CN117011717B

CN117011717B - Perfluorinated compound pollution evaluation method and system based on Internet of things

Info

Publication number: CN117011717B
Application number: CN202311277226.1A
Authority: CN
Inventors: 王蓓丽; 郭丽莉; 瞿婷; 韩亚萌; 薛晋美; 李亚秀
Original assignee: BCEG Environmental Remediation Co Ltd
Current assignee: BCEG Environmental Remediation Co Ltd
Priority date: 2023-10-07
Filing date: 2023-10-07
Publication date: 2023-12-19
Anticipated expiration: 2043-10-07
Also published as: CN117011717A

Abstract

The invention relates to the technical field of environmental assessment, in particular to a perfluorinated compound pollution assessment method and system based on the Internet of things, which are used for acquiring a preset emission source of a target enterprise, determining a monitoring area according to the preset emission source, planning a sampling point layout according to the terrain condition of the monitoring area, and sampling and detecting each preset sampling point in the sampling point layout at a first preset time node to obtain a first perfluorinated compound distribution condition diagram; sampling and detecting each preset sampling point in the sampling point layout diagram at a second preset time node to obtain a second perfluorinated compound distribution situation diagram; the first perfluorinated compound distribution situation diagram and the second perfluorinated compound distribution situation diagram are analyzed to obtain average migration speeds of the perfluorinated compounds in the monitoring area in all migration directions, and the migration speeds of the perfluorinated compounds in all migration directions can be automatically and accurately evaluated through the method.

Description

Perfluorinated compound pollution evaluation method and system based on Internet of things

Technical Field

The invention relates to the technical field of environmental assessment, in particular to a perfluoro compound pollution assessment method and system based on the Internet of things.

Background

Perfluorocompounds (PFAS) are widely used in industrial and consumer product manufacturing because of their durability, bioaccumulation, and potential toxicity following discharge of industrial waste streams. PFAS can be absorbed and enriched by certain plants and is difficult to degrade, negatively affecting the ecosystem and human health, and therefore monitoring and assessing the presence and migration of PFAS in the environment is critical. The traditional PFAS evaluation method generally needs to rely on manual experience for analysis, is affected by human factors, so that the reliability of an evaluation result is low, the migration speed of the PFAS in a plurality of migration directions cannot be accurately evaluated, the refinement degree is low, the refined management and control of a perfluorinated compound polluted area cannot be realized, the management and control efficiency is low, and a large amount of resources are wasted. With the high-speed development of the internet of things technology, the wide application of the internet of things technology enables monitoring and evaluating of the pollution of the perfluorinated compounds in the environment to be more intelligent and efficient.

Disclosure of Invention

The invention overcomes the defects of the prior art and provides a perfluorinated compound pollution evaluation method and system based on the Internet of things.

The technical scheme adopted by the invention for achieving the purpose is as follows:

the invention discloses a perfluoro compound pollution evaluation method based on the Internet of things, which comprises the following steps:

acquiring a preset emission source of a target enterprise, determining a monitoring area according to the preset emission source, and planning a sampling point layout according to the topography condition of the monitoring area;

sampling and detecting each preset sampling point in the sampling point layout diagram at a first preset time node to obtain a first perfluorinated compound distribution situation diagram; sampling and detecting each preset sampling point in the sampling point layout diagram at a second preset time node to obtain a second perfluorinated compound distribution situation diagram;

analyzing the first perfluorinated compound distribution situation diagram and the second perfluorinated compound distribution situation diagram to obtain average migration speeds of the perfluorinated compounds in each migration direction in the monitoring area;

acquiring crop real-time image information of each migration direction in a preset range, and judging whether each migration direction is an early warning area or not according to the crop real-time image information; if the early warning area is the early warning area, early warning judgment is carried out on the early warning area so as to judge whether the perfluorinated compounds in the early warning area endanger crops.

Further, in a preferred embodiment of the present invention, a preset emission source of a target enterprise is obtained, a monitoring area is determined according to the preset emission source, and a sampling point layout is planned according to a topography condition of the monitoring area, specifically:

acquiring a preset emission source of a target enterprise, taking the preset emission source as a central point, and determining a monitoring area based on the central point;

acquiring a three-dimensional terrain model diagram corresponding to a monitoring area and acquiring density distribution requirement information of sampling points; importing the three-dimensional terrain model map and the density distribution requirement information into an ant colony algorithm for iterative planning to obtain a plurality of preset sampling points;

acquiring engineering construction information of a monitoring area, and searching each preset sampling point according to the engineering construction information to search whether a condition of burying preset type equipment exists in the preset sampling points or not;

if the condition that the preset type of equipment is buried in the preset sampling points exists, re-planning the preset sampling points to obtain new preset sampling points, and generating a sampling point layout diagram based on the new preset sampling points until the condition that the preset type of equipment is buried in the new preset sampling points does not exist, and outputting the sampling point layout diagram;

If the condition that the preset type of equipment is not buried in the preset sampling points, generating a sampling point layout diagram based on the preset sampling points, and outputting the sampling point layout diagram.

Further, in a preferred embodiment of the present invention, sampling and detecting each preset sampling point in the sampling point layout diagram at a first preset time node to obtain a first perfluorocompound distribution diagram, which specifically includes:

sampling and detecting soil of preset sampling points in the sampling point layout diagram at a first preset time node to detect whether perfluorinated compounds exist in each preset sampling point at the first preset time node;

if the perfluorinated compounds exist in the preset sampling points on the first preset time node, marking the corresponding preset sampling points in the sampling point layout diagram to obtain a plurality of first pollution marking sampling points;

generating a first pollution area based on a plurality of first pollution mark sampling points, and rendering the first pollution area in the sampling point layout diagram to obtain a first perfluorinated compound distribution situation diagram expressed in a first color on a first preset time node.

Further, in a preferred embodiment of the present invention, sampling and detecting each preset sampling point in the sampling point layout diagram at a second preset time node to obtain a second perfluorocompound distribution diagram, which specifically includes:

Sampling and detecting soil of preset sampling points in the sampling point layout diagram at a second preset time node to detect whether perfluorinated compounds exist in each preset sampling point at the second preset time node;

if the perfluorinated compounds exist in the preset sampling points on the second preset time nodes, marking the corresponding preset sampling points in the sampling point layout diagram to obtain a plurality of second pollution marking sampling points;

generating a second pollution area based on a plurality of second pollution mark sampling points, and rendering the second pollution area in the sampling point layout diagram to obtain a second perfluorinated compound distribution situation diagram expressed by a second color on a second preset time node.

Further, in a preferred embodiment of the present invention, the first perfluorinated compound distribution pattern and the second perfluorinated compound distribution pattern are analyzed to obtain an average migration velocity of the perfluorinated compound in each migration direction in the monitored area, specifically:

constructing a virtual space, and importing a first perfluorinated compound distribution situation diagram and a second perfluorinated compound distribution situation diagram into the virtual space;

the method comprises the steps that the preset sampling points with the same positions in a first perfluorinated compound distribution situation diagram and a second perfluorinated compound distribution situation diagram are overlapped in the virtual space, so that the first perfluorinated compound distribution situation diagram and the second perfluorinated compound distribution situation diagram are paired, and a paired perfluorinated compound distribution situation diagram is obtained;

Searching a position node where a preset emission source is located in the paired perfluorinated compound distribution situation diagram, taking the position node as a coordinate origin, and constructing a rectangular coordinate system in the paired perfluorinated compound distribution situation diagram based on the coordinate origin;

respectively searching curve outlines of the first pollution area and the second pollution area in the paired perfluorinated compound distribution situation diagram according to the color characteristics of the first pollution area and the second pollution area; the curve outlines of the first pollution area and the second pollution area are divided into four migration directions of east, south, west and north through four quadrant areas in the rectangular coordinate system;

the coordinate origin is taken as a ray starting point, a plurality of rays are emitted to four quadrant areas based on the ray starting point, intersection points of curve outlines of the first pollution area and the second pollution area of each ray in each quadrant area are obtained, line segments of each ray among the curve outline intersection points in each quadrant area are obtained, and a plurality of intersection point line segments are obtained;

calculating the distance value of each intersection point line segment in each quadrant region, and calculating according to the distance value of each intersection point line segment, the first preset time node and the second preset time node to obtain the migration speed of the perfluorinated compound on a plurality of nodes;

And carrying out average value processing on the migration velocity of the perfluorinated compound in each quadrant region on each node to obtain the average migration velocity of the perfluorinated compound in each quadrant region, so as to obtain the average migration velocity of the perfluorinated compound in each migration direction in the monitored region.

Further, in a preferred embodiment of the present invention, real-time image information of crops in which each migration direction is within a preset range is obtained, and whether each migration direction is an early warning area is determined according to the real-time image information of crops, which specifically includes:

prefabricating a plurality of preset crop model diagrams, constructing a database, and importing the plurality of preset crop model diagrams into the database to obtain a characteristic database;

acquiring crop real-time image information of each migration direction in a preset range, and constructing a crop real-time model diagram in the migration direction according to the crop real-time image information;

importing the crop real-time model diagram into the characteristic database, calculating the similarity between the crop real-time model diagram and various preset crop model diagrams through a Euclidean distance algorithm to obtain a plurality of similarities, and comparing the similarities with the preset similarities;

If the similarity is not greater than the preset similarity, indicating that the crops planted in the migration direction are not of the preset type, and marking the migration direction as a non-early-warning area;

if at least one similarity is larger than the preset similarity, the condition that the crops planted in the migration direction are the preset type of crops is indicated, and the migration direction is marked as an early warning area.

Further, in a preferred embodiment of the present invention, if the area is an early warning area, the early warning area is subjected to early warning judgment to judge whether the perfluorinated compounds in the early warning area endanger crops, specifically:

if a certain migration direction is an early warning area, acquiring a crop real-time model diagram in the early warning area, and identifying the crop type and the growth period of crops in the early warning area according to the crop real-time model diagram;

generating a search tag according to the crop type and the growth period of the crops in the early warning area, and searching in a big data network based on the search tag to obtain the predicted growth rate of the crops in the early warning area;

determining the mature time node of the crops in the early warning area according to the predicted growth rate and the growth period;

Acquiring the average migration speed of the perfluorinated compounds in the early warning area, acquiring a crop position area of crops in the early warning area, and determining the real-time pollution position of the perfluorinated compounds in the early warning area according to the second perfluorinated compound distribution situation diagram;

calculating a predicted time node of the migration of the perfluorinated compounds to the crop position area according to the average migration speed and the real-time pollution position of the perfluorinated compounds;

comparing the mature time node of the crops in the early warning area with the predicted time node of the perfluorinated compounds migrating to the crop position area; and if the mature time node of the crops in the early warning area is larger than the predicted time node of the perfluoro compound migrating to the crop position area, generating alarm information and outputting the alarm information.

The invention discloses a perfluorinated compound pollution evaluation system based on the Internet of things, which comprises a memory and a processor, wherein a perfluorinated compound pollution evaluation method program is stored in the memory, and when the perfluorinated compound pollution evaluation method program is executed by the processor, the following steps are realized:

The invention solves the technical defects existing in the background technology, and has the following beneficial effects: acquiring a preset emission source of a target enterprise, determining a monitoring area according to the preset emission source, planning a sampling point layout chart according to the topography condition of the monitoring area, and sampling and detecting each preset sampling point in the sampling point layout chart at a first preset time node to obtain a first perfluorinated compound distribution situation chart; sampling and detecting each preset sampling point in the sampling point layout diagram at a second preset time node to obtain a second perfluorinated compound distribution situation diagram; the first perfluorinated compound distribution situation diagram and the second perfluorinated compound distribution situation diagram are analyzed to obtain average migration speeds of perfluorinated compounds in each migration direction in a monitoring area, and the migration speeds of perfluorinated compounds in each migration direction can be automatically and accurately evaluated through the method, so that pollution control and emergency response strategies can be formulated, the efficiency and effect of environmental management can be improved, and potential environmental and health risks can be reduced.

Drawings

In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other embodiments of the drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a first method flow chart of a perfluoro compound pollution evaluation method based on the Internet of things;

FIG. 2 is a second method flow chart of a perfluoro compound pollution evaluation method based on the Internet of things;

FIG. 3 is a third method flow chart of a perfluoro compound pollution evaluation method based on the Internet of things;

fig. 4 is a system block diagram of a perfluorocompound pollution evaluation system based on the internet of things.

Detailed Description

In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.

As shown in fig. 1, the first aspect of the invention discloses a perfluoro compound pollution evaluation method based on the internet of things, comprising the following steps:

s102: acquiring a preset emission source of a target enterprise, determining a monitoring area according to the preset emission source, and planning a sampling point layout according to the topography condition of the monitoring area;

s104: sampling and detecting each preset sampling point in the sampling point layout diagram at a first preset time node to obtain a first perfluorinated compound distribution situation diagram; sampling and detecting each preset sampling point in the sampling point layout diagram at a second preset time node to obtain a second perfluorinated compound distribution situation diagram;

s106: analyzing the first perfluorinated compound distribution situation diagram and the second perfluorinated compound distribution situation diagram to obtain average migration speeds of the perfluorinated compounds in each migration direction in the monitoring area;

s108: acquiring crop real-time image information of each migration direction in a preset range, and judging whether each migration direction is an early warning area or not according to the crop real-time image information; if the early warning area is the early warning area, early warning judgment is carried out on the early warning area so as to judge whether the perfluorinated compounds in the early warning area endanger crops.

The method comprises the steps of obtaining a preset emission source of a target enterprise, determining a monitoring area according to the preset emission source, and planning a sampling point layout according to the topography condition of the monitoring area, wherein the method specifically comprises the following steps:

It should be noted that the ant colony algorithm solves the optimization problem by simulating the process of moving ants in the problem space. Ants start from an initial point and select the next moving position according to certain rules. This process is iterated until a stop condition is reached.

It should be noted that the target enterprise is an enterprise that produces and manages products related to the perfluorinated compounds; the preset emission source is the industrial wastewater emission site planned in advance by the target enterprise. And determining a monitoring area by taking the preset emission source as a central point according to the diameter of a preset range of the central point, wherein the diameter of the monitoring area is 10 km, 20 km, 30 km and the like. The three-dimensional terrain model map corresponding to the Deao monitoring area can be obtained according to a remote sensing technology or directly in map software. The sampling points are soil sampling monitoring points, and the density distribution requirement information of the sampling points is specified by technicians. The engineering construction information is engineering planning information of the monitoring area and can be obtained from a related engineering planning table. And generating a plurality of preset sampling points by combining the three-dimensional terrain model diagram corresponding to the monitoring area and the density distribution requirement information of the sampling points through an ant colony algorithm, wherein the distribution condition of the preset sampling points can be ring-buckled circular type or ring-buckled square type and the like. The preset type of equipment includes underground cables, underground pipes, etc. If the preset sampling points are buried in the preset type of equipment, for safety, the preset sampling points are required to be re-planned when the monitoring area is sampled and detected, and the places are required to be avoided. Through this above step can be according to the topography condition automatic planning of monitoring area and go out the sampling point that corresponds, can avoid engineering facilities during the sampling, improve the security, can make the sampling point more reasonable, avoid appearing the condition of oversampling or sampling inadequately.

Sampling and detecting each preset sampling point in the sampling point layout diagram at a first preset time node to obtain a first perfluorinated compound distribution situation diagram, as shown in fig. 2, specifically:

s202: sampling and detecting soil of preset sampling points in the sampling point layout diagram at a first preset time node to detect whether perfluorinated compounds exist in each preset sampling point at the first preset time node;

s204: if the perfluorinated compounds exist in the preset sampling points on the first preset time node, marking the corresponding preset sampling points in the sampling point layout diagram to obtain a plurality of first pollution marking sampling points;

s206: generating a first pollution area based on a plurality of first pollution mark sampling points, and rendering the first pollution area in the sampling point layout diagram to obtain a first perfluorinated compound distribution situation diagram expressed in a first color on a first preset time node.

It should be noted that, each preset sampling point in the sampling point layout diagram may be sampled on a first preset time node by an automatic sampling device, such as an unmanned sampling trolley, and then whether a perfluorinated compound exists in soil in each sampling point is detected by a mass spectrometry, a nuclear magnetic resonance, and an infrared spectrometry, if so, the corresponding preset sampling point is marked in the sampling point layout diagram, after all the sampling points are detected, each first pollution marked sampling point is subjected to connection processing, and then a rendering and coloring processing is performed on the connected region by using software such as 3Dmax, so as to color the connected region into a first perfluorinated compound distribution diagram represented by a first color (such as blue). The colored area is the area where the perfluorinated compound exists in the monitoring area on the first preset time node. The method can visually display the polluted area with the perfluorinated compounds in the monitored area.

Sampling and detecting each preset sampling point in the sampling point layout diagram at a second preset time node to obtain a second perfluorinated compound distribution situation diagram, wherein the specific steps are as follows:

It should be noted that, each preset sampling point in the sampling point layout diagram may be sampled on a second preset time node by an automatic sampling device, such as an unmanned sampling trolley, and then whether the perfluorinated compound exists in the soil in each sampling point is detected by mass spectrometry, nuclear magnetic resonance, and infrared spectrometry, if so, the corresponding preset sampling point is marked in the sampling point layout diagram, after all the sampling points are detected, each second pollution marked sampling point is subjected to connection processing, and then the connected area is subjected to rendering and coloring processing by software such as 3Dmax, so as to color the connected area into a second perfluorinated compound distribution diagram represented by a second color (such as red). The colored area is the area where the perfluorinated compound exists in the monitoring area on the second preset time node. The method can visually display the polluted area with the perfluorinated compounds in the monitored area.

The first perfluorinated compound distribution situation diagram and the second perfluorinated compound distribution situation diagram are analyzed to obtain average migration speeds of the perfluorinated compounds in each migration direction in the monitoring area, wherein the average migration speeds are specifically as follows:

The virtual space is constructed through modeling software such as SolidWorks and the like so as to pair the first perfluorinated compound distribution situation diagram and the second perfluorinated compound distribution situation diagram to obtain a paired perfluorinated compound distribution situation diagram; a rectangular coordinate system is built according to a position node where a preset emission source is located, so that a first quadrant region, a second quadrant region, a third quadrant region and a fourth quadrant region are obtained; to divide the curve outline of the first pollution area and the second pollution area into four migration directions of east, south, west and north. Then in modeling software such as SolidWorks and the like, the origin of coordinates is taken as a ray starting point, a plurality of rays are simulated and emitted to four quadrant areas based on the ray starting point (the specific quantity can be set according to actual conditions, the more the quantity is, the higher the calculated average migration speed precision is), after a plurality of rays are emitted, each ray can generate intersection points with curve outlines (namely the intersection lines of a coloring area and a non-coloring area) of a first pollution area and a second pollution area, at the moment, coordinate information of each intersection point is acquired in a rectangular coordinate system, distance values of each intersection point line segment can be quickly calculated according to the coordinate information, then the corresponding actual distance values can be obtained by multiplying the distance values of each intersection point line segment by corresponding drawing proportions, so that migration speeds of a perfluorinated compound on a plurality of nodes are calculated, average migration speeds of the perfluorinated compound on each node in each quadrant area are processed by taking an average value, and the average migration speeds of the perfluorinated compound in each migration direction in the monitored area can be calculated. The method can accurately calculate the migration speed of the perfluorinated compounds in each migration direction and finely calculate the migration speed of the perfluorinated compounds in each direction, thereby being beneficial to formulating pollution control and emergency response strategies, improving the efficiency and effect of environmental management and reducing potential environmental and health risks; meanwhile, the accurate evaluation provides scientific basis for sustainable resource management and compliance supervision, and is beneficial to creating healthier and sustainable environments.

The method comprises the steps of acquiring real-time image information of crops with each migration direction in a preset range, judging whether each migration direction is an early warning area according to the real-time image information of the crops, and specifically, as shown in fig. 3:

s302: prefabricating a plurality of preset crop model diagrams, constructing a database, and importing the plurality of preset crop model diagrams into the database to obtain a characteristic database;

s304: acquiring crop real-time image information of each migration direction in a preset range, and constructing a crop real-time model diagram in the migration direction according to the crop real-time image information;

s306: importing the crop real-time model diagram into the characteristic database, calculating the similarity between the crop real-time model diagram and various preset crop model diagrams through a Euclidean distance algorithm to obtain a plurality of similarities, and comparing the similarities with the preset similarities;

s308: if the similarity is not greater than the preset similarity, indicating that the crops planted in the migration direction are not of the preset type, and marking the migration direction as a non-early-warning area;

s310: if at least one similarity is larger than the preset similarity, the condition that the crops planted in the migration direction are the preset type of crops is indicated, and the migration direction is marked as an early warning area.

It should be noted that with regard to perfluorinated compounds, different types of crops have different absorption and enrichment capacities, and in general, root vegetables (e.g. carrots, potatoes) and leaf vegetables (e.g. spinach, salad) may be more sensitive to PFAS in the soil, as their roots and leaves are in direct contact with the soil. In contrast, some nuts, fruits and beans may be less susceptible to PFAS. Thus, in determining whether the perfluorinated compounds in each migration direction would endanger the corresponding crop, consideration may be given to the actual crop type of the crop.

The preset crop model diagram is a crop model diagram of root vegetables, leaf vegetables and the like, and the model diagram can be directly obtained in a big data network or can be drawn in three-dimensional software by a technician. The crop real-time image information of each migration direction in a preset range can be obtained through an unmanned aerial vehicle shooting technology or a remote sensing technology, and then a crop real-time model diagram is constructed based on a three-dimensional point cloud mode. Euclidean distance algorithms measure similarity between two models by calculating the distance between corresponding vertices in the two three-dimensional models, and then combining these distances into one total or average distance. The crops of the preset type are crops such as root vegetables, leaf vegetables and the like which are easy to be polluted by perfluorinated compounds. If the similarity is not greater than the preset similarity, the crops planted in the migration direction are not the preset type of crops, the crops in the migration direction are not easily affected by the perfluorinated compounds, and the migration direction is marked as a non-early-warning area. If at least one similarity is larger than the preset similarity, the crops planted in the migration direction are of the preset type, the crops in the migration direction are easily affected by perfluorinated compounds, and the migration direction is marked as an early warning area.

If the early warning area is the early warning area, early warning judgment is carried out on the early warning area to judge whether the perfluorinated compounds in the early warning area endanger crops or not, specifically:

If a certain migration direction is an early warning area, it is indicated that crops such as root vegetables and leaf vegetables which are easy to be polluted by perfluorinated compounds exist in the early warning area, at the moment, the crop type and the growth period of the crops in the early warning area are further identified according to the crop real-time model diagram, and then the predicted growth rate of the crops in the early warning area is searched in a big data network, so that the mature time node of the crops in the early warning area is calculated; calculating a predicted time node of the migration of the perfluorinated compounds to the crop position area according to the average migration speed and the real-time pollution position of the perfluorinated compounds; if the mature time node of the crops in the early warning area is larger than the predicted time node of the perfluoro compound migrating to the crop position area, the perfluoro compound migrates on the crop area before the crops in the early warning area are ripe and picked, so that the crops are polluted, alarm information needs to be generated, and technicians are informed to formulate corresponding pollution control and emergency response strategies so as to avoid the crops from being polluted. If a barrier can be added on the migration path of the perfluorinated compounds, the migration direction of the perfluorinated compounds can be changed, and crops are prevented from being polluted. By the method, whether crops planted in each migration direction area are affected by pollution of perfluorinated compounds can be rapidly identified, and the method is helpful for intelligently distributing funds, manpower and equipment to deal with pollution problems, so that the treatment cost can be reduced, and the efficient use of resources is ensured.

In addition, in the perfluoro compound pollution evaluation method based on the internet of things, a crop real-time model diagram in the migration direction is constructed according to the crop real-time image information, and specifically comprises the following steps:

performing feature extraction processing on the crop real-time image information through an ORB algorithm to obtain a plurality of feature points; searching out the center point of the crop in the crop real-time image information;

constructing a coordinate system according to the center point, introducing a plurality of characteristic points into the coordinate system, acquiring point coordinate values corresponding to the characteristic points in the coordinate system, and calculating based on the coordinate values to obtain Euclidean distance between the characteristic points and the center point;

comparing the Euclidean distance between each characteristic point and the central point with a preset threshold value, and eliminating the characteristic points corresponding to the Euclidean distance larger than the preset threshold value to eliminate the outlier characteristic points, so as to obtain outlier screened characteristic points;

and acquiring three-dimensional point cloud data of the feature points after outlier screening, registering the three-dimensional point cloud data, performing rigid body transformation on the three-dimensional point cloud data to enable each three-dimensional point cloud data to be represented by a unified coordinate system, and performing gridding treatment on the three-dimensional point cloud data to obtain a crop real-time model map.

It should be noted that, after the real-time image information of the crop is obtained, the feature points of the crop in the real-time image information of the crop are extracted, and because the feature point drift phenomenon exists in the extraction process, the outlier feature points need to be screened out to improve the modeling accuracy. The crop model diagram can be quickly constructed and obtained by the method, the obtained model is high in precision, and the reliability of the model pairing result can be improved.

In addition, the perfluorinated compound pollution evaluation method based on the Internet of things further comprises the following steps:

acquiring toxic effects of perfluorinated compounds on different types of plants through a big data network, constructing a knowledge graph, and importing the toxic effects of perfluorinated compounds on different types of plants into the knowledge graph;

acquiring plant image information in a preset area of preset sampling points through a remote sensing technology, and identifying the plant image information to identify whether toxic effect conditions occur on plants in the preset area of each preset sampling point;

if a toxic effect condition occurs in plants in a preset area of a certain preset sampling point, marking the preset sampling point as a pollution correction mark sampling point;

Retrieving from the first and second perfluorinated compound profiles whether the modified contamination label sampling point has been marked as a contamination label sampling point;

and if the corrected pollution mark sampling point is not marked as the pollution mark sampling point, correcting the first perfluorinated compound distribution situation map and the second perfluorinated compound distribution situation map according to the corrected pollution mark sampling point.

The toxic effect means an adverse effect or damage of the perfluoro compound on plants and the like. These effects may occur immediately after exposure to the toxic substances or may develop after prolonged exposure. The nature and severity of the toxic effects depends on many factors including exposure dose, exposure time, exposure route, characteristics and health of the organism, etc. PFAS can exert toxic effects on plants, impairing the cellular structure and function of the plants, and thus may cause symptoms such as leaf yellowing, spotting, dead spots, etc. According to the method, whether the perfluorinated compounds migrate to a certain preset sampling point can be rapidly estimated by combining the phytotoxicity effect, so that the pollution condition of each preset sampling point is corrected, the condition that the sampling point is polluted by missing marks due to missing sampling of the preset sampling point or detection errors is avoided, and the migration estimation precision of the perfluorinated compounds is improved.

obtaining the volatilization rate of the perfluorinated compounds under various preset environmental factor combination conditions through a big data network;

constructing a second database, and importing the volatilization rate of the perfluorinated compound under the combination condition of various preset environmental factors into the second database to obtain a second characteristic database;

acquiring actual environmental factors of an early warning area in a preset time period, importing the actual environmental factors into the second characteristic database, and calculating the association degrees between the actual environmental factors and various preset environmental factor combinations through a gray association analysis method to obtain a plurality of association degrees;

constructing a sorting table, inputting a plurality of relevance degrees into the sorting table for numerical value sorting, and extracting the maximum relevance degree after sorting is completed;

acquiring a preset environment factor combination corresponding to the maximum association degree, and determining the predicted volatilization rate of the perfluorinated compound in the early warning area under the condition of the actual environment factor according to the preset environment factor combination corresponding to the maximum association degree;

and correcting the average migration speed of the early warning area according to the predicted volatilization rate of the perfluorinated compound in the early warning area under the condition of an actual environmental factor.

Wherein the environmental factors include temperature, humidity, wind speed, gas convection, and the like.

The temperature is an important factor affecting volatilization of the perfluoro compound. At low temperatures, the rate of volatilization of PFAS is generally low, as lower temperatures result in stronger intermolecular forces that are not easily overcome, slowing the volatilization process. Conversely, at high temperatures, the volatility may increase because the molecules more readily gain enough energy to overcome intermolecular forces. Aerodynamic conditions, such as wind speed and gas convection, also affect the rate of volatilization of PFAS molecules from the surface into the air. Higher wind speeds or stronger gas convection can increase the mass transfer rate during volatilization. Humidity is the content of water vapor in the air. In high humidity environments, the water vapor molecules may interact with the PFAS molecules to form hydrates or reduce the rate of PFAS volatilization. This may slow the volatilization of the PFAS. The migration rate of PFAS is affected by the PFAS concentration, and PFAS is usually adsorbed on the surface of solid particles in solid media such as soil or rock. At lower PFAS concentrations, adsorption may be weaker and PFAS molecules move relatively easily in the medium. However, as the PFAS concentration increases, the adsorption sites may become progressively saturated, resulting in more PFAS molecules being immobilized on the solid particle surface. This slows the migration rate of PFAS, as fewer molecules are able to enter the aqueous phase and move. Therefore, the average migration speed of the early warning area can be further corrected according to the volatilization characteristics of the perfluorinated compounds under different environmental factors, and the reliability of the evaluation result is improved.

As shown in fig. 4, the second aspect of the present invention discloses a system for evaluating the contamination of a perfluoro compound based on the internet of things, the system for evaluating the contamination of a perfluoro compound comprises a memory 18 and a processor 20, wherein the memory 18 stores a perfluoro compound contamination evaluation method program, and when the perfluoro compound contamination evaluation method program is executed by the processor 20, the following steps are implemented:

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.

Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.

The foregoing is merely illustrative embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the technical scope of the present invention, and the invention should be covered. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims

1. The method for evaluating the pollution of the perfluorinated compounds based on the Internet of things is characterized by comprising the following steps of:

Acquiring crop real-time image information of each migration direction in a preset range, and judging whether each migration direction is an early warning area or not according to the crop real-time image information; if the early warning area is the early warning area, early warning judgment is carried out on the early warning area so as to judge whether the perfluorinated compounds in the early warning area endanger crops;

2. The method for evaluating the pollution of the perfluorinated compounds based on the Internet of things according to claim 1, wherein a preset emission source of a target enterprise is obtained, a monitoring area is determined according to the preset emission source, and a sampling point layout is planned according to the topography condition of the monitoring area, specifically comprising the following steps:

3. The method for evaluating the pollution of the perfluorinated compounds based on the internet of things according to claim 1, wherein each preset sampling point in the sampling point layout diagram is sampled and detected at a first preset time node to obtain a first perfluorinated compound distribution situation diagram, specifically comprising the following steps:

4. The method for evaluating the pollution of the perfluorinated compounds based on the internet of things according to claim 1, wherein each preset sampling point in the sampling point layout diagram is sampled and detected at a second preset time node to obtain a second perfluorinated compound distribution situation diagram, specifically comprising the following steps:

5. The method for evaluating the pollution of the perfluorinated compounds based on the internet of things according to claim 1, wherein the method is characterized in that real-time image information of crops with each migration direction within a preset range is obtained, and whether each migration direction is an early warning area or not is judged according to the real-time image information of the crops, specifically:

6. The method for evaluating the pollution of the perfluorinated compounds based on the internet of things according to claim 1, wherein if the area is an early warning area, the early warning area is subjected to early warning judgment to judge whether the perfluorinated compounds in the early warning area endanger crops, specifically:

7. The system for evaluating the perfluorinated compound pollution based on the Internet of things is characterized by comprising a memory and a processor, wherein a perfluorinated compound pollution evaluation method program is stored in the memory, and when the perfluorinated compound pollution evaluation method program is executed by the processor, the following steps are realized: