A method and system for realizing uniform dimming of high-power LED area lighting

Abstract

A method and system for realizing uniform dimming of lighting in a high-power LED area, and relates to the field of data processing technology. The method includes: obtaining crowd distribution data of a target area and illumination data of multiple segmented lighting areas in the target area; determining the distribution position and coverage range of dense crowds in the target area based on the crowd distribution data; calculating the distance value between each segmented lighting area and the distribution position of dense crowds, and determining the lighting demand level corresponding to each distance value; determining the illumination compensation value of each segmented lighting area in combination with the illumination demand level and illumination data of each segmented lighting area, and determining the light output angle of each segmented lighting area in combination with the distribution position and coverage range of dense crowds; adjusting the LED light group of each segmented lighting area according to the illumination compensation value and light output angle of each segmented lighting area to illuminate the target area. The implementation of the technical solution provided by the present application achieves the effect of improving the efficiency of uniform dimming of regional lighting.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, system, electronic device and storage medium for achieving uniform dimming of illumination in a high-power LED area. Background Art

[0002] With the advancement of technology, high-power LED lighting has been widely used in lighting systems in public places around the world due to its high efficiency and long life. These public places include commercial centers, transportation hubs and public activity areas, which serve a large number of mobile people every day. Although LED lighting technology has significant advantages over traditional lighting equipment in terms of energy consumption and maintenance, how to further improve the intelligence level and energy efficiency of these lighting systems is still a key issue that needs to be solved in the development of urban infrastructure.

[0003] At present, the existing methods for achieving uniform dimming of high-power LED regional lighting usually use a preset fixed lighting mode to automatically dim the LED light groups in public places to meet the lighting needs of different time periods. However, in actual applications, due to the large fluctuations in the flow of people in public places, it is often difficult to dynamically adjust the LED light groups using only a fixed lighting mode to adapt to the changes in the flow of people. Some areas are insufficiently lit when there are many people, and excessively lit when there are few people, which causes energy waste, thereby reducing the efficiency of uniform dimming of regional lighting. Summary of the invention

[0004] The present application provides a method and system for achieving uniform dimming of regional lighting of high-power LEDs, which has the effect of improving the efficiency of uniform dimming of regional lighting.

[0005] In a first aspect, the present application provides a method for achieving uniform dimming of lighting in a high-power LED area, comprising:

[0006] Acquire crowd flow distribution data of a target area and illumination data of a plurality of segmented lighting areas within the target area;

[0007] Based on the crowd flow distribution data, determine the distribution position and coverage of dense crowd flow in the target area;

[0008] Calculating the distance value between each of the segmented lighting areas and the distribution position of the dense human flow, and determining the lighting demand level corresponding to each of the distance values;

[0009] Determine the illumination compensation value of each segmented illumination area in combination with the illumination demand level and illumination data of each segmented illumination area, and determine the light output angle of each segmented illumination area in combination with the distribution position and coverage range of the dense flow of people;

[0010] The LED light groups of each segmented lighting area are adjusted according to the illumination compensation value and the light output angle of each segmented lighting area to illuminate the target area.

[0011] In a second aspect of the present application, a system for achieving uniform dimming of illumination in a high-power LED area is provided, the system comprising:

[0012] A data acquisition module, used to acquire crowd distribution data of a target area and illumination data of a plurality of segmented lighting areas in the target area;

[0013] A level classification module is used to determine the distribution position and coverage of the dense crowd flow in the target area based on the crowd flow distribution data; calculate the distance value between each of the segmented lighting areas and the distribution position of the dense crowd flow, and determine the lighting demand level corresponding to each of the distance values;

[0014] A lighting parameter determination module, used to determine the illumination compensation value of each segmented lighting area in combination with the lighting demand level and illumination data of each segmented lighting area, and determine the light output angle of each segmented lighting area in combination with the distribution position and coverage range of the dense flow of people;

[0015] The lighting dimming module is used to adjust the LED light groups of each segmented lighting area according to the illumination compensation value and the light output angle of each segmented lighting area to illuminate the target area.

[0016] In a third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and a program stored in the memory and executable on the processor, wherein the program can implement a method for achieving uniform dimming of lighting in a high-power LED area when loaded and executed by the processor.

[0017] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements a method for achieving uniform dimming of lighting in a high-power LED area.

[0018] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0019] By adopting the above technical solution, the crowd distribution and illumination data of the target area are obtained in real time. The system accurately identifies the location and coverage of dense crowds based on the crowd distribution data, and establishes a dynamic grading mechanism for lighting needs by calculating the distance value between the segmented lighting area and the dense crowd location, which effectively solves the problem of inability to make targeted adjustments under fixed lighting mode. By combining the lighting demand level with real-time illumination data, the system can accurately calculate the illumination compensation value required for each segmented lighting area, and determine the optimal light output angle based on the spatial distribution characteristics of dense crowds, avoiding the problems of insufficient lighting and excessive lighting. The system can accurately adjust the LED light group in real time based on the calculated illumination compensation value and light output angle, so that the lighting effect always matches the actual crowd distribution, thereby improving the efficiency of uniform dimming of regional lighting. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of a method for realizing uniform dimming of high-power LED area provided in an embodiment of the present application;

[0021] Figure 2 This is a structural schematic diagram of a system for realizing uniform dimming of high-power LED area lighting provided by an embodiment of the present application;

[0022] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0023] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0024] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0025] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0026] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0027] The present application embodiment provides a method for achieving uniform dimming of high-power LED area lighting. In one embodiment, please refer to Figure 1 , Figure 1 The present invention provides a flowchart of a method for realizing uniform dimming of high-power LED areas provided by an embodiment of the present invention. The method can be realized by a computer program, which can be integrated into an application or run as an independent tool application. The method can also be realized by a single-chip microcomputer or run in a system for realizing uniform dimming of high-power LED areas based on a von Neumann system. Specifically, the method can include the following steps:

[0028] Step 101: Obtain crowd flow distribution data of a target area and illumination data of multiple segmented lighting areas in the target area.

[0029] Among them, crowd distribution data refers to numerical information that reflects the activity patterns and distribution characteristics of people in the target area. Specifically, it can be understood as a collection of data such as population density, population flow, and population movement trends at different locations in the target area at a specific time point.

[0030] The segmented lighting area refers to a number of relatively independent lighting sub-areas that divide the entire target area according to the lighting control requirements. Each sub-area is equipped with an independent LED light group and its control unit, which can achieve regionalized precise lighting adjustment. In the embodiment of the present application, the segmented lighting area can be understood as a lighting control unit divided according to the spatial layout, functional requirements and lighting coverage of the target area. Each segmented lighting area has independent illumination detection and lighting adjustment capabilities.

[0031] Illuminance data refers to numerical information reflecting the light intensity level in each segmented lighting area, which represents the amount of light flux received per unit area in a specific area. In the embodiment of the present application, illuminance data can be understood as the light intensity measurement value collected in real time by the illuminance sensor installed in each segmented lighting area, which reflects the actual lighting effect provided by the current LED light group.

[0032] Specifically, multiple crowd detection devices, such as infrared sensors, cameras, etc., are set up in the target area, and crowd information in the area is collected in real time through these detection devices; at the same time, illuminance sensors are installed in each segmented lighting area to collect real-time illuminance data of each area. The data collected by the crowd detection device is processed to form a crowd density distribution map, reflecting the size of the crowd flow in each area; the data collected by the illuminance sensor directly reflects the lighting intensity of each segmented lighting area. The system transmits this data to the control center in real time through the communication network to provide data support for subsequent intelligent lighting adjustment. This method based on multi-source data collection enables the system to fully grasp the real-time lighting needs of the target area and lay the foundation for precise lighting control.

[0033] Step 102: Based on the crowd flow distribution data, determine the distribution location and coverage of dense crowd flow in the target area.

[0034] Among them, dense human flow refers to the regional state where the degree of human gathering exceeds the preset threshold within a specific time and space range in the target area. In the embodiment of the present application, dense human flow can be understood as the phenomenon of human gathering when the human flow detected in a single grid unit after grid analysis is greater than the flow threshold set by the system. This flow threshold can be flexibly set according to the actual application scenario and lighting requirements of the target area.

[0035] In the present invention, the distribution position refers to the spatial coordinate point where dense human flow appears in the target area, reflecting the specific spatial location information of the crowd gathering. In the embodiment of the present application, the distribution position can be understood as the coordinates of the geometric center point of the grid unit identified as dense human flow after grid analysis. These coordinate points can be represented by a two-dimensional or three-dimensional spatial coordinate system to accurately locate the spatial distribution characteristics of dense human flow.

[0036] The coverage range refers to the spatial range of the actual activities and diffusion of dense human flow in the target area, which represents the boundary of the area that needs key lighting. In the embodiment of the present application, the coverage range can be understood as a continuous area composed of multiple adjacent grid cells identified as dense human flow, which is merged to form a complete spatial outline.

[0037] Specifically, the target area is first divided into multiple grid units of preset grid sizes. This grid processing method can provide a more accurate spatial analysis basis. Then, based on the crowd distribution data, the actual flow of people in each grid unit is calculated, and the grid units with a flow of people greater than the preset flow threshold are identified as dense crowd areas. The system then determines the center point position of these dense crowd areas as the distribution position of dense crowds, and this distribution position will serve as an important reference point for the subsequent adjustment of the light output angle of the LED light group. For adjacent dense crowd grid units, the system will automatically merge and process to form a complete coverage range, which reflects the actual spatial range of dense crowd activities. Through this grid analysis method, the system can accurately identify dense crowd areas in the target area and provide accurate spatial location information for subsequent lighting parameter adjustment. This grid analysis-based method not only improves the recognition accuracy of crowd distribution characteristics, but also can dynamically track changes in dense crowd areas, so that lighting control can better adapt to real-time changes in crowd distribution, thereby achieving accurate matching of lighting effects with actual needs.

[0038] Based on the above embodiment, as an optional embodiment, in step 102: determining the distribution position and coverage of dense human flow in the target area based on human flow distribution data, this step may also include the following steps:

[0039] Step 201: Divide the target area into a plurality of grid units of a preset grid size; and determine the flow of people in each grid unit based on the crowd flow distribution data.

[0040] Among them, the grid unit refers to the smallest spatial analysis unit formed by dividing the target area according to a preset unified standard, and each grid unit has the same geometric shape and area size. In the embodiment of the present application, the grid unit can be understood as a regular square area whose side length is the preset grid size, such as a spatial range of 5 meters × 5 meters.

[0041] Human flow refers to the number of people passing through or staying in a grid unit within a specific period of time, reflecting the density of human activities in the spatial area.

[0042] Specifically, in order to more accurately identify and analyze the distribution characteristics of the flow of people in the target area, it is necessary to first perform standardized division and quantitative analysis of the space. The grid processing method is used to divide the target area into several grid units of equal size. The size of these grid units is pre-set, and its size needs to comprehensively consider factors such as the actual spatial size of the target area, the detection accuracy of the flow of people detection device, and the requirements of lighting control. For example, in places such as large commercial centers, the grid unit can be set to a square area of ​​5 meters × 5 meters. This grid size can not only ensure sufficient spatial analysis accuracy, but also facilitate the system to perform data processing and control calculations. After completing the grid division, the system will calculate the actual flow of people in each grid unit based on the real-time collected flow distribution data. During the specific calculation, the system maps the data collected by the flow of people detection device to the corresponding grid unit, and determines the flow of people by counting the number of people passing through the grid unit or staying in the grid unit within a specific time window. This grid analysis method enables the system to perform accurate flow analysis of the entire target area with a unified standard, providing a data basis for the subsequent identification of dense flow areas.

[0043] Step 202: Determine the grid cells whose pedestrian flow is greater than the flow threshold as dense pedestrian flow, and use the center point position of the dense pedestrian flow as the distribution position of the dense pedestrian flow.

[0044] Specifically, a flow threshold is first set. The setting of this threshold needs to consider factors such as the actual application scenario, spatial characteristics and lighting requirements of the target area. For example, in a commercial area with dense traffic, a higher flow threshold may need to be set, while a lower threshold standard can be used in a general public area. The system compares the actual flow of people counted in each grid unit with the preset flow threshold. When the flow of people in a grid unit exceeds the flow threshold, the system identifies the grid unit as a dense traffic area. For grid units identified as dense traffic, the system calculates the spatial coordinates of their geometric center points and uses the center point position as the distribution position of the dense traffic. When multiple adjacent dense traffic grid units appear, the system calculates the centroid positions of these adjacent grid units and uses them as the representative distribution position of the entire dense traffic area. This method based on threshold judgment and center point positioning enables the system to accurately grasp the spatial distribution characteristics of dense traffic areas and provide accurate spatial reference points for subsequent adjustment of the light output angle of the LED light group. At the same time, this method also facilitates the system to dynamically track and update. When the distribution of pedestrian flow changes, the system can adjust the coordinates of the distribution position in time to ensure that the lighting control can respond to changes in pedestrian flow in real time and provide the most suitable lighting effect.

[0045] Step 203: merging the grid cells adjacent to the dense crowd flow to obtain the coverage of the dense crowd flow.

[0046] Specifically, the spatial relationship between all grid cells identified as dense crowds is first detected, and adjacent grid cells with common boundaries are identified. When two or more dense crowd grid cells are found to be adjacent, the system automatically triggers a merge operation to combine these adjacent grid cells into a continuous area. During the merging process, the system will consider the continuity of the crowd between the grid cells to ensure that the merged area can fully reflect the actual range of crowd activities. At the same time, the system will also smooth the boundaries of the merged area, eliminate the irregular edges caused by grid division, and form a continuous coverage range that is more in line with the actual crowd distribution characteristics. This merging processing method can not only more accurately reflect the actual spatial distribution of dense crowds, but also provide a more reasonable spatial reference for lighting control. By identifying the complete coverage range, the system can better plan the lighting area to ensure that the lighting range of the LED light group can fully cover the dense crowd area and avoid lighting dead spots or over-lighting. This merging method based on spatial continuity improves the system's recognition accuracy of crowd distribution characteristics and makes lighting control more accurate and efficient.

[0047] Step 103: Calculate the distance between each segmented lighting area and the distribution position of the dense human flow, and determine the lighting demand level corresponding to each distance value.

[0048] Among them, the lighting demand level refers to the classification of the priority and importance of lighting adjustment needs based on the distance value between the segmented lighting area and the location of dense human flow distribution. The closer the distance, the higher the lighting demand level.

[0049] Specifically, after determining the distribution position of dense crowd flow, it is necessary to evaluate the lighting contribution of each segmented lighting area to the dense crowd flow area, which requires quantitative analysis through distance value calculation. The system first obtains the center coordinates of each segmented lighting area and the distribution position coordinates of dense crowd flow, and uses the spatial distance calculation formula to calculate the Euclidean distance between the two points to obtain the distance value between each segmented lighting area and the dense crowd flow distribution position. In the case of multiple dense crowd flow distribution positions, the system will calculate the distance value between the segmented lighting area and each distribution position respectively. Based on the calculated distance value, the system will divide the lighting demand into different levels according to the preset distance threshold, for example, it can be divided into three levels: emergency lighting demand, key lighting demand and general lighting demand. When the distance value is less than the first threshold, it is determined to be an emergency lighting demand; when the distance value is greater than the first threshold and less than the second threshold, it is determined to be a key lighting demand; when the distance value is greater than the second threshold, it is determined to be a general lighting demand. This method of lighting demand level division based on distance value enables the system to determine the priority and adjustment range of lighting adjustment according to the spatial relationship between the segmented lighting area and the dense crowd flow. The smaller the distance value of the segmented lighting area, the higher the lighting demand level, and it will receive a greater adjustment weight in the subsequent lighting parameter adjustment. This hierarchical control strategy not only ensures that densely populated areas can obtain more sufficient lighting support, but also realizes the reasonable allocation of lighting resources, avoids excessive lighting of segmented lighting areas far away from densely populated areas, and thus improves the energy efficiency of the entire lighting system.

[0050] Based on the above embodiment, as an optional embodiment, in step 103: calculating the distance value between each segmented lighting area and the distribution position of the dense human flow, this step may also include the following steps:

[0051] Step 301: Obtain the installation position of the LED light group in each segmented lighting area; based on each installation position and the distribution position of dense human flow, calculate the distance value between each segmented lighting area and the distribution position of dense human flow.

[0052] Specifically, in order to accurately evaluate the lighting contribution of each segmented lighting area to the dense pedestrian flow area, the system needs to first obtain the specific spatial position information of the lighting equipment. The system reads the installation position coordinates of the LED light group in each segmented lighting area. These coordinate information include the specific installation point position of the LED light group in three-dimensional space, which can be expressed by (x, y, z) coordinates. For each segmented lighting area, the system uses the installation position of its LED light group as a spatial reference point. After obtaining the installation position, the system calculates the spatial distance between these coordinate points and the previously determined dense pedestrian flow distribution position. When calculating specifically, the system uses the Euclidean distance calculation formula in three-dimensional space, that is, the actual spatial distance between the LED light group and the dense pedestrian flow is determined by calculating the straight-line distance between two points. When there are multiple dense pedestrian flow distribution positions, the system will calculate the distance value between the installation position of each LED light group and each dense pedestrian flow distribution position respectively, and record these distance data. This distance calculation method based on the actual installation position enables the system to more accurately evaluate the lighting impact of each segmented lighting area on the dense pedestrian flow area, and provides a reliable quantitative basis for the subsequent lighting demand level determination.

[0053] Based on the above embodiment, as an optional embodiment, in step 103: determining the lighting requirement level corresponding to each distance value, this step may also include the following steps:

[0054] Step 302: Obtain a lighting requirement level mapping table, where the lighting requirement level mapping table includes distance value intervals corresponding to a plurality of different lighting requirement levels.

[0055] Specifically, in order to achieve scientific grading of lighting needs, the system needs to establish a standardized basis for judgment. In the specific implementation process, the system will call the pre-configured lighting demand level mapping table, which defines the correspondence between different lighting demand levels and distance value intervals. The design of the mapping table comprehensively considers the lighting range of the LED light group, the law of light intensity attenuation, and the demand characteristics of the actual application scenario. For example, when the distance value is less than 5 meters, it corresponds to the emergency lighting demand level, indicating that the area requires the highest level of lighting support; when the distance value is between 5 meters and 10 meters, it corresponds to the key lighting demand level, indicating that the area requires strong lighting support; when the distance value is greater than 10 meters, it corresponds to the general lighting demand level, indicating that the area can use standard lighting parameters. The system will read this mapping table in real time during operation, match the calculated distance value with the distance value interval defined in the table, and determine the corresponding lighting demand level. This grading method based on the mapping table provides a unified evaluation standard for the system, making the determination of lighting needs more standardized and controllable. At the same time, the parameters of the mapping table can be flexibly adjusted according to actual application requirements. This configurability enables the system to better adapt to the lighting requirements of different scenarios.

[0056] Step 303: Determine the lighting requirement level corresponding to each distance value based on the distance value interval in which each distance value is located.

[0057] Specifically, after obtaining the lighting demand level mapping table, the system needs to accurately determine the actual lighting demand of each segmented lighting area. The system will match and analyze the distance value between each segmented lighting area and the dense flow distribution location calculated previously with the distance value interval defined in the mapping table. The system determines the corresponding lighting demand level by determining in which distance value interval each distance value falls. For example, when the distance value between a segmented lighting area and the dense flow distribution location is 3 meters, since the distance value falls within the interval of less than 5 meters, the system will determine the lighting demand of the segmented lighting area as an emergency lighting demand level; when the distance value is 7 meters, since it falls within the interval of 5 meters to 10 meters, it will be determined as a key lighting demand level; when the distance value is 12 meters, since it is greater than 10 meters, it will be determined as a general lighting demand level. This determination method based on interval matching enables the system to accurately identify the actual lighting demand level of each segmented lighting area and provide clear priority guidance for subsequent lighting parameter adjustments. At the same time, the system will update the judgment results to the control database in real time. When the distribution of people flow changes, the system can timely adjust the lighting demand level of each segmented lighting area to ensure that the lighting control can always accurately respond to changes in actual demand. This dynamic and accurate demand level judgment mechanism improves the response speed and control accuracy of the entire lighting system, so that the lighting effect can better meet the actual lighting needs of different areas.

[0058] Step 104: Determine the illumination compensation value of each segmented lighting area in combination with the illumination demand level and illumination data of each segmented lighting area, and determine the light output angle of each segmented lighting area in combination with the distribution position and coverage range of the dense crowd flow.

[0059] The illumination compensation value refers to the illumination value that needs to be supplemented or reduced, which is calculated by the system according to the lighting demand level and the actual illumination state, and is used to adjust the current lighting environment to the optimal lighting state. In the embodiment of the present application, the illumination compensation value can be understood as the system comparing the difference between the actual illumination value of the segmented lighting area and the standard illumination value corresponding to its lighting demand level, thereby determining the specific illumination value that needs to be adjusted.

[0060] The light output angle refers to the angle between the center line of the light beam emitted by the LED light group and its installation plane. This angle determines the lighting coverage and lighting direction of the LED light group. In the embodiment of the present application, the light output angle can be understood as the optimal light projection angle obtained by the system through spatial geometry calculation based on the distribution position and coverage of dense traffic.

[0061] Specifically, the reference value of illumination compensation is first set based on the lighting demand level. For example, the reference compensation value corresponding to the emergency lighting demand level is 300 lux, the key lighting demand level corresponds to 200 lux, and the general lighting demand level corresponds to 100 lux. Then, the system reads the real-time illumination data of each segmented lighting area, compares the current illumination value with the standard illumination value corresponding to the lighting demand level, and calculates the specific illumination value that needs to be compensated. While determining the illumination compensation value, the system also needs to adjust the light output angle of the LED light group to ensure that the light can accurately cover the dense crowd area. The system will calculate the angle from the LED light group to each boundary point of the coverage range according to the distribution position coordinates of the dense crowd and the coverage range boundary, and calculate the optimal light output angle through trigonometric functions. For example, when the coverage range of the dense crowd is large, the system will appropriately increase the light output angle to ensure complete coverage of the lighting range; when the coverage range is small but the crowd density is high, the light output angle will be narrowed to provide more concentrated lighting. This dynamic adjustment method based on multi-dimensional parameters enables the system to optimize the intensity and direction of the lighting at the same time, ensuring that each segmented lighting area can provide the most suitable lighting effect. Through the coordinated adjustment of illumination compensation value and light output angle, the system can not only ensure that areas with dense traffic have sufficient lighting support, but also avoid the waste of lighting resources, achieving the optimal balance between lighting effect and energy efficiency.

[0062] Based on the above embodiment, as an optional embodiment, in step 104: combining the lighting requirement level and the illumination data of each segmented lighting area to determine the illumination compensation value of each segmented lighting area, this step may also include the following steps:

[0063] Step 401: based on each illumination data, determine the current illumination value of each segmented illumination area; calculate the difference between the current illumination value of each segmented illumination area and the reference illumination value to obtain a reference compensation value.

[0064] Specifically, in order to achieve precise adjustment of the lighting environment, the system needs to first grasp the actual lighting status of each segmented lighting area. The system collects real-time illumination data of each segmented lighting area through an illumination sensor, which reflects the actual light intensity of the current environment. The system will process and analyze the collected illumination data to determine the current illumination value of each segmented lighting area. At the same time, the system will set the corresponding benchmark illumination value according to the lighting demand level. For example, the benchmark illumination value corresponding to the emergency lighting demand level is 300 lux, the key lighting demand level corresponds to 200 lux, and the general lighting demand level corresponds to 100 lux. After obtaining these two sets of data, the system calculates the difference between the current illumination value of each segmented lighting area and its corresponding benchmark illumination value to obtain the benchmark value that needs to be compensated. For example, if the current illumination value of a segmented lighting area is 150 lux, and its lighting demand level is emergency lighting demand, and the corresponding benchmark illumination value is 300 lux, then the calculated benchmark compensation value is 150 lux. This calculation method based on actual measurement and standard comparison enables the system to accurately grasp the lighting adjustment requirements of each segmented lighting area and provide a quantitative basis for subsequent lighting parameter optimization. By calculating the benchmark compensation value, the system can accurately determine the specific illuminance value that needs to be increased or decreased in each segmented lighting area, thereby achieving precise adjustment of the lighting environment.

[0065] Step 402: Determine the illumination adjustment coefficient corresponding to each lighting demand level according to a preset coefficient mapping table.

[0066] Among them, in the present invention, the preset coefficient mapping table refers to a pre-configured comparison table, which is used to define the mapping relationship between different lighting demand levels and their corresponding illumination adjustment coefficients.

[0067] The illumination adjustment coefficient refers to an adjustment ratio parameter determined according to the lighting demand level, which is used to weight the reference compensation value. In the embodiment of the present application, the illumination adjustment coefficient can be understood as a weight factor reflecting the importance of the lighting demand, and differentiated illumination adjustment is achieved by multiplying it with the reference compensation value.

[0068] Specifically, in order to achieve differentiated control of lighting adjustment, the system needs to set corresponding adjustment weights for different lighting demand levels. The system will call the pre-configured coefficient mapping table, which defines the correspondence between different lighting demand levels and illumination adjustment coefficients. The design of the mapping table fully considers the importance and adjustment sensitivity requirements of different levels of lighting demand. For example, the adjustment coefficient corresponding to the emergency lighting demand level is 1.5, indicating that a large adjustment force is required; the adjustment coefficient corresponding to the key lighting demand level is 1.2, indicating that a medium degree of adjustment is required; the adjustment coefficient corresponding to the general lighting demand level is 1.0, indicating that a standard adjustment range is adopted. When the system is running, it will read the corresponding illumination adjustment coefficient from the mapping table according to the lighting demand level of each segmented lighting area. This level-based coefficient allocation method enables the system to implement differentiated control of lighting demands of different importance, ensuring that important areas can obtain faster and more significant lighting adjustment responses. Through the introduction of illumination adjustment coefficients, the system realizes refined management of lighting adjustment, which not only improves the accuracy of adjustment, but also enhances the system's adaptability to different scene requirements, making lighting control more intelligent and efficient. At the same time, the parameters of the coefficient mapping table can be dynamically adjusted according to actual application requirements. This flexible configuration mechanism enables the system to better adapt to the lighting control requirements of different environments.

[0069] Step 403: multiplying the reference compensation value of each segmented lighting area by the corresponding illumination adjustment coefficient to obtain the illumination compensation value of each segmented lighting area.

[0070] Specifically, in order to achieve differentiated and precise adjustment of lighting needs, the system needs to perform comprehensive calculations on the benchmark compensation value and the illumination adjustment coefficient. The system will perform a product operation on each segmented lighting area, multiplying the previously obtained benchmark compensation value by the illumination adjustment coefficient corresponding to its lighting demand level, so as to obtain the final illumination compensation value. For example, the benchmark compensation value of a segmented lighting area is 100 lux, its lighting demand level is emergency lighting demand, and the corresponding illumination adjustment coefficient is 1.5, then the calculated illumination compensation value is 150 lux; when the lighting demand level is key lighting demand, the illumination adjustment coefficient is 1.2, then the final illumination compensation value is 120 lux; when the lighting demand level is general lighting demand, the illumination adjustment coefficient is 1.0, then the illumination compensation value remains at 100 lux. This adjustment method based on weighted calculation enables the system to dynamically adjust the compensation intensity according to the importance of lighting needs, ensuring that important areas can obtain stronger lighting support. Through the precise calculation of illumination compensation values, the system realizes intelligent and refined lighting adjustment, which can not only accurately respond to the lighting needs of different areas, but also avoid the waste of lighting resources and improve the operating efficiency of the entire lighting system.

[0071] Based on the above embodiment, as an optional embodiment, in step 104: combining the distribution position and coverage of the dense flow of people to determine the light output angle of each segmented lighting area, this step may also include the following steps:

[0072] Step 404: Calculate the angle between the horizontal plane and the line between the installation position of the LED light group of each segmented lighting area and the distribution position of the dense human flow, and use each angle as the reference light output angle of the corresponding segmented lighting area.

[0073] Specifically, in order to achieve accurate projection of the lighting beam, the system needs to determine the optimal light-emitting direction based on the spatial relationship between the LED light group and the dense flow of people. The system first obtains the installation position coordinates of the LED light group in each segmented lighting area and the distribution position coordinates of the dense flow of people. These coordinate data contain spatial three-dimensional position information. Based on these coordinate information, the system uses spatial geometry calculation methods to calculate the line from the installation position of the LED light group to the distribution position of the dense flow of people, and solves the angle formed between the line and the horizontal plane. For example, when the installation height of the LED light group is 3 meters and the horizontal distance from the dense flow of people is 4 meters, the angle calculated by the system through the inverse tangent function is about 37 degrees. This angle will be used as the benchmark light-emitting angle of the segmented lighting area. This angle calculation method based on spatial position relationship enables the system to determine the most suitable light-emitting direction for each LED light group to ensure that the light beam can directly illuminate the target area.

[0074] Step 405: Determine an angle compensation value based on the coverage of the dense crowd flow.

[0075] Specifically, to ensure that the lighting coverage can fully meet the needs of dense crowd activities, the system needs to fine-tune the reference light angle according to the actual coverage of dense crowds. The system analyzes the coverage characteristics of dense crowds, including factors such as the shape, size and distribution density of the coverage area. When the coverage is large, the system calculates the maximum angle difference from the LED light group to the boundary of the coverage, and uses half of this angle difference as the angle compensation value to ensure that the lighting can evenly cover the entire target area. For example, when the coverage of dense crowds is large, the maximum angle difference from the LED light group to the boundary of the coverage is 30 degrees, and the system uses 15 degrees as the angle compensation value; when the coverage is small but the crowd density is high, the system sets a smaller angle compensation value, such as 5 degrees, to provide more concentrated lighting. This compensation mechanism based on coverage enables the system to dynamically adjust the divergence range of the light beam to ensure that the lighting effect matches the actual needs. Through the introduction of the angle compensation value, the system achieves precise control of lighting coverage, which not only avoids energy waste caused by excessive illumination range, but also prevents lighting dead spots caused by insufficient coverage, and improves the service quality and operation efficiency of the entire lighting system.

[0076] Based on the above embodiment, as an optional embodiment, in step 405: determining the angle compensation value based on the coverage of the dense flow of people, this step may also include the following steps:

[0077] Step 415: Obtain the reference irradiation area of ​​the LED light group and the coverage area of ​​the coverage range; and use the ratio of the reference irradiation area to the coverage area as a compensation coefficient.

[0078] The reference illumination area refers to the area that the LED light group can effectively illuminate under standard installation conditions. This area is determined by the optical characteristics, installation height and light output angle of the LED light group. In the embodiment of the present application, the reference illumination area can be understood as a standard coverage area under an ideal lighting condition. The calculation method is based on the installation height and light output angle of the LED light group, and the conical cross-sectional area is calculated by the projection geometry principle.

[0079] The coverage area refers to the actual projection area of ​​the dense crowd activity area on the ground. This area reflects the target area that needs to be focused on. In the embodiment of the present application, the coverage area can be understood as the actual area of ​​the crowd gathering area obtained by the crowd density monitoring system. Its value is determined by the boundary points of the crowd distribution range and can be an irregularly shaped area.

[0080] Specifically, to ensure that the lighting effect is accurately matched with the actual needs, the system needs to consider the relationship between the illumination capacity of the LED light group and the area of ​​the target area. The system first obtains the reference illumination area of ​​the LED light group at the standard installation height and light angle, which reflects the basic illumination coverage capacity of the LED light group. At the same time, the system also obtains the coverage area of ​​the dense flow of people, which represents the size of the target area that actually needs to be illuminated. The system calculates the ratio of the reference illumination area to the coverage area to obtain a compensation coefficient that reflects the area difference. For example, when the reference illumination area of ​​the LED light group is 100 square meters and the coverage area of ​​the dense flow of people is 150 square meters, the calculated compensation coefficient is 0.67, indicating that the lighting intensity needs to be increased to compensate for the lack of coverage area; when the reference illumination area is 100 square meters and the coverage area is 80 square meters, the compensation coefficient is 1.25, indicating that the lighting intensity can be appropriately reduced to avoid excessive lighting. This compensation mechanism based on area ratio enables the system to adjust the lighting parameters according to the actual coverage requirements to ensure that the lighting effect matches the size of the target area.

[0081] Step 425: Multiply the compensation coefficient by the maximum light output angle of the LED light group to obtain an angle compensation value.

[0082] Specifically, in order to achieve precise compensation adjustment of the light output angle, the system needs to convert the area difference into the angle adjustment amount. The system multiplies the compensation coefficient calculated previously by the maximum light output angle of the LED light group to obtain the actual required angle compensation value. For example, when the maximum light output angle of the LED light group is 60 degrees and the compensation coefficient is 0.67, the calculated angle compensation value is 40.2 degrees, indicating that the beam angle needs to be adjusted to this range to accommodate a larger coverage area; when the compensation coefficient is 1.25, the angle compensation value obtained is 75 degrees, indicating that the beam divergence angle can be appropriately increased to provide a wider lighting range. This angle calculation method based on the compensation coefficient enables the system to dynamically adjust the light output angle of the LED light group according to the area difference to ensure that the lighting range matches the actual needs.

[0083] Step 406: superimpose the reference light emitting angle of each segmented lighting area and the angle compensation value to obtain the light emitting angle of each segmented lighting area.

[0084] Specifically, in order to achieve the precise setting of the final lighting angle, the system needs to comprehensively calculate the reference light output angle and the angle compensation value. In the specific implementation process, the system performs an angle superposition operation on each segmented lighting area, and adds the previously calculated reference light output angle to the angle compensation value to obtain the final light output angle. For example, the reference light output angle of a segmented lighting area is 37 degrees. When the coverage area of ​​dense traffic is large, the angle compensation value is 15 degrees, and the final calculated light output angle is 52 degrees; when the coverage area is small but the traffic density is high, the angle compensation value may be 5 degrees, and the final light output angle is 42 degrees. This angle adjustment method based on superposition calculation enables the system to accurately control the light output direction of the LED light group according to actual lighting needs, ensuring that the illumination range can fully cover the target area without excessive divergence. Through the precise calculation of the light output angle, the system realizes dynamic optimization of the lighting direction.

[0085] Step 105: adjusting the LED light groups of each segmented lighting area according to the illumination compensation value and the light output angle of each segmented lighting area to illuminate the target area.

[0086] Specifically, in order to achieve precise optimization of lighting effects, the system needs to use two key parameters, namely, illumination compensation value and light output angle, to adjust the LED light group. The system first receives the illumination compensation value and light output angle data of each segmented lighting area, and then sends adjustment instructions to the LED light group through the intelligent control module. For the adjustment of illumination compensation value, the system adjusts the input current or PWM signal duty cycle of the LED light group to achieve precise control of lighting intensity; for the adjustment of light output angle, the system changes the light emission direction by controlling the adjustable bracket or optical component of the LED light group. For example, when the illumination compensation value of a segmented lighting area is 150 lux and the light output angle is 52 degrees, the system will adjust the output power of the LED light group in the area to the corresponding level, and precisely adjust the angle of the light group to the specified position of 52 degrees. This comprehensive adjustment method based on dual parameters enables the system to optimize the lighting intensity and illumination direction at the same time, ensuring that each segmented lighting area can obtain the most suitable lighting effect. Through the coordinated adjustment of illumination and angle, the system achieves precise control of lighting, which not only meets the differentiated lighting needs of different areas, but also realizes the efficient use of lighting resources. At the same time, this intelligent adjustment mechanism also provides the system with real-time response capabilities, allowing the lighting effect to be dynamically optimized as the environment changes, thereby improving the operating efficiency of the entire lighting system.

[0087] It should be noted that in order to avoid obvious illumination faults between adjacent lighting areas, the system needs to optimize and adjust the lighting transition. The system first detects the target illumination values ​​of adjacent segmented lighting areas in real time through the illumination sensor. When the illumination difference between two adjacent areas is detected to exceed the preset threshold (such as 100 lux), the system will start the illumination smoothing adjustment mechanism. For example, when the target illumination of area A is detected to be 500 lux, and the target illumination of the adjacent area B is 300 lux, the system determines that the illumination difference is 200 lux, which exceeds the preset threshold. At this time, the system will gradually process the illumination of the two areas, set a transition zone at the boundary of the two areas, and gradually transition the illumination values ​​in a linear or nonlinear manner through an algorithm. The illumination value of area A close to area B can be adjusted to 400 lux, and the illumination value of area B close to area A can be adjusted to 400 lux, thereby forming a smooth illumination transition. This dynamic adjustment method based on difference detection enables the system to effectively eliminate the phenomenon of lighting faults and provide a more comfortable visual experience. Through illumination smoothing, the system achieves a uniform transition of lighting effects, which not only avoids the discomfort caused by abrupt changes in brightness and darkness to the human eye, but also improves the quality of the overall lighting environment. At the same time, this intelligent transition adjustment mechanism also provides a more sophisticated optimization method for the system's lighting control, making the lighting effect more natural and coordinated.

[0088] Reference Figure 2, a lighting uniform dimming system for a high-power LED area provided in an embodiment of the present application, the system comprises: a data acquisition module, a level classification module, a lighting parameter determination module, and a lighting dimming module, wherein:

[0089] A data acquisition module, used to acquire crowd distribution data of a target area and illumination data of multiple segmented lighting areas in the target area;

[0090] The level classification module is used to determine the distribution position and coverage of dense crowds in the target area based on crowd distribution data; calculate the distance value between each segmented lighting area and the distribution position of dense crowds, and determine the lighting demand level corresponding to each distance value;

[0091] The lighting parameter determination module is used to determine the illumination compensation value of each segmented lighting area in combination with the lighting demand level and illumination data of each segmented lighting area, and determine the light output angle of each segmented lighting area in combination with the distribution position and coverage range of dense human flow;

[0092] The lighting dimming module is used to adjust the LED light groups of each segmented lighting area according to the illumination compensation value and the light output angle of each segmented lighting area to illuminate the target area.

[0093] On the basis of the above embodiment, the hierarchical division module is also used to divide the target area into multiple grid units of preset grid sizes; determine the flow of people in each grid unit based on the crowd distribution data; determine the grid unit with a crowd flow greater than the flow threshold as a dense crowd flow, and use the center point position of the dense crowd flow as the distribution position of the dense crowd flow; merge the grid units adjacent to the dense crowd flow to obtain the coverage range of the dense crowd flow.

[0094] Based on the above embodiment, the grading module is also used to obtain the installation position of the LED light group in each segmented lighting area; based on each installation position and the distribution position of dense human flow, the distance value between each segmented lighting area and the distribution position of dense human flow is calculated.

[0095] Based on the above embodiment, the level classification module is also used to obtain a lighting requirement level mapping table, which includes distance value intervals corresponding to multiple different lighting requirement levels; based on the distance value interval in which each distance value is located, the lighting requirement level corresponding to each distance value is determined.

[0096] On the basis of the above embodiment, the lighting parameter determination module is also used to determine the current illumination value of each segmented lighting area based on various illumination data; calculate the difference between the current illumination value of each segmented lighting area and the benchmark illumination value to obtain a benchmark compensation value; determine the illumination adjustment coefficient corresponding to each lighting demand level according to a preset coefficient mapping table; multiply the benchmark compensation value of each segmented lighting area by the corresponding illumination adjustment coefficient to obtain the illumination compensation value of each segmented lighting area.

[0097] On the basis of the above embodiments, the lighting parameter determination module is also used to calculate the angle between the horizontal plane and the line between the installation position of the LED light group in each segmented lighting area and the distribution position of the dense human flow, and use each angle as the reference light output angle of the corresponding segmented lighting area; determine the angle compensation value based on the coverage range of the dense human flow; superimpose the reference light output angle and the angle compensation value of each segmented lighting area to obtain the light output angle of each segmented lighting area.

[0098] Based on the above embodiment, the lighting dimming module is also used to obtain the baseline illumination area of ​​the LED light group and the coverage area of ​​the coverage range; the ratio of the baseline illumination area to the coverage area is used as the compensation coefficient; the compensation coefficient is multiplied by the maximum light output angle of the LED light group to obtain the angle compensation value.

[0099] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0100] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0101] The communication bus 302 is used to realize the connection and communication between these components.

[0102] The user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0103] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0104] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface diagrams and applications, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0105] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 The memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for realizing a method for uniformly dimming the lighting of a high-power LED area.

[0106] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the memory 305 to store an application program for realizing a method for uniform dimming of lighting in a high-power LED area. When executed by one or more processors 301, the electronic device 300 executes one or more methods in the above-mentioned embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0107] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0108] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0109] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0110] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0111] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, 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, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0112] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0113] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not recorded in the present disclosure. The description and examples are to be regarded as exemplary only.

Claims

1. A method for achieving uniform dimming of high-power LED area lighting, characterized in that: include: Acquire crowd flow distribution data of a target area and illumination data of a plurality of segmented lighting areas within the target area; Based on the crowd flow distribution data, determine the distribution position and coverage of dense crowd flow in the target area; Calculating the distance value between each of the segmented lighting areas and the distribution position of the dense human flow, and determining the lighting demand level corresponding to each of the distance values; Determine the illumination compensation value of each segmented illumination area in combination with the illumination demand level and illumination data of each segmented illumination area, and determine the light output angle of each segmented illumination area in combination with the distribution position and coverage range of the dense flow of people; Adjusting the LED light groups of each segmented lighting area according to the illumination compensation value and the light output angle of each segmented lighting area to illuminate the target area; The step of determining the light output angle of each segmented lighting area in combination with the distribution position and coverage of the dense crowd flow includes: Calculate the angle between the horizontal plane and the line between the installation position of the LED light group of each segmented lighting area and the distribution position of the dense human flow, and use each of the angles as the reference light output angle of the corresponding segmented lighting area; Determining an angle compensation value based on the coverage range of the dense crowd flow; Superimposing the reference light emitting angle of each segmented lighting area and the angle compensation value to obtain the light emitting angle of each segmented lighting area; The determining of the angle compensation value based on the coverage range of the dense flow of people includes: Obtaining a reference irradiation area of ​​the LED light group and a coverage area of ​​the coverage range; taking the ratio of the reference irradiation area to the coverage area as a compensation coefficient; The compensation coefficient is multiplied by the maximum light emission angle of the LED lamp group to obtain an angle compensation value.

2. The method for achieving uniform dimming of high-power LED area lighting according to claim 1, characterized in that: The determining, based on the crowd flow distribution data, the distribution position and coverage of the dense crowd flow in the target area includes: Dividing the target area into a plurality of grid units of a preset grid size; Based on the crowd flow distribution data, determining the crowd flow in each of the grid units; Determine the grid cells where the flow of people is greater than the flow threshold as dense flow of people, and use the center point position of the dense flow of people as the distribution position of the dense flow of people; The grid cells adjacent to the dense human flow are merged to obtain the coverage of the dense human flow.

3. The method for achieving uniform dimming of high-power LED area lighting according to claim 1, characterized in that: The calculating the distance value between each of the segmented lighting areas and the distribution position of the dense human flow includes: Obtaining the installation position of the LED light group in each of the segmented lighting areas; Based on each of the installation positions and the distribution position of the dense human flow, the distance value between each of the segmented lighting areas and the distribution position of the dense human flow is calculated.

4. The method for achieving uniform dimming of high-power LED area lighting according to claim 1, characterized in that: The determining of the lighting requirement level corresponding to each of the distance values ​​includes: Obtaining a lighting demand level mapping table, wherein the lighting demand level mapping table includes distance value intervals corresponding to a plurality of different lighting demand levels; Based on the distance value interval in which each of the distance values ​​lies, a lighting requirement level corresponding to each of the distance values ​​is determined.

5. The method for achieving uniform dimming of high-power LED area lighting according to claim 1, characterized in that: The step of determining the illumination compensation value of each segmented illumination area by combining the illumination requirement level and illumination data of each segmented illumination area comprises: Based on each of the illumination data, determining a current illumination value of each of the segmented lighting areas; Calculating the difference between the current illumination value of each segmented lighting area and the reference illumination value to obtain a reference compensation value; Determine the illumination adjustment coefficient corresponding to each lighting demand level according to a preset coefficient mapping table; The reference compensation value of each segmented lighting area is multiplied by the corresponding illumination adjustment coefficient to obtain the illumination compensation value of each segmented lighting area.

6. A system for realizing uniform dimming of high-power LED area lighting, characterized in that: The system comprises: A data acquisition module, used to acquire crowd distribution data of a target area and illumination data of a plurality of segmented lighting areas in the target area; A level classification module is used to determine the distribution position and coverage of the dense crowd flow in the target area based on the crowd flow distribution data; calculate the distance value between each of the segmented lighting areas and the distribution position of the dense crowd flow, and determine the lighting demand level corresponding to each of the distance values; A lighting parameter determination module, used to determine the illumination compensation value of each segmented lighting area in combination with the lighting demand level and illumination data of each segmented lighting area, and determine the light output angle of each segmented lighting area in combination with the distribution position and coverage range of the dense flow of people; A lighting dimming module, used for adjusting the LED light groups of each segmented lighting area according to the illumination compensation value and the light output angle of each segmented lighting area, so as to illuminate the target area; The step of determining the light output angle of each segmented lighting area in combination with the distribution position and coverage of the dense crowd flow includes: Calculate the angle between the horizontal plane and the line between the installation position of the LED light group of each segmented lighting area and the distribution position of the dense human flow, and use each of the angles as the reference light output angle of the corresponding segmented lighting area; Determining an angle compensation value based on the coverage range of the dense crowd flow; Superimposing the reference light emitting angle of each segmented lighting area and the angle compensation value to obtain the light emitting angle of each segmented lighting area; The determining of the angle compensation value based on the coverage range of the dense flow of people includes: Obtaining a reference irradiation area of ​​the LED light group and a coverage area of ​​the coverage range; taking the ratio of the reference irradiation area to the coverage area as a compensation coefficient; The compensation coefficient is multiplied by the maximum light emission angle of the LED lamp group to obtain an angle compensation value.

7. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method for realizing uniform dimming of lighting in a high-power LED area as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method for achieving uniform dimming of lighting in a high-power LED area as described in any one of claims 1 to 5 is executed.

Images