New pollutant input source early warning method in urban aquatic ecosystem

Abstract

The invention discloses an early warning method for a new pollutant input source in an urban aquatic ecosystem, and relates to the technical field of pollution early warning, and the method comprises the steps: obtaining target region data, target meteorological data, historical pollution meteorological data and historical pollution data of a target region, obtaining key points based on the historical pollution data and the target region data, and carrying out the early warning of the new pollutant input source in the urban aquatic ecosystem; monitoring equipment is installed at the key points, monitoring data of the key points are obtained based on the monitoring equipment, and a first monitoring result is obtained based on the monitoring data and historical pollution meteorological data; and a second monitoring result is obtained based on the target meteorological data and the historical pollution meteorological data, and a pollution input source is obtained based on the first monitoring result and the second monitoring result, so that the problem that tracing is delayed due to the fact that tracing is performed by using a pipeline robot regularly in an existing pollutant tracing method of the urban aquatic ecosystem can be solved.

Description

Technical Field

[0001] The present invention relates to the field of pollution early warning technology, and in particular to an early warning method for new pollutant input sources in urban aquatic ecosystems. Background Art

[0002] With the acceleration of modern urbanization and the intensification of human activities, a large number of new chemical substances have entered rivers, lakes and other aquatic environments through various channels such as urban sewage, industrial wastewater, agricultural wastewater, and pharmaceutical wastewater. Urban aquatic ecosystems, which are composed of water, sediments, suspended solids and other aquatic media in urban rivers and lakes, as well as aquatic foods such as freshwater fish, freshwater shrimp, freshwater crabs and frogs, have become the main carriers of new pollutants. Faced with the pressure of the input and accumulation of large amounts of new pollutants, urban aquatic ecosystems have become one of the most important environmental problems at present. Therefore, it is indispensable to investigate and trace the sources of pollution and pollutants. Only by effectively tracing the source of pollution can we cut off the pollution source in a timely manner and prevent the pollution from further deteriorating. It is also necessary to identify and hold accountable the water dischargers and better regulate them to prevent their illegal discharge and water pollution again.

[0003] The current method for tracing the source of pollutants in urban aquatic ecosystems is to regularly use pipeline robots to climb pipes. However, this method only traces the source after the pollution problem has been discovered. This is not only not conducive to timely tracing the source, but may even aggravate the impact of water pollution due to delays. Summary of the Invention

[0004] In order to solve the problem that existing methods for tracing pollutants in urban aquatic ecosystems regularly use pipeline robots for tracing, which has a delay in tracing, the present invention provides an early warning method for the input source of new pollutants in urban aquatic ecosystems, the method comprising:

[0005] Acquire target area data, target meteorological data, historical pollution meteorological data, and historical pollution data of the target area, wherein the target area data includes a regional map and a sewage pipeline topology map;

[0006] Obtaining historical pollution points and first data of the historical pollution points based on the historical pollution data, obtaining target points based on the target area data, and obtaining key points based on the target points and the historical pollution points, wherein the target points include river sources, river outlets, tributary junctions, and sewage outlets;

[0007] Installing monitoring equipment at the key points, the monitoring equipment including water quality monitoring buoys, collection equipment and underwater robots;

[0008] obtaining monitoring data of the key point based on the monitoring device, wherein the monitoring data includes first pollution data, a pollution image, and second pollution data;

[0009] A first monitoring result is obtained based on the monitoring data and the first data; a second monitoring result is obtained based on the target meteorological data and the historical pollution meteorological data; based on the first monitoring result and the second monitoring result, a pollution input source is obtained, and an early warning is issued for the pollution input source.

[0010] The present invention determines the target point through the city map and the sewage pipe topology map, and determines the key point in combination with the historical pollution points, pays more attention to the key ports of urban pollution, controls the key ports, and is more effective in locating the polluted area; collects water surface pollution data and underwater pollution data in real time through monitoring equipment, and compares them with the historical pollution data, and comprehensively judges the first abnormal point through the concentration and quantity of pollutants, the water color and water flux of the river; and compares the real-time meteorological data with the historical meteorological data to obtain the abnormal area, and locates the second abnormal point in the abnormal area through positioning; jointly analyzes the first abnormal point and the second abnormal point to realize spatiotemporal joint analysis, and comprehensively obtains the pollution path through the flow direction of the river and the pollution propagation direction, so as to trace the pollution source, realize more timely and accurate tracing, and issue early warnings, deal with the pollution source more timely, and reduce further pollution spread.

[0011] Furthermore, the specific steps of obtaining the first monitoring result include:

[0012] Obtaining a first similarity based on the first contaminated data and the first data, obtaining a second similarity based on the second contaminated data and the first data, and obtaining a first abnormal point based on the first similarity and the second similarity;

[0013] obtaining a first pollution concentration based on the first pollution data and the second pollution data;

[0014] Obtaining pixel values and flow rates based on the pollution image, obtaining water color based on the pixel values, obtaining target water flux based on the flow rate, and obtaining a second abnormal point based on the water color, the target water flux, and the first pollution concentration;

[0015] Acquiring preset data, and obtaining preset pollutants based on the preset data, wherein the preset data includes sales data, breeding data, and medical data, and the preset pollutants include product pollutants, breeding pollutants, and medical pollutants;

[0016] Screening the first abnormal point and the second abnormal point based on the preset pollutant and the preset error range to obtain a third abnormal point;

[0017] Based on the third abnormal point, the first monitoring result is obtained.

[0018] By comparing the similarity of the composition and quantity of pollutants, and obtaining real-time water color and water flux through images, combined with the pollution concentration, the real-time pollution level is comprehensively judged, thereby locating its anomalies; considering that the products produced by factories are different, breeding plants or farms apply pesticides, antibiotics and other drugs with the seasons, as well as seasonal diseases, all of which will cause changes in the composition and concentration of pollutants, the present invention obtains relevant data, sets an error range, reduces interference, and locates anomalies more accurately according to the real-time situation.

[0019] Furthermore, the specific steps of obtaining the second monitoring result include:

[0020] Obtaining target air pollution data of the target area based on the drone equipment;

[0021] obtaining a target wind direction, a target wind speed, and a target temperature stratification based on the target meteorological data, and obtaining a historical wind direction, a historical wind speed, a historical target temperature stratification, historical air pollution data, and a historical pollution area based on the historical pollution meteorological data and the first data;

[0022] Obtaining a positioning method based on the historical pollution points, the historical pollution areas, the historical wind directions, the historical wind speeds, and the historical target temperature stratification;

[0023] Obtaining an abnormal area based on the target air pollution data and the historical air pollution data;

[0024] Based on the positioning method, the target wind direction, the target wind speed and the target temperature stratification, a third abnormal point is obtained, and the second monitoring result is obtained based on the third abnormal point.

[0025] Considering tracing the source from the perspective of air pollution diffusion, combining wind speed, wind direction and temperature stratification, we can obtain the relationship between the above factors and historical pollution areas and historical pollution points, so as to obtain the positioning method of pollution points, which is more in line with actual meteorological conditions and more accurate.

[0026] Furthermore, the positioning method is obtained as follows:

[0027] Obtaining a diffusion direction based on the historical direction, and obtaining a farthest diffusion point based on the diffusion direction and the historical pollution area;

[0028] Obtaining a longest diffusion distance based on the historical wind speed and the target temperature stratification;

[0029] The positioning method is obtained based on the longest diffusion distance, the farthest diffusion point and the historical pollution point.

[0030] The farthest diffusion point is determined by the area and propagation direction, the longest diffusion distance is determined according to the wind speed and temperature stratification, and the pollution point is located based on the principle of determining a straight line between two points.

[0031] Furthermore, the method further comprises:

[0032] Fluorescent tracers are placed at the key points to construct a new pollutant library, which includes fingerprint features of several new pollutants;

[0033] Obtaining a target pollution migration path based on the fluorescent tracer, and obtaining a target fingerprint feature based on the first pollution data;

[0034] obtaining a plurality of historical fingerprint features and historical pollution migration paths corresponding to the historical fingerprint features based on the historical pollution data;

[0035] A third similarity between the target pollution migration path and the historical pollution migration path is obtained, and a prediction result of an unknown pollutant is obtained based on the third similarity and the target fingerprint feature.

[0036] Taking into account the co-migration effect of fluorescent tracers and pollutants, the present invention moves different fluorescent tracers from each key point together with the water flow. By comparing with the migration paths of historical pollutants, the migration paths of unknown new pollutants are identified, thereby achieving rapid analog prediction of unknown pollutants, better predicting the toxicity of pollutants, and issuing toxicity warnings in advance, further reducing the hazards of pollutant spread.

[0037] Furthermore, the method further comprises:

[0038] Obtaining an abnormal sewage discharge area based on the first monitoring result;

[0039] A first pipeline in the abnormal sewage discharge area is obtained based on the sewage discharge pipeline topology map, pressure fluctuation data of the first pipeline is obtained, pressure fluctuation characteristics are obtained based on the pressure fluctuation data, and a first abnormal pipeline is obtained based on the pressure fluctuation characteristics.

[0040] Considering that factories, farms, etc. may privately connect illegal sewage pipes to sewage pipes to discharge more pollutants, the present invention obtains the concentration and water flux of pollutants through pollution data, and compares them with historical concentration and water flux images to obtain abnormal concentration and abnormal water flux, thereby obtaining abnormal sewage discharge areas, and then obtains the pressure fluctuation data of the pipelines in the area, extracts the characteristics of the pressure fluctuation data, and identifies abnormal pipelines through the characteristics, thereby obtaining the location of illegal sewage pipes, processing them, and reducing pollutant emissions.

[0041] Furthermore, the method further comprises:

[0042] Based on the regional map, a first river area and a first preset point of the abnormal sewage discharge area are obtained; based on the first pipeline, a preset channel from the first preset point to the first river area is obtained; based on a preset range, an outlet image of the preset channel is obtained; and based on the outlet image, a second abnormal pipeline is obtained.

[0043] Considering that factories, farms, etc. may privately install sewage pipes into rivers and discharge more pollutants, the present invention obtains the location of the river area and the location of the factory, farm, etc. in the abnormal sewage discharge area, obtains the installation path of the sewage pipe that can be realized between the two, locates the outlet of the path, and obtains the outlet image near it, so as to determine whether there is a second abnormal pipe.

[0044] Furthermore, the preset channel is obtained as follows:

[0045] Based on the regional map, obtaining a plurality of first paths from the first preset point to the first river area, obtaining first coordinates of the first river area, and obtaining a first remoteness based on the first coordinates;

[0046] obtaining a plurality of first nodes of the first path and a connection path between two adjacent first nodes, obtaining second coordinates of the first nodes, and obtaining a second remoteness based on the second coordinates;

[0047] obtaining a difficulty of the first path based on the connection path;

[0048] The preset channel is obtained based on the first path, the scale data of the first preset point, the difficulty, the first remoteness, and the second remoteness.

[0049] When considering the unauthorized installation of sewage pipes to rivers, relatively remote rivers and secluded paths are typically chosen. This invention uses traffic volume, visibility, and fame to determine remoteness, thereby identifying the most likely sewage channel and improving the accuracy of locating illegal sewage pipes. The taller the buildings, the more vegetation, and the higher the vegetation near the path and river, the easier it is to hide the sewage outlet. Therefore, determining its visibility based on these factors is more conducive to identifying the most likely sewage channel. Furthermore, the harder the road, the more difficult it is to dig, the more complete it is, and the easier it is to see. The longer the road, the higher the installation cost, and the less likely it is to be considered.

[0050] Furthermore, the remoteness is obtained as follows:

[0051] Obtaining foot traffic, visibility, and fame based on the coordinates, and obtaining the remoteness value based on the foot traffic, visibility, and fame;

[0052] The difficulty level is obtained as follows:

[0053] Obtaining a path distance, a path type, and a path image of the connection path, obtaining a path integrity based on the path image, and obtaining the difficulty based on the path type, the path distance, and the path integrity;

[0054] The visibility is obtained as follows:

[0055] A first image is obtained based on the coordinates, a building height, a vegetation area, and a vegetation height are obtained based on the first image, and the visibility is obtained based on the building height, the vegetation area, and the vegetation height.

[0056] Considering that the emission of pollutants is closely related to the production activities of factories and the breeding activities of farms, the present invention obtains their production plans, predicts the pollutants that may be emitted through their raw materials and corresponding production methods, and matches them with the pollutants actually monitored, thereby reducing the situation where the pollution source is incorrectly located due to a sudden drop or increase in real-time pollutants.

[0057] Furthermore, the specific steps of obtaining the preset pollutants include:

[0058] Construct a pollution library, which includes a product library, a breeding library, and a medical library. The product library includes a number of products, a number of raw materials corresponding to the products, production methods corresponding to the raw materials, and first pollutants generated by the production methods; the breeding library includes drugs for different target organisms at different times and second pollutants corresponding to the drugs; the medical library includes drugs for different diseases and third pollutants corresponding to the drugs;

[0059] Based on the preset data and the pollution library, the preset pollutants are obtained.

[0060] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0061] 1. The present invention determines the target point through the city map and the sewage pipe topology map, and determines the key point in combination with the historical pollution points, pays more attention to the key points of urban pollution, controls the key points, and is more effective in locating the polluted area; collects water surface pollution data and underwater pollution data in real time through monitoring equipment, and compares them with historical pollution data, and comprehensively judges the first abnormal point through the concentration and quantity of pollutants, the water color of the river, the water flux, etc.; and compares the real-time meteorological data with the historical meteorological data to obtain the abnormal area, and locates the second abnormal point in the abnormal area through positioning; jointly analyzes the first abnormal point and the second abnormal point to realize spatiotemporal joint analysis, and comprehensively obtains the pollution path through the flow direction of the river and the pollution propagation direction, so as to trace the source of pollution more timely and accurately, and issue early warnings, deal with the pollution source more timely, and reduce further pollution spread.

[0062] 2. The first and second abnormal points are screened based on the preset pollutants and the preset error range to obtain the third abnormal point; the similarity is compared by comparing the composition and quantity of the pollutants, and the real-time water color and water flux are obtained through images. Combined with the pollution concentration, the real-time pollution level is comprehensively judged to locate the abnormal point; considering that the products produced by factories are different, the pesticides, antibiotics and other drugs are applied in breeding plants or farms with different seasons, as well as seasonal diseases, all of which will cause the composition and concentration of pollutants to change, the present invention obtains relevant data, sets an error range, reduces interference, and locates the abnormal point more accurately according to the real-time situation.

[0063] 3. Obtain positioning methods based on the longest diffusion distance, farthest diffusion point, and historical pollution points; determine the farthest diffusion point by region and propagation direction, as well as wind speed and temperature stratification, to determine the longest diffusion distance. Based on the principle of two points determining a straight line, the pollution point can be located more simply and quickly.

[0064] 4. Based on the regional map, obtain the first river area and the first preset point of the abnormal sewage discharge area. Based on the first pipeline, obtain the preset channel from the first preset point to the first river area. Based on the preset range, obtain the exit image of the preset channel. Based on the exit image, obtain the second abnormal pipeline. Filter the paths by remoteness, difficulty, and visibility to obtain the sewage discharge channel with the highest probability, thereby improving the accuracy of locating illegal sewage discharge pipelines. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation of the embodiments of the present invention;

[0066] Figure 1 It is a schematic flow chart of the method for early warning of new pollutant input sources in urban aquatic ecosystems according to the present invention;

[0067] Figure 2 It is a schematic diagram of the positioning method in the present invention;

[0068] Among them, A is the pollution point, and B is the farthest diffusion point. DETAILED DESCRIPTION

[0069] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features therein can be combined with each other without conflict.

[0070] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0071] Example 1

[0072] refer to Figure 1 This embodiment provides an early warning method for new pollutant input sources in urban aquatic ecosystems, the method comprising:

[0073] Acquire target area data, target meteorological data, historical pollution meteorological data, and historical pollution data of the target area, wherein the target area data includes a regional map and a sewage pipeline topology map;

[0074] Obtaining historical pollution points and first data of the historical pollution points based on the historical pollution data, obtaining target points based on the target area data, and obtaining key points based on the target points and the historical pollution points, wherein the target points include river sources, river outlets, tributary junctions, and sewage outlets;

[0075] Monitoring equipment is installed at the key points, and the monitoring equipment includes a water quality monitoring buoy, a collection device and an underwater robot. In this embodiment, the water quality monitoring buoy can be a fixed multi-parameter water quality buoy (core indicators such as pH, COD, NH3-N), equipped with a miniature mass spectrometer and a bioluminescent sensor, the collection device can be a camera, and the underwater robot can be an existing underwater robot with a sampling function equipped with a molecular imprinting polymer sampler. In this embodiment, water or sediments from different water layers can also be collected for laboratory research to obtain more accurate pollutant data.

[0076] The monitoring data of the key point is obtained based on the monitoring device, and the monitoring data includes first pollution data, a pollution image, and second pollution data. In this embodiment, the first pollution data is pollution data collected by the water quality monitoring buoy, the pollution image is pollution data collected by the collection device, and the second pollution data is pollution data collected by the underwater robot.

[0077] A first monitoring result is obtained based on the monitoring data and the first data; a second monitoring result is obtained based on the target meteorological data and the historical pollution meteorological data. Based on the first and second monitoring results, the pollution input source is determined, and an early warning is issued for the pollution input source. For example, by connecting all abnormal points, based on the propagation direction and the river direction, the upstream abnormal point is obtained, thereby determining it as the pollution source, and the relevant information of the pollution source is sent to the backend for early warning processing.

[0078] The specific steps of obtaining the first monitoring result include:

[0079] A first similarity is obtained based on the first pollution data and the first data, a second similarity is obtained based on the second pollution data and the first data, and a first anomaly point is obtained based on the first similarity and the second similarity; if data corresponding to the first pollution data in the first data is obtained, that is, the data collected by the water quality monitoring buoy, the first pollution data and the components of the pollutants and the concentration of each component in the data are compared, and then their different weights are assigned to obtain similarity. Similarly, the second pollution data and the first data are subjected to the above operation to obtain similarity, and the similarities of the two are added to obtain the final similarity. If the similarity is greater than the preset value, the corresponding point is marked as the first anomaly point.

[0080] obtaining a first pollution concentration based on the first pollution data and the second pollution data;

[0081] A pixel value and flow rate are obtained based on the pollution image, a water color is obtained based on the pixel value, a target water flux is obtained based on the flow rate, and a second abnormal point is obtained based on the water color, the target water flux and the first pollution concentration; if an abnormal pixel range, a safe water flux threshold and a safe concentration threshold are set, if the pixel value is within the range and / or the water flow is greater than the threshold and or the first pollution concentration is greater than the threshold, the corresponding point is marked as a second abnormal point.

[0082] Acquire preset data, and obtain preset pollutants based on the preset data, wherein the preset data includes sales data, breeding data, and medical data, and the preset pollutants include product pollutants, breeding pollutants, and medical pollutants;

[0083] The specific steps of obtaining the preset pollutants include:

[0084] Construct a pollution library, which includes a product library, a breeding library, and a medical library. The product library includes a number of products, a number of raw materials corresponding to the products, production methods corresponding to the raw materials, and first pollutants generated by the production methods; the breeding library includes drugs for different target organisms at different times and second pollutants corresponding to the drugs; the medical library includes drugs for different diseases and third pollutants corresponding to the drugs;

[0085] Based on the preset data and the contamination database, the preset contaminants are obtained. The acquired real-time data is compared with the data in the contamination database to obtain the preset contaminants. The preset data may include production plans, production data, and related pharmaceutical data for processing plants, hospitals, manufacturing plants, breeding farms, plantations, and farms.

[0086] Screening the first abnormal point and the second abnormal point based on the preset pollutant and the preset error range to obtain a third abnormal point;

[0087] Based on the first three abnormal points, the first monitoring result is obtained.

[0088] The specific steps of obtaining the second monitoring result include:

[0089] Obtaining target air pollution data of the target area based on the drone equipment;

[0090] obtaining a target wind direction, a target wind speed, and a target temperature stratification based on the target meteorological data, and obtaining a historical wind direction, a historical wind speed, a historical target temperature stratification, historical air pollution data, and a historical pollution area based on the historical pollution meteorological data and the first data;

[0091] Obtaining a positioning method based on the historical pollution points, the historical pollution areas, the historical wind directions, the historical wind speeds, and the historical target temperature stratification;

[0092] Obtaining abnormal areas based on the target air pollution data and the historical air pollution data; for example, dividing the target area into different regions, obtaining the historical air pollution data and the target air pollution data of each region, comparing the air pollution components and the concentrations of the components between the two, obtaining their similarity, and marking the corresponding region as an abnormal area if a preset threshold is reached;

[0093] Based on the positioning method, the target wind direction, the target wind speed and the target temperature stratification, a third abnormal point is obtained, and the second monitoring result is obtained based on the third abnormal point.

[0094] The positioning method is obtained as follows:

[0095] Obtaining a diffusion direction based on the historical direction, and obtaining a farthest diffusion point based on the diffusion direction and the historical pollution area;

[0096] Based on the historical wind speed and the target temperature stratification, the longest diffusion distance is obtained. In this embodiment, the model can be pre-trained using meteorological data, including wind speed and temperature stratification, so that it can predict the longest diffusion distance under different wind directions.

[0097] The positioning method is obtained based on the longest diffusion distance, the farthest diffusion point and the historical pollution point.

[0098] like Figure 2 As shown, point B is the farthest diffusion point under the current diffusion direction, AB is the longest diffusion distance through the historical wind speed and target temperature stratification, and point A is determined as the pollution point through point B and line segment AB.

[0099] Example 2

[0100] On the basis of the first embodiment, in this embodiment, the method further includes:

[0101] Fluorescent tracers are placed at the key points to construct a new pollutant library, which includes fingerprint features of several new pollutants;

[0102] Obtaining a target pollution migration path based on the fluorescent tracer, and obtaining a target fingerprint feature based on the first pollution data; for example, utilizing the co-migration effect of the fluorescent tracer and the pollutant, placing different fluorescent tracers corresponding to pollution data at different key points, obtaining the corresponding pollution migration path based on whether the fluorescent tracer is present in the pollution data, and obtaining the corresponding fingerprint feature based on the pollution data;

[0103] Based on the historical pollution data, a number of historical fingerprint features and historical pollution migration paths corresponding to the historical fingerprint features are obtained; different pollutants, fingerprint features corresponding to the pollutants, and migration paths corresponding to the pollutants are matched one by one;

[0104] A third similarity between the target pollution migration path and the historical pollution migration path is obtained, and a prediction result for the unknown pollutant is obtained based on the third similarity and the target fingerprint. For example, the migration paths are first matched to obtain the corresponding pollutants, and then the fingerprints are compared to obtain the pollutant with the highest similarity. Based on the relevant information, a rapid analog prediction of the unknown pollutant is performed to predict its toxicity, etc.

[0105] Example 3

[0106] Based on the above embodiment, in this embodiment, the method further includes:

[0107] Obtaining an abnormal sewage discharge area based on the first monitoring result; for example, obtaining an upstream area within a preset range of the abnormal point to obtain the abnormal sewage discharge area;

[0108] A first pipeline in the abnormal sewage discharge area is obtained based on the sewage discharge pipeline topology map. Distributed acoustic sensing (DAS) and a pressure sensor are used to obtain pressure fluctuation data for the first pipeline. Pressure fluctuation characteristics are obtained based on the pressure fluctuation data. The first abnormal pipeline is then obtained based on the pressure fluctuation characteristics. If abnormal data is identified using a pre-trained model based on historical fluctuation data, the first abnormal pipeline is obtained.

[0109] Example 4

[0110] Based on the above embodiment, in this embodiment, the method further includes:

[0111] Obtaining a first river area and a first preset point in the abnormal sewage discharge area based on the regional map, and obtaining a preset channel from the first preset point to the first river area based on the first pipeline; if paths from all preset points to different rivers are obtained, the paths that are identical to the first pipeline are deleted, and then the preset channels therein are obtained;

[0112] An exit image of the preset channel is acquired based on a preset range, and a second abnormal pipeline is obtained based on the exit image.

[0113] In this embodiment, the first preset point may include a factory, a hospital, a farm, a snack street, etc.

[0114] The preset channel is obtained as follows:

[0115] Based on the regional map, obtaining a plurality of first paths from the first preset point to the first river area, obtaining first coordinates of the first river area, and obtaining a first remoteness based on the first coordinates;

[0116] obtaining a plurality of first nodes of the first path and a connection path between two adjacent first nodes, obtaining second coordinates of the first nodes, and obtaining a second remoteness based on the second coordinates;

[0117] obtaining a difficulty of the first path based on the connection path;

[0118] The preset channel is obtained based on the first path, the scale data of the first preset point, the difficulty, the first remoteness, and the second remoteness. Different weights are assigned to the first remoteness and the second remoteness to obtain a total remoteness, which is used to filter the first path. A corresponding difficulty range is then selected based on the scale data. A secondary filter is performed based on the difficulty range and the difficulty, thereby obtaining different preset channels. In this embodiment, the scale data may include the size of the factory, hospital, or farm, annual profit data, etc.

[0119] The remoteness is obtained as follows:

[0120] The flow of people, visibility and fame are obtained based on the coordinates, and the remoteness value is obtained based on the flow of people, visibility and fame; for example, the flow of people is obtained by obtaining the number of people passing by the point within a certain time range, and the fame is obtained by obtaining the number of searches and views of the point based on real-time data on the Internet, and then different weights are assigned to the flow of people, visibility and fame to obtain its remoteness value.

[0121] The difficulty level is obtained as follows:

[0122] Obtaining a path distance, a path type, and a path image of the connection path, obtaining a path integrity based on the path image, and obtaining the difficulty based on the path type, the path distance, and the path integrity;

[0123] The visibility is obtained as follows:

[0124] A first image is obtained based on the coordinates, a building height, a vegetation area, and a vegetation height are obtained based on the first image, and the visibility is obtained based on the building height, the vegetation area, and the vegetation height. If different weights are assigned to them, the visibility is obtained.

[0125] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0126] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. An early warning method for new pollutant input sources in urban aquatic ecosystems, characterized by: The method comprises: Acquire target area data, target meteorological data, historical pollution meteorological data, and historical pollution data of the target area, wherein the target area data includes a regional map and a sewage pipeline topology map; Obtaining historical pollution points and first data of the historical pollution points based on the historical pollution data, obtaining target points based on the target area data, and obtaining key points based on the target points and the historical pollution points, wherein the target points include river sources, river outlets, tributary junctions, and sewage outlets; Install monitoring equipment at the key points, including water quality monitoring buoys, collection equipment and underwater robots; obtaining monitoring data of the key point based on the monitoring device, wherein the monitoring data includes first pollution data, a pollution image, and second pollution data; A first monitoring result is obtained based on the monitoring data and the first data; a second monitoring result is obtained based on the target meteorological data and the historical pollution meteorological data; based on the first monitoring result and the second monitoring result, a pollution input source is obtained, and an early warning is issued for the pollution input source.

2. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 1, characterized in that: The specific steps of obtaining the first monitoring result include: Obtaining a first similarity based on the first contaminated data and the first data, obtaining a second similarity based on the second contaminated data and the first data, and obtaining a first abnormal point based on the first similarity and the second similarity; obtaining a first pollution concentration based on the first pollution data and the second pollution data; Obtaining pixel values and flow rates based on the pollution image, obtaining water color based on the pixel values, obtaining target water flux based on the flow rate, and obtaining a second abnormal point based on the water color, the target water flux, and the first pollution concentration; Acquiring preset data, and obtaining preset pollutants based on the preset data, wherein the preset data includes sales data, breeding data, and medical data, and the preset pollutants include product pollutants, breeding pollutants, and medical pollutants; Screening the first abnormal point and the second abnormal point based on the preset pollutant and the preset error range to obtain a third abnormal point; Based on the third abnormal point, the first monitoring result is obtained.

3. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 1, characterized in that: The specific steps of obtaining the second monitoring result include: Obtaining target air pollution data of the target area based on the drone equipment; obtaining a target wind direction, a target wind speed, and a target temperature stratification based on the target meteorological data, and obtaining a historical wind direction, a historical wind speed, a historical target temperature stratification, historical air pollution data, and a historical pollution area based on the historical pollution meteorological data and the first data; Obtaining a positioning method based on the historical pollution points, the historical pollution areas, the historical wind directions, the historical wind speeds, and the historical target temperature stratification; Obtaining an abnormal area based on the target air pollution data and the historical air pollution data; Based on the positioning method, the target wind direction, the target wind speed and the target temperature stratification, a third abnormal point is obtained, and the second monitoring result is obtained based on the third abnormal point.

4. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 3, characterized in that: The positioning method is obtained as follows: Obtaining a diffusion direction based on the historical direction, and obtaining a farthest diffusion point based on the diffusion direction and the historical pollution area; Obtaining a longest diffusion distance based on the historical wind speed and the target temperature stratification; The positioning method is obtained based on the longest diffusion distance, the farthest diffusion point and the historical pollution point.

5. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 1, characterized in that: The method further comprises: Fluorescent tracers are placed at the key points to construct a new pollutant library, which includes fingerprint features of several new pollutants; Obtaining a target pollution migration path based on the fluorescent tracer, and obtaining a target fingerprint feature based on the first pollution data; obtaining a plurality of historical fingerprint features and historical pollution migration paths corresponding to the historical fingerprint features based on the historical pollution data; A third similarity between the target pollution migration path and the historical pollution migration path is obtained, and a prediction result of an unknown pollutant is obtained based on the third similarity and the target fingerprint feature.

6. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 1, characterized in that: The method further comprises: Obtaining an abnormal sewage discharge area based on the first monitoring result; A first pipeline in the abnormal sewage discharge area is obtained based on the sewage discharge pipeline topology map, pressure fluctuation data of the first pipeline is obtained, pressure fluctuation characteristics are obtained based on the pressure fluctuation data, and a first abnormal pipeline is obtained based on the pressure fluctuation characteristics.

7. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 6, characterized in that: The method further comprises: Based on the regional map, a first river area and a first preset point of the abnormal sewage discharge area are obtained; based on the first pipeline, a preset channel from the first preset point to the first river area is obtained; based on a preset range, an outlet image of the preset channel is obtained; and based on the outlet image, a second abnormal pipeline is obtained.

8. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 7, characterized in that: The preset channel is obtained as follows: Based on the regional map, obtaining a plurality of first paths from the first preset point to the first river area, obtaining first coordinates of the first river area, and obtaining a first remoteness based on the first coordinates; obtaining a plurality of first nodes of the first path and a connection path between two adjacent first nodes, obtaining second coordinates of the first nodes, and obtaining a second remoteness based on the second coordinates; obtaining a difficulty of the first path based on the connection path; The preset channel is obtained based on the first path, the scale data of the first preset point, the difficulty, the first remoteness, and the second remoteness.

9. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 8, characterized in that: Remoteness is obtained as follows: Obtaining foot traffic, visibility, and fame based on the coordinates, and obtaining the remoteness value based on the foot traffic, visibility, and fame; The difficulty level is obtained as follows: Obtaining a path distance, a path type, and a path image of the connection path, obtaining a path integrity based on the path image, and obtaining the difficulty based on the path type, the path distance, and the path integrity; The visibility is obtained as follows: A first image is obtained based on the coordinates, a building height, a vegetation area, and a vegetation height are obtained based on the first image, and the visibility is obtained based on the building height, the vegetation area, and the vegetation height.

10. The method for early warning of new pollutant input sources in urban aquatic ecosystems according to claim 2, characterized in that: The specific steps of obtaining the preset pollutants include: constructing a pollution library, the pollution library including a product library, a breeding library, and a medical library, the product library including a number of products, a number of raw materials corresponding to the products, production methods corresponding to the raw materials, and first pollutants generated by the production methods; the breeding library including drugs for different target organisms at different time periods and second pollutants corresponding to the drugs; the medical library including drugs for different diseases and third pollutants corresponding to the drugs; Based on the preset data and the pollution library, the preset pollutants are obtained.

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