparing whether the light intensity compensation value of the adjacent area in the linkage area is less than the preset light intensity compensation value. If so, the obtained light intensity compensation value is set to 0; otherwise, the currently obtained light intensity compensation value is retained.

[0066] In a specific embodiment, the module 103 for determining the lighting sub-area to be regulated in the system is also used to determine whether a request information for a regional light intensity preset illumination threshold set by a user is received; if received, the size of the regional light intensity preset illumination threshold requested by the user is compared with the regional light intensity safety illumination threshold. If it is less than, the user request is ignored; if it is greater than or equal to, the regional light intensity preset illumination threshold received from the user is used to replace the regional light intensity preset illumination threshold that matches the climate data in different time periods; wherein, each area is set with a regional light intensity safety illumination threshold.

[0067] In a specific embodiment, the lighting area data acquisition module 101 is preset in the system, and is also used to determine the type of each lighting area according to the location of each lighting area when dividing the scope of the urban lighting area; according to the type corresponding to each lighting area, a corresponding number of light intensity sensors of the corresponding type are set and evenly deployed in each divided lighting area; wherein the types of lighting areas include: commercial area type, residential area type and public facility area type, and each type corresponds to a number of light intensity sensors of the corresponding type.

[0068] The embodiment of the present application also discloses a computer-readable storage medium.

[0069] Specifically, the computer-readable storage medium stores a computer program that can be loaded by a processor and execute the above-mentioned urban lighting control method based on distributed light illumination. The computer-readable storage medium includes, for example: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0070] The embodiment of the present application also discloses a computer device.

[0071] Specifically, the computer device includes a memory and a processor, and the memory stores a computer program that can be loaded by the processor and execute the above-mentioned urban lighting control method based on distributed illuminance.

[0072] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A method for controlling urban lighting based on distributed illuminance, characterized in that: include: Divide the scope of urban lighting areas, deploy light intensity sensors and meteorological sensors in each divided lighting sub-area, and collect light intensity data and meteorological data of each lighting sub-area; Use big data analysis algorithms to analyze the collected illuminance data of each lighting sub-area and generate a real-time illuminance field for the city; Monitor the generated real-time urban illumination field, compare the illumination of each lighting sub-area to see if it is lower than the preset illumination threshold of the corresponding area, and dynamically adjust the preset illumination threshold of each area according to the climate data at different time periods; Obtain lighting sub-areas whose illuminance is lower than a preset illuminance threshold of the corresponding area, record them as lighting sub-areas to be regulated, and statistically distinguish adjacent lighting sub-areas and independent lighting sub-areas among all lighting sub-areas to be regulated; the illuminance of each lighting sub-area refers to the average illuminance; For each independent lighting sub-area, a first control instruction is correspondingly generated so that the lighting equipment in the lighting sub-area adjusts the illumination of the lighting sub-area to a preset illumination threshold of the illumination of the corresponding area according to the first control instruction; Adjacent lighting sub-areas are clustered, and adjacent lighting sub-areas belonging to the same category are regionally linked and recorded as linked areas; a light intensity compensation neural network model is used to obtain the light intensity compensation value of the adjacent areas in the linked area during the process of gradually adjusting the light intensity of each area in the linked area to the preset light intensity threshold of the corresponding area; a multi-objective optimization algorithm is used to obtain the light intensity adjustment plan of the linked area by combining the light intensity of each area in the linked area, the preset light intensity threshold of the corresponding area of ​​each area, and the compensation value of the adjacent areas in the linked area during the process of adjusting the light intensity of each area to the preset light intensity threshold of the corresponding area, so that the light intensity of each area in the linked area reaches the preset light intensity threshold of the corresponding area and the adjustment energy consumption is minimized; a second control instruction is generated according to the light intensity adjustment plan of the linked area so that the lighting equipment in the linked area completes the light intensity adjustment control of the linked area according to the second control instruction.

2. The urban lighting control method based on distributed illuminance according to claim 1 is characterized in that: Also includes: The camera device installed in each lighting sub-area to be regulated is used to collect and obtain the historical crowd density in the corresponding area in real time, and the regional unit with the largest crowd density in the corresponding area in the recent period of time is statistically obtained; For each independent lighting sub-area counted, a first control instruction is generated accordingly so that the lighting equipment in the lighting sub-area adjusts the illuminance of the lighting sub-area to the preset illuminance threshold of the corresponding area according to the first control instruction, and the lighting equipment at the location of the statistically obtained area unit is the adjustment object; According to the linkage area illumination adjustment plan, a second control instruction is generated correspondingly so that the lighting equipment in the linkage area completes the linkage area illumination adjustment control process according to the second control instruction, and the lighting equipment at the location of the area unit corresponding to each area of ​​the linkage area obtained by statistics is taken as the adjustment object.

3. The urban lighting control method based on distributed illuminance according to claim 1, characterized in that: Before comparing whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, the method further includes: determining whether the illuminance of the lighting sub-area was adjusted at the last moment; If not performed, then compare the illuminance of each lighting sub-area at the current moment with the illuminance of the lighting sub-area at the previous moment in advance; if the difference between the two is less than the preset difference, then continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; if the difference between the two is greater than the preset difference, then temporarily stop continuing to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; when it is determined that the illuminance at the next moment is still lower than the preset illuminance threshold of the corresponding area, continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be regulated; If so, continue to compare whether the illuminance of each lighting sub-area is lower than the preset illuminance threshold of the corresponding area, obtain the sub-area whose illuminance is lower than the preset illuminance threshold of the corresponding area, and record it as the lighting sub-area to be adjusted.

4. The urban lighting control method based on distributed illuminance according to claim 1, characterized in that: After obtaining the illumination compensation value of the adjacent area in the linkage area during the process of gradually adjusting the illumination of each area in the linkage area to the preset illumination threshold of the illumination of the corresponding area by using the illumination compensation neural network model, using the multi-objective optimization algorithm, combining the illumination of each area in the linkage area, the preset illumination threshold of the illumination of each area corresponding to the area, and the compensation value of the adjacent area in the linkage area during the process of adjusting the illumination of each area to the preset illumination threshold of the illumination of the corresponding area, before obtaining the illumination adjustment plan of the linkage area, it also includes: Compare whether the illumination compensation value of the adjacent area in the linkage area is less than the preset illumination compensation value; if so, set the obtained illumination compensation value to 0; otherwise, retain the currently obtained illumination compensation value.

5. The urban lighting control method based on distributed illuminance according to claim 1, characterized in that: Also includes: According to the real-time illumination field of the city generated by monitoring, it is determined that the illumination of each lighting sub-area does not fall below the preset illumination threshold of the illumination of the corresponding area, and then the illumination of each lighting sub-area in the future is obtained by using the big data analysis algorithm for analysis and prediction, and the real-time illumination field of the city in the future is generated accordingly; Predict the meteorological data for a period of time in the future based on the meteorological data collected in real time, and determine the preset illumination threshold of the corresponding regional illumination for a period of time in the future by combining the predicted meteorological data with the information of the future time period; determine whether there is a lighting sub-area whose illumination is lower than the preset illumination threshold of the corresponding regional illumination for a period of time in the future based on the predicted real-time illumination field of the city for a period of time in the future; if so, determine the corresponding lighting sub-area to be regulated, continue to statistically distinguish the adjacent lighting sub-areas and independent lighting sub-areas in all the lighting sub-areas to be regulated, and complete the regional illumination adjustment control according to the statistical distinction results.

6. The urban lighting control method based on distributed illuminance according to claim 1, characterized in that: Also includes: Determine whether a request for a preset illumination threshold value of regional illumination set by a user is received; If received, the size of the regional light illumination preset illuminance threshold requested by the user is compared with the regional light illumination safety threshold. If it is less than, the user request is ignored; if it is greater than or equal to, the regional light illumination preset illuminance threshold received from the user is used to replace the regional light illumination preset illuminance threshold that matches the climate data in different time periods; wherein each area is set with a regional light illumination safety threshold.

7. The urban lighting control method based on distributed illuminance according to claim 1, characterized in that: Also includes: When dividing the scope of urban lighting areas, the type of each lighting sub-area is determined according to the location of each lighting sub-area; According to the type corresponding to each lighting sub-area, a corresponding number of light intensity sensors of the corresponding type is set and evenly deployed in each divided lighting sub-area; wherein the types of lighting sub-areas include: commercial area type, residential area type and public facility area type, and each type is matched with a corresponding number of light intensity sensors.

8. An urban lighting control system based on distributed illumination, characterized in that: include: A lighting area data acquisition module is preset to divide the scope of urban lighting areas, deploy light intensity sensors and meteorological sensors in each divided lighting sub-area, and collect and obtain light intensity data and meteorological data of each lighting sub-area; A real-time illumination field acquisition module for preset lighting areas is used to analyze the collected illumination data of each lighting sub-area using a big data analysis algorithm to generate a real-time illumination field for the city; The module for determining the lighting sub-areas to be regulated is used to monitor the generated real-time urban light illumination field, compare whether the light illumination of each lighting sub-area is lower than the preset light illumination threshold of the corresponding area, and dynamically match and adjust the preset light illumination threshold of each area according to the climate data in different time periods; Obtain lighting sub-areas whose illuminance is lower than a preset illuminance threshold of the corresponding area, record them as lighting sub-areas to be regulated, and statistically distinguish adjacent lighting sub-areas and independent lighting sub-areas among all lighting sub-areas to be regulated; the illuminance of each lighting sub-area refers to the average illuminance; The lighting sub-area control module to be controlled is used to generate a first control instruction for each independent lighting sub-area so that the lighting equipment in the lighting sub-area adjusts the illumination of the lighting sub-area to the preset illumination threshold of the corresponding area illumination according to the first control instruction; clustering is performed for adjacent lighting sub-areas, and the adjacent lighting sub-areas belonging to the same category are regionally linked, which are recorded as linkage areas; using the illumination compensation neural network model, the illumination compensation value of the adjacent area in the linkage area is obtained in the process of gradually adjusting the illumination of each area in the linkage area to the preset illumination threshold of the illumination of the corresponding area; using a multi-objective optimization algorithm, combined with the illumination of each area in the linkage area, the preset illumination threshold of the illumination of each area corresponding to the area illumination, and the compensation value of the adjacent area in the linkage area in the process of adjusting the illumination of each area to the preset illumination threshold of the illumination of the corresponding area, to obtain the linkage area illumination adjustment plan so that the illumination of each area in the linkage area reaches the preset illumination threshold of the illumination of the corresponding area illumination and the adjustment energy consumption is minimized; according to the linkage area illumination adjustment plan, a second control instruction is generated so that the lighting equipment in the linkage area completes the linkage area illumination adjustment control according to the second control instruction.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A computer device, characterized in that: The computer device comprises a memory, a processor and a program stored and executable on the memory, and the program implements the steps of the method according to any one of claims 1 to 7 when executed by the processor.

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