A governance event monitoring method based on smart city

Abstract

The present invention discloses a method for monitoring governance events based on smart cities, which specifically relates to the field of urban governance event monitoring, including: using diversified dynamic monitoring equipment to count the distribution of mobile catering, calculate the aggregation density and adjust the monitoring frequency; integrating optical detection elements and GPS positioning devices, synchronously controlling the light source cycle and sensor acquisition time, collecting images based on the density changes in the monitoring area, and identifying the distribution of planar liquids in the image, marking them as suspected locations of illegal discharge. By adjusting the position of the monitoring equipment to ensure that the reflected light path covers the suspicious location, and calculating the propagation direction of the reflected light path, the receiving point is moved until interference fringes are monitored; after collecting the interference image, the hue value change is analyzed to determine whether there is a rainbow interference effect; if it is confirmed that there is an interference effect, the dimensionless thickness of the oil film is further estimated and the location of the illegal discharge is marked and uploaded.

Description

Technical Field

[0001] The present invention relates to the technical field of urban governance event monitoring, and more specifically, to a governance event monitoring method based on a smart city. Background Art

[0002] In the management of smart cities, with the rapid development of the mobile catering industry, how to effectively monitor and manage the illegal discharge of mobile catering in public areas has become a problem that needs to be solved urgently. Most of the existing monitoring methods rely on manual inspections or traditional video monitoring, which have shortcomings such as limited coverage, low monitoring accuracy, and slow response speed, making it difficult to achieve real-time and accurate monitoring of illegal discharge behaviors of mobile catering.

[0003] Therefore, how to introduce real-time detection technology based on optical interference effect, combined with dynamic monitoring equipment (such as drones, patrol cars, etc.) and precise GPS positioning system, to realize an intelligent urban governance method that monitors the dimensionless thickness of the oil film in the discharged wastewater in the mobile catering gathering area, determines whether there is any illegal discharge behavior in the area, and conducts intelligent and comprehensive monitoring of the mobile catering area, is an urgent problem to be solved.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a governance event monitoring method based on a smart city to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: S1: Divide the monitoring period and monitoring area, use diversified dynamic monitoring equipment to conduct distribution statistics on the number of catering individuals, and calculate the mobile catering aggregation density in each monitoring area; S2: Integrate the optical detection element with the GPS positioning device and implant it into the diversified dynamic monitoring equipment, and synchronize the periodic switching of the light source with the acquisition time of the sensor; S3: Deploy an open source model for plane liquid recognition. According to the density changes of the time-series dynamic aggregation density list of mobile catering in different monitoring areas, dynamically set the image acquisition frequency of different monitoring periods in linear proportion. Based on the set image acquisition frequency, control the diversified dynamic monitoring equipment to collect and upload the monitoring area images, identify the distribution of plane liquids in the image, and mark the identification results as suspected locations of illegal discharge; S4: real-time processing of the monitoring area image after the suspected illegal discharge location is marked, adjusting the specific position of the dynamic monitoring device so that the coaxial line between the two dynamic monitoring devices in the horizontal plane passes through the suspected illegal discharge location, and at the same time determining the incident light source starting point and the reflected light receiving point; S5: Calculate the propagation direction of the reflected light path based on the set incident angle, and control the reflected light receiving point to move in the vertical direction on one side of the reflected light path until the reflected light receiving point detects interference fringes; S6: Collect interference images and extract interference fringes in the images, analyze the changes in their hue values ​​to determine whether there is a rainbow interference effect at the suspected location of illegal discharge; S7: When it is determined that there is a rainbow interference effect at a suspected illegal discharge location, the dimensionless thickness of the oil film is estimated, and the illegal discharge location is marked and uploaded.

[0007] In a preferred embodiment, in S1, the monitoring time period and monitoring area are divided, and the distribution statistics of the number of catering individuals are performed through diversified dynamic monitoring equipment, and the mobile catering aggregation density of each monitoring area is calculated, which specifically includes: The predefined regular operating hours of mobile catering in the city are divided into equally spaced monitoring periods, and the number of mobile catering individuals in all blocks of the city are distributed and counted in different monitoring periods through diversified dynamic monitoring equipment; The daily gathering locations of mobile catering individuals are marked as monitoring areas. At least two diversified dynamic monitoring devices are set up in each monitoring area to cover the area. Based on the statistical number and distribution range of mobile catering individuals in the monitoring area, the mobile catering gathering density of each monitoring area is calculated; The calculated cluster density of each monitoring area is integrated in time series based on the designated monitoring period to establish a time series dynamic cluster density list of mobile catering in different monitoring areas.

[0008] In a preferred embodiment, in S2, the optical detection element is integrated with the GPS positioning device and implanted into the diversified dynamic monitoring device, and the periodic switching of the light source and the acquisition time of the sensor are synchronously aligned, specifically including: Integrate a lightweight optical detection element with a GPS positioning device and implant it into a diversified dynamic monitoring device corresponding to each monitoring area, wherein the optical detection element at least includes an LED light source, an optical collimator, and a CMOS sensor; An LED light source array with set band conversion is used, and the light source of each band is alternately lit at a set period through a pulse width modulation signal; The periodic switching of the LED light source array is synchronized with the acquisition time of the CMOS sensor through a synchronous trigger signal.

[0009] In a preferred embodiment, in S4, the monitoring area image after the suspected illegal discharge location is marked is processed in real time, and the specific position of the dynamic monitoring device is adjusted so that the coaxial line between the two dynamic monitoring devices in the horizontal plane passes through the suspected illegal discharge location, and at the same time, the incident light source starting point and the reflected light receiving point are determined specifically including: Process the uploaded monitoring area images in real time, conduct three-dimensional projection position analysis on the suspected illegal discharge locations, and establish a three-dimensional rectangular coordinate system with the suspected illegal discharge locations as the coordinate origin; The real-time position of the diversified dynamic monitoring equipment is obtained through the integrated GPS positioning device, and the real-time position is converted into a coordinate representation in a three-dimensional rectangular coordinate system; Select two dynamic monitoring devices that are closest to the coordinate origin in the monitoring area, and adjust the specific positions of the dynamic monitoring devices so that the coaxial line between the two dynamic monitoring devices in the horizontal plane passes through the coordinate origin and is distributed on both sides of the origin; Select the monitoring device with a lower height after position adjustment as the starting point of the LED incident light source, and the monitoring device with a higher height as the receiving point of the reflected light; An optical collimator is used to adjust the parallel light beam emitted by the LED light source array at the starting point of the incident light source to project it to the suspected location of illegal emission at a set incident angle.

[0010] In a preferred embodiment, in S5, calculating the propagation direction of the reflected light path based on the set incident angle, and controlling the reflected light receiving point to move in the vertical direction on one side of the reflected light path until the reflected light receiving point detects interference fringes specifically includes: Calculate the propagation direction of the reflected light path based on the set incident angle, and control the vertical movement of the reflected light receiving point on one side of the reflected light path; When the angle between the line connecting the reflected light receiving point and the origin of the three-dimensional rectangular coordinates and the ground is greater than the incident angle, the reflected light receiving point is controlled to move vertically downward; When the angle between the line connecting the reflected light receiving point and the origin of the three-dimensional rectangular coordinates and the ground is smaller than the incident angle, the reflected light receiving point is controlled to move vertically upward; The adjustment is completed until the reflected light receiving point is on the reflected light path and interference fringes are detected.

[0011] In a preferred embodiment, in S6, collecting the interference image and extracting the interference fringes in the image, analyzing the change of the hue value to determine whether there is a rainbow interference effect at the suspected illegal discharge location specifically includes: In each band of the light source irradiation cycle, the CMOS sensor at the reflected light receiving point is controlled to collect a number of continuous interference images, and the image with the highest pixel saturation is selected as the analysis image; Convert the image from RGB color space to HSV color space, use edge detection algorithm to identify and extract interference fringes in the image, analyze the change of hue value for each extracted rainbow fringes area, and confirm the color order of the fringes; Determine whether the color sequence of the interference fringes is a continuous color band from red to purple and whether there is a periodic change. If so, it is determined that a rainbow interference effect exists at the current suspected illegal emission location. If not, it is determined that no rainbow interference effect exists at the current suspected illegal emission location.

[0012] In a preferred embodiment, in S7, when it is determined that a rainbow interference effect exists at a suspected illegal discharge location, estimating the dimensionless thickness of the oil film and marking and uploading the illegal discharge location specifically includes: When the rainbow interference effect is judged to exist at the suspected location of illegal discharge, the interference formula is used to estimate the dimensionless thickness of the oil film, specifically:

[0013] In the formula, is the dimensionless thickness of the estimated oil film, is the set refractive index of the oil film, is the incident angle of the incident light, is the interference order, Interference order The wavelength of reflected light that corresponds to the color of the interference fringe.

[0014] The location where the estimated dimensionless thickness of the oil film exceeds the set monitoring dimensionless thickness threshold is marked as a violation emission location, and the corresponding location information is uploaded to the terminal of the violation emission management personnel.

[0015] The technical effects and advantages of the smart city-based governance event monitoring method of the present invention are as follows: Through diversified dynamic monitoring equipment, the distribution of mobile catering is counted, the aggregation density is calculated and the monitoring frequency is adjusted. The integrated optical detection element and GPS positioning device synchronously control the light source cycle and the sensor acquisition time, collect images according to the density changes in the monitoring area, and identify the distribution of planar liquids in the image, marking them as suspected locations of illegal discharge. By adjusting the position of the monitoring equipment to ensure that the reflected light path covers the suspicious location, and calculating the propagation direction of the reflected light path, the receiving point is moved until interference fringes are detected. After collecting the interference image, analyze its hue value changes to determine whether there is a rainbow interference effect. If the interference effect is confirmed, further estimate the dimensionless thickness of the oil film and mark and upload the location of the illegal discharge.

[0016] This solution uses the principle of optical interference effect. By analyzing the interference fringes of reflected light, it can accurately identify the characteristics of the oil film produced by mobile catering emissions. Combined with the position adjustment function of the dynamic monitoring equipment, it ensures that the monitoring of the interference effect is not interfered by the outside world, and realizes the rapid identification and location of illegal emissions. This method can provide more efficient and accurate technical means for urban governance, and assist in environmental supervision and pollution control in the construction of smart cities. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic diagram of a governance event monitoring method based on a smart city according to the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Example 1 Figure 1 The present invention provides a governance event monitoring method based on smart city, which includes the following steps: S1: Divide the monitoring period and monitoring area, use diversified dynamic monitoring equipment to conduct distribution statistics on the number of catering individuals, and calculate the mobile catering aggregation density in each monitoring area; S2: Integrate the optical detection element with the GPS positioning device and implant it into the diversified dynamic monitoring equipment, and synchronize the periodic switching of the light source with the acquisition time of the sensor; S3: Deploy an open source model for plane liquid recognition. According to the density changes of the time-series dynamic aggregation density list of mobile catering in different monitoring areas, dynamically set the image acquisition frequency of different monitoring periods in linear proportion. Based on the set image acquisition frequency, control the diversified dynamic monitoring equipment to collect and upload the monitoring area images, identify the distribution of plane liquids in the image, and mark the identification results as suspected locations of illegal discharge; S4: real-time processing of the monitoring area image after the suspected illegal discharge location is marked, adjusting the specific position of the dynamic monitoring device so that the coaxial line between the two dynamic monitoring devices in the horizontal plane passes through the suspected illegal discharge location, and at the same time determining the incident light source starting point and the reflected light receiving point; S5: Calculate the propagation direction of the reflected light path based on the set incident angle, and control the reflected light receiving point to move in the vertical direction on one side of the reflected light path until the reflected light receiving point detects interference fringes; S6: Collect interference images and extract interference fringes in the images, analyze the changes in their hue values ​​to determine whether there is a rainbow interference effect at the suspected location of illegal discharge; S7: When it is determined that there is a rainbow interference effect at a suspected illegal discharge location, the dimensionless thickness of the oil film is estimated, and the illegal discharge location is marked and uploaded.

[0020] In S1, the monitoring time periods and monitoring areas are divided, and the number of catering individuals is distributed and counted through diversified dynamic monitoring equipment to calculate the mobile catering aggregation density in each monitoring area.

[0021] The monitoring period of urban mobile catering is divided into equally spaced time periods to ensure the uniformity and comparability of monitoring data. During each monitoring period, diversified dynamic monitoring equipment (such as drones, patrol cars, movable high-definition surveillance cameras, etc.) is used to count the number of mobile catering individuals in all blocks of the city to obtain the distribution of mobile catering individuals in different blocks during each period. The division of each monitoring period is specifically set based on the activity patterns of mobile catering and the characteristics of urban traffic flow. The default predefined regular operating hours are 6:00-9:00 in the morning and 17:00-21:00 in the afternoon, which are divided into one-hour monitoring periods.

[0022] The daily gathering locations of mobile catering individuals are marked as monitoring areas (such as community gates, streets, etc.). At least two diversified dynamic monitoring devices are set up in each monitoring area (ensuring that at least one can be dynamically displaced to receive reflected light) to ensure that there are no blind spots in the monitoring of the area. Through the collaborative work of diversified dynamic monitoring devices, the number and location data of mobile catering individuals in the area are collected in real time, and the mobile catering gathering density in each monitoring area is calculated.

[0023] The calculated mobile catering density data in the monitoring area are integrated in time series, and the time series dynamic density of mobile catering is established based on the designated monitoring period. Through time series data analysis, a list of mobile catering dynamic density is generated for subsequent analysis and monitoring.

[0024] In S2, the optical detection element is integrated with the GPS positioning device and implanted into the diversified dynamic monitoring equipment, and the periodic switching of the light source and the acquisition time of the sensor are synchronously aligned.

[0025] The lightweight optical detection element is integrated with the GPS positioning device and implanted into the diversified dynamic monitoring equipment corresponding to each monitoring area. The optical detection element at least includes an LED light source, an optical collimator and a CMOS sensor. The LED light source is used to provide light illumination, and the optical collimator is used to adjust the propagation direction of the light beam to ensure that the light irradiates the target area. The CMOS sensor is used to receive reflected light and collect light reflection information in the area.

[0026] An LED light source array with set band conversion is used, and the light source of each band is alternately lit at a set period (set between 1ms and 10ms) through a pulse width modulation signal. The specific band settings are 400-420nm (purple light), 420-495nm (blue light), 495-570nm (green light), 570-590nm (yellow light), 590-620nm (orange light), and 620-700nm (red light).

[0027] The periodic switching of the LED light source array is synchronized with the acquisition time of the CMOS sensor through a synchronous trigger signal to ensure that the wavelength relationship between the collected reflected light and the incident light corresponds.

[0028] In S3, the deployed open source models (such as U-Net, Mask R-CNN, etc.) are trained through deep learning and can identify different types of liquids and extract their key features, such as shape, boundary, transparency, etc. The model extracts the liquid area through image segmentation technology and uses convolutional neural network (CNN) to further optimize the recognition accuracy. Based on the physical properties of liquids, the model can distinguish between liquids and ordinary roads, and make quick judgments based on features such as pixel values ​​and color changes in the image.

[0029] The density change is mapped to the acquisition frequency through a linear algorithm. For example, if a fixed mapping value is set, if the density of mobile catering in the monitoring area increases, the image acquisition frequency will be increased proportionally to capture more detailed information. When the density is low, the acquisition frequency can be appropriately reduced to save resources and improve efficiency.

[0030] Through morphological analysis and color space conversion, liquid distribution areas are identified as suspected locations of illegal discharge (the presence of liquid distribution does not necessarily mean that it is accompanied by the discharge of catering waste such as oil film).

[0031] In S4, the image of the monitoring area after the suspected illegal discharge location is marked is processed in real time, and the specific position of the dynamic monitoring device is adjusted so that the coaxial line between the two dynamic monitoring devices in the horizontal plane passes through the suspected illegal discharge location, and the starting point of the incident light source and the receiving point of the reflected light are determined at the same time.

[0032] The two-dimensional image data of the monitoring area is converted into a position in a three-dimensional coordinate system, and the spatial position of the liquid distribution is calculated by the ratio of the image resolution to the actual size of the ground. Through the known coordinates of the monitoring area, the sensor position and the image data, a three-dimensional projection analysis is performed to determine the spatial position of the suspected illegal discharge location, and this position is used as the coordinate origin of the three-dimensional rectangular coordinate system. In the three-dimensional rectangular coordinate system, the origin is established and the directions of the X-axis, Y-axis and Z-axis are determined, where the X-axis and Y-axis are the coordinate axes on the horizontal plane, and the Z-axis is the coordinate axis perpendicular to the ground, to ensure that the coordinate system conforms to the physical space of the actual monitoring area.

[0033] Each dynamic monitoring device is equipped with a high-precision GPS positioning device to transmit the coordinate information of the device's location in real time. The geographical coordinates of the device, including longitude, latitude and altitude, are obtained through GPS data. The acquired GPS coordinate information (latitude, longitude and altitude in the geographic coordinate system) is converted into location data in a three-dimensional rectangular coordinate system through an algorithm. This conversion uses a preset geographic information system (GIS) algorithm to ensure seamless connection between GPS coordinates and the three-dimensional coordinate system.

[0034] According to the three-dimensional coordinate system calculated in real time, select the two dynamic monitoring devices closest to the suspected illegal discharge location. The two devices should have the minimum spatial distance and be able to cover the illegal discharge location together. By fine-tuning the position of the monitoring device, ensure that the two devices are located on both sides of the coaxial line in the horizontal plane, and the line passes through the coordinate origin. The position of the device can be adjusted by moving the device or changing its rotation angle.

[0035] Select equipment that is close to the suspected illegal emission location on the horizontal plane and at a low height to ensure that the light source can be projected to the target location at the set angle and the light propagation path is the shortest. By using high-precision optical collimation devices, ensure that the light beam emitted from the LED light source forms a parallel beam after collimation. The parallelism of the light beam ensures the uniformity of light propagation and avoids irregular beam scattering.

[0036] In S5, the propagation direction of the reflected light path is calculated based on the set incident angle, and the reflected light receiving point is controlled to move in the vertical direction on one side of the reflected light path until the reflected light receiving point detects interference fringes.

[0037] The propagation direction of the reflected light path is calculated based on the set incident angle. When the reflected light receiving point deviates from the predetermined light path, its position is adjusted by controlling the movement of the reflected light receiving point in the vertical direction (Z-axis direction). This movement can be achieved by adjusting the height of the drone and the height of the signal receiving device of the patrol car.

[0038] The position deviation of the receiving point is determined by calculating the angle between the line connecting the reflected light receiving point and the origin and the ground. The dot product operation in the three-dimensional coordinate system is required to determine the angle of the reflected light receiving point relative to the ground. When the angle is greater than the incident angle, the position of the reflected light receiving point is too high and should be moved downward along the Z axis (vertical direction).

[0039] The angle between the line connecting the reflected light receiving point and the coordinate origin and the ground is calculated in the same way. If the angle is less than the incident angle, it means that the reflected light receiving point is too low and needs to be adjusted. In this case, the reflected light receiving point should be moved upward along the Z axis (vertical direction) until the angle returns to the set condition. In this way, ensure that the reflected light receiving point is aligned with the reflected light path.

[0040] When the reflected light receiving point is on the reflected light path, the interference fringes of the reflected light are monitored in real time by an optical sensor (CMOS sensor). The appearance of interference fringes indicates that the interference effect between the reflected light and the incident light occurs, indicating that the receiving point position has been accurately aligned.

[0041] In S6, the interference image is collected and the interference fringes in the image are extracted, and the change of the hue value is analyzed to determine whether there is a rainbow interference effect at the suspected location of illegal emission.

[0042] By controlling the periodic changes of the light source, the CMOS sensor receives several consecutive frames (more than 3 frames, the default setting is 3 frames) of interference images at the reflected light receiving point. Each image collected covers the interference phenomenon at different time points and can capture dynamically changing interference fringes. Pixel saturation is used as an indicator of image quality. By calculating the saturation value of all pixels in each frame of the image, the image with the highest saturation is selected for subsequent analysis. This method ensures that the collected image reaches the optimal state in terms of brightness, contrast, etc., so that the interference fringe features can be extracted more accurately.

[0043] The image is converted from RGB color space to HSV color space, and the converted HSV image is processed using a classic edge detection algorithm (such as Canny edge detection) to extract the edge information of the interference fringes.

[0044] For each extracted rainbow stripe area, extract its corresponding hue value (H value). The hue value represents the basic category of color, usually expressed in a range of 0° to 360°. In the rainbow interference effect, the color of the stripes should change in an orderly manner from red (low hue value) to purple (high hue value).

[0045] By analyzing the continuous interference fringe area, check whether the hue value shows periodic changes, that is, whether the color of the fringe transitions from red to purple in sequence. This periodic change is a typical feature of the interference effect. If so, it is judged that the current suspected illegal emission location has a rainbow interference effect. If not, it is judged that the current suspected illegal emission location does not have a rainbow interference effect.

[0046] In S7, when it is determined that a rainbow interference effect exists at a suspected illegal discharge location, the dimensionless thickness of the oil film is estimated, and the illegal discharge location is marked and uploaded.

[0047] When the rainbow interference effect is judged to exist at the suspected location of illegal discharge, the interference formula is used to estimate the dimensionless thickness of the oil film, specifically:

[0048] In the formula, is the dimensionless thickness of the estimated oil film, is the set refractive index of the oil film, is the incident angle of the incident light, is the interference order, Interference order The wavelength of reflected light corresponds to the color of the interference fringe. In practical applications, the interference order is usually determined by image analysis methods. In this method, the image is converted to a uniform scale and the interference order at the same position in all images is monitored to quickly identify the dimensionless thickness of the oil film.

[0049] The location where the estimated dimensionless thickness of the oil film exceeds the set monitoring dimensionless thickness threshold (dynamically set based on historical data, regulatory standards or urban environmental requirements) is marked as a violation emission location, and the corresponding location information is uploaded to the terminal of the violation emission management personnel. After the terminal device of the management personnel receives the violation emission location information, it is displayed through a map or a graphical interface to help personnel quickly locate and respond, and then carry out management.

[0050] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0051] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or may be transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium may be a solid-state hard disk.

[0052] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0053] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0054] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0055] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0056] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0057] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0058] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0059] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A governance event monitoring method based on smart city, characterized in that: The steps include: S1: Divide the monitoring period and monitoring area, use diversified dynamic monitoring equipment to conduct distribution statistics on the number of catering individuals, and calculate the mobile catering aggregation density in each monitoring area; S2: Integrate the optical detection element with the GPS positioning device and implant it into the diversified dynamic monitoring equipment, and synchronize the periodic switching of the light source with the acquisition time of the sensor; S3: Deploy an open source model for plane liquid recognition. According to the density changes of the time-series dynamic aggregation density list of mobile catering in different monitoring areas, dynamically set the image acquisition frequency of different monitoring periods in linear proportion. Based on the set image acquisition frequency, control the diversified dynamic monitoring equipment to collect and upload the monitoring area images, identify the distribution of plane liquids in the image, and mark the identification results as suspected locations of illegal discharge; S4: real-time processing of the monitoring area image after the suspected illegal discharge location is marked, adjusting the specific position of the dynamic monitoring device so that the coaxial line between the two dynamic monitoring devices in the horizontal plane passes through the suspected illegal discharge location, and at the same time determining the incident light source starting point and the reflected light receiving point; S5: Calculate the propagation direction of the reflected light path based on the set incident angle, and control the reflected light receiving point to move in the vertical direction on one side of the reflected light path until the reflected light receiving point detects interference fringes; S6: Collect interference images and extract interference fringes in the images, analyze the changes in their hue values ​​to determine whether there is a rainbow interference effect at the suspected location of illegal discharge; S7: When it is determined that there is a rainbow interference effect at a suspected illegal discharge location, the dimensionless thickness of the oil film is estimated, and the illegal discharge location is marked and uploaded.

2. According to the smart city governance event monitoring method of claim 1, it is characterized in that: In S1, the monitoring time period and monitoring area are divided, and the distribution statistics of the number of catering individuals are carried out through diversified dynamic monitoring equipment, and the mobile catering aggregation density in each monitoring area is calculated, including: The predefined regular operating hours of mobile catering in the city are divided into equally spaced monitoring periods, and the number of mobile catering individuals in all blocks of the city are distributed and counted in different monitoring periods through diversified dynamic monitoring equipment; The daily gathering locations of mobile catering individuals are marked as monitoring areas. At least two diversified dynamic monitoring devices are set up in each monitoring area to cover the area. Based on the statistical number and distribution range of mobile catering individuals in the monitoring area, the mobile catering gathering density of each monitoring area is calculated; The calculated cluster density of each monitoring area is integrated in time series based on the designated monitoring period to establish a time series dynamic cluster density list of mobile catering in different monitoring areas.

3. According to the smart city governance event monitoring method of claim 2, it is characterized in that: In S2, the optical detection element and the GPS positioning device are integrated and implanted into the diversified dynamic monitoring equipment, and the periodic switching of the light source and the acquisition time of the sensor are synchronously aligned, specifically including: Integrate a lightweight optical detection element with a GPS positioning device and implant it into a diversified dynamic monitoring device corresponding to each monitoring area, wherein the optical detection element at least includes an LED light source, an optical collimator, and a CMOS sensor; An LED light source array with set band conversion is used, and the light source of each band is alternately lit at a set period through a pulse width modulation signal; The periodic switching of the LED light source array is synchronized with the acquisition time of the CMOS sensor through a synchronous trigger signal.

4. According to the smart city governance event monitoring method of claim 3, it is characterized in that: In S4, the monitoring area image after the suspected illegal discharge location is marked is processed in real time, and the specific position of the dynamic monitoring device is adjusted so that the coaxial line between the two dynamic monitoring devices in the horizontal plane passes through the suspected illegal discharge location, and at the same time, the incident light source starting point and the reflected light receiving point are determined to include: Process the uploaded monitoring area images in real time, conduct three-dimensional projection position analysis on the suspected illegal emission locations, and establish a three-dimensional rectangular coordinate system with the suspected illegal emission locations as the coordinate origin; The real-time position of the diversified dynamic monitoring equipment is obtained through the integrated GPS positioning device, and the real-time position is converted into a coordinate representation in a three-dimensional rectangular coordinate system; Select two dynamic monitoring devices that are closest to the coordinate origin in the monitoring area, and adjust the specific positions of the dynamic monitoring devices so that the coaxial line between the two dynamic monitoring devices in the horizontal plane passes through the coordinate origin and is distributed on both sides of the origin; Select the monitoring device with a lower height after position adjustment as the starting point of the LED incident light source, and the monitoring device with a higher height as the receiving point of the reflected light; An optical collimator is used to adjust the parallel light beam emitted by the LED light source array at the starting point of the incident light source to project it to the suspected location of illegal emission at a set incident angle.

5. According to the smart city governance event monitoring method of claim 4, it is characterized in that: In S5, calculating the propagation direction of the reflected light path based on the set incident angle, and controlling the reflected light receiving point to move in the vertical direction on one side of the reflected light path until the reflected light receiving point detects interference fringes specifically includes: Calculate the propagation direction of the reflected light path based on the set incident angle, and control the vertical movement of the reflected light receiving point on one side of the reflected light path; When the angle between the line connecting the reflected light receiving point and the origin of the three-dimensional rectangular coordinates and the ground is greater than the incident angle, the reflected light receiving point is controlled to move vertically downward; When the angle between the line connecting the reflected light receiving point and the origin of the three-dimensional rectangular coordinates and the ground is smaller than the incident angle, the reflected light receiving point is controlled to move vertically upward; The adjustment is completed until the reflected light receiving point is on the reflected light path and interference fringes are detected.

6. According to the smart city governance event monitoring method of claim 5, it is characterized in that: In S6, the interference image is collected and the interference fringes in the image are extracted, and the change of the hue value is analyzed to determine whether there is a rainbow interference effect at the suspected location of illegal discharge. Specifically, the following steps are performed: In each band of the light source irradiation cycle, the CMOS sensor at the reflected light receiving point is controlled to collect a number of continuous interference images, and the image with the highest pixel saturation is selected as the analysis image; Convert the image from RGB color space to HSV color space, use edge detection algorithm to identify and extract interference fringes in the image, analyze the change of hue value for each extracted rainbow fringes area, and confirm the color order of the fringes; Determine whether the color sequence of the interference fringes is a continuous color band from red to purple and whether there is a periodic change. If so, it is determined that a rainbow interference effect exists at the current suspected illegal emission location. If not, it is determined that no rainbow interference effect exists at the current suspected illegal emission location.

7. A method for monitoring governance events based on smart cities according to claim 6, characterized in that: In S7, when it is determined that there is a rainbow interference effect at a suspected illegal discharge location, the dimensionless thickness of the oil film is estimated, and the illegal discharge location is marked and uploaded, including: When the rainbow interference effect is judged to exist at the suspected location of illegal discharge, the interference formula is used to estimate the dimensionless thickness of the oil film, specifically: In the formula, is the dimensionless thickness of the estimated oil film, is the set refractive index of the oil film, is the incident angle of the incident light, is the interference order, Interference order The wavelength of reflected light corresponding to the color of the interference fringe; The location where the estimated dimensionless thickness of the oil film exceeds the set monitoring dimensionless thickness threshold is marked as a violation emission location, and the corresponding location information is uploaded to the terminal of the violation emission management personnel.

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