Self-adaptive dimming LED street lamp for low-carbon environment-friendly smart city and control method of self-adaptive dimming LED street lamp

Abstract

The invention relates to the technical field of street lamp control, in particular to a self-adaptive dimming LED street lamp for a low-carbon environment-friendly smart city and a control method of the self-adaptive dimming LED street lamp. The method comprises the following steps: acquiring road-related information of ambient light intensity, pedestrian flow and traffic flow in real time, preprocessing the road-related information, and processing and analyzing the road-related information; the ambient light intensity, the pedestrian flow and the traffic flow are used as input variables, and the LED street lamp brightness is used as an output variable; and adjusting the brightness of the LED street lamp according to the output variable, communicating with a smart city security system, and detecting the state of the street lamp in real time by the smart city security system. The system comprises an information and transmission acquisition module, a light control module and a road early warning module. According to the invention, the problems of low intelligent degree, insufficient remote control and monitoring capability and limited energy-saving effect are solved; the LED street lamp is remarkable in energy-saving effect, the service life of the LED lamp is prolonged, the maintenance cost is reduced, and the city safety and attractiveness are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of street lamp control, and in particular to an adaptive dimming LED street lamp for low-carbon, environmentally friendly smart cities and a control method thereof. Background Art

[0002] As a typical representative of new green light sources, LED street lights are widely used in general lighting, road lighting, special lighting and other fields. Traditional LED street lights cannot meet the actual lighting needs and consume a large part of the energy. The core goal of the smart induction street light system is to realize the intelligent management and control of street lights through the Internet of Things technology, so as to achieve energy saving and emission reduction, improve lighting efficiency and user experience.

[0003] Prior art 1, Chinese patent, application number: 202321197283.4 discloses an LED street lamp capable of self-sensing control, belonging to the technical field of LED lighting fixtures, including a sensing device electrically connected to the signal end of the control device, the input end and the output end of the control device are electrically connected to the output end of the signal device and the dimming control end of the dimming power supply respectively, the input end of the signal device is electrically connected to the input end of the dimming power supply through the wiring terminal, the output end of the dimming power supply is electrically connected to the LED light source, the control device is electrically connected to the wiring terminal, and the wiring terminal is electrically connected to the municipal power supply network. Disclosed is an LED street lamp capable of self-sensing control, which has a simple structure. While using the LED light source to save energy, when the sensing device cannot sense that there are no people or vehicles on the road. Although the signal device and the dimming power supply cooperate to automatically reduce the brightness to reduce energy consumption, the problem of unnecessary energy consumption in the way of staying lit all night is reduced; however, the remote control and monitoring capabilities are insufficient.

[0004] Prior art 2, Chinese patent, application number: 202323314782.X involves the field of street lamp control, specifically, it involves a control circuit of an induction energy-saving LED street lamp, including a driving power supply, a controller and a motion sensor. When the target road section is in a low-flow period at night, the sensor control circuit controls the motion sensor to be in a power-on state; the motion sensor is connected to the driving power supply signal, and when the motion sensor detects a moving object, the LED lamp is controlled to recover from the energy-saving working mode to the normal working mode and delays switching back to the energy-saving working mode. After the street lamps are lit for a period of time, the working state of all street lamps is switched to the energy-saving working mode. When a moving object appears in the target road section, the working state of the street lamps in the section is temporarily switched to the normal working mode. Although, in order to ensure the lighting needs of the road section at this time, the waste of electricity resources is greatly reduced. However, due to the lack of a comprehensive management platform, it is impossible to achieve global monitoring and management of all street lamps.

[0005] Prior art three, Chinese patent, application number: 202311662254.5, involves the field of street lamp control technology, specifically, a time-sharing control method for an induction energy-saving LED street lamp, comprising the following steps: setting the lighting time T1 and the extinguishing time T2; calculating the time control period of the street lamp; wherein T3 and T4 are the preset light-on delay time and light-off delay time, respectively; during the brightness control period, the brightness of all street lamps on the target section is lowered; during the brightness control period, whether there are moving objects on the road surface of the target section is detected. When the street lamp is in the lighting working state, the street lamps of the entire section are set to a low-brightness energy-saving working mode during the low traffic period. Although, when a vehicle or other moving object passes by, the street lamps of the section where the vehicle or moving object passes are temporarily set to a high-brightness normal working mode, which greatly reduces the waste of power resources; however, the degree of intelligence is low, and it is not possible to flexibly respond to complex environmental changes.

[0006] At present, the existing technologies 1, 2 and 3 have insufficient remote control and monitoring capabilities, lack of a comprehensive management platform, and cannot achieve global monitoring and management of all street lamps. They have a low degree of intelligence and cannot flexibly respond to complex environmental changes. Therefore, the present invention provides an adaptive dimming LED street lamp and a control method thereof for a low-carbon, environmentally friendly smart city. Summary of the invention

[0007] In order to achieve the above object, the present invention adopts the following technical scheme: In one aspect of the present invention, there is provided an adaptive dimming LED street lamp for a low-carbon, environmentally friendly smart city, comprising: An information and transmission acquisition module is used to collect road-related information such as ambient light intensity, pedestrian flow, and vehicle flow in real time, pre-process the road-related information, and transmit the pre-processed road-related information to the lighting control module; The lighting control module is used to process and analyze road-related information, taking ambient light intensity, pedestrian flow and vehicle flow as input variables and LED street light brightness as output variables. The brightness of LED street lights is adjusted according to the output variables, and the status and data of street lights are uploaded to the central management system. The road warning module is used to realize communication between the central management system and the smart city security system. The smart city security system detects the status of street lights in real time. If an abnormality is detected in the street lights, the relevant departments will be notified for maintenance. If the smart city security system detects an abnormality in the road, it will adjust the LED street lights.

[0008] In an optional implementation manner, the information and transmission acquisition module includes: The data acquisition submodule is used to obtain the environmental status data set of the LED street lamp, the pedestrian status data set and the vehicle flow status data set, and perform pre-processing operations such as cleaning, noise removal, outlier removal and data conversion. The environmental status data set includes the street lamp density of the environment where the street lamp is located, the data density of the environment where the street lamp is located, and the absolute value of the difference between the tree height of the environment where the street lamp is located and the reference tree height; The data analysis submodule is used to compare the environmental status data set of the LED lamp to obtain the benchmark brightness of the LED street lamp; to conduct a comprehensive analysis on the monitored pedestrian status data set to obtain the pedestrian status characteristic value; to calculate the traffic flow status data set to obtain the traffic flow status characteristic value; The data output submodule is used to output the LED street lamp benchmark lighting brightness, pedestrian status characteristic values ​​and traffic flow status values ​​to the lighting control module.

[0009] In an optional implementation, the data analysis submodule includes: The environmental status module is used to obtain the environmental status data set of the street lamp, comprehensively analyze and obtain the characteristic value of the environmental status of the street lamp, and use the characteristic value of the environmental status of the street lamp as a comparison to obtain the basis for analyzing the reference brightness of the street lamp; compare the characteristic value of the environmental status of the street lamp with the reference brightness of the street lamp corresponding to the characteristic value of the environmental status of each street lamp stored in the database, and obtain the reference brightness of the street lamp corresponding to the characteristic value of the environmental status of the street lamp; The pedestrian flow unit is used to turn on the reference brightness of the street lamp when a pedestrian is detected; obtain the data set of the street lamp monitoring pedestrian status, and conduct a comprehensive analysis to obtain the street lamp monitoring pedestrian characteristic value, and the intelligent street lamp monitoring pedestrian status characteristic value is used as the analysis basis for the comprehensive analysis to obtain the street lamp brightness evaluation value; Among them, the pedestrian status data set detected by street lights includes the closest distance between pedestrians and street lights, the walking speed of pedestrians closest to street lights, the number of pedestrians monitored by street lights, and the length of the continuous straight-line walking distance of pedestrians monitored by street lights; The vehicle flow unit is used to light up the street light at a reference brightness when a vehicle is detected; obtain the vehicle status data set for street light monitoring, and obtain the vehicle characteristic value for street light monitoring through comprehensive analysis. The vehicle status characteristic value for intelligent street light monitoring is used as the analysis basis for comprehensive analysis to obtain the street light brightness evaluation value; Among them, the pedestrian status data set for light detection includes the closest distance between the vehicle and the street light, the speed of the vehicle closest to the street light, the number of vehicles monitored by the street light, and the length of the continuous straight-line walking distance of the vehicle monitored by the street light.

[0010] In an optional implementation, the lighting control module includes: The fuzzy processing submodule is used to collect road-related information such as ambient light intensity, pedestrian flow and vehicle flow in real time; the collected deterministic variables are fuzzy processed, and the ambient light intensity, pedestrian flow and vehicle flow are used as input variables, the input variables are mapped to the fuzzy set, and the membership function is defined for each input variable to obtain the fuzzy variable.

[0011] The fuzzy control submodule is used to set the fuzzy control rule base according to the relationship between the input variables and the output variables; perform calculations based on the input variables and the fuzzy control rule base, perform weighted average on the variable characteristic values, and obtain the final fuzzy control quantity; The control command submodule is used to convert the final fuzzy control variables into clear numerical values, use the clear numerical values ​​as output variables, issue commands to control LED street lights, and upload the street light status and data to the central management system.

[0012] In an optional implementation manner, the fuzzy control submodule includes: The characteristic value sorting unit is used to sort the collected input variables according to the timestamps; count the characteristic values, segment the characteristic values ​​after counting, and set the corresponding characteristic areas with the timestamps as nodes; The calculation element unit is used to convert the precise quantity into a fuzzy single point set, convert the precise quantity correspondence into a basic element, and perform nonlinear fuzzification algorithm calculation on it; analyze the input variable and the output variable to obtain the relationship between the input variable and the output variable, and set the fuzzy control rule base; The final precise quantity unit is used to infer the fuzzy value according to the nonlinear fuzzy algorithm, and obtain the final precise quantity output after defuzzifying the value; and convert the fuzzy control quantity into a clear numerical value.

[0013] In an optional implementation manner, the calculation element unit includes: The fuzzy control rule base subunit is used to determine the membership function and establish the fuzzy control rule base; perform fuzzification input and convert the precise input into the membership value in the fuzzy set; evaluate each rule in the fuzzy control rule base and determine the activation degree of each rule; The control instruction subunit is used to determine the membership, combine all activated rules for data, use the minimum operation for aggregation, and convert the fuzzy input into precise control rules after evaluating the rules; the defuzzification process will determine the final control LED street light brightness instruction; The adjustment strategy subunit is used to perform fuzzification using the weighted average method and perform weighted average of the membership degree; based on the defuzzification results, it generates control light instructions to adjust the brightness of the LED street lights; finally, it performs closed-loop feedback, compares the controller output results with the preset light targets, and adjusts the control strategy based on the deviation.

[0014] In an optional implementation manner, the control command submodule includes: The clear value unit is used to infer the fuzzy value according to the nonlinear fuzzy algorithm, and obtain the final accurate output after defuzzifying the value; and convert the fuzzy control amount into a clear value; The scale value calculation unit is used to calculate the scale values ​​of the input and output, determine the fuzzy sum corresponding to the scale values ​​of the input and output, track the input changes in real time, and calculate the output scale value according to the input changes; The upload transmission unit is used to use clear numerical values ​​as output variables, issue commands to control LED street lights, and upload street light status and data to the central management system.

[0015] In an optional implementation, the road warning module includes: The road monitoring submodule is used to monitor street lights and road conditions in real time. If an abnormality of a street light is detected, an alarm signal will be issued immediately and the relevant departments will be notified for maintenance. The light warning submodule is used to detect abnormal road conditions, adjust the flashing of street lights according to the abnormal conditions, analyze them, and take corresponding measures; abnormal road conditions include illegal parking, speeding, and traffic accidents; The strategy adjustment submodule is used to collect historical street light data, analyze it, and adjust the street light strategy based on the analysis results; the historical street light data includes energy consumption data, fault data, lighting time, etc.

[0016] Another aspect of the present invention provides a control method for an adaptive dimming LED street lamp for a low-carbon, environmentally friendly smart city, comprising: Collect road-related information such as ambient light intensity, pedestrian flow, and vehicle flow in real time, pre-process the road-related information, and transmit the pre-processed road-related information to the lighting control module; It is used to process and analyze road-related information, taking ambient light intensity, pedestrian flow and vehicle flow as input variables and LED street light brightness as output variables, adjusting the brightness of LED street lights according to the output variables, and uploading the status and data of street lights to the central management system; The central management system communicates with the smart city security system, which detects the status of street lights in real time. If an abnormality is detected in a street light, the relevant department will be notified for repair. If an abnormality is detected in the road, the smart city security system will adjust the LED street lights.

[0017] The present invention uses the Internet of Things (IoT) technology with its powerful connectivity and intelligent characteristics to automatically adjust the brightness or switch status of street lights according to real-time data such as road traffic and ambient light intensity, which not only ensures the safety and convenience of nighttime driving, but also effectively reduces unnecessary energy waste and builds a low-carbon and environmentally friendly smart city. The present invention uses the Internet of Things technology to achieve remote monitoring and real-time data analysis of lighting facilities. Managers can discover and handle faults in a timely manner, reduce energy waste and safety hazards caused by equipment failures, and reduce the frequency and maintenance costs of manual inspections; accurate energy consumption statistics provide management departments with a basis for scientific decision-making, and further optimize resource allocation. Through linkage with the security system, smart street lights can also issue alarms in a timely manner under abnormal circumstances to protect urban safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a block diagram of an adaptive dimming LED street lamp for a low-carbon, environmentally friendly smart city provided in Example 1 of the present invention; Figure 2 This is a block diagram of the information and transmission acquisition module provided in Example 2 of the present invention; Figure 3 This is a block diagram of a data analysis submodule provided in Embodiment 3 of the present invention; Figure 4 This is a block diagram of a lighting control module provided in Embodiment 4 of the present invention; Figure 5 This is a block diagram of the fuzzy control submodule provided in Embodiment 5 of the present invention; Figure 6 This is a block diagram of a computing element unit provided in Embodiment 6 of the present invention; Figure 7 This is a block diagram of a control command submodule provided in Embodiment 7 of the present invention; Figure 8 This is a block diagram of a road warning module provided in Embodiment 8 of the present invention; Fig. 9 This is another block diagram of the adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities provided in Example 9 of the present invention; Fig.10 This is a flow chart of a control method for an adaptive dimming LED street lamp for a low-carbon, environmentally friendly smart city provided in Embodiment 10 of the present invention; Fig.11 A block diagram of an electronic device provided by the present invention; Fig.12 A block diagram of a computer-readable storage medium provided for the present invention. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0020] In the following, the terms "first", "second", etc. are used only for convenience of description and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0021] In the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense, for example, "connection" can be a fixed mechanical connection, or a detachable mechanical connection, or integrated; or, "connection" can be a direct connection, or an indirect connection through an intermediate medium. In addition, unless otherwise clearly specified and limited, the term "coupling" should be understood in a broad sense, for example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components, and can also be understood as electrical connection between different components in a circuit structure through physical lines such as copper foil or wires on a printed circuit board (PCB) that can transmit electrical signals to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in an air-spaced / non-contact manner, for example, two components are electrically connected by capacitive coupling to transmit electrical signals.

[0022] In the embodiments of the present invention, directional terms such as "up", "down", "left" and "right" may be defined including but not limited to the orientation relative to the schematic placement of the components in the drawings. It should be understood that these directional terms may be relative concepts, which are used for relative description and clarification, and may change accordingly according to the change of the orientation of the components in the drawings.

[0023] The embodiments of the present invention can be used for urban road lighting, residential and park lighting, parking lots, underground garages, parks and squares, and tunnel and bridge lighting.

[0024] The key technical features of the embodiments of the present invention are as follows: The Internet of Things (IoT) technology, with its powerful connectivity and intelligent characteristics, can automatically adjust the brightness or switch status of street lights according to real-time data such as road traffic and ambient light intensity, which not only ensures the safety and convenience of night driving, but also effectively reduces unnecessary energy waste and builds a low-carbon and environmentally friendly smart city. Through the Internet of Things technology, remote monitoring and real-time data analysis of lighting facilities can be achieved. Managers can discover and handle faults in a timely manner, reduce energy waste and safety hazards caused by equipment failures, and reduce the frequency and maintenance costs of manual inspections. Accurate energy consumption statistics provide a basis for scientific decision-making for management departments, and further optimize resource allocation. Through linkage with the security system, smart street lights can also issue alarms in time under abnormal circumstances to protect urban safety.

[0025] Embodiment 1: like Figure 1 As shown, an embodiment of the present invention provides an adaptive dimming LED street lamp for a low-carbon and environmentally friendly smart city, comprising: The information and transmission acquisition module 1 is used to collect road-related information such as ambient light intensity, pedestrian flow, and vehicle flow in real time, pre-process the road-related information, and transmit the pre-processed road-related information to the lighting control module 2; Lighting control module 2 is used to process and analyze road-related information, taking ambient light intensity, pedestrian flow and vehicle flow as input variables and LED street light brightness as output variables, adjusting the brightness of LED street lights according to the output variables, and uploading the status and data of street lights to the central management system; The road warning module 3 is used to realize the communication between the central management system and the smart city security system. The smart city security system detects the status of the street lamps in real time. If an abnormality is detected in the street lamps, the relevant departments will be notified for maintenance. If the smart city security system detects an abnormality in the road, it will adjust the LED street lamps.

[0026] In the above embodiments, this embodiment can automatically adjust the brightness or switch status of street lamps according to real-time data such as road traffic and ambient light intensity through the Internet of Things (IoT) technology with its powerful connectivity and intelligent characteristics, which not only ensures the safety and convenience of night driving, but also effectively reduces unnecessary energy waste and builds a low-carbon and environmentally friendly smart city. Through the Internet of Things technology, remote monitoring and real-time data analysis of lighting facilities can be achieved. Managers can discover and handle faults in a timely manner, reduce energy waste and safety hazards caused by equipment failures, and reduce the frequency and maintenance costs of manual inspections. Accurate energy consumption statistics provide a basis for scientific decision-making for management departments and further optimize resource allocation. Through linkage with the security system, smart street lamps can also issue alarms in time under abnormal circumstances to protect urban safety.

[0027] Embodiment 2: like Figure 2 As shown, based on Example 1, the information and transmission acquisition module 1 provided in this embodiment of the present invention includes: The data acquisition submodule 11 is used to obtain the environmental status data set of the LED street lamp, the pedestrian status data set and the vehicle flow status data set, and perform pre-processing operations such as cleaning, noise removal, outlier removal and data conversion on them; The environmental status data set includes the street lamp density of the environment where the street lamp is located, the data density of the environment where the street lamp is located, and the absolute value of the difference between the tree height of the environment where the street lamp is located and the reference tree height; The data analysis submodule 12 is used to compare the environmental status data set of the LED lamp to obtain the reference brightness of the LED street lamp; to comprehensively analyze the pedestrian status data set to obtain the pedestrian status characteristic value; to calculate the traffic flow status data set to obtain the traffic flow status characteristic value; The expression of traffic flow state characteristic value is obtained: We can devise a more complex expression: In the formula, V It represents the total number of vehicles passing a monitoring point in unit time. S It represents the average speed of all vehicles passing through the monitoring point per unit time. W Represents the weight coefficients of different types of vehicles, such as small cars, medium-sized cars, large cars, etc. Each type of vehicle has a different impact on the traffic status. T Indicates the traffic flow distribution in different time periods. R Represents the influence coefficient of different road types, W Indicate the impact of different weather conditions on traffic; represents the number of monitoring points, Indicates i The traffic volume at each monitoring point, Indicates i The average vehicle speed at each monitoring point, Indicates i The vehicle type weight of each monitoring point, Indicates i The time distribution of monitoring points, Indicates i The road type of each monitoring point, Indicates i Weather conditions at each monitoring point; , , , , , They are the weight coefficients of each factor. The expression comprehensively considers the impact of multiple factors on the traffic state. By adjusting each weight coefficient, the actual traffic state can be more accurately reflected. The weight coefficient can be optimized and adjusted according to historical data and actual needs to improve the accuracy and practicality of the traffic state characteristic value. The data output submodule 13 is used to output the LED street lamp reference lighting brightness, pedestrian status characteristic value and traffic flow status value to the lighting control module.

[0028] In the above embodiment, the data acquisition submodule 11 of this embodiment is responsible for real-time acquisition of the state data set of the environment in which the LED street lamp is located, the pedestrian state data set and the vehicle flow state data set. The data of this embodiment includes environmental parameters such as street lamp density, environmental density, tree height difference, light intensity, temperature, humidity, and pedestrian and vehicle flow information. Through high-precision sensors and analog-to-digital converters. In addition, the module also pre-processes the data, such as cleaning, removing noise and outliers, to improve data quality. The data analysis submodule 12 calculates the reference lighting brightness of the LED street lamp by comparing the environmental state data set; comprehensively analyzes the pedestrian state data set to obtain the pedestrian state characteristic value; calculates the vehicle flow state data set to obtain the vehicle flow state characteristic value; uses advanced data analysis algorithms, such as time series analysis or machine learning algorithms, to process and analyze the collected data, so as to obtain accurate control instructions. The data output submodule 13 outputs the LED street lamp reference lighting brightness, pedestrian state characteristic value and vehicle flow state characteristic value to the lighting control module to realize intelligent adjustment of the street lamp brightness. The processed data is transmitted to the control center through wireless communication technology to ensure the stability and real-time performance of data transmission. At the same time, the module also supports flexible control strategies, which can dynamically adjust the brightness of street lights according to different environments and traffic conditions.

[0029] Embodiment 3: like Figure 3 As shown, based on Example 2, the data analysis submodule 12 provided in this embodiment of the present invention includes: The environmental state unit 121 is used to obtain the environmental state data set of the street lamp, comprehensively analyze and obtain the characteristic value of the environmental state of the street lamp, and use the characteristic value of the environmental state of the street lamp as a comparison to obtain the reference brightness analysis basis of the street lamp; compare the characteristic value of the environmental state of the street lamp with the reference lighting brightness of the street lamp corresponding to the characteristic value of the environmental state of each street lamp stored in the database, and obtain the reference lighting brightness of the street lamp corresponding to the characteristic value of the environmental state of the street lamp; The pedestrian flow unit 122 is used to light up the street lamp to a reference brightness when a pedestrian is detected; obtain a data set of the street lamp monitoring pedestrian status, and comprehensively analyze to obtain the street lamp monitoring pedestrian characteristic value, and the intelligent street lamp monitoring pedestrian status characteristic value is used as the analysis basis for comprehensively analyzing to obtain the street lamp brightness evaluation value; Among them, the pedestrian status data set detected by street lights includes the closest distance between pedestrians and street lights, the walking speed of pedestrians closest to street lights, the number of pedestrians monitored by street lights, and the length of the continuous straight-line walking distance of pedestrians monitored by street lights; The vehicle flow unit 123 is used to light up the street lamp at a reference brightness when a vehicle is detected; obtain the vehicle status data set of the street lamp monitoring line, and obtain the vehicle characteristic value of the street lamp monitoring by comprehensive analysis, and the intelligent street lamp monitoring vehicle status characteristic value is used as the analysis basis for the comprehensive analysis to obtain the street lamp brightness evaluation value; Among them, the pedestrian status data set for light detection includes the closest distance between the vehicle and the street light, the speed of the vehicle closest to the street light, the number of vehicles monitored by the street light, and the length of the continuous straight-line walking distance of the vehicle monitored by the street light.

[0030] In the above embodiment, the environment state unit 121 of this embodiment obtains the environment state data set of the street lamp, comprehensively analyzes and obtains the environment state characteristic value of the street lamp, and uses it as the basis for comparison benchmark brightness analysis. The module can compare the street lamp benchmark lighting brightness corresponding to the environment state characteristic value of each street lamp stored in the database according to the environment state characteristic value, so as to determine the street lamp benchmark lighting brightness corresponding to the environment state characteristic value of the street lamp. The sensor network is used to monitor the ambient light, meteorological conditions and other data in real time to realize dynamic adjustment of street lamp brightness, improve road safety, and efficiently use energy. When the pedestrian flow unit 122 detects a pedestrian, the street lamp turns on the benchmark brightness. By obtaining the street lamp monitoring pedestrian state data set, the street lamp monitoring pedestrian characteristic value is obtained through comprehensive analysis, which is used as the analysis basis for comprehensive analysis to obtain the street lamp brightness evaluation value. Including the closest distance between the pedestrian and the street lamp, the pedestrian walking speed, the number of pedestrians monitored by the street lamp, the length of the continuous straight walking distance of the pedestrian monitored by the street lamp, etc., the street lamp brightness can be intelligently adjusted through the data set to adapt to different pedestrian flows and pedestrian activities. When the vehicle flow unit 123 detects a vehicle, the street light turns on the reference brightness. By acquiring the vehicle status data set of the street light monitoring, a comprehensive analysis is performed to obtain the vehicle characteristic value of the street light monitoring, which is used as the analysis basis for the comprehensive analysis to obtain the street light brightness evaluation value. Including data sets such as the closest distance between the vehicle and the street light, the vehicle's driving speed, the number of vehicles monitored by the street light, and the length of the continuous straight-line walking distance of the vehicle monitored by the street light. The street light brightness can be intelligently adjusted through the data set to adapt to different traffic flows and vehicle activities. This embodiment realizes dynamic adjustment of street light brightness through real-time monitoring and intelligent analysis of environmental conditions, pedestrian flow and vehicle flow data, thereby improving energy utilization efficiency and road safety, while reducing maintenance costs.

[0031] Embodiment 4: like Figure 4 As shown, based on the embodiment 1, the lighting control module 2 provided in the embodiment of the present invention includes: The fuzzy processing submodule 21 is used to collect road-related information such as ambient light intensity, pedestrian flow and vehicle flow in real time; fuzzy process the collected deterministic variables, take ambient light intensity, pedestrian flow and vehicle flow as input variables, map the input variables to fuzzy sets, and define a membership function for each input variable to obtain a fuzzy variable.

[0032] The fuzzy control submodule 22 is used to set the fuzzy control rule base according to the relationship between the input variable and the output variable; perform calculations based on the input variable and the fuzzy control rule base, perform weighted average on the variable characteristic values, and obtain the final fuzzy control amount; The control command submodule 23 is used to convert the final fuzzy control variable into a clear value, use the clear value as the output variable, issue a command to control the LED street light, and upload the street light status and data to the central management system.

[0033] In the above embodiment, the fuzzy processing submodule 21 of this embodiment is responsible for collecting road-related information such as ambient light intensity, pedestrian flow and vehicle flow in real time, and fuzzifying the determined variables. By mapping the ambient light intensity, pedestrian flow and vehicle flow into fuzzy sets, and defining a membership function for each input variable, a fuzzy variable is obtained. Fuzzy processing enables the system to handle uncertainty and subjectivity, converting precise input values ​​into fuzzy sets, which is convenient for subsequent fuzzy reasoning and control. The fuzzy control submodule 22 is the core of the fuzzy controller based on the fuzzy control rule base of the input variables and the output variables, and directly affects the performance and efficiency of the controller. The control of the controlled object is achieved through fuzzy rules, without the need to establish a mathematical model, but through fuzzy logic reasoning to achieve control. The system can flexibly adjust the brightness of the street lamp to adapt to changes in the surrounding environment, thereby achieving energy saving and improving user experience. The fuzzy control rule base is set according to the relationship, and calculations are performed based on the input variables and the fuzzy control rule base, and the variable characteristic values ​​are weighted averaged to obtain the final fuzzy control quantity. The control command submodule 23 converts the final fuzzy control variable into a clear numerical value as the output variable, issues a command to control the LED street lamp, and uploads the street lamp status and data to the central management system. The defuzzification process maps the fuzzy output variable into a specific control signal to ensure that the system can issue clear control instructions. In addition, by uploading data to the central management system, the intelligent management and remote monitoring of the system are realized, and the overall efficiency and reliability of the system are improved. This embodiment constitutes the core part of the smart street lamp system. Through the steps of fuzzification processing, fuzzy control and defuzzification, the intelligent adjustment of the street lamp brightness is realized, and the energy utilization efficiency and user experience are improved.

[0034] Embodiment 5: like Figure 5As shown, based on Example 4, the fuzzy control submodule 22 provided in this embodiment of the present invention includes: The characteristic value sorting unit 221 is used to sort the collected input variables according to the timestamps; count the characteristic values, segment the characteristic values ​​after counting, and set the corresponding characteristic regions with the timestamps as nodes; The calculation element unit 222 is used to convert the precise quantity into a fuzzy single point set, convert the precise quantity correspondence into a basic element, and perform nonlinear fuzzification algorithm calculation on it; analyze the input variable and the output variable to obtain the relationship between the input variable and the output variable, and set the fuzzy control rule base; The final precise quantity unit 223 is used to infer the fuzzy value according to the nonlinear fuzzy algorithm, and obtain the final precise quantity output after defuzzifying the value; and convert the fuzzy control quantity into a clear value; Among them, the process of nonlinear fuzzification algorithm is: In the formula, the input variable I Indicates the input variables collected in the system, timestamp T Indicates the time point when the input variable is collected, the characteristic value F Represents the eigenvalue of the input variable, a fuzzy single point set S Represents a fuzzy single point set that converts the exact quantity into the basic element E Represents the basic elements corresponding to the exact quantity; nonlinear fuzzification algorithm A Represents the algorithm used to calculate fuzzy values, fuzzy control rule base R Represents the set fuzzy control rule base, fuzzy value F Represents the fuzzy value calculated by the nonlinear fuzzification algorithm, and the final accurate value P Represents the final accurate quantity obtained after defuzzification; represents the number of input variables, Indicates j input variables, Indicates j The timestamps of the input variables, Indicates j The eigenvalues ​​of the input variables, Indicates j The fuzzy single point set corresponding to the input variables is Indicates j The basic elements corresponding to the input variables are Indicates j The fuzzy control rules corresponding to the input variables are: , , are the weight coefficients of each factor, represents a nonlinear function of the input variables, timestamps, and eigenvalues, Represents nonlinear functions of fuzzy single point sets and basic elements, A nonlinear function that represents a fuzzy control rule. The expression comprehensively considers multiple factors such as input variables, timestamps, eigenvalues, fuzzy single point sets, basic elements, and fuzzy control rules, and calculates through nonlinear functions and weight coefficients to obtain the final fuzzy value; nonlinear functions and weight coefficients can be optimized and adjusted according to actual needs to improve the accuracy and practicality of the fuzzification algorithm.

[0035] In the above embodiment, the eigenvalue sorting unit 221 of this embodiment realizes orderly management and feature extraction of input data by sorting input variables according to timestamps and performing statistics and segmentation processing on eigenvalues. Using timestamps as nodes, data is segmented to ensure the continuity and integrity of data, thereby providing reliable basic data support for fuzzy control. The computing element unit 222 converts the precise quantity into a fuzzy single point set and calculates it through a nonlinear fuzzification algorithm, thereby realizing an in-depth analysis of the relationship between input variables and output variables. By establishing a fuzzy rule base, the unit can flexibly set the relationship between input and output, so that the fuzzy controller can make corresponding control decisions according to different input conditions. The final precision unit 223 infers the fuzzy value through a nonlinear fuzzy algorithm, and obtains the final precise quantity output after removing the fuzzy value. The fuzzy control quantity is converted into a clear value, and the fuzzy result is converted into an actual control quantity through defuzzification processing, thereby realizing the conversion from fuzzy to precise, and enhancing the control accuracy and stability of the system. This embodiment constitutes a complete fuzzy control system, which improves the overall performance and adaptability of the system through orderly data processing, flexible fuzzy reasoning and precise control output.

[0036] Embodiment 6: like Figure 6 As shown, based on Example 5, the computing element unit 223 provided in this embodiment of the present invention includes: The fuzzy control rule base subunit 2231 is used to determine the membership function and establish the fuzzy control rule base; perform fuzzification input and convert the precise input into the membership value in the fuzzy set; evaluate each rule in the fuzzy control rule base and determine the activation degree of each rule; The control instruction subunit 2232 is used to determine the membership, combine all activated rules for data, use the minimum operation for aggregation, and after evaluating the rules, convert the fuzzy input into a precise control rule; the defuzzification process will determine the final control LED street light brightness instruction; The adjustment strategy subunit 2233 is used to perform fuzzification using the weighted average method and perform weighted average of the membership degree; based on the defuzzification result, generate a light control instruction to adjust the brightness of the LED street light; finally, perform closed-loop feedback, compare the controller output result with the preset light target, and adjust the control strategy according to the deviation.

[0037] In the above embodiment, the fuzzy control rule subunit 2231 of this embodiment realizes the conversion of precise input into membership value in fuzzy set by determining membership function and establishing fuzzy control rule base, and evaluates each rule to determine its activation degree. The system can flexibly match and apply different control rules according to the fuzzification processing of input variables, thereby improving the adaptability and robustness of the system. By fuzzifying input variables, uncertainty and subjectivity are introduced into the system, so that the fuzzy controller can handle complex input-output relationships, and realize approximate control of the system through membership function and fuzzy rule base. After determining the membership, the control instruction subunit 2232 aggregates data by combining all activated rules and uses minimum operation for aggregation, and finally converts the fuzzy input into precise control rules. The defuzzification process determines the final control instruction of LED street lamp brightness, ensuring the accuracy and reliability of the output. Through minimum operation and defuzzification method (such as centroid method or maximum membership method), the result of fuzzy reasoning is converted into specific control quantity, thereby realizing precise adjustment of LED street lamp brightness. The adjustment strategy subunit 2233 uses the weighted average method to perform fuzzification, performs weighted average of the membership, and generates a control light instruction based on the defuzzification result to adjust the brightness of the LED street lamp. Finally, a closed-loop feedback is performed to compare the controller output result with the preset light target, and the control strategy is adjusted according to the deviation to ensure stable operation of the system. Through the closed-loop feedback mechanism, the control strategy is dynamically adjusted to cope with environmental changes and system errors, thereby improving the system's adaptability and stability. This embodiment constitutes a complete fuzzy control system, which realizes intelligent adjustment of the brightness of LED street lamps through the steps of fuzzification, reasoning, defuzzification and closed-loop feedback, thereby improving the flexibility and reliability of the system.

[0038] Embodiment 7: like Figure 7 As shown, based on Example 4, the control command submodule 23 provided in this embodiment of the present invention includes: The clear value unit 231 is used to infer the fuzzy value according to the nonlinear fuzzy algorithm, and obtain the final accurate value output after defuzzifying the value; and convert the fuzzy control amount into a clear value; The scale value calculation unit 232 is used to calculate the scale values ​​of the input and output, determine the fuzziness corresponding to the scale values ​​of the input and output, track the input changes in real time, and calculate the scale value of the output according to the input changes; The upload transmission unit 233 is used to use the clear numerical value as the output variable, issue a command to control the LED street light, and upload the street light status and data to the central management system.

[0039] In the above embodiment, the numerical clarity unit 231 of this embodiment infers the fuzzy value through a nonlinear fuzzy algorithm, and converts the fuzzy control amount into a clear numerical value, and finally outputs an accurate amount. The calculation scale value unit 232 is responsible for calculating the scale values ​​of the input and output, and tracking the input changes in real time, and calculating the corresponding output scale value according to the changes. By calculating the scale values ​​of the input and output, the unit can ensure that the response of the system is real-time and accurate, thereby improving the adaptability and flexibility of the system. The upload transmission unit 233 uses the clear numerical value as the output variable, issues a command to control the LED street lamp, and uploads the status and data of the street lamp to the central management system. Through the upload and transmission unit, the system can realize remote transmission and centralized management of data, enhancing the intelligence level and management efficiency of the system. This embodiment realizes intelligent adjustment and management of LED street lamps through fuzzy control technology, improving energy utilization efficiency and user experience.

[0040] Embodiment 8: like Figure 8 As shown, based on Example 1, the road warning module 3 provided in this embodiment of the present invention includes: The road monitoring submodule 31 is used to monitor the street lamps and road conditions in real time. If an abnormality of a street lamp is detected, an alarm signal is immediately issued and the relevant departments are notified to carry out maintenance. The light warning submodule 32 is used to detect abnormal road conditions, adjust the flashing of street lights according to the abnormal conditions, analyze them, and take corresponding measures; wherein the abnormal road conditions include illegal parking, speeding, and traffic accidents; The strategy adjustment submodule 33 is used to collect historical street light data, analyze it, and adjust the street light strategy according to the analysis results; wherein the historical street light data includes energy consumption data, fault data, lighting time, etc.

[0041] In the above embodiment, the road monitoring submodule 31 of this embodiment is used to monitor the street lamp and road condition in real time. Once an abnormal situation of the street lamp is detected, an alarm signal is immediately issued and the relevant departments are notified for maintenance. Through the real-time data collection and detection function, the system can timely detect and alarm the abnormal situation of the street lamp, such as lamp failure, terminal failure, cable failure, etc., to ensure the stable operation of the street lamp system. The light warning submodule 32 can adjust the flickering of the street lamp according to the abnormal situation when the abnormal situation is detected on the road, and analyze it to obtain corresponding measures. For example, when abnormal situations such as illegal parking, speeding or traffic accidents are detected, the system will automatically adjust the flickering frequency or brightness of the street lamp to improve road safety. It integrates a variety of sensors and intelligent control systems, can perceive environmental changes in real time and make corresponding adjustments, such as automatically adjusting brightness, flickering frequency, etc., so as to improve the road lighting effect and management efficiency. The adjustment strategy subunit 33 collects historical street lamp data (including energy consumption data, fault data, lighting duration, etc.), analyzes it, and adjusts the street lamp strategy according to the analysis results. By using big data analysis and cloud computing technology, the system can conduct in-depth mining and analysis of historical data, generate optimization suggestions, and achieve refined management. In addition, the module also supports remote control and management, further improving the intelligence level of the system.

[0042] Embodiment 9: like Fig. 9 As shown, based on Example 1, the adaptive dimming LED street lamp for a low-carbon, environmentally friendly smart city provided by the embodiment of the present invention further comprises: The sensor module is responsible for real-time collection of environmental data, such as air quality (PM2.5, toxic gas concentration), noise level, temperature, humidity, light intensity, etc.; it obtains environmental information through various sensors (such as air quality sensors, noise sensors, temperature and humidity sensors, light sensors, etc.) and transmits the data to the control center; The control and processing module is responsible for receiving the data transmitted by the sensor module and performing real-time analysis and processing. According to the preset fuzzy rules and algorithms, the brightness of the street lamps is automatically adjusted. For example, when the PM2.5 concentration reaches the preset threshold, the control module will issue a command to turn on the street lamps and transmit the relevant data to the environmental monitoring center. In addition, this module is also responsible for monitoring the current, voltage, brightness and other parameters of the street lamps to ensure the normal operation of the street lamps; The communication and data transmission module is responsible for transmitting the collected environmental data and street light status information to the environmental monitoring center. It uses wireless communication technologies (such as Wi-Fi, 4G / 5G, LoRa, etc.) to ensure the real-time and reliability of the data. At the same time, it is also responsible for receiving instructions from the environmental monitoring center, such as adjusting the brightness of street lights and starting emergency lighting.

[0043] In the above embodiment, this embodiment has an environmental monitoring function, can monitor environmental indicators such as air quality and noise level in real time, can read the current current, voltage, brightness, temperature, humidity, PM2.5, toxic gases, light intensity and video images of street lamps, and can realize timely adjustment of street lamp brightness; after receiving the automatic adjustment instruction through the street lamp node, the control program automatically adjusts the brightness of the street lamp according to the collected PM2.5, light sensor data, and the set fuzzy rules. If it is detected that the air pollution reaches the preset threshold, the street lamp is turned on and the data is transmitted to the environmental monitoring center. By integrating multiple sensors, smart street lamps can monitor environmental parameters such as air quality (such as PM2.5, PM10), temperature, humidity, noise, etc. in real time, providing accurate data support for urban managers. Based on fuzzy control theory, smart street lamps can automatically adjust the brightness according to the collected PM2.5 concentration and lighting conditions. When the air pollution is serious, the street lamp will increase the brightness to improve visibility, thereby reducing light pollution. Street lamps support multiple communication interfaces, such as Wi-Fi, LoRa, 4G / 5G, etc., to realize real-time transmission and remote monitoring of environmental data. The city management platform can receive and analyze the incoming data in real time, respond and adjust management strategies in a timely manner, and improve the city's emergency response capabilities and management efficiency. Street lamps are equipped with high-definition cameras that can monitor the situation of roads and surrounding areas in real time, providing strong support for public security prevention and control and traffic management. In addition to basic lighting functions, they also integrate multiple functions such as environmental monitoring, intelligent dimming, and video surveillance, simplifying equipment deployment and management and improving monitoring efficiency.

[0044] Embodiment 10: like Fig.10 As shown, based on Embodiments 1 to 9, a control method for an adaptive dimming LED street lamp for a low-carbon, environmentally friendly smart city provided by an embodiment of the present invention comprises the following steps: Step S100: collecting road-related information such as ambient light intensity, pedestrian flow, and vehicle flow in real time, preprocessing the road-related information, and transmitting the preprocessed road-related information to the lighting control module; Step S200 is used to process and analyze road-related information, taking ambient light intensity, pedestrian flow and vehicle flow as input variables and LED street lamp brightness as output variables, adjusting the brightness of the LED street lamp according to the output variables, and uploading the status and data of the street lamp to the central management system; Step S300 is used to realize communication between the central management system and the smart city security system. The smart city security system detects the status of street lamps in real time. If an abnormality is detected in the street lamps, the relevant departments are notified for maintenance. If an abnormality is detected in the road, the smart city security system adjusts the LED street lamps.

[0045] In the above embodiment, in step S100 of this embodiment, road-related information such as ambient light intensity, pedestrian flow, and vehicle flow is collected in real time, and preprocessed to ensure the accuracy and availability of the data. Environmental data such as light intensity, pedestrian flow, and vehicle flow are monitored in real time through the sensor module. In step S200, road-related information is processed and analyzed, the brightness of the LED street lamp is adjusted according to the input variables (ambient light intensity, pedestrian flow, and vehicle flow), and the street lamp status and data are uploaded to the central management system. By using the intelligent controller and the management cloud platform, the optimal street lamp control strategy is formulated through big data analysis and artificial intelligence algorithms to achieve dynamic dimming and intelligent switching, thereby achieving energy-saving effects. In addition, the system can automatically adjust the brightness and switching time of the street lamp according to seasonal changes, weather conditions, and traffic flow, further improving management efficiency and reducing energy consumption. In step S300, the central management system communicates with the smart city security system to detect the status of the street lamp in real time. If the street lamp is detected to be abnormal, the relevant department is notified for maintenance; at the same time, the smart city security system adjusts the LED street lamp when the road is detected to be abnormal. Remote monitoring and fault diagnosis of the street lamp status are achieved through the Internet of Things technology to ensure the normal operation of the street lamp. In addition, the system also has an intelligent alarm function, which can promptly notify relevant departments for repairs when street lights fail, thereby improving maintenance efficiency. The smart city security system can also adjust the brightness of LED street lights according to abnormal road conditions to ensure nighttime driving safety.

[0046] Embodiment 11: On the basis of Embodiments 1 to 9, an adaptive dimming LED street lamp control device for a low-carbon, environmentally friendly smart city provided in an embodiment of the present invention comprises: an electronic device including an ARM embedded processor, a wireless data transmission unit, an LED street lamp, a light intensity sensor, a vehicle monitoring sensor, a pedestrian monitoring sensor, a haze monitoring sensor, a temperature and humidity sensor, and a toxic gas sensor; ARM embedded processor, light intensity sensor, vehicle monitoring sensor, pedestrian monitoring sensor, haze monitoring sensor, temperature and humidity sensor and toxic gas sensor transmit the collected data to the ARM embedded processor, which performs fuzzy processing on the data, controls the brightness of LED street lamps according to the fuzzy processing, and performs real-time monitoring based on the collected data, and transmits the data with monitoring data greater than the preset value to the corresponding system to issue a light warning; Fig.11 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present invention is shown.

[0047] The electronic device may include a central processing unit / microprocessor / main control chip, etc. 4; a storage medium 5, coupled to the central processing unit / microprocessor / main control chip, etc. 4, and storing computer executable instructions therein, for performing the steps of each method of an embodiment of the present invention when executed by the processor.

[0048] The central processing unit / microprocessor / main control chip 4 may include but is not limited to, for example, one or more processors or microprocessors.

[0049] The storage medium 5 may include, but is not limited to, for example, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (such as hard disk, floppy disk, solid state drive, removable disk, CD‑ROM, DVD‑ROM, Blu-ray disc, etc.).

[0050] In addition, the electronic device may also include (but not limited to) a data bus 6, an input / output bus / external bus / device bus 7, a display 8, and input / output devices 9 (eg, keyboard, mouse, speaker, etc.).

[0051] The central processing unit / microprocessor / main control chip etc. 4 can communicate with external devices ( 8 , 9 etc.) through the I / O bus 7 via a wired or wireless network (not shown).

[0052] The storage medium 5 may also store at least one computer executable instruction for executing the various functions and / or method steps in the embodiments described in the present technology when executed by the central processing unit / microprocessor / main control chip 4.

[0053] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0054] Fig.12 A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0055] like Fig.12As shown, instructions are stored on a non-transitory computer-readable storage medium 11, and the instructions are, for example, computer-readable instructions 10. When the computer-readable instructions 10 are executed by the processor, the various methods described above can be executed. Non-transitory computer-readable storage media include, but are not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. Non-transitory non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium 11 can be connected to a computing device such as a computer, and then, when the computing device runs the computer-readable instructions 10 stored on the computer-readable storage medium 11, the various methods described above can be performed.

[0056] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0057] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0058] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0059] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions for executing all or part of the steps of the various embodiments of the method of the present invention through a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (full name in English: Read-Only Memory, English abbreviation: ROM), random access memory (full name in English: Random Access Memory, English abbreviation: RAM), disk or optical disk and other media that can store program code.

[0060] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities, characterized in that: Adaptive dimming LED street lights for low-carbon and environmentally friendly smart cities, including: An information and transmission acquisition module is used to collect information related to ambient light intensity, pedestrian flow, and vehicle flow in real time, pre-process the road-related information, and transmit the pre-processed road-related information to the lighting control module; The lighting control module is used to process and analyze road-related information, taking ambient light intensity, pedestrian flow and vehicle flow as input variables and LED street light brightness as output variables. The brightness of LED street lights is adjusted according to the output variables, and the status and data of street lights are uploaded to the central management system. The road warning module is used to realize communication between the central management system and the smart city security system. The smart city security system detects the status of street lights in real time. If an abnormality is detected in the street lights, the relevant departments will be notified for maintenance. If the smart city security system detects an abnormality in the road, it will adjust the LED street lights.

2. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities according to claim 1, characterized in that: Information and transmission acquisition module, including: The data acquisition submodule is used to obtain the environmental status data set of the LED street lamp, the pedestrian status data set and the vehicle flow status data set, and perform cleaning, noise removal, outlier removal and data conversion preprocessing operations on them; The data analysis submodule is used to compare the environmental status data set of the LED lamp to obtain the benchmark brightness of the LED street lamp; to conduct a comprehensive analysis on the monitored pedestrian status data set to obtain the pedestrian status characteristic value; to calculate the traffic flow status data set to obtain the traffic flow status characteristic value; The data output submodule is used to output the LED street lamp benchmark lighting brightness, pedestrian status characteristic values ​​and traffic flow status values ​​to the lighting control module.

3. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities as claimed in claim 2, characterized in that: Data analysis submodule, including: The environmental status module is used to obtain the environmental status data set of the street lamp, comprehensively analyze and obtain the characteristic value of the environmental status of the street lamp, and use the characteristic value of the environmental status of the street lamp as a comparison to obtain the basis for analyzing the reference brightness of the street lamp; compare the characteristic value of the environmental status of the street lamp with the reference brightness of the street lamp corresponding to the characteristic value of the environmental status of each street lamp stored in the database, and obtain the reference brightness of the street lamp corresponding to the characteristic value of the environmental status of the street lamp; The pedestrian flow unit is used to turn on the reference brightness of the street lamp when a pedestrian is detected; obtain the data set of the street lamp monitoring pedestrian status, and conduct a comprehensive analysis to obtain the street lamp monitoring pedestrian characteristic value, and the intelligent street lamp monitoring pedestrian status characteristic value is used as the analysis basis for the comprehensive analysis to obtain the street lamp brightness evaluation value; The vehicle flow unit is used to light up the street light at a reference brightness when a vehicle is detected; a data set of vehicle status monitored by the street light is obtained, and a comprehensive analysis is performed to obtain a characteristic value of the vehicle monitored by the street light. The characteristic value of the vehicle status monitored by the intelligent street light is used as the analysis basis for the comprehensive analysis to obtain the evaluation value of the street light brightness.

4. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities as claimed in claim 2, characterized in that: Lighting control module, including: The fuzzy processing submodule is used to collect information related to ambient light intensity, pedestrian flow and vehicle flow in real time; fuzzy processing is performed on the collected deterministic variables, and ambient light intensity, pedestrian flow and vehicle flow are used as input variables, the input variables are mapped to fuzzy sets, and a membership function is defined for each input variable to obtain fuzzy variables; The fuzzy control submodule is used to set the fuzzy control rule base according to the relationship between the input variables and the output variables; perform calculations based on the input variables and the fuzzy control rule base, perform weighted average on the variable characteristic values, and obtain the final fuzzy control quantity; The control command submodule is used to convert the final fuzzy control variables into clear numerical values, use the clear numerical values ​​as output variables, issue commands to control LED street lights, and upload the street light status and data to the central management system.

5. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities as claimed in claim 4, characterized in that: Fuzzy control submodule, including: The characteristic value sorting unit is used to sort the collected input variables according to the timestamps; count the characteristic values, segment the characteristic values ​​after counting, and set the corresponding characteristic areas with the timestamps as nodes; The calculation element unit is used to convert the precise quantity into a fuzzy single point set, convert the precise quantity correspondence into a basic element, and perform nonlinear fuzzification algorithm calculation on it; analyze the input variable and the output variable to obtain the relationship between the input variable and the output variable, and set the fuzzy control rule base; The final precise quantity unit is used to infer the fuzzy value according to the nonlinear fuzzy algorithm, and obtain the final precise quantity output after defuzzifying the value; and convert the fuzzy control quantity into a clear numerical value.

6. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities as claimed in claim 5, characterized in that: Computational element units, including: The fuzzy control rule base subunit is used to determine the membership function and establish the fuzzy control rule base; perform fuzzification input and convert the precise input into the membership value in the fuzzy set; evaluate each rule in the fuzzy control rule base and determine the activation degree of each rule; The control instruction subunit is used to determine the membership, combine all activated rules for data, use the minimum operation for aggregation, and convert the fuzzy input into precise control rules after evaluating the rules; the defuzzification process will determine the final control LED street light brightness instruction; The adjustment strategy subunit is used to perform fuzzification using the weighted average method and perform weighted average of the membership degree; based on the defuzzification results, it generates control light instructions to adjust the brightness of the LED street lights; finally, it performs closed-loop feedback, compares the controller output results with the preset light targets, and adjusts the control strategy based on the deviation.

7. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities as claimed in claim 4, characterized in that: Control command submodule, including: The clear value unit is used to infer the fuzzy value according to the nonlinear fuzzy algorithm, and obtain the final accurate output after defuzzifying the value; and convert the fuzzy control amount into a clear value; The scale value calculation unit is used to calculate the scale values ​​of the input and output, determine the fuzzy sum corresponding to the scale values ​​of the input and output, track the input changes in real time, and calculate the output scale value according to the input changes; The upload transmission unit is used to use clear numerical values ​​as output variables, issue commands to control LED street lights, and upload street light status and data to the central management system.

8. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities as claimed in claim 1, characterized in that: Road warning module, including: The road monitoring submodule is used to monitor street lights and road conditions in real time. If an abnormality of a street light is detected, an alarm signal will be issued immediately and the relevant departments will be notified for maintenance. The light warning submodule is used to detect abnormal road conditions, adjust the flashing of street lights according to the abnormal conditions, analyze them, and take corresponding measures; The strategy adjustment submodule is used to collect historical street light data, analyze it, and adjust the street light strategy based on the analysis results.

9. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities as claimed in claim 8, characterized in that: The road abnormalities detected by the light warning submodule include illegal parking, speeding and traffic accidents.

10. A control method for an adaptive dimming LED street lamp for a low-carbon, environmentally friendly smart city, implementing an adaptive dimming LED street lamp for a low-carbon, environmentally friendly smart city as claimed in any one of claims 1 to 9, characterized in that: The control method of the adaptive dimming LED street lamp for a low-carbon and environmentally friendly smart city comprises: Collect information about ambient light intensity, pedestrian flow, and vehicle flow in real time, pre-process the road-related information, and transmit the pre-processed road-related information to the lighting control module; It is used to process and analyze road-related information, taking ambient light intensity, pedestrian flow and vehicle flow as input variables and LED street light brightness as output variables, adjusting the brightness of LED street lights according to the output variables, and uploading the status and data of street lights to the central management system; The central management system communicates with the smart city security system, which detects the status of street lights in real time. If an abnormality is detected in a street light, the relevant department will be notified for repair. If an abnormality is detected in the road, the smart city security system will adjust the LED street lights.

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