Adaptive Dimming LED Street Lamp for Low-Carbon, Environmentally Friendly Smart City and Its Control Method

Abstract

The present invention relates to the technical field of street lamp control, and particularly to an adaptive dimming LED street lamp for a low-carbon and environmentally friendly smart city and its control method. The method includes: collecting real-time information on ambient light intensity, pedestrian flow, and vehicle flow on the road, preprocessing the road-related information, and processing and analyzing the road-related information; using the ambient light intensity, pedestrian flow, and vehicle flow as input variables and the brightness of the LED street lamp as the output variable; adjusting the brightness of the LED street lamp according to the output variable, communicating with the smart city security system, and the smart city security system detecting the status of the street lamp in real time. The system includes: an information and transmission collection module, a lighting control module, and a road warning module. The present invention solves the problems of low intelligence, insufficient remote control and monitoring capabilities, and limited energy-saving effects; the LED street lamp of the present invention has a significant energy-saving effect, prolongs the service life of the LED lamp, reduces the maintenance cost, and improves the safety and beauty of the city.

Description

Technical Field

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

[0002] As a typical representative of a new type of green light source, LED street lamps are widely used in fields such as general lighting, road lighting, and special lighting. Traditional LED street lamps cannot meet the actual lighting needs and consume and waste a large part of the energy. The core goal of an intelligent induction street lamp system is to achieve intelligent management and control of street lamps through Internet of Things technology, so as to achieve the purposes of energy conservation and emission reduction, improving lighting efficiency, and user experience.

[0003] Prior Art One, a Chinese patent, application number: 202321197283.4 discloses an LED street lamp capable of self-inductive control, belonging to the technical field of LED lighting fixtures, including an induction device electrically connected to the signal end of a control device. The input end and output end of the control device are respectively electrically connected to the output end of a signal device and the dimming control end of a dimming power supply. The input end of the signal device is electrically connected to the input end of the dimming power supply through a wiring terminal. The output end of the dimming power supply is electrically connected to an LED light source. The control device is electrically connected to the wiring terminal, and the wiring terminal is electrically connected to a municipal power supply network. It discloses an LED street lamp capable of self-inductive control, which has a simple structure. While saving energy with the LED light source, when the induction device fails to detect no people and 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 exists in the way of staying lit all night; however, the remote control and monitoring capabilities are insufficient.

[0004] Prior Art Two, a Chinese patent, application number: 202323314782.X relates to the field of street lamp control, and specifically relates to a control circuit for an inductive energy-saving LED street lamp, including a driving power supply, a controller, and a motion sensor. When the target section is in a low-traffic period at night, the sensor control circuit controls the motion sensor to be powered on; the motion sensor is signal-connected to the driving power supply. When the motion sensor detects a moving object, it controls the LED lamp to resume 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 states of all street lamps are switched to the energy-saving working mode. When a moving object appears in the target section, the working states of the street lamps in that section are temporarily switched to the normal working mode. Although, to ensure the lighting demand in this section at this time, the waste of electric power resources is greatly reduced. However, there is a lack of an integrated management platform and it is impossible to achieve global monitoring and management of all street lamps.

[0005] Prior Art Three, a Chinese patent with the application number 202311662254.5, relates to the field of street lamp control technology. Specifically, it relates to a time-sharing control method for an inductive energy-saving LED street lamp, which includes the following steps: setting the lighting time T1 and the extinguishing time T2; calculating the time control period of the street lamp; where T3 and T4 are respectively the preset lighting delay time and extinguishing delay time; within the brightness regulation period, lower the brightness of all street lamps on the target road section; during the brightness regulation period, detect whether there are moving objects on the road surface of the target road section. When the street lamp is in the lit working state, set the street lamps on the whole road section to the energy-saving working mode with low brightness during the low traffic volume period. Although, when a vehicle or other moving object passes by, temporarily set the street lamps on the road section where the vehicle or moving object passes to the normal working mode with high brightness, which greatly reduces the waste of electric power resources; however, the degree of intelligence is relatively low and it cannot flexibly meet the requirements of complex environmental changes.

[0006] Currently, Prior Art One, Prior Art Two, and Prior Art Three have problems such as insufficient remote control and monitoring capabilities, lack of a comprehensive management platform, inability to achieve global monitoring and management of all street lamps, relatively low degree of intelligence, and inability to flexibly meet the requirements of complex environmental changes. Therefore, the present invention provides an adaptive dimming LED street lamp and its control method for a low-carbon and environmentally friendly smart city. Summary of the Invention

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] On the one hand, the present invention provides an adaptive dimming LED street lamp for a low-carbon and environmentally friendly smart city, including:

[0009] An information and transmission collection module, which is used to collect road-related information such as ambient light intensity, pedestrian flow, and vehicle flow in real time, preprocess the road-related information, and transmit the preprocessed road-related information to the lighting control module;

[0010] A lighting control module, which is used to process and analyze the road-related information, take the ambient light intensity, pedestrian flow, and vehicle flow as input variables and the brightness of the LED street lamp as the output variable, adjust the brightness of the LED street lamp according to the output variable, and upload the status and data of the street lamp to the central management system;

[0011] A road warning module, which is used to communicate between the central management system and the smart city security system. The smart city security system detects the status of the street lamp in real time. If an abnormal street lamp is detected, it notifies the relevant department for repair; if the smart city security system detects an abnormal road, it adjusts the LED street lamp.

[0012] In an optional implementation manner, the information and transmission collection module includes:

[0013] A data acquisition sub-module, which is used to obtain the environmental status data set, pedestrian status data set, and traffic flow status data set of the LED street lamp, and perform preprocessing operations such as cleaning, noise removal, outlier removal, and data conversion on them;

[0014] Among them, the environmental status data set includes the street lamp density in the environment where the street lamp is located, the data density in the environment where the street lamp is located, and the absolute value of the difference between the height of the tree in the environment where the street lamp is located and the reference tree height;

[0015] A data analysis sub-module, which is used to compare the environmental status data set where the LED lamp is located to obtain the reference brightness for the LED street lamp to light up; comprehensively analyze the pedestrian status data set to obtain the pedestrian status characteristic value; calculate the traffic flow status data set to obtain the traffic flow status characteristic value;

[0016] A data output sub-module, which is used to output the reference brightness for the LED street lamp to light up, the pedestrian status characteristic value, and the traffic flow status value to the lighting control module.

[0017] In an optional implementation manner, the data analysis sub-module includes:

[0018] An environmental status module, which is used to obtain the environmental status data set of the environment where the street lamp is located, comprehensively analyze to obtain the environmental status characteristic value of the environment where the street lamp is located, and use the environmental status characteristic value of the environment where the street lamp is located as the analysis basis for comparing to obtain the reference brightness of the street lamp; compare the environmental status characteristic value of the environment where the street lamp is located with the reference brightness for the street lamp to light up corresponding to the environmental status characteristic value of each street lamp stored in the database to obtain the reference brightness for the street lamp to light up corresponding to the environmental status characteristic value of the environment where the street lamp is located;

[0019] A pedestrian flow unit, which is used to make the street lamp light up with the reference brightness when a pedestrian is detected; obtain the pedestrian status data set monitored by the street lamp, comprehensively analyze to obtain the pedestrian characteristic value monitored by the street lamp, and use the pedestrian status characteristic value monitored by the intelligent street lamp as the analysis basis for comprehensively analyzing to obtain the street lamp brightness evaluation value;

[0020] Among them, the pedestrian status data set monitored by the street lamp includes the closest distance between the pedestrian and the street lamp, the walking speed of the pedestrian closest to the street lamp, the number of pedestrians monitored by the street lamp, and the length of the continuous straight walking distance of the pedestrians monitored by the street lamp;

[0021] A traffic flow unit, which is used to make the street lamp light up with the reference brightness when a vehicle is detected; obtain the vehicle status data set monitored by the street lamp, comprehensively analyze to obtain the vehicle characteristic value monitored by the street lamp, and use the vehicle status characteristic value monitored by the intelligent street lamp as the analysis basis for comprehensively analyzing to obtain the street lamp brightness evaluation value;

[0022] Among them, the lamp detection pedestrian status dataset includes the closest distance between the vehicle and the street lamp, the driving speed of the vehicle closest to the street lamp, the number of vehicles monitored by the street lamp, and the length of the continuous straight walking distance of the vehicle monitored by the street lamp.

[0023] In an optional implementation manner, the lighting control module includes:

[0024] The fuzzification processing sub-module is used to collect road-related information such as ambient light intensity, pedestrian flow, and vehicle flow in real time; perform fuzzification processing on the collected determined variables, use the ambient light intensity, pedestrian flow, and vehicle flow as input variables, map the input variables to the fuzzy set, and define a membership function for each input variable to obtain fuzzy variables.

[0025] The fuzzy control sub-module is used to set a fuzzy control rule base according to the relationship between the input variable and the output variable; perform calculations according to the input variable and the fuzzy control rule base, perform weighted averaging on its variable characteristic values, and obtain the final fuzzy control quantity;

[0026] The control command sub-module is used to convert the final fuzzy control variable into a clear numerical value, use the clear numerical value as the output variable, issue a control command for the LED street lamp, and upload the street lamp status and data to the central management system.

[0027] In an optional implementation manner, the fuzzy control sub-module includes:

[0028] The eigenvalue sorting unit is used to sort the collected input variables according to the time stamp; perform statistics on its eigenvalue, perform segmented processing on the statistically processed eigenvalue, and set the corresponding characteristic area with the time stamp as the node;

[0029] The calculation element unit is used to convert the accurate quantity into a fuzzy singleton set, convert the accurate quantity correspondence into basic elements, and perform non-linear 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 a fuzzy control rule base;

[0030] The final accurate quantity unit is used to perform reasoning on the fuzzy value according to the non-linear fuzzy algorithm, obtain the final accurate quantity output after defuzzification; and convert the fuzzy control quantity into a clear numerical value.

[0031] In an optional implementation manner, the calculation element unit includes:

[0032] The fuzzy control rule base sub-unit is used to determine the membership function, establish a fuzzy control rule base; perform fuzzification input, convert the accurate input into the membership degree value in the fuzzy set; evaluate each rule in the fuzzy control rule base to determine the activation degree of each rule;

[0033] The control instruction sub-unit is used to determine the membership degree, combine all activated rules for data, aggregate using the minimum operation, and after evaluating the rules, convert the fuzzy input into an exact control rule; the defuzzification process will determine the final control instruction for the brightness of the LED street lamp;

[0034] The adjustment strategy sub-unit is used to perform fuzzification using the weighted average method and perform a weighted average on the membership degree; according to the result of defuzzification, generate a control instruction for the light, adjust the brightness of the LED street lamp; finally, perform closed-loop feedback, compare the output result of the controller with the preset light target, and adjust the control strategy according to the deviation.

[0035] In an alternative embodiment, the control command sub-module includes:

[0036] The crisp value unit is used to perform inference on the fuzzy value according to the non-linear fuzzy algorithm, and after defuzzifying the value, obtain the final exact quantity output; and convert the fuzzy control quantity into a crisp value;

[0037] The calculation scale value unit is used to calculate the scale values of the input and output, determine the fuzzy sets corresponding to the scale values of the input and output, track the input change in real time, and calculate the scale value of the output according to the input change;

[0038] The upload transmission unit is used to use the crisp value as the output variable, issue a control command for the LED street lamp, and upload the street lamp status and data to the central management system.

[0039] In an alternative embodiment, the road warning module includes:

[0040] The road monitoring sub-module is used to monitor the street lamp and road conditions in real time. If an abnormal situation of the street lamp is detected, an alarm signal is immediately issued and relevant departments are notified for maintenance;

[0041] The light warning sub-module is used to adjust the flashing situation of the street lamp according to the abnormal situation when an abnormal situation of the road is detected, and analyze it to obtain corresponding measures; among them, the abnormal situations of the road include abnormal situations such as vehicle illegal parking, speeding behavior, and car accidents;

[0042] The adjustment strategy sub-module is used to collect historical street lamp data and analyze it, and adjust the street lamp strategy according to the analysis result; among them, the historical street lamp data includes energy consumption data, fault data, lighting duration, etc.

[0043] On the other hand, the present invention provides a control method for an adaptive dimming LED street lamp for a low-carbon environmental protection smart city, including:

[0044] Collect real-time road-related information such as ambient light intensity, pedestrian flow, and vehicle flow, preprocess the road-related information, and transmit the preprocessed road-related information to the lighting control module;

[0045] It is used to process and analyze road-related information. Taking ambient light intensity, pedestrian flow, and vehicle flow as input variables and the brightness of LED street lights as output variables, it adjusts the brightness of LED street lights according to the output variables, and uploads the status and data of the street lights to the central management system;

[0046] The central management system communicates with the smart city security system. The smart city security system detects the status of street lights in real time. If an abnormal street light is detected, it notifies the relevant department for maintenance; if an abnormal road is detected by the smart city security system, it adjusts the LED street lights.

[0047] Through the Internet of Things (IoT) technology, the present invention can automatically adjust the brightness or switch status of street lights according to real-time data such as road pedestrian and vehicle flow and ambient light intensity with its powerful connectivity and intelligent features. It not only ensures the safety and convenience of night driving, but also effectively reduces unnecessary energy waste, and constructs a low-carbon and environmentally friendly smart city. Through the Internet of Things technology, the present invention realizes 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 of manual inspections and maintenance costs; accurate energy consumption statistics provide a basis for scientific decision-making by the management department, and further optimize resource allocation. Through the linkage with the security system, smart street lights can also issue alarms in a timely manner in case of abnormalities, escorting the safety of the city. Description of the Drawings

[0048] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0049] Figure 1 It is a block diagram of an adaptive dimming LED street light for a low-carbon and environmentally friendly smart city provided in Embodiment 1 of the present invention;

[0050] Figure 2 It is a block diagram of an information and transmission collection module provided in Embodiment 2 of the present invention;

[0051] Figure 3 It is a block diagram of a data analysis sub-module provided in Embodiment 3 of the present invention;

[0052] Figure 4 It is a block diagram of a lighting control module provided in Embodiment 4 of the present invention;

[0053] Figure 5It is the block diagram of the fuzzy control sub-module provided in Embodiment 5 of the present invention;

[0054] Figure 6 It is the block diagram of the computing element unit provided in Embodiment 6 of the present invention;

[0055] Figure 7 It is the block diagram of the control command sub-module provided in Embodiment 7 of the present invention;

[0056] Figure 8 It is the block diagram of the road warning module provided in Embodiment 8 of the present invention;

[0057] Figure 9 It is another block diagram of the adaptive dimming LED street lamp for a low-carbon and environmentally friendly smart city provided in Embodiment 9 of the present invention;

[0058] Figure 10 It is the flowchart of the control method of the adaptive dimming LED street lamp for a low-carbon and environmentally friendly smart city provided in Embodiment 10 of the present invention;

[0059] Figure 11 It is the block diagram of the electronic device provided by the present invention;

[0060] Figure 12 It is the block diagram of the computer-readable storage medium provided by the present invention. Detailed implementation manners

[0061] Next, the technical solutions in the embodiments of the present invention will be described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0062] Hereinafter, terms such as "first" and "second" are only for convenience of description, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise stated, the meaning of "a plurality" is two or more.

[0063] In the present invention, unless otherwise clearly specified or limited, the term "connection" shall be understood in a broad sense. For example, "connection" can be a fixed mechanical connection, a detachable mechanical connection, or an integral one; or, "connection" can be a direct connection, or an indirect connection through an intermediate medium. In addition, unless otherwise clearly specified or limited, the term "coupling" shall be understood in a broad sense. For example, "coupling" can be a direct electrical connection. For example, there is physical contact and electrical conduction between two components, and it can also be understood that different components in a circuit structure are electrically connected through an entity line such as a copper foil or a wire of a printed circuit board (PCB) that can transmit electrical signals for electrical signal transmission; 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 a non-contact manner. For example, two components are electrically connected by means of capacitive coupling for electrical signal transmission.

[0064] In the embodiments of the present invention, orientation terms such as "upper", "lower", "left", and "right" can include but are not limited to being defined relative to the schematic placement of components in the drawings. It should be understood that these directional terms can be relative concepts, which are used for relative description and clarification, and they can change accordingly with the change of the placement orientation of the components in the drawings.

[0065] The embodiments of the present invention can be used for urban road lighting, community and park lighting, parking lots, underground garages, parks and squares, as well as tunnel and bridge lighting.

[0066] Key technical features of the embodiments of the present invention: Through the Internet of Things (IoT) technology with its powerful connectivity and intelligent features, it can automatically adjust the brightness or switch state of street lights according to real-time data such as road traffic flow of people and vehicles, ambient light intensity, etc., which not only ensures the safety and convenience of night driving, but also effectively reduces unnecessary energy waste, and constructs a low-carbon and environmentally friendly smart city. Through the Internet of Things technology, remote monitoring and real-time data analysis of lighting facilities are realized. Managers can discover and handle faults in a timely manner, reduce energy waste and potential safety hazards caused by equipment failures, and reduce the frequency of manual inspections and maintenance costs. Accurate energy consumption statistics provide a basis for scientific decision-making for management departments, and further optimize resource allocation. Through the linkage with the security system, intelligent street lights can also issue alarms in a timely manner in case of abnormalities, escorting the safety of the city.

[0067] Embodiment 1:

[0068] As Figure 1 shown, the embodiments of the present invention provide an adaptive dimming LED street light for a low-carbon and environmentally friendly smart city, comprising:

[0069] An 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, preprocess the road-related information, and transmit the preprocessed road-related information to the lighting control module 2;

[0070] A 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 the brightness of LED street lights as output variables, it adjusts the brightness of LED street lights according to the output variables, and uploads the status and data of the street lights to the central management system;

[0071] A road warning module 3 is used to communicate 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 abnormal street light is detected, it notifies the relevant department for repair; if an abnormal road is detected by the smart city security system, it adjusts the LED street lights.

[0072] In the above embodiment, in this embodiment, through the Internet of Things (IoT) technology with its powerful connectivity and intelligent features, it can automatically adjust the brightness or switch status of street lights according to real-time data such as road pedestrian and vehicle flow, ambient light intensity, etc., which not only ensures the safety and convenience of night driving, but also effectively reduces unnecessary energy waste, and constructs a low-carbon and environmentally friendly smart city. Through the Internet of Things technology, remote monitoring and real-time data analysis of lighting facilities are realized. Managers can discover and handle faults in time, reduce energy waste and safety hazards caused by equipment failures, and reduce the frequency of manual inspections and maintenance costs. Accurate energy consumption statistics provide a basis for scientific decision-making for management departments, and further optimize resource allocation. Through the linkage with the security system, smart street lights can also issue alarms in a timely manner in case of abnormalities, escorting the safety of the city.

[0073] Embodiment 2:

[0074] As Figure 2 shown, on the basis of Embodiment 1, in the information and transmission acquisition module 1 provided by the embodiment of the present invention, it includes:

[0075] A data acquisition sub-module 11 is used to obtain datasets of the environmental status of LED street lights, datasets of monitoring pedestrian status, and datasets of vehicle flow status, and perform preprocessing operations such as cleaning, noise removal, outlier removal, and data conversion on them;

[0076] Among them, the environmental status dataset includes the street light density in the environment where the street light is located, the data density in the environment where the street light is located, and the absolute value of the difference between the height of the tree in the environment where the street light is located and the height of the reference tree;

[0077] The data analysis sub-module 12 is used to compare the environmental state data sets of the LED lights to obtain the reference brightness for the LED street lights to turn on; comprehensively analyze the pedestrian state data sets to obtain pedestrian state characteristic values; calculate the traffic flow state data sets to obtain traffic flow state characteristic values.

[0078] The expression for obtaining the traffic flow state characteristic value:

[0079] We can design a more complex expression:

[0080]

[0081] In the formula, V represents the total number of vehicles passing through a certain monitoring point per unit time, S 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 state. T represents the traffic flow distribution in different time periods, R represents the influence coefficient of different road types, Wc represents the influence of different weather conditions on traffic; represents the number of monitoring points, represents the i traffic flow at the th monitoring point, i represents the average vehicle speed at the th monitoring point, i represents the vehicle type weight at the th monitoring point, i represents the time distribution at the th monitoring point, i represents the road type at the th monitoring point, i represents the weather condition at the th monitoring point; th monitoring point; th monitoring point; th monitoring point; th monitoring point; th monitoring point are the weight coefficients of each factor respectively. The expression comprehensively considers the influence of multiple factors on the traffic flow state. By adjusting each weight coefficient, the actual traffic state can be more accurately reflected; the weight coefficients can be optimized and adjusted according to historical data and actual needs to improve the accuracy and practicality of the traffic flow state characteristic values;

[0082] The data output sub-module 13 is used to output the reference brightness for the LED street lights to turn on, the pedestrian state characteristic values, and the traffic flow state values to the lighting control module.

[0083] In the above embodiments, the data acquisition sub-module 11 of this embodiment is responsible for collecting in real time the state data set of the environment where the LED street lamp is located, the pedestrian state data set, and the traffic 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, etc., as well as the traffic flow information of pedestrians and vehicles. Through high-precision sensors and analog-to-digital converters. In addition, this module also preprocesses the data, such as cleaning, removing noise and outliers, to improve the data quality. The data analysis sub-module 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 traffic flow state data set to obtain the traffic 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 sub-module 13 outputs the reference lighting brightness of the LED street lamp, the pedestrian state characteristic value, and the traffic 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 of data transmission. At the same time, this module also supports flexible control strategies and can dynamically adjust the brightness of the street lamp according to different environmental and traffic conditions.

[0084] Embodiment 3:

[0085] As Figure 3 shown, on the basis of Embodiment 2, in the data analysis sub-module 12 provided by the embodiment of the present invention, it includes:

[0086] The environmental state unit 121 is used to obtain the environmental state data set where the street lamp is located, comprehensively analyze to obtain the environmental state characteristic value where the street lamp is located, and use the environmental state characteristic value where the street lamp is located as the analysis basis for comparing and obtaining the reference brightness of the street lamp; compare the environmental state characteristic value where the street lamp is located with the reference lighting brightness of the street lamp corresponding to the environmental state characteristic value of each street lamp stored in the database to obtain the reference lighting brightness of the street lamp corresponding to the environmental state characteristic value where the street lamp is located;

[0087] The pedestrian flow unit 122 is used to turn on the reference brightness of the street lamp when a pedestrian is detected; obtain the pedestrian state data set monitored by the street lamp, comprehensively analyze to obtain the pedestrian characteristic value monitored by the street lamp, and use the pedestrian state characteristic value monitored by the intelligent street lamp as the analysis basis for comprehensively analyzing and obtaining the street lamp brightness evaluation value;

[0088] Among them, the pedestrian state data set detected by the street lamp includes the closest distance between the pedestrian and the street lamp, the walking speed of the pedestrian closest to the street lamp, the number of pedestrians detected by the street lamp, and the length of the continuous straight walking distance of the pedestrians detected by the street lamp;

[0089] The traffic flow unit 123 is used to turn on the street lamp at the reference brightness when a vehicle is detected; obtain the vehicle status data set monitored by the street lamp, comprehensively analyze to obtain the vehicle characteristic value monitored by the street lamp, and use the intelligent street lamp monitored vehicle status characteristic value as the analysis basis for comprehensively analyzing the street lamp brightness evaluation value;

[0090] Among them, the lamp detects the pedestrian status data set including the closest distance between the vehicle and the street lamp, the driving speed of the vehicle closest to the street lamp, the number of vehicles monitored by the street lamp, and the length of the continuous straight-line walking distance of the vehicles monitored by the street lamp.

[0091] In the above embodiment, the environmental status unit 121 of this embodiment obtains the environmental status data set where the street lamp is located, comprehensively analyzes to obtain the environmental status characteristic value where the street lamp is located, and uses it as the basis for analyzing the comparison reference brightness. This module can compare the environmental status characteristic value with the reference brightness of the street lamp corresponding to the environmental status characteristic value of each street lamp stored in the database, so as to determine the reference brightness of the street lamp corresponding to the environmental status characteristic value where the street lamp is located. Use the sensor network to real-time monitor data such as environmental illumination and meteorological conditions, realize dynamic adjustment of street lamp brightness, improve road surface safety, and efficiently utilize energy. The pedestrian flow unit 122 turns on the street lamp at the reference brightness when a pedestrian is detected. By obtaining the pedestrian status data set monitored by the street lamp, comprehensively analyze to obtain the pedestrian characteristic value monitored by the street lamp, as the analysis basis for comprehensively analyzing the street lamp brightness evaluation value. It includes data sets such as the closest distance between the pedestrian and the street lamp, the walking speed of the pedestrian, the number of pedestrians monitored by the street lamp, and the length of the continuous straight-line walking distance of the pedestrians monitored by the street lamp. Through the data set, the street lamp brightness can be intelligently adjusted to adapt to different pedestrian flows and pedestrian activities. The traffic flow unit 123 turns on the street lamp at the reference brightness when a vehicle is detected. By obtaining the vehicle status data set monitored by the street lamp, comprehensively analyze to obtain the vehicle characteristic value monitored by the street lamp, as the analysis basis for comprehensively analyzing the street lamp brightness evaluation value. It includes data sets such as the closest distance between the vehicle and the street lamp, the driving speed of the vehicle, the number of vehicles monitored by the street lamp, and the length of the continuous straight-line walking distance of the vehicles monitored by the street lamp. Through the data set, the street lamp brightness can be intelligently adjusted to adapt to different traffic flows and vehicle activities. This embodiment realizes the dynamic adjustment of street lamp brightness by real-time monitoring and intelligent analysis of environmental status, pedestrian flow, and traffic flow data, improves energy utilization efficiency and road surface safety, and reduces maintenance costs at the same time.

[0092] Embodiment 4:

[0093] As Figure 4 shown, on the basis of Embodiment 1, the lighting control module 2 provided by the embodiment of the present invention includes,

[0094] The fuzzification sub-module 21 is used to collect road-related information such as ambient light intensity, pedestrian flow, and vehicle flow in real time; perform fuzzification processing on the collected determined variables, use the ambient light intensity, pedestrian flow, and vehicle flow as input variables, map the input variables into fuzzy sets, and define membership functions for each input variable to obtain fuzzy variables.

[0095] The fuzzy control sub-module 22 is used to set up a fuzzy control rule base according to the relationship between input variables and output variables; perform calculations based on the input variables and the fuzzy control rule base, perform weighted averaging on the variable characteristic values, and obtain the final fuzzy control quantity;

[0096] The control command sub-module 23 is used to convert the final fuzzy control variable into a clear numerical value, use the clear numerical value as the output variable, issue a control command for the LED street lamp, and upload the street lamp status and data to the central management system.

[0097] In the above embodiment, the fuzzification sub-module 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 performing fuzzification processing on the determined variables. By mapping the ambient light intensity, pedestrian flow, and vehicle flow into fuzzy sets, and defining membership functions for each input variable, fuzzy variables are obtained. Fuzzification processing enables the system to handle uncertainty and subjectivity, converting precise input values into fuzzy sets for subsequent fuzzy reasoning and control. The fuzzy control sub-module 22 sets up a fuzzy control rule base according to the relationship between input variables and output variables, which is the core of the fuzzy controller and directly affects the performance and efficiency of the controller. The control of the controlled object is achieved through fuzzy rules without establishing a mathematical model, but through fuzzy logic reasoning. This enables the system to flexibly adjust the brightness of the street lamp to adapt to changes in the surrounding environment, thereby achieving the effects of energy conservation and improved 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 weighted averaging is performed on the variable characteristic values to obtain the final fuzzy control quantity. The control command sub-module 23 converts the final fuzzy control variable into a clear numerical value as the output variable, issues a control command for 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, improving the overall efficiency and reliability of the system. This embodiment constitutes the core part of the intelligent street lamp system. Through steps such as fuzzification processing, fuzzy control, and defuzzification, the intelligent adjustment of the street lamp brightness is realized, improving the energy utilization efficiency and user experience.

[0098] Embodiment 5:

[0099] As Figure 5As shown in the figure, on the basis of Embodiment 4, in the fuzzy control sub-module 22 provided by the embodiment of the present invention, it includes:

[0100] The eigenvalue sorting unit 221 is used to sort the collected input variables according to the time stamp; count their eigenvalues, perform segmented processing on the statistically processed eigenvalues, and set corresponding characteristic regions with the time stamp as the node;

[0101] The calculation element unit 222 is used to convert the accurate quantity into a fuzzy singleton set, convert the accurate quantity correspondence into basic elements, and perform non-linear fuzzy algorithm calculation on them; analyze the input variables and output variables to obtain the relationship between the input variables and output variables, and set the fuzzy control rule base;

[0102] The final accurate quantity unit 223 is used to infer the fuzzy value according to the non-linear fuzzy algorithm, and after defuzzifying the value, obtain the final accurate quantity output; and convert the fuzzy control quantity into a clear numerical value;

[0103] Among them, the process of the non-linear fuzzy algorithm is:

[0104]

[0105] In the formula, the input variable I represents the input variable collected in the system, and the time stamp T represents the time point when the input variable is collected, and the eigenvalue F represents the eigenvalue of the input variable, and the fuzzy singleton set S represents the fuzzy singleton set obtained by converting the accurate quantity, and the basic element E represents the basic element corresponding to the accurate quantity; the non-linear fuzzy algorithm A represents the algorithm for calculating the fuzzy value, and the fuzzy control rule base R represents the set fuzzy control rule base, and the fuzzy value F represents the fuzzy value obtained by calculating through the non-linear fuzzy algorithm, and the final accurate quantity P represents the final accurate quantity obtained after defuzzification; represents the number of input variables, represents the j th input variable, represents the j th time stamp of the input variable, represents the j th eigenvalue of the input variable, represents the j th fuzzy singleton set corresponding to the input variable, represents the j th basic element corresponding to the input variable, represents the jThe fuzzy control rules corresponding to the input variables , , are the weight coefficients of each factor respectively, represents the non-linear function of the input variable, timestamp and eigenvalue, represents the non-linear function of the fuzzy singleton set and the basic element, represents the non-linear function of the fuzzy control rule. The expression comprehensively considers multiple factors such as input variables, timestamps, eigenvalues, fuzzy singleton sets, basic elements and fuzzy control rules, and calculates through non-linear functions and weight coefficients to obtain the final fuzzy value; the non-linear functions and weight coefficients can be optimized and adjusted according to actual needs to improve the accuracy and practicality of the fuzzification algorithm.

[0106] In the above embodiment, the eigenvalue sorting unit 221 of this embodiment sorts the input variables according to the timestamp, and performs statistics and segmentation processing on the eigenvalues, realizing the orderly management and feature extraction of the input data. Using the timestamp as a node, the data is segmented to ensure the continuity and integrity of the data, thus providing reliable basic data support for fuzzy control. The calculation element unit 222 converts the precise quantity into a fuzzy singleton set and calculates through a non-linear fuzzification algorithm, thus realizing an in-depth analysis of the relationship between the input variable and the output variable. By establishing a fuzzy rule base, this unit can flexibly set the relationship between the input and the output, enabling the fuzzy controller to make corresponding control decisions according to different input conditions. Finally, the precision unit 223 infers the fuzzy value through a non-linear fuzzy algorithm and obtains the final precise quantity output after removing the fuzzy value. The fuzzy control quantity is converted into a clear numerical value, and through defuzzification processing, the fuzzy result is converted into an actual control quantity, thus realizing the conversion from fuzzy to precise and enhancing the control precision 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.

[0107] Embodiment 6:

[0108] As Figure 6 shown, on the basis of Embodiment 5, in the calculation element unit 223 provided by the embodiment of the present invention, it includes:

[0109] The fuzzy control rule base sub-unit 2231 is used to determine the membership function, establish a fuzzy control rule base; perform fuzzification input, convert the precise input into the membership degree value in the fuzzy set; evaluate each rule in the fuzzy control rule base to determine the activation degree of each rule;

[0110] The control instruction sub-unit 2232 is used to combine all activated rules for data after determining the membership degree, aggregate using the minimum operation, and convert the fuzzy input into an exact control rule after evaluating the rules; the defuzzification process will determine the final control instruction for the brightness of the LED street lamp;

[0111] The adjustment strategy sub-unit 2233 is used to perform defuzzification using the weighted average method and weight-average the membership degrees; generate a control light instruction according to the result of defuzzification to adjust the brightness of the LED street lamp; finally, perform closed-loop feedback, compare the output result of the controller with the preset light target, and adjust the control strategy according to the deviation.

[0112] In the above embodiments, the fuzzy control rule sub-unit 2231 of this embodiment realizes the conversion of the exact input into the membership degree value in the fuzzy set by determining the membership function and establishing the fuzzy control rule base, and evaluates each rule to determine its activation degree. This enables the system to flexibly match and apply different control rules according to the fuzzy processing of the input variables, thereby improving the adaptability and robustness of the system. By fuzzifying the input variables, uncertainty and subjectivity are introduced into the system, enabling the fuzzy controller to handle complex input-output relationships and realizing approximate control of the system through the membership function and the fuzzy rule base. After determining the membership degree, the control instruction sub-unit 2232 aggregates the data by combining all activated rules and uses the minimum operation for aggregation, and finally converts the fuzzy input into an exact control rule. The defuzzification process determines the final control instruction for the brightness of the LED street lamp, ensuring the accuracy and reliability of the output. Through the minimum operation and defuzzification methods (such as the centroid method or the maximum membership degree method), the result of fuzzy inference is converted into a specific control quantity, thereby realizing the precise adjustment of the brightness of the LED street lamp. The adjustment strategy sub-unit 2233 performs defuzzification using the weighted average method, weight-averages the membership degrees, generates a control light instruction according to the result of defuzzification, and adjusts the brightness of the LED street lamp. Finally, closed-loop feedback is performed, comparing the output result of the controller with the preset light target and adjusting the control strategy according to the deviation to ensure the 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, improving the adaptive ability and stability of the system. This embodiment constitutes a complete fuzzy control system, and through steps such as fuzzification, inference, defuzzification, and closed-loop feedback, it realizes the intelligent adjustment of the brightness of the LED street lamp, improving the flexibility and reliability of the system.

[0113] Embodiment 7:

[0114] As Figure 7 shown, on the basis of Embodiment 4, in the control command sub-module 23 provided by the embodiment of the present invention, it includes:

[0115] A clear value unit 231 is used to reason about fuzzy values according to a non-linear fuzzy algorithm. After defuzzifying the values, a final accurate quantity is output; and the fuzzy control quantity is converted into a clear value.

[0116] A calculation scale value unit 232 is used to calculate the scale values of the input and output, determine the corresponding fuzziness of the input and output scale values, track the input changes in real time, and calculate the output scale value according to the input changes.

[0117] An upload and transmission unit 233 is used to use the clear value as an output variable, issue a command to control the LED street lamp, and upload the street lamp status and data to the central management system.

[0118] In the above embodiment, the numerical clarity unit 231 of this embodiment reasons about the fuzzy value through a non-linear fuzzy algorithm, converts the fuzzy control quantity into a clear value, and finally outputs an accurate quantity. The calculation scale value unit 232 is responsible for calculating the scale values of the input and output, 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, this 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 and transmission unit 233 uses the clear value as an 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 the remote transmission and centralized management of data, enhancing the intelligent level and management efficiency of the system. This embodiment realizes the intelligent adjustment and management of the LED street lamp through fuzzy control technology, improving the energy utilization efficiency and user experience.

[0119] Embodiment 8:

[0120] As Figure 8 shown, on the basis of Embodiment 1, in the road warning module 3 provided by the embodiment of the present invention, it includes:

[0121] A monitoring road sub-module 31 is used to monitor the street lamp and road conditions in real time. If an abnormal situation of the street lamp is detected, an alarm signal is immediately issued, and relevant departments are notified for maintenance.

[0122] A lighting warning sub-module 32 is used to adjust the flashing situation of the street lamp according to the abnormal situation when an abnormal situation of the road is detected, and analyze it to obtain corresponding measures to be taken; among them, the abnormal road conditions include abnormal situations such as vehicle illegal parking, speeding, and car accidents.

[0123] An adjustment strategy sub-module 33 is used to collect historical street lamp data, analyze it, and adjust the street lamp strategy according to the analysis results; among them, the historical street lamp data includes energy consumption data, fault data, lighting duration, etc.

[0124] In the above embodiments, the monitoring road sub-module 31 of this embodiment is used to monitor the street lamp and road conditions in real time. Once an abnormal situation of the street lamp is detected, an alarm signal is immediately sent out, and relevant departments are notified for maintenance. Through the real-time data collection and detection function, the system can timely discover and alarm the abnormal situations of the street lamps, such as lamp failures, terminal failures, cable failures, etc., to ensure the stable operation of the street lamp system. The light warning sub-module 32 can adjust the flashing situation of the street lamps according to the abnormal situation and analyze it to obtain corresponding measures when detecting abnormal road conditions. For example, when detecting abnormal situations such as vehicle illegal parking, speeding or car accidents, the system will automatically adjust the flashing frequency or brightness of the street lamps to improve road safety. It integrates a variety of sensors and intelligent control systems, can sense environmental changes in real time and make corresponding adjustments, such as automatically adjusting brightness, flashing frequency, etc., so as to improve road lighting effects and management efficiency. The adjustment strategy sub-unit 33 collects historical street lamp data (including energy consumption data, fault data, lighting duration, etc.) and analyzes it, and adjusts the street lamp strategy according to the analysis results. Using big data analysis and cloud computing technologies, the system can deeply mine and analyze historical data, generate optimization suggestions, and achieve refined management. In addition, this module also supports remote control and management, further improving the intelligent level of the system.

[0125] Embodiment 9:

[0126] As Figure 9 shown, on the basis of Embodiment 1, the adaptive dimming LED street lamp of the low-carbon environmental protection smart city provided by the embodiment of the present invention further includes:

[0127] A sensor module, responsible for collecting environmental data in real time, such as air quality (PM2.5, concentration of toxic gases), noise level, temperature, humidity, light intensity, etc.; obtaining environmental information through various sensors (such as air quality sensors, noise sensors, temperature and humidity sensors, light sensors, etc.) and transmitting the data to the control center;

[0128] A control and processing module, responsible for receiving the data transmitted by the sensor module, performing real-time analysis and processing. Automatically adjust the brightness of the street lamp according to preset fuzzy rules and algorithms. For example, when it is detected that the PM2.5 concentration reaches the preset threshold, the control module will issue an instruction to turn on the street lamp and transmit the relevant data to the environmental monitoring center. In addition, this module is also responsible for monitoring parameters such as the current, voltage, and brightness of the street lamp to ensure the normal operation of the street lamp;

[0129] The communication and data transmission module is responsible for transmitting the collected environmental data and street lamp 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 data. At the same time, it is also responsible for receiving instructions from the environmental monitoring center, such as adjusting the brightness of street lamps, starting emergency lighting, etc.

[0130] In the above embodiments, this embodiment has the environmental monitoring function, can monitor environmental indicators such as air quality and noise level in real time, can read the current, voltage, brightness, temperature, humidity, PM2.5, toxic gases, light intensity and video images of the street lamp, and can realize the timely adjustment of the street lamp brightness; after receiving the automatic adjustment instruction through the street lamp node, the control program automatically adjusts the street lamp brightness 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 will be turned on and the data will be transmitted to the environmental monitoring center. By integrating multiple sensors, the smart street lamp can monitor environmental parameters such as air quality (such as PM2.5, PM10), temperature, humidity, and noise in real time, providing accurate data support for urban managers. Based on the fuzzy control theory, the smart street lamp can automatically adjust the brightness according to the collected PM2.5 concentration and light conditions. When the air pollution is serious, the street lamp will increase the brightness to improve visibility, thereby reducing light pollution. The street lamp supports multiple communication interfaces, such as Wi-Fi, LoRa, 4G / 5G, etc., to realize the real-time transmission and remote monitoring of environmental data. The urban management platform can receive and analyze the transmitted data in real time, respond and adjust management strategies in a timely manner, and improve the urban emergency response ability and management efficiency. The street lamp is equipped with a high-definition camera, which can monitor the situation of the road and surrounding areas in real time, providing strong support for public security prevention and control and traffic management. It not only has the basic lighting function, but also integrates multiple functions such as environmental monitoring, intelligent dimming, and video monitoring, simplifies the equipment deployment and management, and improves the monitoring efficiency.

[0131] Embodiment 10:

[0132] As Figure 10 shown, on the basis of Embodiments 1-9, a control method for an adaptive dimming LED street lamp for a low-carbon and environmentally friendly smart city provided by an embodiment of the present invention includes the following steps:

[0133] Step S100: Collect road-related information such as ambient light intensity, pedestrian flow, and vehicle flow in real time, preprocess the road-related information, and transmit the preprocessed road-related information to the lighting control module;

[0134] Step S200 is used to process and analyze road-related information. Taking the environmental light intensity, pedestrian flow, and vehicle flow as input variables and the brightness of the LED street lamp as the output variable, it adjusts the brightness of the LED street lamp according to the output variable, and uploads the status and data of the street lamp to the central management system;

[0135] Step S300 is used to enable communication between the central management system and the smart city security system. The smart city security system detects the status of the street lamp in real time. If an abnormal street lamp is detected, it notifies the relevant department for maintenance; if an abnormal road is detected by the smart city security system, it adjusts the LED street lamp.

[0136] In the above embodiment, in step S100 of this embodiment, road-related information such as environmental light intensity, pedestrian flow, and vehicle flow is collected in real time and preprocessed to ensure the accuracy and availability of the data. The environmental data such as light intensity, pedestrian flow, and vehicle flow are monitored in real time through the sensor module. In step S200, the road-related information is processed and analyzed, and the brightness of the LED street lamp is adjusted according to the input variables (environmental light intensity, pedestrian flow, vehicle flow), and the status and data of the street lamp are uploaded to the central management system. 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 the energy-saving effect. 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 the 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 an abnormal street lamp is detected, it notifies the relevant department for maintenance; at the same time, when the smart city security system detects an abnormal road, it adjusts the LED street lamp. Through the Internet of Things technology, the remote monitoring and fault diagnosis of the street lamp status are realized to ensure the normal operation of the street lamp. In addition, the system also has an intelligent alarm function, which can notify the relevant department for maintenance in time when the street lamp fails, improving the maintenance efficiency. The smart city security system can also adjust the brightness of the LED street lamp according to the abnormal road conditions to ensure night driving safety.

[0137] Embodiment 11:

[0138] Based on Embodiments 1 - 9, an adaptive dimming LED street lamp control device for a low-carbon and environmentally friendly smart city provided by an embodiment of the present invention includes: The electronic device includes 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;

[0139] The 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. The ARM embedded processor performs fuzzy processing on the data, controls the brightness of the LED street lamp according to the fuzzy processing, and performs real-time monitoring based on the collected data. The monitoring data greater than the preset value is transmitted to the corresponding system to issue a lighting warning.

[0140] Figure 11 A block diagram of an exemplary electronic device suitable for use in implementing embodiments of the present invention is shown.

[0141] The electronic device may include a central processing unit / microprocessor / master control chip, etc. 4; a storage medium 5, coupled to the central processing unit / microprocessor / master control chip, etc. 4, and storing computer-executable instructions therein for performing the steps of the various methods of the embodiments of the present invention when executed by the processor.

[0142] The central processing unit / microprocessor / master control chip, etc. 4 may include, but are not limited to, for example, one or more processors or microprocessors, etc.

[0143] The storage medium 5 may include, but are 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 disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0144] In addition, the electronic device may further include (but is not limited to) a data bus 6, an input / output bus / external bus / device bus, etc. 7, a display 8, and input / output devices 9 (such as a keyboard, mouse, speaker, etc.).

[0145] The central processing unit / microprocessor / master control chip, etc. 4 may communicate with external devices (8, 9, etc.) via the I / O bus 7 through a wired or wireless network (not shown).

[0146] The storage medium 5 may also store at least one computer-executable instruction for performing the steps of the various functions and / or methods in the embodiments described in the present technology when run by the central processing unit / microprocessor / master control chip, etc. 4.

[0147] In one embodiment, the at least one computer-executable instruction may also be compiled into or form a software product, where one or more computer-executable instructions perform the steps of the various functions and / or methods in the embodiments described in the present technology when run by the processor.

[0148] Figure 12A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0149] As Figure 12 shown, instructions are stored on the non-transitory computer-readable storage medium 11, and the instructions are, for example, computer-readable instructions 10. When the computer-readable instructions 10 are run by a processor, the various methods described above can be executed. The non-transitory computer-readable storage medium includes but is 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, etc. The 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 may be connected to a computing device such as a computer. Then, when the computing device runs the computer-readable instructions 10 stored on the non-transitory computer-readable storage medium 11, the various methods described above can be performed.

[0150] In several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed couplings or direct couplings or communication connections between each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical or other forms.

[0151] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0152] In addition, the functional units in various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0153] When an 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 such an 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 and includes several instructions for executing all or part of the steps of the methods of the various embodiments of the present invention through a computer device (which may be a personal computer, a server, or a network device, etc.). The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (English full name: Read-Only Memory, English abbreviation: ROM), random access memories (English full name: Random Access Memory, English abbreviation: RAM), magnetic disks, or optical discs that can store program codes.

[0154] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various 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 the 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. 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 environmental status data set includes the street lamp density of the street lamp environment, the data density of the street lamp environment, and the absolute value of the difference between the tree height of the street lamp environment data and the reference tree height; the data analysis submodule is used to compare the LED lamp environment status data set to obtain the LED street lamp benchmark brightness; conduct a comprehensive analysis of the pedestrian status data set to obtain the pedestrian status characteristic value; calculate the traffic flow status data set to obtain the traffic flow status characteristic value; 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, small cars, medium-sized cars, and large cars. Each type of vehicle has a different impact on traffic conditions. 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; , , , , , are the weight coefficients of each factor; The data output submodule 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; 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; 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; 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 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; 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 precision unit is used to infer the fuzzy value according to the nonlinear fuzzy algorithm, and obtain the final precision 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 representing 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; the nonlinear function and weight coefficients can be optimized and adjusted according to actual needs to improve the accuracy and practicality of the fuzzification algorithm; The adaptive dimming LED street lights for low-carbon and environmentally friendly smart cities also include: The sensor module is responsible for collecting environmental data in real time, including air quality of PM2.5, toxic gas concentration, noise level, temperature, humidity, and light intensity; it obtains environmental information through various sensors such as air quality sensors, noise sensors, temperature and humidity sensors, and light sensors, and transmits the data to the control center; The control and processing module is responsible for receiving the data transmitted by the sensor module, performing real-time analysis and processing, and automatically adjusting the brightness of the street lamps according to the preset fuzzy rules and algorithms. 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, it is also responsible for monitoring the current, voltage, and brightness parameters of the street lamps. The communication and data transmission module is responsible for transmitting the collected environmental data and street lamp status information to the environmental monitoring center. It uses wireless communication technology 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 to adjust the brightness of street lamps and start emergency lighting.

2. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities according to claim 1, 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.

3. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities according to claim 1, 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.

4. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities according to 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.

5. The adaptive dimming LED street lamp for low-carbon and environmentally friendly smart cities as claimed in claim 4, characterized in that: The road abnormalities detected by the light warning submodule include illegal parking, speeding and traffic accidents.

6. 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 5, 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, the relevant department will be notified for repair. If the smart city security system detects an abnormality on the road, it will adjust the LED street lights. 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 reference lighting brightness, pedestrian status characteristic value and traffic flow status value to the lighting control module; 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; 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; 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 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; 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 precision unit is used to infer the fuzzy value according to the nonlinear fuzzy algorithm, and obtain the final precision output after defuzzifying the value; and convert the fuzzy control quantity into a clear value; The adaptive dimming LED street lights for low-carbon and environmentally friendly smart cities also include: The sensor module is responsible for collecting environmental data in real time, including air quality of PM2.5, toxic gas concentration, noise level, temperature, humidity, and light intensity; it obtains environmental information through various sensors such as air quality sensors, noise sensors, temperature and humidity sensors, and light sensors, and transmits the data to the control center; The control and processing module is responsible for receiving the data transmitted by the sensor module, performing real-time analysis and processing, and automatically adjusting the brightness of the street lamps according to the preset fuzzy rules and algorithms. 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, it is also responsible for monitoring the current, voltage, and brightness parameters of the street lamps. The communication and data transmission module is responsible for transmitting the collected environmental data and street lamp status information to the environmental monitoring center. It uses wireless communication technology 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 to adjust the brightness of street lamps and start emergency lighting. 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 reference brightness of the LED street lamp; conduct a comprehensive analysis on the monitored pedestrian status data set to obtain the pedestrian status characteristic value; calculate the traffic flow status data set to obtain the traffic flow status characteristic value; 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 coefficient of different types of vehicles. Each type of vehicle, such as small cars, medium-sized cars, and large cars, has a different impact on traffic conditions. 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; , , , , , are the weight coefficients of each factor; 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, The nonlinear function that represents the fuzzy control rule takes into account multiple factors such as input variables, timestamps, eigenvalues, fuzzy single point sets, basic elements and fuzzy control rules. The final fuzzy value is obtained by calculation through nonlinear functions and weight coefficients. The nonlinear function and weight coefficients are optimized and adjusted according to actual needs to improve the accuracy and practicality of the fuzzification algorithm.

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