A method and system for monitoring sewage outlets based on unmanned aerial vehicles

Abstract

This invention relates to the field of image processing technology and discloses a method and system for monitoring sewage outlets based on unmanned aerial vehicles (UAVs). The method includes: generating a dynamic flight strategy for the UAV based on meteorological information and lighting conditions of the target area; conducting preliminary monitoring of sewage outlets in the target area based on their distribution to obtain effective sewage outlet locations and images; filtering out ineffective sewage outlet locations from the distribution; compensating for ineffective sewage outlet locations using historical pollution data and a pre-set multi-period pollution model to generate a pollution heat map; extracting sewage outlet features from the effective sewage outlet images; marking anomalies in the target area's sewage outlets to obtain abnormal sewage outlet locations; conducting centralized inspections of these abnormal locations to obtain the monitoring results for the target sewage outlets. This invention effectively improves the stability of image acquisition quality, the comprehensiveness of sewage outlet location monitoring, and the accuracy of identification under extreme weather and lighting conditions.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method and system for monitoring sewage outlets based on unmanned aerial vehicles (UAVs). Background Technology

[0002] With the continuous increase in urban drainage systems and industrial wastewater discharge, real-time monitoring and supervision of sewage outlets have become crucial for ensuring water environment safety. Traditional sewage outlet monitoring methods mainly rely on manual inspections or fixed monitoring point water quality sensors, which suffer from limited monitoring range, long inspection cycles, and untimely data updates, making it difficult to meet the real-time monitoring needs of large-scale areas. In recent years, unmanned aerial vehicle (UAV)-based sewage outlet monitoring methods have been gradually applied. UAVs can flexibly patrol sewage outlet areas, carrying visible light, infrared, or multispectral sensors to collect images and video information. Through image processing and artificial intelligence recognition algorithms, sewage outlets can be located and their pollution status determined. Compared with traditional manual inspections, UAV monitoring has advantages such as wide coverage, high monitoring efficiency, and flexible operation.

[0003] While drone monitoring methods offer high efficiency and flexibility, existing technologies still have significant drawbacks. The effectiveness of drone monitoring is easily affected by environmental factors such as weather and lighting. Under extreme conditions such as rain, fog, snow, nighttime, or strong backlighting, the acquired monitoring images may not clearly show the characteristics of the discharge outlet, leading to invalid data or identification failures. Due to changes in environmental factors, the quality of data acquisition is unstable; images or videos may suffer from blurring, occlusion, or uneven exposure, directly affecting the accuracy of subsequent pollution feature extraction and intelligent identification algorithms. When image features are invalid, existing systems lack robustness and cannot autonomously complete pollution source identification and early warning, still requiring reliance on manual intervention or supplementary data from ground sensors.

[0004] In summary, improving the reliability of UAV monitoring of sewage outlets under various weather and lighting conditions, and ensuring the stability of data collection and the accuracy of identification results, has become an urgent technical problem to be solved. At the same time, while maintaining the flexibility and high coverage of UAV monitoring, it is necessary to enhance the system's adaptability to extreme environments, providing continuous and reliable data support for environmental supervision.

[0005] Therefore, existing drone-based methods for monitoring sewage outlets suffer from problems such as unstable image acquisition quality and incomplete monitoring of sewage outlet locations under extreme weather and lighting conditions, leading to decreased identification accuracy. Summary of the Invention

[0006] This invention provides a method for monitoring sewage outlets based on unmanned aerial vehicles (UAVs). Its main purpose is to solve the problems of unstable image acquisition quality and incomplete monitoring of sewage outlet locations under extreme weather and lighting conditions, which leads to a decrease in identification accuracy.

[0007] Firstly, to achieve the above objectives, the present invention provides a method for monitoring sewage outlets based on unmanned aerial vehicles (UAVs), comprising:

[0008] Acquire meteorological information and lighting conditions of the target area, and generate a dynamic flight strategy for the UAV based on the meteorological information and lighting conditions;

[0009] Acquire the distribution of sewage outlets and historical pollution data in the target area, and use the UAV dynamic flight strategy to conduct preliminary monitoring of the sewage outlets in the target area based on the distribution of sewage outlets in the target area, to obtain the effective sewage outlet locations and images of the effective sewage outlets at the effective sewage outlet locations;

[0010] Based on the effective sewage outlet locations, invalid sewage outlet locations are selected from the sewage outlet distribution in the target area;

[0011] The historical pollution data and a preset multi-period pollution model are used to compensate for the location of the invalid discharge outlets, and a pollution heat map is generated.

[0012] Extract the sewage outlet features from the effective sewage outlet images, and mark the sewage outlets in the target area as abnormal based on the sewage outlet features and the pollution heat map to obtain the abnormal sewage outlet locations;

[0013] A concentrated inspection was conducted on the abnormal locations of the sewage outlets to obtain the monitoring results of the target sewage outlets.

[0014] Secondly, the present invention also provides a sewage outlet monitoring system based on unmanned aerial vehicles (UAVs), the system comprising:

[0015] The flight strategy generation module is used to acquire meteorological information and lighting conditions of the target area, and generate a dynamic flight strategy for the UAV based on the meteorological information and lighting conditions.

[0016] An effective sewage outlet monitoring module is used to acquire the distribution of sewage outlets and historical pollution data in the target area, and to use the UAV dynamic flight strategy to perform preliminary monitoring of sewage outlets in the target area based on the distribution of sewage outlets in the target area, thereby obtaining the location of effective sewage outlets and images of effective sewage outlets at the location of effective sewage outlets;

[0017] The invalid sewage outlet screening module is used to screen out the locations of invalid sewage outlets from the distribution of sewage outlets in the target area based on the locations of the valid sewage outlets.

[0018] The pollution data compensation module is used to compensate for the location of the invalid discharge outlet by using the historical pollution data and the preset multi-period pollution model, and generate a pollution heat map.

[0019] The sewage outlet anomaly labeling module is used to extract the sewage outlet features of the effective sewage outlet image, and to annotate the sewage outlets in the target area according to the sewage outlet features and the pollution heat map to obtain the abnormal sewage outlet locations.

[0020] The abnormal sewage outlet inspection module is used to conduct centralized inspections of abnormal locations of the sewage outlets and obtain the monitoring results of the target sewage outlets.

[0021] This invention acquires meteorological information and lighting conditions of a target area, and generates a dynamic flight strategy for a drone based on this information and lighting conditions. This strategy dynamically adjusts the drone's flight altitude, speed, heading, and monitoring path according to real-time changes in meteorological and lighting data, thereby avoiding the effects of adverse factors such as strong winds, rain, fog, or glare, improving flight path stability, and enabling the drone to have higher environmental perception and autonomous decision-making capabilities. Furthermore, it acquires the distribution of sewage outlets and historical pollution data in the target area, and uses the drone's dynamic flight strategy to perform preliminary monitoring of the sewage outlets in the target area based on the distribution, obtaining the effective locations of sewage outlets and images of the effective sewage outlets at those locations. The drone can then... The system autonomously adjusts its flight path based on the distribution information of sewage outlets to ensure coverage of all key areas and acquires real-time locations and images of effective sewage outlets. This not only improves the coverage and accuracy of monitoring but also enables timely identification and recording of potential pollution sources, thereby enhancing monitoring efficiency. Furthermore, by filtering out invalid sewage outlet locations from the distribution of sewage outlets in the target area based on the locations of the effective outlets, it helps identify problematic outlets in the monitoring process, ensuring that subsequent data compensation does not miss any potential monitoring blind spots. Using historical pollution data and a preset multi-period pollution model to compensate for data gaps caused by inability to monitor properly or unclear images, the monitoring data becomes more complete and continuous. The generated pollution heat map can intuitively reflect the pollution intensity and distribution of invalid sewage outlets in the entire area. Even if clear data cannot be obtained directly from these sewage outlets, the pollution status can be estimated through model prediction and historical data. Extracting the sewage outlet features from the images of the valid sewage outlets and marking anomalies in the target area based on these features and the pollution heat map, the abnormal locations of the sewage outlets can be obtained. This enables accurate identification of sewage outlets that may have abnormal emissions or pollution problems, allowing monitoring to focus on abnormal locations, improving the targeting and efficiency of monitoring, and reducing false positives and false negatives. Centralized inspections of the abnormal locations of the sewage outlets yield the monitoring results of the target sewage outlets, allowing for the acquisition of high-precision emission data to verify the results of previous anomaly identification and prediction. Simultaneously, resources are concentrated on prioritizing the most polluted sewage outlets, effectively improving the stability of image acquisition quality, the comprehensiveness of sewage outlet location monitoring, and the accuracy of identification under extreme weather and lighting conditions. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the 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.

[0023] Figure 1 This is a flowchart illustrating a method for monitoring sewage outlets based on unmanned aerial vehicles (UAVs) according to an embodiment of the present invention.

[0024] Figure 2 A functional block diagram of a sewage outlet monitoring system based on an unmanned aerial vehicle (UAV) provided in an embodiment of the present invention;

[0025] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0026] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] This application provides a method for monitoring sewage outlets based on unmanned aerial vehicles (UAVs). This method can be executed by software or hardware installed on terminal or server devices. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be a standalone server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and demand forecasting platforms.

[0029] Reference Figure 1 The diagram shown is a flowchart illustrating a method for monitoring sewage outlets based on unmanned aerial vehicles (UAVs) according to an embodiment of the present invention. In this embodiment, the method for monitoring sewage outlets based on UAVs includes:

[0030] S1. Obtain meteorological information and lighting conditions of the target area, and generate a dynamic flight strategy for the UAV based on the meteorological information and lighting conditions.

[0031] In this embodiment of the invention, the target area is the specific geographical area where the UAV flight mission needs to be carried out. Meteorological information refers to data related to climate and weather, including information such as temperature, humidity, and wind speed. Lighting conditions refer to the intensity and variation of sunlight within the target area, which are usually related to factors such as the angle of the sun and cloud cover.

[0032] Dynamic flight strategy for unmanned aerial vehicles (UAVs) is a control strategy that adjusts the flight path, speed, and other parameters of the UAV based on real-time environmental information (such as weather and lighting conditions).

[0033] Specifically, generating a dynamic flight strategy for the UAV based on the meteorological information and the lighting conditions includes:

[0034] The environmental state of the target area is analyzed based on the meteorological information and the lighting conditions to obtain environmental state characteristics;

[0035] The target region is characterized based on the environmental state features to obtain a marked region;

[0036] The initial flight parameters of the UAV are obtained, and the initial flight parameters are adaptively adjusted according to the marked area to obtain the flight adjustment parameters;

[0037] Acquire terrain data of the marked area, and generate a primary monitoring path and a backup monitoring path based on the terrain data;

[0038] A dynamic flight strategy for the UAV is generated based on the flight adjustment parameters, the primary monitoring path, and the backup monitoring path.

[0039] In this embodiment of the invention, by collecting meteorological information (such as temperature, humidity, wind speed, etc.) and lighting conditions (such as light intensity, sunshine duration, etc.) of the target area, features reflecting the current environmental state of the target area are extracted, such as weather stability, changes in light intensity, and whether there is abnormal weather.

[0040] Furthermore, specific environmental factors within the target area, such as strong winds, low visibility, and intense sunlight, can be identified through environmental condition characteristics. Based on these specific environmental factors, the target area can be divided into different sub-regions. For example, areas with high wind speeds can be marked as "high-wind areas," or areas with insufficient sunlight can be marked as "low-light areas." This helps drones avoid high-risk areas during flight or adjust their flight strategies to adapt to different environmental conditions.

[0041] In this embodiment of the invention, the initial flight parameters of the UAV include flight speed, flight altitude, heading angle, etc. These initial flight parameters are adjusted according to the marked area of ​​the target area to obtain flight adjustment parameters. For example, if the UAV enters a "high wind zone", the flight altitude and speed may be adjusted to avoid being affected by wind; if the UAV enters a "low light zone", the flight mode may need to be adjusted to enhance the adaptability of the sensors.

[0042] In this embodiment of the invention, terrain data of the target area, such as surface undulations and obstacle distribution, helps in designing the UAV's flight path and ensuring flight safety. The primary monitoring path is the main flight route generated based on the terrain data, while the backup monitoring path is an alternative route when the primary monitoring path is unreachable or interfered with. Using these two paths, the UAV can flexibly respond to terrain changes, avoid collisions, and ensure the mission proceeds smoothly.

[0043] Furthermore, flight adjustment parameters are combined with the primary and backup monitoring paths to formulate a dynamic flight strategy for the UAV. Based on real-time collected flight adjustment parameters (including wind speed, illumination, image clarity, and energy consumption), the primary and backup monitoring paths are dynamically evaluated and weighted. When any waypoint on the primary monitoring path becomes abnormal or the flight safety factor falls below the safety threshold, a path switching mechanism is triggered. The optimal path is selected from the backup paths, and the waypoint sequence is re-planned based on the current flight attitude, speed, and mission priority to generate a dynamic flight strategy for the UAV. This enables adaptive switching and continuous monitoring and control between the primary and backup paths. The dynamic flight strategy for the UAV not only includes the selection of flight paths but also involves how to dynamically adjust the flight path and flight mode based on real-time data (such as weather changes and illumination changes), enabling the UAV to respond to different environmental changes in real time and optimize mission performance and flight safety.

[0044] This invention can dynamically adjust the flight altitude, speed, heading and monitoring path of a UAV based on real-time changes in weather and lighting data, thereby avoiding the effects of adverse factors such as strong winds, rain, fog or glare, improving flight path stability, and enabling the UAV to have higher environmental perception and autonomous decision-making capabilities.

[0045] S2. Obtain the distribution of sewage outlets and historical pollution data in the target area. Utilize the UAV dynamic flight strategy to perform preliminary monitoring of the sewage outlets in the target area based on the distribution of sewage outlets in the target area, and obtain the effective sewage outlet locations and images of the effective sewage outlets at those locations.

[0046] In this embodiment of the invention, the distribution of sewage outlets in the target area refers to the location and distribution of all sewage outlets within the target area. Historical pollution data refers to past records of pollution conditions at sewage outlets within the target area, including information such as pollutant types and concentrations. Effective sewage outlet locations are those that can be monitored normally and whose images are clear when captured by the drone. Effective sewage outlet images are clear and usable images of effective sewage outlets captured by the drone.

[0047] In detail, the step of using the UAV dynamic flight strategy to perform preliminary monitoring of sewage outlets in the target area based on the distribution of sewage outlets in the target area, and obtaining the effective sewage outlet locations and images of the effective sewage outlets at those locations, includes:

[0048] Based on the distribution of sewage outlets in the target area, obtain the sewage outlets in the target area and the initial sewage outlet locations in the target area;

[0049] The initial sewage outlet location is used to update the UAV's dynamic flight strategy, generating flight routes and flight mission plans;

[0050] Preliminary monitoring of the sewage outlets in the target area is conducted based on the flight route and the flight mission plan, and initial sewage outlet images of the initial sewage outlet locations are collected during the monitoring process.

[0051] Perform ambiguity analysis on the initial sewage outlet image, and filter out initial sewage outlet images with ambiguity values ​​less than a preset ambiguity threshold based on the ambiguity obtained from the analysis.

[0052] The selected initial sewage outlet images are subjected to sign recognition to obtain recognition results;

[0053] When the identification result indicates that the initial sewage outlet image shows signs of pollution, the corresponding initial sewage outlet location is marked as a valid sewage outlet location;

[0054] The initial image of the effective sewage outlet location is taken as the effective sewage outlet image.

[0055] In this embodiment of the invention, the location distribution of all sewage outlets within the target area is obtained through a geographic information system or remote sensing technology. The initial location of the sewage outlets in the target area is the coordinate position of the monitored sewage outlets.

[0056] Furthermore, the initial sewage outlet locations are mapped to the target area coordinate system, and the spatial distance and visual coverage between each sewage outlet in the target area and the main monitoring path and backup path are calculated. The path nodes are reordered or new waypoints are inserted based on the spatial distance, visible range, and importance of the sewage outlets. When some sewage outlets are in blind spots or overlapping monitoring areas, the flight altitude, heading angle, and shooting interval in the UAV's dynamic flight strategy are automatically adjusted to ensure effective coverage of all initial sewage outlets. A flight route and flight mission plan containing a sequence of waypoints, flight attitude parameters, and mission execution time are generated to achieve dynamic matching between path planning and monitoring targets, ensuring that the UAV's mission can be completed efficiently.

[0057] In this embodiment of the invention, during the flight mission, the UAV flies along a planned flight path and performs preliminary monitoring of the sewage outlets in the target area. During the monitoring process, the UAV uses onboard sensors or cameras to collect initial sewage outlet images at each initial sewage outlet location.

[0058] In this embodiment of the invention, image processing algorithms, such as calculating edge sharpness and contrast, are used to perform blur analysis on the acquired initial sewage outlet images to evaluate the clarity of each image. If the blur of the initial sewage outlet image exceeds a preset threshold, it indicates that the initial sewage outlet image is unclear and cannot provide effective information; while if the blur of the initial sewage outlet image is less than the threshold, it is considered that the initial sewage outlet image is clear and can be used as effective monitoring data.

[0059] In this embodiment of the invention, an image recognition model (such as a detection framework based on convolutional neural networks (CNN) or an improved YOLO framework) is used to extract features from the initial sewage outlet image to obtain the texture features, color distribution, edge contours, and thermal radiation features of the sewage outlet area in the initial sewage outlet image. The feature vectors are clustered and classified using a pattern recognition algorithm to identify suspicious discharge signs, such as abnormal water color, bubble diffusion, thermal imaging bright spots, or changes in the morphology of stains. During the identification process, a supervised learning model (such as a support vector machine (SVM) or random forest (RF)) is used to evaluate the confidence of the feature results, filter out false detections, and output the final identification result.

[0060] Furthermore, when the sign recognition indicates that the initial sewage outlet image shows signs of pollution, the corresponding sewage outlet location is automatically marked as a valid sewage outlet location, indicating that the sewage outlet at the valid sewage outlet location may have a pollution risk and requires close attention and monitoring. After the valid sewage outlet location is confirmed, the corresponding initial sewage outlet image is saved as a valid sewage outlet image, which contains image data of the sewage outlet showing signs of pollution.

[0061] This invention enables drones to autonomously adjust their flight paths based on the distribution information of sewage outlets, ensuring coverage of all key areas and acquiring real-time locations and images of effective sewage outlets. This not only improves the coverage and accuracy of monitoring but also allows for timely identification and recording of potential pollution sources, thereby enhancing monitoring efficiency.

[0062] S3. Based on the effective sewage outlet locations, filter out the invalid sewage outlet locations from the sewage outlet distribution in the target area.

[0063] In this embodiment of the invention, invalid discharge outlet locations are those that cannot be properly monitored and whose images captured by the drone are unclear. Identifying these unclear discharge outlet locations provides a reference for subsequent data compensation.

[0064] In this embodiment of the invention, based on the previously confirmed valid sewage outlet locations, the sewage outlets in the entire target area are marked, and the valid locations in the sewage outlet distribution are marked as "valid". Further, sewage outlet locations that have not been marked as "valid" are searched in the sewage outlet distribution of the target area. These unmarked sewage outlets may not have been identified as valid sewage outlets due to unclear monitoring data, incomplete images, or other factors. Further, the unmarked sewage outlet locations are considered invalid sewage outlet locations.

[0065] This invention helps identify problematic sewage outlets during monitoring by filtering out invalid sewage outlet locations, ensuring that subsequent data compensation does not miss any potential monitoring blind spots and providing a clear target for subsequent data compensation.

[0066] S4. Using the historical pollution data and the preset multi-period pollution model, perform data compensation on the location of the invalid sewage outlet to generate a pollution heat map.

[0067] In this embodiment of the invention, the multi-period pollution model is a mathematical model that analyzes and predicts pollution based on different time periods (such as daytime, nighttime, seasonal variations, etc.) to describe the distribution and variation patterns of pollutants. Data compensation is the process of filling in and correcting missing or incomplete monitoring data of invalid discharge outlet locations by using historical pollution data and multi-period pollution model predictions. The pollution heat map is an image that uses data visualization technology to present the spatial distribution of pollution intensity within a target area in color form, used to display the intensity and distribution trend of pollution.

[0068] In detail, the step of using the historical pollution data and a preset multi-period pollution model to perform data compensation on the locations of the invalid discharge outlets and generate a pollution heat map includes:

[0069] The historical pollution data is standardized to obtain standard pollution data;

[0070] By using a pre-set multi-period pollution model and the standard pollution data, the pollution emissions from the location of the invalid discharge outlet in each future period are analyzed to obtain pollution emission prediction data.

[0071] Identify missing pollution emission data in the pollution emission prediction data;

[0072] Kriging interpolation was performed on the missing pollution emission data to obtain interpolated pollution emission data;

[0073] The pollution emission interpolation data is corrected using the standard pollution data to obtain pollution emission compensation data;

[0074] A pollution heat map is generated based on the pollution emission compensation data.

[0075] In this embodiment of the invention, pollution data from different times and locations are converted into a unified dimension or scale to eliminate differences between different pollutants, regions, or time periods, making the data comparable.

[0076] In this embodiment of the invention, a pre-defined multi-period pollution model (such as one based on Long Short-Term Memory (LSTM) or Sequence-to-Sequence-to-Sequence (Seq2Seq) model) is used. Standard pollution data is divided into training and validation sets according to time sequence. Multi-dimensional features such as pollutant concentration, emission intensity, and meteorological conditions are normalized. Pollution time-series data from different time periods are input into the model. Through the time memory units of the LSTM or the encoder-decoder structure of Sequence-to-Sequence (Seq2Seq), the model learns the time dependence and dynamic change patterns of pollution emissions. After model training, pollution data from invalid discharge outlets are used as input. The model recursively predicts the future pollution emission trends for each time period based on the time-series characteristics, thereby obtaining pollution emission prediction data.

[0077] In this embodiment of the invention, there may be some missing or unpredictable gaps in the pollution emission prediction data, which may be caused by incomplete model predictions, incomplete data or other factors. Kriging interpolation can be used to effectively compensate for and make the missing pollution emission data continuous, thereby restoring the integrity and continuity of the pollution emission prediction data.

[0078] Furthermore, Kriging interpolation is used to estimate and fill in missing values ​​in pollution emission prediction data. The Kriging interpolation method uses surrounding known data points to extrapolate the pollution emission values ​​for missing data. The calculation formula is shown below:

[0079]

[0080] in, This indicates missing pollution emission data in the pollution emission forecast data. Pollution emission values, This represents the total number of pollution emission forecast data. Indicates the first Pollution emission values ​​from pollution emission forecast data. Indicates the first The weighting coefficients for each pollution emission prediction data point are used to summarize the calculated pollution emission values ​​into interpolated pollution emission data.

[0081] In this embodiment of the invention, by comparing the interpolated pollution emission data with the actual standard pollution data, the correction process adjusts the interpolated pollution emission data to better reflect actual pollution emission patterns. Furthermore, the corrected pollution emission data is then added to the original pollution emission prediction data, replacing previously missing data points. The compensated data forms a complete and more accurate pollution emission dataset.

[0082] In this embodiment of the invention, generating a pollution heat map based on the pollution emission compensation data includes:

[0083] The pollution emission compensation data is divided into spatial grids according to the target area to obtain the pollution attribute value of each grid unit;

[0084] Based on the pollution attribute values, generate the pollution intensity distribution for all invalid discharge outlet locations;

[0085] Based on the pollution intensity distribution, a multi-level independent thermal layer is constructed;

[0086] Color mapping is performed on the independent thermal layers to obtain multi-level color thermal layers;

[0087] Obtain the pollution time of the pollution intensity distribution, and generate a dynamic thermal sequence frame based on the pollution time using a preset time-series sliding window;

[0088] A pollution heat map of the invalid discharge outlet location is generated based on the color thermal layer and the dynamic thermal sequence frame.

[0089] In this embodiment of the invention, the target area is divided into several spatial grids of fixed size, each grid corresponding to a certain geographical range. Pollution emission compensation data is mapped to each grid cell, and the pollution attribute value of each grid cell is obtained by statistically analyzing the pollution emissions within that grid cell. Furthermore, using the pollution attribute value of each grid cell, the pollution intensity of invalid discharge outlets is calculated. The pollution emission compensation data is then correlated with each invalid discharge outlet to obtain the spatial distribution of pollution intensity at each invalid discharge outlet location, reflecting the relative severity of pollution at different locations.

[0090] In this embodiment of the invention, the pollution intensity distribution is divided into several independent layers according to different pollution levels, with each layer corresponding to a specific range of pollution intensity. For example, low, medium, and high pollution intensities correspond to different levels of thermal layers, which can respectively display the spatial distribution of different pollution intensities. Furthermore, each independent thermal layer is assigned a different color according to the pollution intensity, and the pollution intensity is converted into an intuitive color representation through color mapping. For example, low pollution intensity can be represented by a light color, and high pollution intensity by a dark color. After color mapping, multi-level color thermal layers are obtained, which can intuitively display the spatial distribution of different pollution levels.

[0091] In this embodiment of the invention, the temporal information corresponding to the pollution intensity distribution is obtained, and the time period to which each pollution intensity belongs is determined. A temporal sliding window is used to group the pollution intensity of consecutive time periods according to a fixed length and step size. The data within each window is used to generate a dynamic thermal sequence frame, reflecting the trend of pollution changes over time. Furthermore, the pollution heat map not only reflects the spatial distribution of pollution intensity from ineffective discharge outlets but also displays the dynamic trend over time, providing an intuitive understanding of the spatial and temporal characteristics of pollution and facilitating the development of targeted treatment and monitoring measures.

[0092] This invention utilizes historical pollution data and a pre-set multi-period pollution model to compensate for data gaps caused by the inability to monitor properly or unclear images, making the monitoring data more complete and continuous. The generated pollution heat map can intuitively reflect the pollution intensity and distribution of invalid discharge outlets throughout the area. Even if clear data cannot be obtained directly from these discharge outlets, the pollution status can be inferred through model prediction and historical data, improving the comprehensiveness and accuracy of monitoring.

[0093] S5. Extract the sewage outlet features from the effective sewage outlet image, and mark the sewage outlets in the target area as abnormal based on the sewage outlet features and the pollution heat map to obtain the abnormal sewage outlet locations.

[0094] In this embodiment of the invention, the discharge outlet features are characteristic information extracted from valid discharge outlet images that can describe the status and pollution situation of the discharge outlet, such as emission pattern, pollutant color, flow rate changes, etc. The abnormal discharge outlet locations are the locations of discharge outlets that may have abnormal emissions or pollution problems, identified through discharge outlet feature analysis and pollution heat maps.

[0095] Specifically, the extraction of sewage outlet features from the effective sewage outlet image includes:

[0096] The brightness of the effective sewage outlet image is enhanced to obtain an enhanced sewage outlet image;

[0097] Edge detection is performed on the enhanced image of the sewage outlet to obtain morphological features;

[0098] Extract the color information from the enhanced image of the sewage outlet, and generate color features based on the color information;

[0099] Extract the texture features from the enhanced image of the sewage outlet;

[0100] The emission changes at the effective sewage outlet locations are analyzed using enhanced images of the sewage outlet in consecutive frames to obtain the pollution outlet emission characteristics;

[0101] The morphological features, color features, texture features, and pollution outlet emission features are summarized into discharge outlet features.

[0102] In this embodiment of the invention, brightness enhancement can highlight key details of the effective sewage outlet image, such as the boundary, color and shape of the discharge, and improve the image quality problems caused by insufficient lighting or shadow effects, resulting in an enhanced sewage outlet image.

[0103] In this embodiment of the invention, the step of performing edge detection on the enhanced image of the sewage outlet to obtain morphological features includes:

[0104] Extract the edge contour of the effective sewage outlet location from the enhanced image of the sewage outlet;

[0105] Identify isolated noise points in the edge contour and remove them to obtain a denoised contour.

[0106] Repair the broken edges of the denoised contour to obtain the target edge contour;

[0107] Extract the morphological parameters of the target edge contour;

[0108] The morphological parameters are subjected to feature analysis to obtain morphological features.

[0109] In detail, the enhanced image of the sewage outlet is grayscaled or weighted fusion is performed on multiple channels, and then an adaptive threshold is used to obtain a binarized candidate region. A high-precision edge operator is run on the candidate region to obtain the position with obvious gradient. In order to improve the sub-pixel accuracy, non-maximum suppression can be performed on the detected edges, and then sub-pixel positioning (such as gradient interpolation or quadratic fitting) can be used to refine the boundary coordinates to obtain a set of edge contours ordered by pixel coordinates.

[0110] Furthermore, based on connected component analysis, short edge contours are separated from the main contours: the pixel length, pixel density, average gradient intensity, and distance to the nearest main contour are calculated for each edge contour; edge contours with lengths below a threshold, low average gradients, or distances to the main contours exceeding a set value are marked as noise. Noise can be directly deleted or cleared using median / morphological opening operations, while edge contours with weak edge intensity but good connectivity are retained using threshold relaxation or merging strategies.

[0111] In this embodiment of the invention, contour breakpoints are identified and the geometric relationship between breakpoint pairs (endpoint coordinates, endpoint normal direction, and endpoint spacing) is calculated. For endpoint pairs that are close to each other and have the same direction, quadratic curve interpolation or spline (e.g., B-spline) is used to directly connect them. For larger gaps or complex breaks, morphological closing operations are first used to attempt to fill them, and then distance transformation and shortest path / graph cut methods are combined to find the optimal connection path in the gray field or edge probability field, so as to achieve natural, continuous edge restoration that is consistent with the image texture.

[0112] Furthermore, the contour is first closed and filled to generate a connected region, and morphological parameters are extracted: area, perimeter, equivalent diameter, length and direction of major and minor axes, roundness or compactness, aspect ratio, convex hull area and convexity, porosity / number of holes, and edge curvature distribution statistics, etc.

[0113] In this embodiment of the invention, the numerical morphological parameters are standardized, and the discriminative power is improved by dimensionality reduction or selection methods: principal component analysis (PCA) can be used to extract the main modes, correlation analysis can be used to remove redundant features, and stability index and mutation index can be calculated by combining morphological changes on the time series (such as parameter differences or trend lines within a sliding window) to obtain morphological features used to determine "normal / suspicious / abnormal".

[0114] In this embodiment of the invention, the main colors, color saturation, and color variation patterns of pollutants in the enhanced image of the sewage outlet are extracted. These color features reflect the type, concentration, and characteristics of the pollutants emitted from the outlet, helping to distinguish different types of pollutants or determine the intensity of emission concentrations.

[0115] In this embodiment of the invention, texture features such as texture pattern, roughness, directionality and repeatability of the sewage outlet and the surface of the discharged material are extracted to reflect the distribution state and surface characteristics of pollutants.

[0116] In this embodiment of the invention, continuous enhanced images of the same discharge outlet taken at different times are compared and analyzed to calculate the trend of emission over time. By analyzing the increase or decrease in emission, the frequency of fluctuations, and the duration, the emission characteristics of the discharge outlet can be obtained, reflecting the dynamic characteristics of the discharge outlet's emission behavior.

[0117] In this embodiment of the invention, the above-mentioned features are integrated to form a comprehensive sewage outlet feature, which includes the geometric shape, color information, texture pattern, and dynamic changes in the discharge behavior of the sewage outlet.

[0118] In this embodiment of the invention, the step of marking the sewage outlets in the target area as abnormal based on the characteristics of the sewage outlets and the pollution heat map to obtain the abnormal locations of the sewage outlets includes:

[0119] The pollution intensity at each invalid discharge outlet location is obtained based on the pollution heat map of the invalid discharge outlet locations;

[0120] Based on the characteristics of the sewage outlets, anomaly analysis is performed on the effective sewage outlet locations in the target area to obtain abnormal sewage outlet characteristics.

[0121] The pollution intensity corresponding to the location of the effective sewage outlet is generated based on the abnormal characteristics of the sewage outlet;

[0122] When the pollution intensity is greater than a preset intensity threshold, the corresponding sewage outlet location in the target area is marked as an abnormal sewage outlet location.

[0123] In this embodiment of the invention, the images of invalid discharge outlets are unclear, making it impossible to extract discharge outlet features from the images. Therefore, the pollution intensity can only be estimated using the pollution heat map (macroscopic data) at the invalid discharge outlet locations. In contrast, the images of valid discharge outlets are clear, allowing for the extraction of fine-grained discharge outlet features such as shape, texture, color, and grayscale. This enables the analysis of abnormal features at valid discharge outlet locations to obtain the pollution intensity (microscopic data).

[0124] Furthermore, using the pollution distribution data displayed in the pollution heatmap of the invalid discharge outlet locations, the pollution intensity value for each invalid discharge outlet location is extracted. The pollution intensity reflects the possible pollution level at the invalid discharge outlet location through color intensity or numerical value.

[0125] In this embodiment of the invention, sewage outlet features extracted from effective sewage outlet images, including morphological, color, texture, and emission dynamics information, are used to analyze effective sewage outlets within a target area. By comparing the features of each sewage outlet with the feature patterns of normal sewage outlets, sewage outlets that significantly differ from the normal state are identified. The analysis results generate abnormal sewage outlet features, which are used to quantify the degree of anomaly and assess potential pollution risks. Furthermore, the abnormal sewage outlet features are converted into quantitative pollution intensity values, reflecting the potential pollution severity of each effective sewage outlet location, for subsequent threshold determination and anomaly labeling.

[0126] In this embodiment of the invention, the pollution intensity of invalid and valid discharge outlet locations is compared with an intensity threshold. If the pollution intensity exceeds the intensity threshold, it indicates that the discharge outlet may have abnormal emissions or pollution problems. The corresponding discharge outlet location is then marked as an abnormal discharge outlet location.

[0127] This invention extracts the features of sewage outlets from valid sewage outlet images and combines them with pollution heat maps to annotate sewage outlets in the target area. This enables accurate identification of sewage outlets that may have abnormal emissions or pollution problems, allowing monitoring to focus on abnormal locations of sewage outlets, improving the targeting and efficiency of monitoring, reducing false positives and false negatives, and improving the accuracy of sewage outlet anomaly detection.

[0128] S6. Conduct centralized inspections of the abnormal locations of the sewage outlets to obtain the monitoring results of the target sewage outlets.

[0129] In this embodiment of the invention, on-site inspections conducted by drones can verify the accuracy of anomaly identification at abnormal locations of sewage outlets, while also obtaining more reliable sewage outlet discharge data and thus obtaining monitoring results for the target sewage outlet.

[0130] In detail, the centralized inspection of abnormal locations at the sewage outlets to obtain monitoring results for the target sewage outlets includes:

[0131] A list of abnormal sewage outlets is generated based on the abnormal locations of the sewage outlets, and a treatment priority is generated based on the pollution intensity of the abnormal locations of the sewage outlets.

[0132] An inspection task is generated using the list of abnormal sewage outlets and the processing priority.

[0133] Based on the target area and the abnormal location of the sewage outlet, the inspection task is routed to obtain the inspection route;

[0134] Collect sewage discharge data during the environmental monitoring process of abnormal locations of the sewage outlets, based on the inspection tasks and inspection routes.

[0135] The pollution level of the discharge data from the discharge outlets is analyzed to obtain the monitoring results of the target discharge outlets.

[0136] In this embodiment of the invention, all locations of sewage outlets marked as abnormal are compiled into an abnormal sewage outlet list. The abnormal sewage outlets are then sorted according to their pollution intensity to determine their treatment priority. Sewage outlets with higher pollution intensity are assigned higher priority so that the most serious pollution problems are addressed first during inspections and remediation.

[0137] Furthermore, each inspection task includes the sewage outlets to be inspected and their priority order, ensuring that inspection activities cover all abnormal sewage outlets in an orderly and efficient manner, and prioritizing the most polluted locations. Spatial optimization of the inspection tasks involves combining the locations of abnormal sewage outlets within the target area with geographic information to plan routes, generating efficient inspection routes. Route planning considers the shortest distance of the inspection path and task priority, ensuring that inspection personnel or drones can complete tasks quickly and systematically, saving time and resources.

[0138] In this embodiment of the invention, abnormal discharge outlets are inspected on-site or by drone according to a pre-defined inspection task and route. During the inspection, discharge data from the outlets is collected in real time, including the types of pollutants and the amount of pollution discharged, ensuring that the monitoring data of each abnormal discharge outlet is completely collected.

[0139] Furthermore, the collected discharge data from sewage outlets (including pollutant concentration, flow rate, temperature, and time series information) are preprocessed and normalized to eliminate sampling errors and abnormal noise. Based on the characteristic thresholds of pollutant types and national or regional emission standards, the exceedance rate of each pollution indicator and the comprehensive pollution index are calculated. Combining the temporal trend and spatial distribution characteristics, the pollution level of the sewage outlets is classified and determined. By integrating historical monitoring records and real-time emission fluctuations, the emission status of the sewage outlets is comprehensively evaluated, generating target sewage outlet monitoring results that include pollution level, exceedance factors, and risk warning information.

[0140] This invention enables centralized inspection of abnormal locations at sewage outlets, ensuring the accuracy and reliability of monitoring results. By utilizing drone inspections, high-precision emission data can be acquired, validating previous anomaly identification and prediction results. Simultaneously, resources can be concentrated on prioritizing the most polluted sewage outlets, improving inspection efficiency.

[0141] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0142] like Figure 2 The diagram shown is a functional block diagram of a sewage outlet monitoring system based on an unmanned aerial vehicle (UAV) according to an embodiment of the present invention.

[0143] This disclosure provides a drone-based sewage outlet monitoring system, which corresponds one-to-one with the drone-based sewage outlet monitoring method described in the previous embodiment. For example... Figure 2 As shown, the UAV-based sewage outlet monitoring system 100 includes a flight strategy generation module 101, an effective sewage outlet monitoring module 102, an invalid sewage outlet screening module 103, a pollution data compensation module 104, a sewage outlet anomaly labeling module 105, and an abnormal sewage outlet inspection module 106. Detailed descriptions of each functional module are as follows:

[0144] The flight strategy generation module 101 is used to acquire meteorological information and lighting conditions of the target area, and generate a dynamic flight strategy for the UAV based on the meteorological information and lighting conditions.

[0145] The effective sewage outlet monitoring module 102 is used to acquire the distribution of sewage outlets and historical pollution data in the target area, and to use the UAV dynamic flight strategy to perform preliminary monitoring of the sewage outlets in the target area based on the distribution of sewage outlets in the target area, so as to obtain the location of the effective sewage outlets and the effective sewage outlet images at the location of the effective sewage outlets.

[0146] The invalid sewage outlet screening module 103 is used to screen out the invalid sewage outlet locations from the sewage outlet distribution in the target area based on the valid sewage outlet locations.

[0147] The pollution data compensation module 104 is used to compensate the invalid discharge outlet locations using the historical pollution data and a preset multi-period pollution model to generate a pollution heat map.

[0148] The sewage outlet anomaly labeling module 105 is used to extract the sewage outlet features of the effective sewage outlet image, and to annotate the sewage outlets in the target area according to the sewage outlet features and the pollution heat map to obtain the abnormal sewage outlet locations.

[0149] The abnormal sewage outlet inspection module 106 is used to conduct centralized inspections of abnormal locations of the sewage outlets and obtain the monitoring results of the target sewage outlets.

[0150] In one embodiment, the flight strategy generation module 101 generates a dynamic flight strategy for the UAV based on the meteorological information and the lighting conditions, for the following purposes:

[0151] The environmental state of the target area is analyzed based on the meteorological information and the lighting conditions to obtain environmental state characteristics;

[0152] The target region is characterized based on the environmental state features to obtain a marked region;

[0153] The initial flight parameters of the UAV are obtained, and the initial flight parameters are adaptively adjusted according to the marked area to obtain the flight adjustment parameters;

[0154] Acquire terrain data of the marked area, and generate a primary monitoring path and a backup monitoring path based on the terrain data;

[0155] A dynamic flight strategy for the UAV is generated based on the flight adjustment parameters, the primary monitoring path, and the backup monitoring path.

[0156] In one embodiment, the effective sewage outlet monitoring module 102, when executing the UAV dynamic flight strategy to perform preliminary monitoring of sewage outlets in the target area based on the distribution of sewage outlets in the target area, obtains the location of effective sewage outlets and images of effective sewage outlets at those locations, for the following purposes:

[0157] Based on the distribution of sewage outlets in the target area, obtain the sewage outlets in the target area and the initial sewage outlet locations in the target area;

[0158] The initial sewage outlet location is used to update the UAV's dynamic flight strategy, generating flight routes and flight mission plans;

[0159] Preliminary monitoring of the sewage outlets in the target area is conducted based on the flight route and the flight mission plan, and initial sewage outlet images of the initial sewage outlet locations are collected during the monitoring process.

[0160] Perform ambiguity analysis on the initial sewage outlet image, and filter out initial sewage outlet images with ambiguity values ​​less than a preset ambiguity threshold based on the ambiguity obtained from the analysis.

[0161] The selected initial sewage outlet images are subjected to sign recognition to obtain recognition results;

[0162] When the identification result indicates that the initial sewage outlet image shows signs of pollution, the corresponding initial sewage outlet location is marked as a valid sewage outlet location;

[0163] The initial image of the effective sewage outlet location is taken as the effective sewage outlet image.

[0164] In one embodiment, the pollution data compensation module 104 performs data compensation on the location of the invalid discharge outlet using the historical pollution data and a preset multi-time period pollution model, generating a pollution heat map, for the following purposes:

[0165] The historical pollution data is standardized to obtain standard pollution data;

[0166] By using a pre-set multi-period pollution model and the standard pollution data, the pollution emissions from the location of the invalid discharge outlet in each future period are analyzed to obtain pollution emission prediction data.

[0167] Identify missing pollution emission data in the pollution emission prediction data;

[0168] Kriging interpolation was performed on the missing pollution emission data to obtain interpolated pollution emission data;

[0169] The pollution emission interpolation data is corrected using the standard pollution data to obtain pollution emission compensation data;

[0170] A pollution heat map is generated based on the pollution emission compensation data.

[0171] In one embodiment, the pollution data compensation module 104 generates a pollution heat map based on the pollution emission compensation data, for the following purposes:

[0172] The pollution emission compensation data is divided into spatial grids according to the target area to obtain the pollution attribute value of each grid unit;

[0173] Based on the pollution attribute values, generate the pollution intensity distribution for all invalid discharge outlet locations;

[0174] Based on the pollution intensity distribution, a multi-level independent thermal layer is constructed;

[0175] Color mapping is performed on the independent thermal layers to obtain multi-level color thermal layers;

[0176] Obtain the pollution time of the pollution intensity distribution, and generate a dynamic thermal sequence frame based on the pollution time using a preset time-series sliding window;

[0177] A pollution heat map of the invalid discharge outlet location is generated based on the color thermal layer and the dynamic thermal sequence frame.

[0178] In one embodiment, the sewage outlet anomaly labeling module 105, when extracting sewage outlet features from the valid sewage outlet image, is used for:

[0179] The brightness of the effective sewage outlet image is enhanced to obtain an enhanced sewage outlet image;

[0180] Edge detection is performed on the enhanced image of the sewage outlet to obtain morphological features;

[0181] Extract the color information from the enhanced image of the sewage outlet, and generate color features based on the color information;

[0182] Extract the texture features from the enhanced image of the sewage outlet;

[0183] The emission changes at the effective sewage outlet locations are analyzed using enhanced images of the sewage outlet in consecutive frames to obtain the pollution outlet emission characteristics;

[0184] The morphological features, color features, texture features, and pollution outlet emission features are summarized into discharge outlet features.

[0185] In one embodiment, the sewage outlet anomaly labeling module 105 performs edge detection on the enhanced image of the sewage outlet to obtain morphological features, which are used for:

[0186] Extract the edge contour of the effective sewage outlet location from the enhanced image of the sewage outlet;

[0187] Identify isolated noise points in the edge contour and remove them to obtain a denoised contour.

[0188] Repair the broken edges of the denoised contour to obtain the target edge contour;

[0189] Extract the morphological parameters of the target edge contour;

[0190] The morphological parameters are subjected to feature analysis to obtain morphological features.

[0191] In one embodiment, the sewage outlet anomaly labeling module 105, when performing anomaly labeling of sewage outlets in the target area based on the sewage outlet characteristics and the pollution heat map to obtain the abnormal location of the sewage outlets, is used for:

[0192] The pollution intensity at each invalid discharge outlet location is obtained based on the pollution heat map of the invalid discharge outlet locations;

[0193] Based on the characteristics of the sewage outlets, anomaly analysis is performed on the effective sewage outlet locations in the target area to obtain abnormal sewage outlet characteristics.

[0194] The pollution intensity corresponding to the location of the effective sewage outlet is generated based on the abnormal characteristics of the sewage outlet;

[0195] When the pollution intensity is greater than a preset intensity threshold, the corresponding sewage outlet location in the target area is marked as an abnormal sewage outlet location.

[0196] In one embodiment, the abnormal discharge outlet inspection module 106 performs centralized inspection of abnormal locations of the discharge outlets to obtain monitoring results of the target discharge outlets, for the following purposes:

[0197] A list of abnormal sewage outlets is generated based on the abnormal locations of the sewage outlets, and a treatment priority is generated based on the pollution intensity of the abnormal locations of the sewage outlets.

[0198] An inspection task is generated using the list of abnormal sewage outlets and the processing priority.

[0199] Based on the target area and the abnormal location of the sewage outlet, the inspection task is routed to obtain the inspection route;

[0200] Collect sewage discharge data during the environmental monitoring process of abnormal locations of the sewage outlets, based on the inspection tasks and inspection routes.

[0201] The pollution level of the discharge data from the discharge outlets is analyzed to obtain the monitoring results of the target discharge outlets.

[0202] In this invention, the specific limitations of the UAV-based sewage outlet monitoring system can be found in the above-described limitations of the UAV-based sewage outlet monitoring method, and will not be repeated here. Each module in the aforementioned UAV-based sewage outlet monitoring system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0203] In the embodiments provided by this invention, it should be understood that the disclosed system can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0204] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0205] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0206] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0207] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0208] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0209] In the embodiments provided in this disclosure, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0210] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0211] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended 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, and should all be included within the protection scope of the present invention.

Claims

1. A method for monitoring sewage outlets based on unmanned aerial vehicles (UAVs), characterized in that, The method includes: Acquire meteorological information and lighting conditions of the target area, and generate a dynamic flight strategy for the UAV based on the meteorological information and lighting conditions; Acquire the distribution of sewage outlets and historical pollution data in the target area, and use the UAV dynamic flight strategy to conduct preliminary monitoring of the sewage outlets in the target area based on the distribution of sewage outlets in the target area, to obtain the effective sewage outlet locations and images of the effective sewage outlets at the effective sewage outlet locations; Based on the effective sewage outlet locations, invalid sewage outlet locations are selected from the sewage outlet distribution in the target area; The historical pollution data and a preset multi-period pollution model are used to compensate for the location of the invalid discharge outlets, and a pollution heat map is generated. Extract the sewage outlet features from the effective sewage outlet images, and mark the sewage outlets in the target area as abnormal based on the sewage outlet features and the pollution heat map to obtain the abnormal sewage outlet locations; A concentrated inspection of the abnormal locations of the sewage outlets was conducted to obtain the monitoring results of the target sewage outlets. The step of using the historical pollution data and a preset multi-period pollution model to perform data compensation on the locations of the invalid discharge outlets and generate a pollution heat map includes: The historical pollution data is standardized to obtain standard pollution data; By using a pre-set multi-period pollution model and the standard pollution data, the pollution emissions from the location of the invalid discharge outlet in each future period are analyzed to obtain pollution emission prediction data. Identify missing pollution emission data in the pollution emission prediction data; Kriging interpolation was performed on the missing pollution emission data to obtain interpolated pollution emission data; The pollution emission interpolation data is corrected using the standard pollution data to obtain pollution emission compensation data; A pollution heat map is generated based on the pollution emission compensation data; The step of generating a pollution heat map based on the pollution emission compensation data includes: The pollution emission compensation data is divided into spatial grids according to the target area to obtain the pollution attribute value of each grid unit; Based on the pollution attribute values, generate the pollution intensity distribution for all invalid discharge outlet locations; Based on the pollution intensity distribution, a multi-level independent thermal layer is constructed; Color mapping is performed on the independent thermal layers to obtain multi-level color thermal layers; Obtain the pollution time of the pollution intensity distribution, and generate a dynamic thermal sequence frame based on the pollution time using a preset time-series sliding window; A pollution heat map of the invalid discharge outlet location is generated based on the color thermal layer and the dynamic thermal sequence frame.

2. The method for monitoring sewage outlets based on unmanned aerial vehicles as described in claim 1, characterized in that, The step of generating a dynamic flight strategy for the UAV based on the meteorological information and the lighting conditions includes: The environmental state of the target area is analyzed based on the meteorological information and the lighting conditions to obtain environmental state characteristics; The target region is characterized based on the environmental state features to obtain a marked region; The initial flight parameters of the UAV are obtained, and the initial flight parameters are adaptively adjusted according to the marked area to obtain the flight adjustment parameters; Acquire terrain data of the marked area, and generate a primary monitoring path and a backup monitoring path based on the terrain data; A dynamic flight strategy for the UAV is generated based on the flight adjustment parameters, the primary monitoring path, and the backup monitoring path.

3. The method for monitoring sewage outlets based on unmanned aerial vehicles as described in claim 1, characterized in that, The process of using the UAV's dynamic flight strategy to perform preliminary monitoring of sewage outlets in the target area based on the distribution of sewage outlets in the target area, and obtaining the effective sewage outlet locations and images of the effective sewage outlets at those locations, includes: Based on the distribution of sewage outlets in the target area, obtain the sewage outlets in the target area and the initial sewage outlet locations in the target area; The initial sewage outlet location is used to update the UAV's dynamic flight strategy, generating flight routes and flight mission plans; Preliminary monitoring of the sewage outlets in the target area is conducted based on the flight route and the flight mission plan, and initial sewage outlet images of the initial sewage outlet locations are collected during the monitoring process. The initial sewage outlet image is subjected to fuzziness analysis, and the initial sewage outlet images with fuzziness values ​​less than a preset fuzziness threshold are selected based on the fuzziness values ​​obtained from the analysis. The selected initial sewage outlet images are subjected to sign recognition to obtain recognition results; When the identification result indicates that the initial sewage outlet image shows signs of pollution, the corresponding initial sewage outlet location is marked as a valid sewage outlet location; The initial image of the effective sewage outlet location is taken as the effective sewage outlet image.

4. The method for monitoring sewage outlets based on unmanned aerial vehicles as described in claim 1, characterized in that, The step of extracting the sewage outlet features from the effective sewage outlet image includes: The brightness of the effective sewage outlet image is enhanced to obtain an enhanced sewage outlet image; Edge detection is performed on the enhanced image of the sewage outlet to obtain morphological features; Extract the color information from the enhanced image of the sewage outlet, and generate color features based on the color information; Extract the texture features from the enhanced image of the sewage outlet; The emission changes at the effective sewage outlet locations are analyzed using enhanced images of the sewage outlet in consecutive frames to obtain the pollution outlet emission characteristics; The morphological features, color features, texture features, and pollution outlet emission features are summarized into discharge outlet features.

5. The method for monitoring sewage outlets based on unmanned aerial vehicles as described in claim 4, characterized in that, The edge detection of the enhanced image of the sewage outlet to obtain morphological features includes: Extract the edge contour of the effective sewage outlet location from the enhanced image of the sewage outlet; Identify isolated noise points in the edge contour and remove them to obtain a denoised contour. Repair the broken edges of the denoised contour to obtain the target edge contour; Extract the morphological parameters of the target edge contour; The morphological parameters are subjected to feature analysis to obtain morphological features.

6. The method for monitoring sewage outlets based on unmanned aerial vehicles as described in claim 1, characterized in that, The step of marking abnormal sewage outlets in the target area based on the characteristics of the sewage outlets and the pollution heat map to obtain the abnormal locations of the sewage outlets includes: The pollution intensity at each invalid discharge outlet location is obtained from the pollution heat map of the invalid discharge outlet locations; Based on the characteristics of the sewage outlets, anomaly analysis is performed on the effective sewage outlet locations in the target area to obtain abnormal sewage outlet characteristics. The pollution intensity corresponding to the location of the effective sewage outlet is generated based on the abnormal characteristics of the sewage outlet; When the pollution intensity is greater than a preset intensity threshold, the corresponding sewage outlet location in the target area is marked as an abnormal sewage outlet location.

7. The method for monitoring sewage outlets based on unmanned aerial vehicles as described in claim 1, characterized in that, The centralized inspection of abnormal locations at the sewage outlets, and the resulting monitoring results for the target sewage outlets, include: A list of abnormal sewage outlets is generated based on the abnormal locations of the sewage outlets, and a treatment priority is generated based on the pollution intensity of the abnormal locations of the sewage outlets. An inspection task is generated using the list of abnormal sewage outlets and the processing priority. Based on the target area and the abnormal location of the sewage outlet, the inspection task is routed to obtain the inspection route; Collect sewage discharge data during the environmental monitoring process of abnormal locations of the sewage outlets, based on the inspection tasks and inspection routes. The pollution level of the discharge data from the discharge outlets is analyzed to obtain the monitoring results of the target discharge outlets.

8. A sewage outlet monitoring system based on unmanned aerial vehicles (UAVs), characterized in that, The system includes: The flight strategy generation module is used to acquire meteorological information and lighting conditions of the target area, and generate a dynamic flight strategy for the UAV based on the meteorological information and lighting conditions. An effective sewage outlet monitoring module is used to acquire the distribution of sewage outlets and historical pollution data in the target area, and to use the UAV dynamic flight strategy to perform preliminary monitoring of sewage outlets in the target area based on the distribution of sewage outlets in the target area, thereby obtaining the location of effective sewage outlets and images of effective sewage outlets at the location of effective sewage outlets; The invalid sewage outlet screening module is used to screen out the locations of invalid sewage outlets from the distribution of sewage outlets in the target area based on the locations of the valid sewage outlets. The pollution data compensation module is used to compensate for the location of the invalid discharge outlet by using the historical pollution data and the preset multi-period pollution model, and generate a pollution heat map. The sewage outlet anomaly labeling module is used to extract the sewage outlet features of the effective sewage outlet image, and to annotate the sewage outlets in the target area according to the sewage outlet features and the pollution heat map to obtain the abnormal sewage outlet locations. The abnormal sewage outlet inspection module is used to conduct centralized inspections of abnormal locations of the sewage outlets and obtain the monitoring results of the target sewage outlets.

Images