An intelligent monitoring control method and monitoring control system for road lighting

Abstract

The application discloses an intelligent monitoring control method and a monitoring control system for road lighting, and the method comprises the following steps: for any target road section to be monitored, acquiring regional images obtained by a plurality of target image acquisition devices pre-determined for image acquisition on a region of interest of the target road section; and performing image processing and analysis operations on the regional images collected by the plurality of target image acquisition devices according to pre-determined road section monitoring requirements to obtain target lighting information corresponding to the target road section. It can be seen that the application can acquire the lighting information corresponding to the road section in the manner of intelligently analyzing and processing the regional images collected on the region of interest of the road section, which is not only beneficial to improving the acquisition efficiency of the lighting information, but also beneficial to improving the accuracy, comprehensiveness and reliability of the acquired lighting information, thereby providing reliable and effective analysis basis / decision basis for actual analysis requirements.

Description

Technical Field

[0001] This invention relates to the field of road lighting monitoring technology, and in particular to an intelligent monitoring and control method and system for road lighting. Background Technology

[0002] As a vital infrastructure for social development, roads not only facilitate daily travel and greatly enhance people's work and life, but also effectively ensure the transportation of goods, making significant contributions to the economic development of a city and even a country. Well-planned roads can also effectively reduce traffic congestion, and most road sections are equipped with streetlights to meet the needs of nighttime driving, thereby providing safety for vehicles and pedestrians traveling at night.

[0003] For road sections with streetlights, it is necessary to collect lighting information (such as illuminance and luminance) for the corresponding road sections. This collected lighting information is then used as a basis for analysis in practical applications, such as analyzing streetlight lighting efficiency, lighting power consumption, or carbon emissions. Currently, the most common method for collecting lighting information relies on personnel using handheld data collection devices for testing. In practice, this method has been found to be inefficient and inaccurate.

[0004] It is evident that improving the efficiency and accuracy of lighting information acquisition are pressing technical issues that need to be addressed. Summary of the Invention

[0005] This invention provides an intelligent monitoring and control method and system for road lighting, which can not only improve the efficiency of acquiring lighting information, but also improve the accuracy, comprehensiveness and reliability of the acquired lighting information.

[0006] To address the aforementioned technical problems, a first aspect of this invention discloses an intelligent monitoring and control method for road lighting, the method comprising: For any target road segment to be monitored, acquire region images obtained by acquiring images of the region of interest of the target road segment by multiple predetermined target image acquisition devices; the multiple target image acquisition devices include fixed image acquisition devices and / or mobile image acquisition devices; Based on the pre-determined road segment monitoring requirements, image processing and analysis operations are performed on the regional images acquired by multiple target image acquisition devices to obtain the target lighting information corresponding to the target road segment.

[0007] As an optional implementation, in the first aspect of the present invention, the step of performing image processing and analysis operations on regional images acquired by multiple target image acquisition devices according to predetermined road segment monitoring requirements to obtain target lighting information corresponding to the target road segment includes: Based on the pre-determined road segment monitoring requirements, image processing and analysis operations are performed on the regional images acquired by multiple target image acquisition devices to obtain at least one type of lighting parameter; Based on the predetermined first processing method and the road segment monitoring requirements, the corresponding first type of lighting parameters are processed to obtain at least one second type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one of the second type of lighting parameters; or, the target lighting information corresponding to the target road segment is determined based on at least one of the first type of lighting parameters and at least one of the second type of lighting parameters.

[0008] As an optional implementation, in the first aspect of the present invention, determining the target lighting information corresponding to the target road segment based on at least one of the second type of lighting parameters includes: At least one of the second type of lighting parameters is determined as the target lighting information corresponding to the target road segment; or... According to the predetermined second processing method and the road section monitoring requirements, the corresponding second type of lighting parameters are processed to obtain at least one third type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one of the third type of lighting parameters, or the target lighting information corresponding to the target road segment is determined based on at least one of the second type of lighting parameters and at least one of the third type of lighting parameters.

[0009] As an optional implementation, in the first aspect of the present invention, at least one of the first type of lighting parameters includes one or more combinations of the lighting brightness, lighting color, and road reflectivity of the target road segment; At least one of the second type of lighting parameters includes one or more combinations of the illuminance information of the target road segment, the lighting source information used by the target road segment, and the spill light of the target road segment in the corresponding direction; At least one of the third type of lighting parameters includes one or more combinations of the lighting environment ratio of the target road segment and lighting glare.

[0010] As an optional implementation, in the first aspect of the present invention, the method further includes: Based on the target lighting information corresponding to the target road segment, determine the light distribution corresponding to the target road segment; fuse the light distribution corresponding to the target road segment into the three-dimensional spatial distribution corresponding to the target road segment to obtain the three-dimensional spatial light distribution corresponding to the target road segment; display the three-dimensional spatial light distribution corresponding to the target road segment on the visualization interface; And / or, Based on the evaluation model corresponding to the pre-determined evaluation requirements, a matching evaluation operation is performed on the target lighting information corresponding to the target road segment to obtain the evaluation result corresponding to the evaluation requirements; or, after obtaining the evaluation result corresponding to the pre-determined evaluation requirements, it is determined whether the evaluation result meets the evaluation requirements corresponding to the evaluation requirements; if the evaluation result does not meet the evaluation requirements corresponding to the evaluation requirements, a matching control strategy is generated based on the evaluation requirements, the evaluation result, and the current road segment information corresponding to the target road segment. And / or, Based on the target lighting information and the lighting source information corresponding to the target road segment, the energy consumption information and / or carbon emission information of the target road segment are analyzed.

[0011] As an optional implementation, in the first aspect of the present invention, for any target road segment to be monitored, before acquiring a region image obtained by acquiring images of the region of interest of the target road segment by a plurality of predetermined target image acquisition devices; wherein the plurality of target image acquisition devices include fixed image acquisition devices and / or mobile image acquisition devices, the method further includes: Determine the region of interest for the target road segment; Determine whether the comprehensive acquisition range corresponding to the multiple predetermined target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment; When it is determined that the combined acquisition range of the multiple target image acquisition devices meets the acquisition requirements of the region of interest of the target road segment, the multiple target image acquisition devices are controlled to perform image acquisition operations on the region of interest of the target road segment; wherein, the image acquisition operations include static image acquisition operations and / or dynamic image acquisition operations.

[0012] As an optional implementation, in the first aspect of the present invention, determining whether the comprehensive acquisition range corresponding to the predetermined plurality of target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment includes: Based on the acquisition range corresponding to each of the predetermined multiple target image acquisition devices, the comprehensive acquisition range corresponding to the multiple target image acquisition devices is determined; Determine whether the area ratio between the overlapping region and the region of interest is greater than or equal to a first preset threshold; and / or, Determine whether the ratio between the number of key feature points covered by the overlapping region and the total number of key feature points in the region of interest is greater than or equal to a second preset threshold. The overlapping region is the region that overlaps between the comprehensive acquisition range and the region of interest.

[0013] As an optional implementation, in the first aspect of the present invention, the method further includes: For each of the predetermined multiple target image acquisition devices, a matching acquisition parameter calibration operation is performed. The acquisition parameter calibration operation is used to calibrate the target image acquisition device until the target parameters of the image acquired by the target image acquisition device meet the predetermined image acquisition requirements. The step of performing a matching acquisition parameter calibration operation on each of the predetermined plurality of target image acquisition devices includes: The multi-dimensional information corresponding to the target road segment is obtained, and the multi-dimensional information is input into a pre-trained and converged acquisition parameter generation model to obtain the target acquisition parameters output by the acquisition parameter generation model. Based on the target acquisition parameters, a matching acquisition parameter calibration operation is performed on each of the pre-determined multiple target image acquisition devices.

[0014] A second aspect of the present invention discloses a monitoring and control system, the monitoring and control system comprising: The image information acquisition module is used to acquire region images of any target road segment to be monitored, obtained by image acquisition of the region of interest of the target road segment by multiple predetermined target image acquisition devices; the multiple target image acquisition devices include fixed image acquisition devices and / or mobile image acquisition devices; The image processing and analysis module is used to perform image processing and analysis operations on the regional images acquired by multiple target image acquisition devices according to the pre-determined road segment monitoring requirements, so as to obtain the target lighting information corresponding to the target road segment.

[0015] As an optional implementation, in the second aspect of the present invention, the image processing and analysis module performs image processing and analysis operations on the area images acquired by multiple target image acquisition devices according to the predetermined road segment monitoring requirements, and obtains the target lighting information corresponding to the target road segment in the following specific ways: Based on the pre-determined road segment monitoring requirements, image processing and analysis operations are performed on the regional images acquired by multiple target image acquisition devices to obtain at least one type of lighting parameter; Based on the predetermined first processing method and the road segment monitoring requirements, the corresponding first type of lighting parameters are processed to obtain at least one second type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one of the second type of lighting parameters; or, the target lighting information corresponding to the target road segment is determined based on at least one of the first type of lighting parameters and at least one of the second type of lighting parameters.

[0016] As an optional implementation, in a second aspect of the present invention, the image processing and analysis module determines the target lighting information corresponding to the target road segment based on at least one of the second type of lighting parameters in the following specific manner: At least one of the second type of lighting parameters is determined as the target lighting information corresponding to the target road segment; or... According to the predetermined second processing method and the road section monitoring requirements, the corresponding second type of lighting parameters are processed to obtain at least one third type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one of the third type of lighting parameters, or the target lighting information corresponding to the target road segment is determined based on at least one of the second type of lighting parameters and at least one of the third type of lighting parameters.

[0017] As an optional implementation, in a second aspect of the invention, at least one of the first type of lighting parameters includes one or more combinations of the lighting brightness, lighting color, and road reflectivity of the target road segment; At least one of the second type of lighting parameters includes one or more combinations of the illuminance information of the target road segment, the lighting source information used by the target road segment, and the spill light of the target road segment in the corresponding direction; At least one of the third type of lighting parameters includes one or more combinations of the lighting environment ratio of the target road segment and lighting glare.

[0018] As an optional implementation, in a second aspect of the invention, the monitoring and control system further includes an information fusion module and / or an information evaluation module, wherein: The information fusion module is used to determine the light distribution of the target road segment based on the target lighting information corresponding to the target road segment; fuse the light distribution of the target road segment into the three-dimensional spatial distribution of the target road segment to obtain the three-dimensional spatial light distribution of the target road segment; and display the three-dimensional spatial light distribution of the target road segment on the visualization interface. The information evaluation module is used to perform a matching evaluation operation on the target lighting information corresponding to the target road segment based on the evaluation model corresponding to the pre-determined evaluation requirements, and obtain the evaluation result corresponding to the evaluation requirements; or, after obtaining the evaluation result corresponding to the pre-determined evaluation requirements, determine whether the evaluation result meets the evaluation requirements corresponding to the evaluation requirements; if the evaluation result does not meet the evaluation requirements corresponding to the evaluation requirements, generate a matching control strategy based on the evaluation requirements, the evaluation result, and the current road segment information corresponding to the target road segment; and / or analyze the energy consumption information and / or carbon emission information of the target road segment based on the target lighting information and the lighting source information corresponding to the target road segment.

[0019] As an optional implementation, in a second aspect of the invention, the monitoring and control system further includes: The acquisition range determination module is used to determine the region of interest of the target road segment and to determine whether the comprehensive acquisition range corresponding to the multiple pre-determined target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment. An image acquisition control module is used to control multiple target image acquisition devices to perform image acquisition operations on the region of interest of the target road segment when the acquisition range determination module determines that the comprehensive acquisition range corresponding to the multiple target image acquisition devices meets the acquisition requirements of the region of interest of the target road segment; wherein, the image acquisition operation includes static image acquisition operation and / or dynamic image acquisition operation.

[0020] As an optional implementation, in the second aspect of the present invention, the specific method by which the acquisition range determination module determines whether the comprehensive acquisition range corresponding to the predetermined plurality of target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment includes: Based on the acquisition range corresponding to each of the predetermined multiple target image acquisition devices, the comprehensive acquisition range corresponding to the multiple target image acquisition devices is determined; Determine whether the area ratio between the overlapping region and the region of interest is greater than or equal to a first preset threshold; and / or, Determine whether the ratio between the number of key feature points covered by the overlapping region and the total number of key feature points in the region of interest is greater than or equal to a second preset threshold. The overlapping region is the region that overlaps between the comprehensive acquisition range and the region of interest.

[0021] As an optional implementation, in a second aspect of the invention, the monitoring and control system further includes: The acquisition parameter calibration module is used to perform a matching acquisition parameter calibration operation on each of a plurality of predetermined target image acquisition devices. The acquisition parameter calibration operation is used to calibrate the target image acquisition device until the target parameters of the image acquired by the target image acquisition device meet the predetermined image acquisition requirements. The specific method by which the acquisition parameter calibration module performs a matching acquisition parameter calibration operation on each of the predetermined multiple target image acquisition devices includes: The multi-dimensional information corresponding to the target road segment is obtained, and the multi-dimensional information is input into a pre-trained and converged acquisition parameter generation model to obtain the target acquisition parameters output by the acquisition parameter generation model. Based on the target acquisition parameters, a matching acquisition parameter calibration operation is performed on each of the pre-determined multiple target image acquisition devices.

[0022] A third aspect of the present invention discloses a monitoring and control system, the monitoring and control system comprising: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute some or all of the steps in the intelligent monitoring and control method for road lighting according to any of the first aspects of the present invention.

[0023] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute some or all of the steps in the intelligent monitoring and control method for road lighting described in any of the first aspects of the present invention.

[0024] Compared with the prior art, the present invention has the following beneficial effects: In this embodiment of the invention, after determining the road segment to be monitored, regional images of the area of ​​interest of the road segment can be acquired by multiple image acquisition devices. Then, based on the road monitoring requirements, the acquired regional images are intelligently analyzed and processed to obtain the lighting information corresponding to the road segment to be monitored. Compared with the method of personnel using handheld acquisition devices for testing, this intelligent method of analyzing lighting information not only improves the efficiency of acquiring lighting information, but also improves the accuracy, comprehensiveness and reliability of the acquired lighting information, thereby providing a reliable and effective basis for analysis / decision-making for actual analysis needs. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart illustrating an intelligent monitoring and control method for road lighting disclosed in an embodiment of the present invention; Figure 2 This is a flowchart illustrating another intelligent monitoring and control method for road lighting disclosed in an embodiment of the present invention; Figure 3 This is a schematic diagram of the imaging coverage area of ​​an image acquisition device disclosed in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a monitoring and control system disclosed in an embodiment of the present invention; Figure 5 This is a schematic diagram of another monitoring and control system disclosed in an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of another monitoring and control system disclosed in an embodiment of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0029] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0030] This invention discloses an intelligent monitoring and control method and system for road lighting. It can acquire lighting information corresponding to road segments by intelligently analyzing and processing regional images collected from areas of interest along the road. This not only improves the efficiency of lighting information acquisition but also enhances the accuracy, comprehensiveness, and reliability of the acquired information, thereby providing reliable and effective analytical and decision-making basis for actual analytical needs. Detailed descriptions follow.

[0031] Example 1 Please see Figure 1 , Figure 1 This is a flowchart illustrating an intelligent monitoring and control method for road lighting disclosed in an embodiment of the present invention. Figure 1 The described method is at least used to monitor road-related lighting information and is applied in a monitoring and control system. This system can be integrated into a cloud server or a local device, such as a local image acquisition device or a local road lighting management device. Furthermore, the image acquisition device can be a fixed monitoring camera installed on the road section, a mobile monitoring camera mounted on a small drone, or a monitoring camera mounted on a moving rail corresponding to a cable. Moreover, the monitoring camera installed on the road section can be installed within the road lighting fixtures or can be installed independently of the lighting fixtures; this embodiment of the invention does not limit this. Figure 1 As shown, the intelligent monitoring and control method for road lighting may include the following operations: 101. For any target road segment to be monitored, acquire the region image obtained by multiple predetermined target image acquisition devices acquiring images of the region of interest of the target road segment.

[0032] In this embodiment of the invention, the multiple target image acquisition devices include fixed image acquisition devices and / or mobile image acquisition devices. Optionally, the region image may include static images and / or dynamic images.

[0033] In this embodiment of the invention, after determining the target road segment to be monitored, a region of interest (ROI) can be further determined within the target road segment. The ROI of the target road segment can be manually set, intelligently determined based on actual needs, or determined through a combination of manual setting and intelligent determination; this embodiment of the invention does not impose any limitations. Furthermore, when intelligently determining the ROI, in addition to considering actual needs, one or more of the following can be used for auxiliary determination: the road condition attributes corresponding to the target road segment, the lighting fixtures installed on the target road segment, the distribution of roadside buildings on the target road segment, and key reference objects along the target road segment. This helps improve the matching degree between the determined ROI and the actual monitoring needs. Furthermore, the road condition attributes corresponding to the target road segment can include one or more combinations of road curvature, road slope, and road surface smoothness.

[0034] In this embodiment of the invention, optionally, after determining the target road segment to be monitored, it can be further determined whether the target road segment needs to be divided into multiple sub-road segments based on the road state attributes corresponding to the target road segment. If so, the target road segment is first divided into multiple road segments based on the road state attributes corresponding to the target road segment, and then each sub-road segment is monitored separately as a new target road segment. Taking the road state attribute corresponding to the original target road segment as "road curvature" and indicating that the original target road segment has a curve design, the original target road segment can be divided into multiple new target road segments based on the actual curve situation of the original target road segment. This method of dividing road segments improves the convenience, comprehensiveness, and accuracy of image acquisition of the region of interest, and also facilitates the rational setting of image acquisition devices for regional image acquisition and / or the rational use of pre-set image acquisition devices for regional image acquisition, thereby improving the resource utilization rate of image acquisition devices.

[0035] In this embodiment of the invention, after identifying the target road segment and its region of interest (ROI) that are easy to monitor directly, if the target road segment is already covered by image acquisition equipment, the existing image acquisition equipment is prioritized. If the target road segment is not yet covered by image acquisition equipment, or if there are few image acquisition equipment covering it, making it impossible to comprehensively acquire images of the ROI, an image acquisition device can be carried by a drone to acquire images of the ROI of the target road segment. Alternatively, the corresponding image acquisition equipment can be installed based on the ROI and the available locations where it can be installed. Another approach is to combine drone-borne image acquisition equipment with the installation of the equipment. Specifically, at least one of the time cost, manpower cost, and monetary cost of each option can be considered. For example, if the monitoring need for the target road segment is urgent, time cost is prioritized, i.e., choosing the option with the shortest time from implementation to the start of regional image acquisition, such as using a drone-borne image acquisition device to acquire images of the ROI of the target road segment. Further optionally, the available locations for the image acquisition equipment are preferably the installation locations of streetlights to effectively utilize existing installation location resources.

[0036] Furthermore, if the target image acquisition device includes a mobile image acquisition device, the mobile image acquisition device performs mobile image acquisition according to predetermined mobile acquisition parameters. These predetermined mobile acquisition parameters can be manually set, intelligently planned based on actual image acquisition needs, or a combination of both; this embodiment of the invention does not impose any limitations. Further optionally, the mobile acquisition parameters may include at least one of the following: a movement path, actual image acquisition points on the movement path, image acquisition angle at the actual image acquisition point, image acquisition height, and image acquisition frequency; this embodiment of the invention does not impose any limitations.

[0037] Further optionally, for the regional images obtained by the target image acquisition device from the region of interest of the target road segment, the regional images acquired during the time period when there are no vehicles traveling on the target road segment are preferred, or the regional images acquired during the time period when there are fewer vehicles traveling on the target road segment are preferred, so as to reduce the impact of vehicles on the regional image acquisition results, and thus reduce the impact of vehicles on the accuracy of lighting information.

[0038] It is important to note that during actual monitoring, whether using newly installed or existing target image acquisition devices, the image acquisition range of all identified target image acquisition devices must cover the region of interest (ROI) of the target road segment. This ensures the comprehensiveness and accuracy of the acquired images, thereby improving the comprehensiveness and accuracy of lighting information analysis. The image acquisition range of an image acquisition device can also be understood as its imaging coverage area. The imaging coverage area of ​​an image acquisition device can be referenced from [reference needed]. Figure 3 As shown, Figure 3 This is a schematic diagram of the imaging coverage area of ​​an image acquisition device disclosed in an embodiment of the present invention.

[0039] 102. Based on the pre-determined road segment monitoring requirements, perform image processing and analysis operations on the regional images acquired by multiple target image acquisition devices to obtain the target lighting information corresponding to the target road segment.

[0040] In this embodiment of the invention, the road segment monitoring requirement can specifically be a lighting information type collection requirement, a lighting information usage requirement, or a combination of both. Specifically, the lighting information type collection requirement directly clarifies which type of lighting parameter is needed, while the lighting information usage requirement indirectly analyzes which type of lighting parameter is required.

[0041] As can be seen, the embodiments of the present invention can obtain lighting information corresponding to road segments by intelligent image analysis and processing based on regional images collected from the region of interest of a road segment. This not only helps to improve the efficiency of obtaining lighting information, but also helps to improve the accuracy, comprehensiveness and reliability of the obtained lighting information, thereby providing reliable and effective analysis basis / decision basis for actual analysis needs.

[0042] In an optional embodiment, the above-mentioned image processing and analysis operation performed on the area images acquired by multiple target image acquisition devices according to the predetermined road segment monitoring requirements to obtain the target lighting information corresponding to the target road segment may include: Based on the pre-determined road segment monitoring requirements, image processing and analysis operations are performed on the regional images acquired by multiple target image acquisition devices to obtain at least one type of lighting parameter; Based on the predetermined first processing method and the road segment monitoring requirements, the corresponding first type of lighting parameters are processed to obtain at least one second type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one second-class lighting parameter; or, the target lighting information corresponding to the target road segment is determined based on at least one first-class lighting parameter and at least one second-class lighting parameter.

[0043] As can be seen, this optional embodiment can also determine the required lighting information based on the actual road segment monitoring needs, which helps to improve the matching degree between lighting information and actual needs.

[0044] In this optional embodiment, further optionally, the process of determining the target lighting information corresponding to the target road segment based on at least one second type of lighting parameter may include: At least one second-class lighting parameter is determined as the target lighting information corresponding to the target road segment; or... According to the predetermined second processing method and the road section monitoring requirements, the corresponding second type of lighting parameters are processed to obtain at least one third type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one third-class lighting parameter, or the target lighting information corresponding to the target road segment is determined based on at least one second-class lighting parameter and at least one third-class lighting parameter.

[0045] It is evident that this optional embodiment can further expand the methods for determining lighting information, which is beneficial to improving the diversity of lighting information and thus expanding the application scenarios of the road monitoring method described in the embodiments of the present invention.

[0046] In this optional embodiment, at least one type of lighting parameter includes one or more combinations of the target road segment's lighting brightness, lighting color, and road reflectivity. At least one type of second-class lighting parameter includes one or more combinations of illuminance information of the target road segment, lighting source information used on the target road segment, and spill light of the target road segment in the corresponding direction; optionally, the lighting source information may include the color temperature and / or light distribution information of the lighting fixtures used for road lighting. At least one third-class lighting parameter includes one or more combinations of the target road segment's lighting ambient ratio and lighting glare.

[0047] In this optional embodiment, the illumination brightness and color of the target road segment are determined based on image parameters of the region image; the road reflectivity can be determined based on the daytime imaging effect and the feature information corresponding to the reference object, and the specific determination steps are as follows: Step 1: According to the light climate database, the sunlight in various places has a certain stability at the corresponding time. Based on the daytime imaging results of multiple days, the corresponding natural light spectrum data can be obtained by mapping the color information. Step 2: Under the natural light conditions corresponding to Step 1, obtain the colors of certain reference objects (such as crops) along the roadside. Through database comparison and mapping, confirm the species of the reference objects and then obtain their reflectance spectra. Step 3: Based on the reflection characteristic ratio in Step 2, and further combined with the road lighting brightness and color information, calculate the road reflectivity.

[0048] In this optional embodiment, the illuminance information of the target road segment is determined based on the aforementioned illumination luminance and average road reflectivity. Furthermore, since the surface of a typical road is rough and the reflected light conforms to Lambertian characteristics, the illuminance information can be calculated using the following formula: E = (π / ρ) * L; in, E It is illuminance information. π Take 3.1415926, ρ The average reflectivity of the road. L This refers to the brightness of road lighting.

[0049] In this optional embodiment, the color temperature of the lighting fixture is obtained from the aforementioned color information, the light distribution information of the lighting fixture is obtained by energy mapping of the light pattern distribution of the road surface, and the spill light of the aforementioned target road segment in the corresponding direction is obtained from the light energy distribution ratio of the road lighting in the corresponding direction.

[0050] As can be seen, this optional embodiment improves the diversity and comprehensiveness of the analyzed lighting parameters, thereby providing a reliable and comprehensive analytical basis for practical applications.

[0051] In another alternative embodiment, the method may further include the following operations: Based on the target lighting information corresponding to the target road segment, determine the light distribution of the target road segment; integrate the light distribution of the target road segment into the three-dimensional spatial distribution of the target road segment to obtain the three-dimensional spatial light distribution of the target road segment; display the three-dimensional spatial light distribution of the target road segment on the visualization interface.

[0052] Optionally, when displaying the three-dimensional spatial light distribution on the visualization interface, the specific visualization form can be a two-dimensional / three-dimensional pseudo-color map visualization form, or an image combined with other representations visualization form, or a visualization form represented by text. This embodiment of the invention does not limit this.

[0053] In this optional embodiment, the three-dimensional spatial distribution corresponding to the target road segment is constructed in conjunction with a GIS system, which includes the road conditions, building conditions, street light conditions, etc. of the target road segment. The spatial light distribution obtained based on the above target lighting information is mapped to the three-dimensional spatial distribution corresponding to the target road segment and displayed visually. This visualization method helps relevant personnel to understand the light distribution of the target road segment more intuitively.

[0054] Example 2 Please see Figure 2 , Figure 2 This is a flowchart illustrating another intelligent monitoring and control method for road lighting disclosed in an embodiment of the present invention. Wherein, Figure 2 The described method is at least used to monitor road-related lighting information and is applied in a monitoring and control system. This system can be integrated into a cloud server or a local device, such as a local image acquisition device or a local road lighting management device. Furthermore, the image acquisition device can be a fixed monitoring camera installed on the road section, a mobile monitoring camera mounted on a small drone, or a monitoring camera mounted on a moving rail corresponding to a cable. Moreover, the monitoring camera installed on the road section can be installed within the road lighting fixtures or can be installed independently of the lighting fixtures; this embodiment of the invention does not limit this. Figure 2 As shown, the intelligent monitoring and control method for road lighting may include the following operations: 201. For any target road segment to be monitored, determine the region of interest of the target road segment and multiple target image acquisition devices for acquiring regional images of the region of interest of the target road segment.

[0055] 202. Determine whether the combined acquisition range of the above multiple target image acquisition devices meets the acquisition requirements of the region of interest of the target road segment.

[0056] In this embodiment of the invention, when the judgment result of step 202 is yes, step 203 can be triggered; when the judgment result of step 202 is no, the above-mentioned operation of determining multiple target image acquisition devices for regional image acquisition of the target road segment's region of interest can be re-executed, and / or, the image acquisition parameters of the determined target image acquisition devices can be adjusted, such as adjusting the acquisition angle and / or adjusting the acquisition range, and / or, the region of interest can be divided into multiple new regions of interest. It should be noted that when the judgment result of step 202 is negative, when selecting a subsequent adjustment plan, the influence factors of the above-mentioned multiple target image acquisition devices not meeting the acquisition requirements corresponding to the region of interest of the target road segment can be determined first. Then, a targeted adjustment plan can be selected based on the influence factors. For example, if there are no image acquisition devices, new image acquisition devices can be added, or the mobile acquisition parameters of the mobile acquisition devices can be replanned, or the region of interest can be divided into multiple new regions of interest for batch acquisition. Furthermore, when there are multiple adjustment plans to solve the influence factors, a comprehensive selection can be made based on the adjustment cost corresponding to each adjustment plan and the urgency of the road monitoring needs.

[0057] 203. When it is determined that the comprehensive acquisition range of the above-mentioned multiple target image acquisition devices meets the acquisition requirements of the region of interest of the target road segment, perform a matching acquisition parameter calibration operation on each of the above-mentioned multiple target image acquisition devices.

[0058] In this embodiment of the invention, the acquisition parameter calibration operation is used to calibrate the target image acquisition device until the target parameters of the image acquired by the target image acquisition device meet the predetermined image acquisition requirements. Optionally, the target parameter of the acquired image can be the brightness of the image, and meeting the predetermined image acquisition requirements can mean that the brightness of the image is as close as possible to the true brightness. As an optional implementation, the above-mentioned execution of a matching acquisition parameter calibration operation on each of the plurality of target image acquisition devices may include: The invention acquires multi-dimensional information corresponding to the target road segment and inputs this information into a pre-trained and converged acquisition parameter generation model to obtain the target acquisition parameters output by the model. Based on these target acquisition parameters, a matching acquisition parameter calibration operation is performed on each of a pre-determined plurality of target image acquisition devices. Therefore, this embodiment of the invention can calibrate the acquisition parameters of image acquisition devices by combining multi-dimensional information corresponding to the target road segment with target acquisition parameters generated by the acquisition parameter generation model. This not only improves the calibration efficiency but also enhances the reliability of the calibration, thereby improving the reliability of the acquired regional images.

[0059] The multi-dimensional information corresponding to the target road segment may include, but is not limited to, one or more of the following: road segment dimensions (e.g., length and width), the distribution of buildings alongside the road segment, the distribution information of lighting fixtures along the road segment (including fixture location, fixture height, and positional relationships between adjacent fixtures), the distribution information of the aforementioned multiple target image acquisition devices, and the models of the aforementioned multiple target image acquisition devices. Furthermore, the acquisition parameter generation model is trained on an initial acquisition parameter generation model based on the multi-dimensional information of several sample road segments and the measured lighting information of several sample road segments.

[0060] It should be noted that when calibrating the acquisition parameters of the target image acquisition device, relevant personnel can also manually calibrate the acquisition parameters of the target image acquisition device based on their experience.

[0061] 204. Control multiple target image acquisition devices to perform image acquisition operations on the region of interest of the target road segment.

[0062] 205. Obtain the region image obtained by the above multiple target image acquisition devices from the region of interest of the target road segment.

[0063] 206. Based on the pre-determined road segment monitoring requirements, perform image processing and analysis operations on the regional images acquired by multiple target image acquisition devices to obtain the target lighting information corresponding to the target road segment.

[0064] It should be noted that the judgment operation involved in step 202 and the calibration operation involved in step 203 may not have a practically restrictive relationship. They can be executed simultaneously, or step 202 can be executed first and step 203 can be executed only if the judgment result of step 202 is yes. This embodiment of the invention does not impose any limitations, as long as it is ensured that the acquisition parameters of the target image acquisition device are calibrated before executing step 204 and that the comprehensive acquisition range of multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment.

[0065] As can be seen, the embodiments of the present invention can obtain lighting information corresponding to road segments by intelligent image analysis and processing based on regional images collected from the region of interest of a road segment. This not only improves the efficiency of lighting information acquisition but also enhances the accuracy, comprehensiveness, and reliability of the acquired lighting information, thereby providing a reliable and effective basis for analysis and decision-making for actual analysis needs. Furthermore, after determining the region of interest and the image acquisition device used for regional image acquisition for the road segment to be monitored, it is possible to further determine whether the acquisition range of the image acquisition device meets the acquisition requirements of the region of interest. If it does, the acquisition parameters of the image acquisition device can be calibrated, which improves the acquisition efficiency, acquisition effect, and acquisition comprehensiveness of the regional images. This, in turn, improves the efficiency, comprehensiveness, and accuracy of the lighting information analyzed based on the regional images, and can also reduce unnecessary acquisition parameter calibration operations to a certain extent.

[0066] In an optional embodiment, the determination of whether the comprehensive acquisition range corresponding to the predetermined multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment may include: Based on the acquisition range corresponding to each of the multiple target image acquisition devices that have been predetermined, the comprehensive acquisition range corresponding to the multiple target image acquisition devices is determined. Determine whether the area ratio between the overlapping region and the region of interest is greater than or equal to a first preset threshold; and / or, Determine whether the ratio between the number of key feature points covered by the overlapping region and the total number of key feature points in the region of interest is greater than or equal to a second preset threshold. The overlapping area refers to the area that overlaps between the comprehensive collection range and the region of interest.

[0067] In this optional embodiment, if the comprehensive collection range is determined to meet the collection requirements corresponding to the region of interest of the target road segment based on the area ratio, then when the area ratio is greater than or equal to a first preset threshold, it is determined that the comprehensive collection range meets the collection requirements corresponding to the region of interest of the target road segment; if the comprehensive collection range is determined to meet the collection requirements corresponding to the region of interest of the target road segment based on the quantity ratio, then when the quantity ratio is greater than or equal to a second preset threshold, it is determined that the comprehensive collection range meets the collection requirements corresponding to the region of interest of the target road segment; if the comprehensive collection range is determined to meet the collection requirements corresponding to the region of interest of the target road segment based on both the area ratio and the quantity ratio, then when the area ratio is greater than or equal to the first preset threshold and the quantity ratio is greater than or equal to the second preset threshold, it is determined that the comprehensive collection range meets the collection requirements corresponding to the region of interest of the target road segment.

[0068] As can be seen, this optional embodiment provides a variety of judgment methods for determining whether the comprehensive acquisition range corresponding to multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment. This not only helps to expand the application scenarios of road monitoring methods, but also helps to improve the reliability and accuracy of the judgment on whether the comprehensive acquisition range corresponding to multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment, thereby helping to improve the acquisition reliability and acquisition efficiency of regional images.

[0069] In another alternative embodiment, the method may further include the following operations: Based on the pre-determined evaluation model corresponding to the evaluation requirements, a matching evaluation operation is performed on the target lighting information corresponding to the target road segment to obtain the evaluation result corresponding to the evaluation requirements; or, after obtaining the evaluation result corresponding to the pre-determined evaluation requirements, it is determined whether the evaluation result meets the evaluation requirements corresponding to the evaluation requirements; if the evaluation result does not meet the evaluation requirements corresponding to the evaluation requirements, a matching control strategy is generated based on the evaluation requirements, the evaluation result, and the current road segment information corresponding to the target road segment; and / or, Based on the target lighting information and the corresponding lighting source information for the target road segment, analyze the energy consumption and / or carbon emission information of the target road segment. Furthermore, the energy consumption information of the target road segment can be obtained through the following steps: Step 1: Obtain the relationship between luminous flux and power (energy consumption) of a single light source; Step 2: Obtain the brightness information of the effective area of ​​the road surface illuminated by a single light source, then obtain the illuminance information from the road reflectivity, and finally obtain the corresponding luminous flux based on the area of ​​the effective area of ​​the illuminated road. Step 3: Map the corresponding luminous flux with the power (energy consumption) of the light source, establish a lookup table or function, and obtain the real-time energy consumption distribution based on the constructed mapping relationship.

[0070] In this optional embodiment, different evaluation requirements correspond to different evaluation models, and different evaluation requirements correspond to different evaluation criteria. Optionally, the evaluation requirements include one or more of the following: road lighting efficiency evaluation requirements, road lighting power consumption evaluation requirements, carbon emission evaluation requirements, brightness evaluation requirements, contrast evaluation requirements, visibility evaluation requirements, spill light evaluation requirements, and human circadian rhythm health evaluation requirements.

[0071] For example, taking a drone equipped with image acquisition equipment for regional image acquisition, the drone obtains road lighting distribution A below the streetlights and road lighting distribution B above the streetlights. Since road reflected light follows a Lambertian distribution, the corresponding brightness and other light parameter distributions at each angle can be directly calculated. By removing the influence of road lighting distribution A from road lighting distribution B, spillover light at each angle can be obtained, along with the overall impact on skylight. Furthermore, based on the light distribution, an energy-light mapping model can be established to obtain road network lighting energy consumption results. Based on these results, an energy consumption and carbon emission mapping database can be constructed to obtain carbon emission data. Finally, based on this database, coefficients can be adjusted for energy consumption and costs in different areas.

[0072] As can be seen, this optional embodiment can also apply the determined lighting information to different evaluation needs, providing a reliable and effective evaluation basis for different evaluation needs. Furthermore, it can also generate matching control strategies based on the evaluation results to achieve closed-loop control.

[0073] It should be noted that other relevant descriptions of the intelligent monitoring and control method for road lighting involved in Embodiment 2 can be found in the relevant descriptions of Embodiment 1, and will not be repeated in detail in Embodiment 2.

[0074] Example 3 This invention discloses yet another intelligent monitoring and control method for road lighting. This method is at least used to monitor road-related lighting information and is applied in a monitoring and control system. This system can be integrated into a cloud server or a local device, such as a local image acquisition device or a local road lighting management device. Furthermore, the image acquisition device can be a fixed monitoring camera installed on the road section, a mobile monitoring camera mounted on a small drone, or a monitoring camera mounted on a moving rail corresponding to a cable. Moreover, the monitoring camera installed on the road section can be installed within the road lighting fixtures or can be installed independently of the lighting fixtures; this invention does not limit the specific installation. The intelligent monitoring and control method for road lighting may include the following operations: For any target road segment to be monitored, determine the region of interest of the target road segment and multiple target image acquisition devices for acquiring regional images of the region of interest of the target road segment; Perform a matching acquisition parameter calibration operation on each of the above multiple target image acquisition devices; After completing the acquisition parameter calibration operation, determine whether the comprehensive acquisition range of the above multiple target image acquisition devices meets the acquisition requirements of the region of interest of the target road segment; When it is determined that the combined acquisition range of multiple target image acquisition devices meets the acquisition requirements of the region of interest of the target road segment, the multiple target image acquisition devices are controlled to perform image acquisition operations on the region of interest of the target road segment. The region image is obtained by acquiring images of the region of interest of the target road segment by the above-mentioned multiple target image acquisition devices; Based on the pre-determined road segment monitoring requirements, image processing and analysis operations are performed on the regional images acquired by multiple target image acquisition devices to obtain the target lighting information corresponding to the target road segment.

[0075] As can be seen, the embodiments of the present invention can obtain lighting information corresponding to road segments by intelligent image analysis and processing based on regional images collected from the region of interest of a road segment. This not only improves the efficiency of lighting information acquisition but also enhances the accuracy, comprehensiveness, and reliability of the acquired lighting information, thereby providing a reliable and effective basis for analysis and decision-making for actual analysis needs. Furthermore, after determining the region of interest and the image acquisition device used for regional image acquisition for the road segment to be monitored, the acquisition parameters of the image acquisition device can be calibrated. After calibration, it can be further determined whether the acquisition range of the image acquisition device meets the acquisition requirements of the region of interest. If it does, then regional images are acquired, which improves the acquisition efficiency, acquisition effect, and acquisition comprehensiveness of regional images. This, in turn, improves the efficiency, comprehensiveness, and accuracy of lighting information analyzed based on regional images, and can also reduce unnecessary acquisition range judgment operations to a certain extent.

[0076] It should be noted that other relevant descriptions of the intelligent monitoring and control method for road lighting involved in Embodiment 3 can be found in the relevant descriptions of Embodiments 1 and 2, and will not be repeated in detail in Embodiment 3.

[0077] Example 4 Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a monitoring and control system disclosed in an embodiment of the present invention. Figure 4The monitoring and control system shown is at least used to monitor road-related lighting information. This system can be integrated into a cloud server or a local device, such as a local image acquisition device or a local road lighting control device. Furthermore, the image acquisition device can be a fixed monitoring camera installed on the road section, a mobile monitoring camera mounted on a small drone, or a monitoring camera mounted on a moving rail corresponding to a cable. Moreover, the monitoring camera installed on the road section can be installed within the road lighting fixtures or can be installed independently of the lighting fixtures; this embodiment of the invention does not limit this. Figure 4 As shown, the monitoring and control system may include: The image information acquisition module 401 is used to acquire regional images of any target road segment to be monitored, obtained by multiple predetermined target image acquisition devices acquiring images of the region of interest of the target road segment; wherein, the multiple target image acquisition devices include fixed image acquisition devices and / or mobile image acquisition devices; The image processing and analysis module 402 is used to perform image processing and analysis operations on the regional images acquired by multiple target image acquisition devices according to the pre-determined road segment monitoring requirements, so as to obtain the target lighting information corresponding to the target road segment.

[0078] As can be seen, the embodiments of the present invention can obtain lighting information corresponding to road segments by intelligent image analysis and processing based on regional images collected from the region of interest of a road segment. This not only helps to improve the efficiency of obtaining lighting information, but also helps to improve the accuracy, comprehensiveness and reliability of the obtained lighting information, thereby providing reliable and effective analysis basis / decision basis for actual analysis needs.

[0079] In an optional embodiment, the image processing and analysis module 402 performs image processing and analysis operations on the area images acquired by multiple target image acquisition devices according to the predetermined road segment monitoring requirements, and obtains the target lighting information corresponding to the target road segment in the following specific ways: Based on the pre-determined road segment monitoring requirements, image processing and analysis operations are performed on the regional images acquired by multiple target image acquisition devices to obtain at least one type of lighting parameter; Based on the predetermined first processing method and the road segment monitoring requirements, the corresponding first type of lighting parameters are processed to obtain at least one second type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one second-class lighting parameter; or, the target lighting information corresponding to the target road segment is determined based on at least one first-class lighting parameter and at least one second-class lighting parameter.

[0080] In this optional embodiment, the image processing and analysis module 402 determines the target lighting information corresponding to the target road segment based on at least one second type of lighting parameter in the following specific ways: At least one second-class lighting parameter is determined as the target lighting information corresponding to the target road segment; or... According to the predetermined second processing method and the road section monitoring requirements, the corresponding second type of lighting parameters are processed to obtain at least one third type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one third-class lighting parameter, or the target lighting information corresponding to the target road segment is determined based on at least one second-class lighting parameter and at least one third-class lighting parameter.

[0081] In this optional embodiment, at least one type of lighting parameter includes one or more combinations of the target road segment's lighting brightness, lighting color, and road reflectivity.

[0082] Further optionally, at least one type of second-class lighting parameter includes one or more combinations of illuminance information of the target road segment, lighting source information used in the target road segment, and spill light of the target road segment in the corresponding direction; optionally, the lighting source information may include the color temperature and / or light distribution information of the lighting fixtures used in the road lighting. Further optionally, at least one third type of lighting parameter includes one or more combinations of the lighting ambient ratio of the target road segment and lighting glare.

[0083] As can be seen, this optional embodiment can also determine the required lighting information based on the actual road segment monitoring needs, which is beneficial to improving the matching degree between lighting information and actual needs. Furthermore, it can further expand the methods for determining lighting information, which is beneficial to improving the diversity of lighting information. This, in turn, is beneficial to expanding the application scenarios of the road monitoring method described in the embodiments of the present invention. Moreover, it improves the diversity and comprehensiveness of the analyzed lighting parameters, thereby providing a reliable and comprehensive analytical basis for practical applications.

[0084] In another alternative embodiment, such as Figure 5 As shown, the monitoring and control system also includes an information fusion module 403 and / or an information evaluation module 404, wherein: The information fusion module 403 is used to determine the light distribution of the target road segment based on the target lighting information corresponding to the target road segment; to fuse the light distribution of the target road segment into the three-dimensional spatial distribution of the target road segment to obtain the three-dimensional spatial light distribution of the target road segment; and to display the three-dimensional spatial light distribution of the target road segment on the visualization interface. Optionally, when displaying the three-dimensional spatial light distribution on the visualization interface, the specific visualization form can be a two-dimensional / three-dimensional pseudo-color map visualization form, or an image combined with other representations visualization form, or a visualization form represented by text. This embodiment of the invention does not limit this.

[0085] The information assessment module 404 is used to perform a matching assessment operation on the target lighting information corresponding to the target road segment based on the assessment model corresponding to the pre-determined assessment requirements, and obtain the assessment result corresponding to the assessment requirements; or, after obtaining the assessment result corresponding to the pre-determined assessment requirements, it determines whether the assessment result meets the assessment requirements corresponding to the assessment requirements; if the assessment result does not meet the assessment requirements corresponding to the assessment requirements, it generates a matching control strategy based on the assessment requirements, the assessment result, and the current road segment information corresponding to the target road segment; and / or, based on the target lighting information and the lighting source information corresponding to the target road segment, it analyzes the energy consumption information and / or carbon emission information of the target road segment. Further, the energy consumption information of the target road segment can be obtained through the following steps: Step 1: Obtain the relationship between luminous flux and power (energy consumption) of a single light source; Step 2: Obtain the brightness information of the effective area of ​​the road surface illuminated by a single light source, then obtain the illuminance information from the road reflectivity, and finally obtain the corresponding luminous flux based on the area of ​​the effective area of ​​the illuminated road. Step 3: Map the corresponding luminous flux with the power (energy consumption) of the light source, establish a lookup table or function, and obtain the real-time energy consumption distribution based on the constructed mapping relationship.

[0086] As can be seen, this optional embodiment, through visualization, helps relevant personnel to more intuitively understand the light distribution of the target road segment. Furthermore, it can apply the determined lighting information to different evaluation needs, providing a reliable and effective evaluation basis for different evaluation needs. Moreover, it can generate matching control strategies based on the evaluation results to achieve closed-loop control.

[0087] In yet another alternative embodiment, such as Figure 5 As shown, the monitoring and control system also includes: The acquisition range determination module 405 is used to determine the region of interest of the target road segment and to determine whether the comprehensive acquisition range corresponding to the above multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment. The image acquisition control module 406 is used to perform a matching acquisition parameter calibration operation on each of the multiple target image acquisition devices when the acquisition range determination module 405 determines that the comprehensive acquisition range corresponding to the multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment.

[0088] As can be seen, after identifying the region of interest and the image acquisition device for acquiring regional images for the road segment to be monitored, this optional embodiment can further determine whether the acquisition range of the image acquisition device meets the acquisition requirements of the region of interest. This is beneficial to improving the acquisition efficiency, acquisition effect, and acquisition comprehensiveness of regional images, and thus to improving the efficiency, comprehensiveness, and accuracy of lighting information analyzed based on regional images.

[0089] In this optional embodiment, the specific method by which the acquisition range determination module 405 determines whether the comprehensive acquisition range corresponding to the above-mentioned multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment includes: Based on the acquisition range corresponding to each of the multiple target image acquisition devices that have been predetermined, the comprehensive acquisition range corresponding to the multiple target image acquisition devices is determined. Determine whether the area ratio between the overlapping region and the region of interest is greater than or equal to a first preset threshold; and / or, Determine whether the ratio between the number of key feature points covered by the overlapping region and the total number of key feature points in the region of interest is greater than or equal to a second preset threshold. The overlapping area refers to the area that overlaps between the comprehensive collection range and the region of interest.

[0090] In this optional embodiment, if the comprehensive collection range is determined to meet the collection requirements corresponding to the region of interest of the target road segment based on the area ratio, then when the area ratio is greater than or equal to a first preset threshold, it is determined that the comprehensive collection range meets the collection requirements corresponding to the region of interest of the target road segment; if the comprehensive collection range is determined to meet the collection requirements corresponding to the region of interest of the target road segment based on the quantity ratio, then when the quantity ratio is greater than or equal to a second preset threshold, it is determined that the comprehensive collection range meets the collection requirements corresponding to the region of interest of the target road segment; if the comprehensive collection range is determined to meet the collection requirements corresponding to the region of interest of the target road segment based on both the area ratio and the quantity ratio, then when the area ratio is greater than or equal to the first preset threshold and the quantity ratio is greater than or equal to the second preset threshold, it is determined that the comprehensive collection range meets the collection requirements corresponding to the region of interest of the target road segment.

[0091] As can be seen, this optional embodiment provides a variety of judgment methods for determining whether the comprehensive acquisition range corresponding to multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment. This not only helps to expand the application scenarios of road monitoring methods, but also helps to improve the reliability and accuracy of the judgment on whether the comprehensive acquisition range corresponding to multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment, thereby helping to improve the acquisition reliability and acquisition efficiency of regional images.

[0092] In yet another alternative embodiment, such as Figure 5 As shown, the monitoring and control system also includes: The acquisition parameter calibration module 407 is used to perform a matching acquisition parameter calibration operation on each of the above-mentioned multiple target image acquisition devices.

[0093] In this embodiment of the invention, the acquisition parameter calibration operation is used to calibrate the target image acquisition device until the target parameters of the image acquired by the target image acquisition device meet the predetermined image acquisition requirements. Optionally, the target parameter of the acquired image can be the brightness of the image, and meeting the predetermined image acquisition requirements can mean that the brightness of the image is as close as possible to the true brightness.

[0094] In this optional embodiment, the specific manner in which the acquisition parameter calibration module 407 performs a matching acquisition parameter calibration operation on each of the plurality of target image acquisition devices may include: The system acquires multi-dimensional information corresponding to the target road segment and inputs the multi-dimensional information into a pre-trained and converged acquisition parameter generation model to obtain the target acquisition parameters output by the acquisition parameter generation model. Based on the target acquisition parameters, the system performs matching acquisition parameter calibration operations on each of the pre-determined multiple target image acquisition devices.

[0095] It should be noted that when calibrating the acquisition parameters of the target image acquisition device, relevant personnel can also manually calibrate the acquisition parameters of the target image acquisition device based on their experience.

[0096] As can be seen, this optional embodiment can also calibrate the acquisition parameters of the image acquisition device by using multi-dimensional information corresponding to the target road segment and further combining the target acquisition parameters generated by the acquisition parameter generation model. This not only helps to improve the calibration efficiency of the acquisition parameters, but also helps to improve the calibration reliability of the acquisition parameters, thereby helping to improve the reliability of the acquired regional images.

[0097] It should be noted that the monitoring and control system described in Embodiment 4 is specifically used to implement any of the intelligent monitoring and control methods for road lighting described in Embodiments 1, 2 and 3. For other related descriptions of the monitoring and control system in Embodiment 3, please refer to the relevant descriptions in Embodiments 1, 2 and 3. This Embodiment 4 will not repeat them.

[0098] Example 5 Please see Figure 6 , Figure 6 This is a schematic diagram of another monitoring and control system disclosed in an embodiment of the present invention. Figure 6 The monitoring and control system shown is at least used to monitor road-related lighting information. This system can be integrated into a cloud server or a local device, such as a local image acquisition device or a local road lighting control device. Furthermore, the image acquisition device can be a fixed monitoring camera installed on the road section, a mobile monitoring camera mounted on a small drone, or a monitoring camera mounted on a moving rail corresponding to a cable. Moreover, the monitoring camera installed on the road section can be installed within the road lighting fixtures or can be installed independently of the lighting fixtures; this embodiment of the invention does not limit this. Figure 6 As shown, the monitoring and control system may include: Memory 501 storing executable program code; Processor 502 coupled to memory; The processor 502 calls the executable program code stored in the memory 501 to execute some or all of the steps in the intelligent monitoring and control method for road lighting described in any of the embodiments one to three of the present invention.

[0099] Example 6 This invention discloses a computer storage medium storing computer instructions. When these computer instructions are invoked, they are used to execute some or all of the steps in the intelligent monitoring and control method for road lighting described in any of Embodiments 1 to 3 of this invention.

[0100] Example 7 This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps in the intelligent monitoring and control method for road lighting described in any of the embodiments 1 to 3 of this invention.

[0101] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0102] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0103] Finally, it should be noted that the intelligent monitoring and control method and monitoring and control system for road lighting disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent monitoring and control method for road lighting, characterized in that, The method includes: For any target road segment to be monitored, acquire region images obtained by acquiring images of the region of interest of the target road segment by multiple predetermined target image acquisition devices; the multiple target image acquisition devices include fixed image acquisition devices and / or mobile image acquisition devices; Based on the pre-determined road segment monitoring requirements, image processing and analysis operations are performed on the regional images acquired by multiple target image acquisition devices to obtain the target lighting information corresponding to the target road segment.

2. The intelligent monitoring and control method for road lighting according to claim 1, characterized in that, The process of performing image processing and analysis on area images acquired by multiple target image acquisition devices based on predetermined road segment monitoring requirements to obtain target lighting information corresponding to the target road segment includes: Based on the pre-determined road segment monitoring requirements, image processing and analysis operations are performed on the regional images acquired by multiple target image acquisition devices to obtain at least one type of lighting parameter; Based on the predetermined first processing method and the road segment monitoring requirements, the corresponding first type of lighting parameters are processed to obtain at least one second type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one of the second type of lighting parameters; or, the target lighting information corresponding to the target road segment is determined based on at least one of the first type of lighting parameters and at least one of the second type of lighting parameters.

3. The intelligent monitoring and control method for road lighting according to claim 2, characterized in that, The step of determining the target lighting information corresponding to the target road segment based on at least one of the second type of lighting parameters includes: At least one of the second type of lighting parameters is determined as the target lighting information corresponding to the target road segment; or... According to the predetermined second processing method and the road section monitoring requirements, the corresponding second type of lighting parameters are processed to obtain at least one third type of lighting parameter; The target lighting information corresponding to the target road segment is determined based on at least one of the third type of lighting parameters, or the target lighting information corresponding to the target road segment is determined based on at least one of the second type of lighting parameters and at least one of the third type of lighting parameters.

4. The intelligent monitoring and control method for road lighting according to claim 3, characterized in that, At least one of the first type of lighting parameters includes one or more combinations of lighting brightness, lighting color, and road reflectivity of the target road segment; At least one of the second type of lighting parameters includes one or more combinations of the illuminance information of the target road segment, the lighting source information used by the target road segment, and the spill light of the target road segment in the corresponding direction; At least one of the third type of lighting parameters includes one or more combinations of the lighting environment ratio of the target road segment and lighting glare.

5. The intelligent monitoring and control method for road lighting according to any one of claims 1-4, characterized in that, The method further includes: Based on the target lighting information corresponding to the target road segment, determine the light distribution corresponding to the target road segment; fuse the light distribution corresponding to the target road segment into the three-dimensional spatial distribution corresponding to the target road segment to obtain the three-dimensional spatial light distribution corresponding to the target road segment; display the three-dimensional spatial light distribution corresponding to the target road segment on the visualization interface; And / or, Based on the evaluation model corresponding to the pre-determined evaluation requirements, a matching evaluation operation is performed on the target lighting information corresponding to the target road segment to obtain the evaluation result corresponding to the evaluation requirements; or, after obtaining the evaluation result corresponding to the pre-determined evaluation requirements, it is determined whether the evaluation result meets the evaluation requirements corresponding to the evaluation requirements; if the evaluation result does not meet the evaluation requirements corresponding to the evaluation requirements, a matching control strategy is generated based on the evaluation requirements, the evaluation result, and the current road segment information corresponding to the target road segment. And / or, Based on the target lighting information and the lighting source information corresponding to the target road segment, the energy consumption information and / or carbon emission information of the target road segment are analyzed.

6. The intelligent monitoring and control method for road lighting according to any one of claims 1-4, characterized in that, For any target road segment to be monitored, the region image is obtained by acquiring images of the region of interest of the target road segment from multiple predetermined target image acquisition devices; Before the plurality of target image acquisition devices include fixed image acquisition devices and / or mobile image acquisition devices, the method further includes: Determine the region of interest for the target road segment; Determine whether the comprehensive acquisition range corresponding to the multiple predetermined target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment; When it is determined that the combined acquisition range of the multiple target image acquisition devices meets the acquisition requirements of the region of interest of the target road segment, the multiple target image acquisition devices are controlled to perform image acquisition operations on the region of interest of the target road segment; wherein, the image acquisition operations include static image acquisition operations and / or dynamic image acquisition operations.

7. The intelligent monitoring and control method for road lighting according to claim 6, characterized in that, The determination of whether the comprehensive acquisition range corresponding to the pre-determined multiple target image acquisition devices meets the acquisition requirements corresponding to the region of interest of the target road segment includes: Based on the acquisition range corresponding to each of the predetermined multiple target image acquisition devices, the comprehensive acquisition range corresponding to the multiple target image acquisition devices is determined; Determine whether the area ratio between the overlapping region and the region of interest is greater than or equal to a first preset threshold; and / or, Determine whether the ratio between the number of key feature points covered by the overlapping region and the total number of key feature points in the region of interest is greater than or equal to a second preset threshold. The overlapping region is the region that overlaps between the comprehensive acquisition range and the region of interest.

8. The intelligent monitoring and control method for road lighting according to any one of claims 1, 2, 3, 4, and 7, characterized in that, The method further includes: For each of the predetermined multiple target image acquisition devices, a matching acquisition parameter calibration operation is performed. The acquisition parameter calibration operation is used to calibrate the target image acquisition device until the target parameters of the image acquired by the target image acquisition device meet the predetermined image acquisition requirements. The step of performing a matching acquisition parameter calibration operation on each of the predetermined plurality of target image acquisition devices includes: The multi-dimensional information corresponding to the target road segment is obtained, and the multi-dimensional information is input into a pre-trained and converged acquisition parameter generation model to obtain the target acquisition parameters output by the acquisition parameter generation model. Based on the target acquisition parameters, a matching acquisition parameter calibration operation is performed on each of the pre-determined multiple target image acquisition devices.

9. A monitoring and control system, characterized in that, The monitoring and control system includes: The image information acquisition module is used to acquire region images of any target road segment to be monitored, obtained by image acquisition of the region of interest of the target road segment by multiple predetermined target image acquisition devices; the multiple target image acquisition devices include fixed image acquisition devices and / or mobile image acquisition devices; The image processing and analysis module is used to perform image processing and analysis operations on the regional images acquired by multiple target image acquisition devices according to the pre-determined road segment monitoring requirements, so as to obtain the target lighting information corresponding to the target road segment.

10. A monitoring and control system, characterized in that, The monitoring and control system includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the intelligent monitoring and control method for road lighting as described in any one of claims 1-8.

11. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the intelligent monitoring and control method for road lighting as described in any one of claims 1-8.

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