A method, device, electronic equipment and storage medium for monitoring and supervising light pollution.

Abstract

This application relates to a method, device, electronic equipment, and storage medium for monitoring light pollution, belonging to the technical field of environmental monitoring. The method includes the following steps: acquiring a road change area uploaded by a user, the road change area carrying first location information; selecting a pre-stored regional building deployment map corresponding to the first location information, and obtaining a lighting model and solar trajectory corresponding to the regional building deployment map; determining adjacent building areas corresponding to the road change area in the regional building deployment map based on the first location information; performing lighting simulation on the adjacent building areas based on the lighting model and solar trajectory, and calculating the light reflection area; marking the overlapping portion of the light reflection area and the road change area to obtain the road light pollution area; and sending the road light pollution area to the user. This application effectively reduces the workload of monitoring personnel.

Description

Technical Field

[0001] This application relates to the technical field of environmental monitoring, and in particular to a method, device, electronic equipment and storage medium for monitoring light pollution. Background Technology

[0002] Currently, light pollution refers to the adverse effects of light on people's normal life or work. Drivers often experience glare from reflections off building windows while driving.

[0003] In related technologies, a device for detecting light pollution includes a power bank, a light intensity sensor, a microcontroller, control buttons, and a display. The control buttons control the power bank to supply power to the microcontroller. The light intensity sensor outputs a voltage level signal, the microcontroller responds to the signal and processes it to obtain a digital signal, which it then outputs. The display screen responds to the digital signal and displays the light intensity value. Inspectors place the light intensity sensor on the modified road for detection. The microcontroller processes the light source received by the sensor and displays the data to the inspectors, allowing them to perform optical detection on the modified road area and determine where light pollution exists.

[0004] In the process of developing this application, the inventors discovered at least the following problems in the technology:

[0005] When the road alteration area is large, the inspectors need to inspect every section of the alteration area, resulting in a large workload. Summary of the Invention

[0006] To address the issue of excessive workload caused by inspectors needing to inspect every area in the road alteration zone, this application provides a light pollution monitoring method, device, electronic equipment, and storage medium.

[0007] Firstly, this application provides a method for monitoring and supervising light pollution, employing the following technical solution:

[0008] A method for monitoring and supervising light pollution includes the following steps:

[0009] Obtain the road change area uploaded by the user, wherein the road change area carries first location information;

[0010] Locate the pre-stored regional building deployment map corresponding to the first location information, and obtain the lighting model and solar trajectory corresponding to the regional building deployment map;

[0011] In the regional building deployment map, based on the first location information, the adjacent building areas corresponding to the road change area are determined;

[0012] Based on the lighting model and the sun's trajectory, a lighting simulation is performed on the adjacent building area, and the light reflection area is calculated.

[0013] The overlapping portion of the light reflection area and the road modification area is marked to obtain the road light pollution area;

[0014] Send the information about the road light pollution area to the user.

[0015] By employing the above technical solution, the server obtains the road change area uploaded by the user, locates the corresponding electronic map (i.e., the regional building deployment map), the lighting model corresponding to the regional building deployment map, and the solar trajectory. The server identifies adjacent building areas in the regional building deployment map, calculates the corresponding light reflection areas of these adjacent building areas, marks the overlapping parts of the light reflection areas and the road change area, and obtains and sends the road light pollution area to the user. The server can determine the adjacent building areas of the road change area through the regional building deployment map, and then calculate the road light pollution area using the lighting model and solar trajectory, which helps inspectors narrow down the inspection scope and improve their work efficiency.

[0016] Optionally, the road change area carries a city identifier;

[0017] After obtaining the user-uploaded road change area, the following steps are also included:

[0018] Select a pre-stored urban building deployment map corresponding to the city identifier;

[0019] Based on the first location information of the road change area, select the regional building deployment map in the city building deployment map.

[0020] By adopting the above technical solution, when the server obtains the city identifier of the road change area, it selects the corresponding city building deployment map, and then selects the regional building deployment map that matches the first location information from the city building deployment map. The server stores building deployment maps of different cities and finds the corresponding regional building deployment map through the first location information, which is beneficial for road changes in different cities and increases the range of areas of road light pollution detected by the server.

[0021] Optionally, the urban building deployment map carries urban location identifiers;

[0022] In the regional building deployment map, determining the adjacent building areas corresponding to the road change area based on the first location information includes the following steps:

[0023] An integrated building deployment map is obtained based on the preset identification sequence and the city location identification.

[0024] In the integrated building deployment map, the adjacent building areas corresponding to the road change areas are determined based on the first location information.

[0025] By adopting the above technical solution, when the road to be changed crosses different areas in a city, the server identifies multiple city location identifiers and, based on the identifier order, obtains an integrated building deployment map and determines the adjacent building areas corresponding to the road change area. The server can detect road changes between areas, reducing the likelihood of obtaining road light pollution areas in a single area's building deployment map by default, and improving the accuracy of the road light pollution areas obtained by the server.

[0026] Optionally, determining the adjacent building areas corresponding to the road change area based on the first location information in the preset regional building deployment map includes the following steps:

[0027] Based on the first location information, all candidate areas adjacent to the road change area are determined in the preset regional building deployment map;

[0028] Select the pre-stored building models corresponding to the candidate area;

[0029] Obtain the light reflection area of ​​each building model to obtain the adjacent building area.

[0030] By adopting the above technical solution, the building facade can be a glass or metal surface that reflects light, or a wall surface that absorbs light. However, the glass or metal surface that reflects light will reflect it onto the road and affect drivers. The server determines all candidate areas adjacent to the road change area, selects the building model corresponding to the candidate area, and selects the building model with a glass or metal surface to obtain the corresponding adjacent building area. This helps to reduce the server's computational load and improve the server's working efficiency.

[0031] Optionally, based on the lighting model and the sun's trajectory, a lighting simulation is performed on the adjacent building area, and the light reflection area is calculated, including the following steps:

[0032] Obtain pre-stored second location information corresponding to the adjacent building area;

[0033] In the regional building deployment map, the vertical lines of each outline of the adjacent building area are calculated based on the second location information;

[0034] A vertical region is generated based on the vertical line and the first position information;

[0035] Based on the solar trajectory, illumination simulation is performed on the vertical region, and the light reflection area is calculated.

[0036] By adopting the above technical solution, the regional building deployment map can be a plan view. The server calculates the vertical lines of the outlines of adjacent building areas in the regional building deployment map, and obtains the intersection points of the vertical lines with the road modification areas to generate vertical areas. Based on the sun's trajectory, the server performs lighting simulation on the vertical areas to obtain the light reflection areas. This allows the server to perform lighting simulation for the outlines of different buildings, which helps to improve the accuracy of the obtained light reflection areas.

[0037] Optionally, the step of simulating illumination in the vertical region based on the sun's trajectory and calculating the illumination reflection area includes the following steps:

[0038] Based on the preset obstacle model, the obstacle areas and corresponding obstacle markers in the vertical region are obtained;

[0039] Select the pre-stored obstacle information corresponding to the obstacle identifier;

[0040] Based on the lighting model and the sun's trajectory, a lighting simulation is performed on the adjacent building area to calculate the candidate reflection area;

[0041] Based on the obstacle information and the candidate reflection area, the light reflection area is obtained.

[0042] By adopting the above technical solution, the server identifies obstacles between the road change area and the adjacent building area, obtains the corresponding obstacle information, and obtains the light reflection area that is not blocked by obstacles based on the obstacle information and the calculated candidate reflection area, thereby further improving the accuracy of the light reflection area obtained by the server.

[0043] Optionally, the method further includes the following steps:

[0044] Obstacle images are acquired regularly via the internet;

[0045] An obstacle model is trained based on the obstacle images.

[0046] By adopting the above technical solution, obstacle models are trained using obstacle images, which can be images of vegetation, decorations, or public facilities, thereby improving the accuracy of the server in recognizing obstacle images.

[0047] Secondly, this application provides a light pollution monitoring device, which adopts the following technical solution:

[0048] A light pollution monitoring device, comprising:

[0049] The first acquisition module is used to acquire the road change area uploaded by the user, and the road change area carries first location information;

[0050] The first selection module is used to select a pre-stored regional building deployment map corresponding to the first location information, and obtain a lighting model and solar trajectory corresponding to the regional building deployment map;

[0051] The first determining module is used to determine, based on the first location information, the adjacent building area corresponding to the road change area in the regional building deployment map;

[0052] The first calculation module is used to perform lighting simulation for the adjacent building area based on the lighting model and the sun's trajectory, and to calculate the light reflection area.

[0053] The first obtaining module is used to mark the overlapping part of the light reflection area and the road change area to obtain the road light pollution area;

[0054] The sending module is used to send the road light pollution area to the user.

[0055] By adopting the above technical solution, the server can determine the adjacent building areas of the road alteration area through the regional building deployment map. The server uses a lighting model and solar trajectory to obtain the light reflection area, and then obtains the overlapping part of the light reflection area and the road alteration area, i.e., the road light pollution area. This helps inspectors narrow down the inspection range and improve their work efficiency.

[0056] Thirdly, this application provides an electronic device that adopts the following technical solution:

[0057] Optionally, the electronic device includes a processor and a memory, the memory storing at least one instruction, at least one program, code set, or instruction set, the at least one instruction, the at least one program, the code set, or instruction set being loaded and executed by the processor to implement a light pollution monitoring method as described in the first aspect.

[0058] By adopting the above technical solution, an electronic device can implement the above-mentioned light pollution monitoring method according to the relevant computer program stored in the memory, thereby improving the cooperation between information from different sources when calculating the road light pollution area, and thus improving the accuracy of the road light pollution area.

[0059] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution:

[0060] Optionally, the storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement a light pollution monitoring method as described in the first aspect.

[0061] By adopting the above technical solution, the corresponding program can be stored, thereby improving the collaboration between information from different sources when calculating road light pollution areas, thus improving the accuracy of road light pollution area calculations.

[0062] In summary, this application includes at least one of the following beneficial technical effects:

[0063] 1. The server can determine the adjacent building areas of the road change area through the regional building deployment map, and then calculate the road light pollution area through the lighting model and the sun trajectory, which helps the inspectors to narrow the inspection range and improve the work efficiency of the inspectors.

[0064] 2. When the server obtains the city identifier of the road change area, it selects the corresponding city building deployment map, and then selects the regional building deployment map that matches the first location information from the city building deployment map. The server stores building deployment maps of different cities and finds the corresponding regional building deployment map through the first location information, which is beneficial for road changes in different cities and increases the range of areas of road light pollution detected by the server.

[0065] 3. When a road requiring modification crosses different areas within a city, the server identifies multiple city location markers and, based on the marker order, generates an integrated building deployment map, determining the adjacent building areas corresponding to the road modification area. The server can detect road modifications between areas, reducing the likelihood of obtaining road light pollution areas in a single area's building deployment map by default, thus improving the accuracy of the road light pollution areas obtained by the server. Attached Figure Description

[0066] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 This is a structural block diagram of the light pollution monitoring and detection device according to an embodiment of this application.

[0068] Figure 2 This is a schematic flowchart of the light pollution monitoring and detection method according to an embodiment of this application.

[0069] Figure 3 This is a schematic flowchart of the light pollution monitoring and detection device according to an embodiment of this application.

[0070] Figure 4 This is a city building deployment diagram of City M, according to an embodiment of this application.

[0071] Figure 5 This is a schematic diagram of the lighting model of a section of a nearby building area according to an embodiment of this application. Detailed Implementation

[0072] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0073] This application provides a method for monitoring and supervising light pollution, which can be applied to a light pollution monitoring and supervising device. The frame structure of the light pollution monitoring and supervising device can be as follows: Figure 1 As shown, it can include a server and multiple user terminals. The user terminals can be computers, mobile phones, or tablets. Specifically, the execution entity of this method can be the server, assisted by the user terminals. The server processes the road change areas uploaded by the user terminals to obtain the road light pollution areas and sends these areas to the user terminals. In detail, the inspector sends the road change areas to the server through the user terminal. The server obtains the uploaded road change areas, processes them to obtain the road light pollution areas, and sends these areas to the user terminals, allowing the inspector to understand the light pollution areas within the road change areas through the user terminals.

[0074] The following will describe the specific implementation methods. Figure 2 The processing flow shown is explained in detail below:

[0075] Step 201: Obtain the road change area uploaded by the user. The road change area carries the first location information.

[0076] In this embodiment, the server obtains the road change area uploaded by the user terminal. The road change area can be a newly added road or a widened road in a certain area of ​​a city. The road change area carries corresponding location information (i.e., first location information). The location information can be the latitude and longitude of the road change area outline, or it can be the coordinates corresponding to the road change area outline in a city map.

[0077] Optionally, the road change area carries a city identifier, and a pre-stored city building deployment map corresponding to the city identifier is selected. Based on the first location information of the road change area, a regional building deployment map is selected from the city building deployment map.

[0078] In this embodiment, the road change area obtained by the server carries a city identifier, which can be a string or a serial number. The server also pre-stores city building deployment maps, which can be planar maps of various cities. After obtaining the road change area uploaded by the user, the server selects the city building deployment map corresponding to the city identifier. Based on the first location information of the road change area, the server selects the regional building deployment map within the city building deployment map. The city building deployment map can be composed of multiple regional building deployment maps.

[0079] Step 202: Locate the pre-stored regional building deployment map corresponding to the first location information, and obtain the lighting model and solar trajectory corresponding to the regional building deployment map.

[0080] In this embodiment, the server stores a regional building deployment map of a certain city. The server also stores a lighting model and a solar trajectory corresponding to the regional building deployment map. The solar trajectory can be a straight line in the regional building deployment map, used to represent the sun's path in the plan view. After obtaining the road change area, the server searches for the regional building deployment map corresponding to the first location information and obtains the lighting model and solar trajectory corresponding to the regional building deployment map.

[0081] Step 203: In the regional building deployment map, determine the adjacent building areas corresponding to the road change area based on the first location information.

[0082] In this embodiment, the server assigns building labels to each building in the regional building deployment map. Based on the location information (i.e., first location information) carried by the road change area, the server marks the corresponding area in the regional building deployment map. The server selects the building labels adjacent to the marked area and the corresponding buildings (i.e., the adjacent building area), thus determining the adjacent building area corresponding to the road change area.

[0083] Optionally, the city building deployment map carries city location identifiers. Based on a preset identifier order and the city location identifiers, an integrated building deployment map is obtained. In the integrated building deployment map, the adjacent building areas corresponding to the road change area are determined based on the first location information.

[0084] In this embodiment, the server assigns a city location identifier to each defined area in the city building deployment map. The city location identifier can be a string. After obtaining the city building deployment map carrying the city location identifier, the server generates an integrated building deployment map composed of multiple area building deployment maps based on a preset identifier order and the city location identifier. For example, the city building deployment map of city M is as follows: Figure 4Accordingly, the server obtains the city location identifiers M1, M2, and M3 from the city building deployment map of city M. Following the identifier order (i.e., the numbers following the letters of the city location identifiers in ascending order), it obtains an integrated building deployment map composed of the regional building deployment maps corresponding to M1, M2, and M3. Within the integrated building deployment map, the server determines the adjacent building areas corresponding to the road change area based on the first location information.

[0085] Optionally, in the preset regional building deployment map, based on the first location information, all candidate areas adjacent to the road change area are determined. Pre-stored building models corresponding to the candidate areas are selected, and the light reflection areas of each building model are obtained to obtain the adjacent building areas.

[0086] In this embodiment, the server, based on a first location information, determines all candidate areas adjacent to the road change area within a preset regional building deployment map. The server pre-stores trained building models, which can be trained using planar images of buildings obtained via the internet. The server also pre-stores the location of each outline of each building model in the regional building deployment map, the dimensions of the facade corresponding to each outline, and the reflective surface area corresponding to each facade—that is, the light reflection area of ​​each building model. The server selects building models corresponding to the candidate areas, obtains the light reflection area of ​​each building model, and thus obtains the adjacent building areas.

[0087] Step 204: Based on the lighting model and the sun's trajectory, perform lighting simulation for the area near the building and calculate the area of ​​light reflection.

[0088] In this embodiment, the server performs lighting simulation on the area near the building based on the lighting model and the sun's trajectory, and calculates the area of ​​light reflection. The lighting model for a specific section of a nearby building area is as follows: Figure 5 Correspondingly, the line connecting the simulated sun and a point on the cross-section of the light reflection area is the incident ray. A horizontal line, the normal, is generated using the point of the incident ray on the light reflection area as a reference point. The server then uses the incident ray and the normal to obtain the intersection of the reflected ray and the road cross-section, which is the reflection point. Simulating each point on the cross-section of this light reflection area yields a reflected ray composed of multiple reflection points. The server then sequentially extracts cross-sections of buildings based on the length of the light reflection area, obtaining different lighting models and thus different reflected ray patterns. The server ultimately obtains a light reflection area composed of multiple reflected ray patterns.

[0089] Optionally, pre-stored second location information corresponding to adjacent building areas is obtained; in the regional building deployment map, vertical lines of each outline of the adjacent building areas are calculated based on the second location information. Vertical regions are generated based on the vertical lines and the first location information. Illumination simulation is performed on the vertical regions based on the solar trajectory, and the light reflection area is calculated.

[0090] In this embodiment, the server obtains pre-stored location information corresponding to adjacent building areas (i.e., second location information). Based on the second location information, the server calculates the vertical lines of each outline of the adjacent building areas in the regional building deployment map. The server obtains the vertical lines that intersect with the outline of the road change area, generating vertical regions. Based on the sun's trajectory, the server performs illumination simulation on the vertical regions and calculates the light reflection areas.

[0091] Optionally, based on a preset obstacle model, obstacle regions and corresponding obstacle markers are obtained in the vertical region, and pre-stored obstacle information corresponding to the obstacle markers is selected. Based on the lighting model and the sun's trajectory, lighting simulation is performed on the adjacent building area to calculate the candidate reflection area. Based on the obstacle information and the candidate reflection area, the light reflection area is obtained.

[0092] In this embodiment, after generating the vertical region, the server obtains the obstacle areas and corresponding obstacle identifiers within the vertical region based on a preset obstacle model. It then selects pre-stored obstacle information corresponding to the obstacle identifiers; this obstacle information characterizes the size of the obstacle. Based on a lighting model and the sun's trajectory, the server performs lighting simulation on the adjacent building area to calculate candidate reflection areas. These candidate reflection areas characterize reflection areas not obstructed by obstacles. Finally, based on the obstacle information, the server deletes obstructed areas from the candidate reflection areas to obtain the light reflection areas.

[0093] Optionally, obstacle images can be acquired periodically via the internet, and an obstacle model can be trained based on these images.

[0094] In this embodiment, the server periodically acquires obstacle images via the internet and trains an obstacle model based on these images. The obstacles can be vegetation, public facilities, or decorative items. The periodicity can be daily, weekly, or monthly.

[0095] Step 205: Mark the overlapping area between the light reflection area and the road modification area to obtain the road light pollution area.

[0096] In this embodiment, the server marks the overlapping area between the light reflection area and the road change area to obtain the road light pollution area.

[0097] Step 206: Send the road light pollution area to the user.

[0098] In this embodiment, the server sends the road light pollution area to the user's terminal so that the inspectors can understand the road light pollution area through the user terminal and carry out remediation of the light pollution area in the road.

[0099] Based on the same technical concept, embodiments of this application also disclose a light pollution monitoring device, such as... Figure 3 As shown, a light pollution monitoring device includes:

[0100] The first acquisition module 301 is used to acquire the road change area uploaded by the user, and the road change area carries the first location information;

[0101] The lookup module 302 is used to look up the pre-stored regional building deployment map corresponding to the first location information, and obtain the lighting model and solar trajectory corresponding to the regional building deployment map;

[0102] The first determining module 303 is used to determine, in the regional building deployment map, the adjacent building area corresponding to the road change area based on the first location information;

[0103] The first calculation module 304 is used to perform lighting simulation for the area near the building based on the lighting model and the sun's trajectory, and to calculate the area of ​​light reflection.

[0104] The first module 305 is used to mark the overlapping part of the light reflection area and the road change area to obtain the road light pollution area;

[0105] The sending module 306 is used to send the road light pollution area to the user.

[0106] Optionally, the first selection module is used to select a pre-stored urban building deployment map corresponding to the city identifier;

[0107] The second selection module is used to select the regional building deployment map in the city building deployment map based on the first location information of the road change area.

[0108] Optionally, the second obtaining module is used to obtain an integrated building deployment map based on a preset identifier order and city location identifiers;

[0109] The second determining module is used to determine, based on the first location information, the adjacent building areas corresponding to the road change area in the integrated building deployment map.

[0110] Optionally, a third determining module is used to determine, based on the first location information, all candidate areas adjacent to the road change area in a preset regional building deployment map;

[0111] The third selection module is used to select pre-stored building models corresponding to the candidate area;

[0112] The second acquisition module is used to acquire the light reflection area of ​​each building model and obtain the adjacent building area.

[0113] Optionally, the third acquisition module is used to acquire pre-stored second location information corresponding to the adjacent building area;

[0114] The second calculation module is used to calculate the vertical lines of each outline of the adjacent building area based on the second location information in the regional building deployment map.

[0115] The generation module is used to generate a vertical region based on the vertical line and the first position information;

[0116] The third calculation module simulates illumination in the vertical region based on the sun's trajectory and calculates the area of ​​light reflection.

[0117] Optionally, the third module is used to obtain the obstacle area and the corresponding obstacle identifier in the vertical region based on the preset obstacle model;

[0118] The fourth selection module is used to select pre-stored obstacle information corresponding to obstacle identifiers;

[0119] The fourth calculation module is used to perform lighting simulation on the area near the building based on the lighting model and the sun's trajectory, and calculate the candidate reflection area.

[0120] The fourth module is used to obtain the light reflection area based on obstacle information and the candidate reflection area.

[0121] Optionally, a fourth acquisition module is used to periodically acquire obstacle images via the Internet;

[0122] The training module is used to train an obstacle model based on obstacle images.

[0123] This application also discloses an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described above for light pollution monitoring and supervision.

[0124] This application also discloses a computer-readable storage medium that stores a computer program that can be loaded by a processor and executed as described above for light pollution monitoring. The computer-readable storage medium includes, for example, various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0125] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit the scope of protection of the application. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on these embodiments, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

Claims

1. A method for monitoring and supervising light pollution, characterized in that, The steps include: obtaining the road change area uploaded by the user, wherein the road change area carries first location information; Locate the pre-stored regional building deployment map corresponding to the first location information, and obtain the lighting model and solar trajectory corresponding to the regional building deployment map; In the regional building deployment map, based on the first location information, the adjacent building areas corresponding to the road change area are determined; Based on the lighting model and the sun's trajectory, lighting simulation is performed on the adjacent building area, and the light reflection area is calculated. The overlapping part of the light reflection area and the road modification area is marked to obtain the road light pollution area. Send the information about the road light pollution area to the user; The step of simulating illumination for the adjacent building area based on the illumination model and the sun's trajectory, and calculating the illumination reflection area, includes the following steps: obtaining pre-stored second location information corresponding to the adjacent building area; calculating the vertical lines of each outline of the adjacent building area based on the second location information in the regional building deployment map; generating a vertical area based on the vertical lines and the first location information; and simulating illumination for the vertical area based on the sun's trajectory, and calculating the illumination reflection area.

2. The light pollution monitoring method according to claim 1, characterized in that, The road change area carries a city identifier; after obtaining the road change area uploaded by the user, the following steps are also included: selecting a pre-stored city building deployment map corresponding to the city identifier; and selecting a regional building deployment map in the city building deployment map according to the first location information of the road change area.

3. The light pollution monitoring method according to claim 2, characterized in that, The city building deployment map carries city location identifiers; the step of determining the adjacent building area corresponding to the road change area based on the first location information in the regional building deployment map includes the following steps: obtaining an integrated building deployment map based on a preset identifier order and the city location identifiers; determining the adjacent building area corresponding to the road change area in the integrated building deployment map based on the first location information.

4. The light pollution monitoring method according to claim 1, characterized in that, The step of determining the adjacent building area corresponding to the road change area based on the first location information in the regional building deployment map includes the following steps: in the preset regional building deployment map, determining all candidate areas adjacent to the road change area based on the first location information; selecting pre-stored building models corresponding to the candidate areas; obtaining the light reflection area of ​​each building model to obtain the adjacent building area.

5. The light pollution monitoring method according to claim 1, characterized in that, The process of simulating illumination in the vertical region based on the sun's trajectory and calculating the illumination reflection area includes the following steps: obtaining obstacle regions and corresponding obstacle markers in the vertical region according to a preset obstacle model; selecting pre-stored obstacle information corresponding to the obstacle markers; performing illumination simulation on the adjacent building area according to the illumination model and the sun's trajectory to calculate the candidate reflection area; and obtaining the illumination reflection area based on the obstacle information and the candidate reflection area.

6. The light pollution monitoring method according to claim 5, characterized in that, The method further includes the following steps: periodically acquiring obstacle images via the Internet; and training an obstacle model based on the obstacle images.

7. A light pollution monitoring device, characterized in that, include: The first acquisition module is used to acquire the road change area uploaded by the user, and the road change area carries first location information; The search module is used to search for a pre-stored regional building deployment map corresponding to the first location information, and to obtain a lighting model and solar trajectory corresponding to the regional building deployment map; The first determining module is used to determine, based on the first location information, the adjacent building area corresponding to the road change area in the regional building deployment map; The first calculation module is used to perform lighting simulation for the adjacent building area based on the lighting model and the sun's trajectory, and to calculate the light reflection area. The first obtaining module is used to mark the overlapping part of the light reflection area and the road change area to obtain the road light pollution area; A sending module is used to send the road light pollution area to the user; wherein, the first calculation module includes: a third acquisition module, used to acquire pre-stored second location information corresponding to the adjacent building area; a second calculation module, used to calculate the vertical lines of each outline of the adjacent building area based on the second location information in the regional building deployment map; a generation module, used to generate a vertical area based on the vertical lines and the first location information; and a third calculation module, used to perform illumination simulation on the vertical area based on the solar trajectory and calculate the light reflection area.

8. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer program is stored that can be loaded by a processor and executed according to any one of claims 1 to 6.

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