CN117853938A - Ecological monitoring system and method based on image recognition - Google Patents
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Abstract
The invention relates to the technical field of ecological environment monitoring, and particularly discloses an ecological monitoring system and method based on image recognition, comprising the following steps: the information acquisition module is used for acquiring ecological image information in the monitoring red line and ecological environment monitoring data corresponding to the image information in real time; the image recognition module is used for recognizing the water area distribution state and the non-water area distribution state in the ecological image information; the analysis module is used for analyzing the water area distribution state and the non-water area distribution state and acquiring an early warning strategy according to an analysis result; the early warning module is used for carrying out regional ecological environment early warning treatment according to an early warning strategy; the data visual service platform is used for visually expressing the ecological monitoring data; according to the invention, the ecological image information is identified, so that the water area distribution state and the non-water area distribution state information in the whole area environment are obtained, and the instantaneity and the accuracy of the ecological monitoring process of the flowing river and lake are improved.
Description
Technical Field
The invention relates to the technical field of ecological environment monitoring, in particular to an ecological monitoring system and method based on image recognition.
Background
Along with the development of scientific and technical means, although the construction of an artificial neural network can ensure the acquisition of monitoring data of the environment in an area, the traditional model cannot monitor the ecological area in real time, and the ecological monitoring under the flowing condition of rivers and lakes is lack of accurate analysis, so that the original ecological monitoring system of the monitoring area is lack of real-time performance and practicability.
In order to avoid the problem of lack of accurate analysis of ecological monitoring under the flowing condition of rivers and lakes in the prior art, the prior layering region division and target recognition method is adopted to improve the definition of the image recognition of the monitoring region and the real-time performance of ecological monitoring, but the monitoring of the flowing rivers and lakes and the nearby ecology is only carried out by adopting a unified image information acquisition mode, so that misjudgment of ecological information of different regions is easy to be caused, and particularly under the condition of complex environment composition structure, the acquired ecological monitoring information needs to be screened and adjusted for a long time, so that a large amount of information acquisition time is wasted; and the output information is easy to be insufficient in real time, and the accuracy of the ecological monitoring data is low.
Disclosure of Invention
The invention aims to provide an ecological monitoring system and method based on image recognition, which solve the following technical problems:
how to improve the real-time performance of the ecological monitoring process of the flowing river and the lake and the accuracy of the monitoring data output.
The aim of the invention can be achieved by the following technical scheme:
an image recognition-based ecological monitoring system comprising:
the information acquisition module is used for acquiring ecological image information in the monitoring red line and ecological environment monitoring data corresponding to the image information in real time;
the image recognition module is used for recognizing the water area distribution state and the non-water area distribution state in the ecological image information;
the analysis module is used for analyzing the water area distribution state and the non-water area distribution state and acquiring an early warning strategy according to an analysis result;
the early warning module is used for carrying out regional ecological environment early warning treatment according to an early warning strategy;
and the data visualization service platform is used for carrying out visual expression on the ecological monitoring data.
Preferably, the specific steps of the image recognition module are as follows:
s1, carrying out gray processing on an ecological image, extracting amphibious features and boundary lines thereof in the ecological image by adopting a Canny algorithm, and dividing the ecological image into a water area and a non-water area;
s2, setting a key frame according to the distribution position characteristics of the water area and the non-water area;
s3, acquiring the water surface gray value of a water area in the key frame in real time, and judging a first state of the key frame according to the water surface gray value;
s4, judging the distribution state of the water area according to the first state information of the corresponding key frame.
Preferably, the image recognition module further comprises:
SS1, collecting standard images of non-water areas in a key frame;
SS2, identifying green block RGB color values and soil distribution RGB color values of preset points of a standard image of the non-water area, and judging a second state of the key frame through the green block RGB color values and the soil distribution RGB color values;
and SS3, judging the distribution state of the non-water area according to the second state information of the corresponding key frame.
Preferably, by the formulaObtain->The->Distribution coefficient of time->And according to the distribution coefficient->GeneratingAn early warning strategy, which is used for carrying out early warning treatment on the regional ecological environment;
wherein,、/>is a weight coefficient, and->、/>Are all greater than 0; />Is->In the individual region->Green quantity distribution state coefficient of time, +.>Is->In the individual region->Soil distribution condition coefficients at the moment; />Is->In the individual region->A time-of-day water level gray value; />The gray value is a standard water surface gray value; />Is->In the individual region->Green blocks and soil distribution influencing functions of the non-water area at moment; />Is->In the individual region->Green block coverage size of the non-water area at the moment.
Preferably, the distribution coefficient isAnd standard threshold [ ]> ，/>]Comparison is performed:
if it is＜/>Generating regional ecological environment early warning information;
if it is≤/>≤/>The current state is maintained;
if it is＞/>And analyzing the ecological environment monitoring data.
Preferably, the analysis process of the ecological environment monitoring data is as follows:
SSS1, acquiring water environment information of a water area and soil environment information of a non-water area according to real-time acquisition ecological environment monitoring data;
SSS2, inputting historical ecological environment monitoring data of different areas into a convolutional neural network for training and constructing an area detection model, and calculating to obtain environment prediction parameters;
SSS3, inputting environment prediction parameters and water environment information of the water area and soil environment information of the non-water area into the area detection model to update and obtain an ecological area real-time monitoring model;
and SSS4, generating water flow distribution information of the water area and soil distribution information of the non-water area according to the data analysis result of the step SSS 3.
Preferably, the information acquisition module receives the monitoring points through the sensors to collect the ecological environment monitoring data in real time.
Preferably, the analysis module is further configured to monitor a water surface environment of the water area:
acquiring the number of plankton in the area of the historical collection water area, and according to a time-varying curve of the number of plankton in the area of the historical collection water area；
Acquiring a time-dependent change curve of plankton number in a water area region in the same time period acquired in real time；
Calculating a curve over a period of timeAnd curve->Corresponding area difference->；
Will beAnd a preset threshold->Comparing, if->≤/>Judging that the water surface environment is good; if->＞/>And judging that the water surface environment is poor.
The ecological monitoring method based on image recognition is applied to an ecological monitoring system based on image recognition, and the specific method comprises the following steps:
the method comprises the steps of firstly, collecting ecological image information in a monitoring red line in real time, and receiving ecological environment monitoring data corresponding to the image information in real time through a sensor;
step two, identifying the water area distribution state and the non-water area distribution state in the ecological image information;
analyzing the water area distribution state and the non-water area distribution state, and acquiring an early warning strategy according to an analysis result;
fourthly, carrying out regional ecological environment early warning treatment according to an early warning strategy, and monitoring the water surface environment of the water area;
and fifthly, constructing a data visualization service platform to realize the visualization expression of the ecological monitoring data.
The invention has the beneficial effects that:
(1) According to the invention, through arranging the information acquisition module, the image recognition module, the analysis module, the early warning module and the data visualization service platform, the connection between the information acquisition module, the image recognition module, the early warning module and the mobile river and lake ecological monitoring system is enhanced through an image recognition technology, and the accuracy and the scientificity of monitoring of the river and lake ecological monitoring system are enhanced and improved.
(2) The ecological image information is identified by the image identification technology of the image identification module, the water area distribution state and the non-water area distribution state in the whole area environment are obtained, and the real-time acquisition of monitoring data is realized; the real-time monitoring and detection process of ecology of the flowing river and lake is realized by analyzing the water area distribution state and the non-water area distribution state information obtained by the image recognition module, then acquiring the early warning strategy according to the analysis result, and realizing the real-time performance and the accuracy of optimizing and updating the environment monitoring model.
Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of an ecological monitoring system based on image recognition according to the present invention;
fig. 2 is a step diagram of an ecological monitoring method for image recognition according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention is an ecological monitoring system based on image recognition, comprising:
the information acquisition module is used for acquiring ecological image information in the monitoring red line and ecological environment monitoring data corresponding to the image information in real time;
the image recognition module is used for recognizing the water area distribution state and the non-water area distribution state in the ecological image information;
the analysis module is used for analyzing the water area distribution state and the non-water area distribution state and acquiring an early warning strategy according to an analysis result;
the early warning module is used for carrying out regional ecological environment early warning treatment according to an early warning strategy;
and the data visualization service platform is used for carrying out visual expression on the ecological monitoring data.
Through above-mentioned technical scheme, this embodiment is in order to solve above-mentioned technical problem, through designing the ecological monitoring system based on image recognition, specifically through setting up information acquisition module, image recognition module, analysis module, early warning module and data visualization's service platform guarantee through the connection between image recognition technology reinforcing and the ecological monitoring system of flowing river and lake, strengthen and improve the accuracy and the scientificalness of the monitoring of ecological monitoring system of river and lake.
Specifically, an information acquisition module is arranged, image information of flowing rivers and lakes and surrounding areas is acquired through images, ecological environment monitoring data of ecological monitoring points is acquired through a wireless sensing technology, the problem existing in current flowing rivers and lakes ecological monitoring is solved through the acquisition of the image information, and an effective path is provided for sustainable development of ecological environment.
An image recognition module is arranged, ecological image information is recognized through an image recognition technology, the water area distribution state and the non-water area distribution state in the whole area environment are obtained, and real-time acquisition of monitoring data is realized; in the process of designing the ecological monitoring of the flowing river and lake, the embodiment considers the difference between the water area and the non-water area, is different from the characteristic extraction process of completing image recognition by training through a convolutional neural network in the prior art, the embodiment divides the water area and the non-water area through image surface and image boundary processing, then processes the real-time water area water surface image according to the water surface flowing characteristic change and the non-water area image according to the land fixed characteristic, and divides the water area water surface image into a plurality of continuous boundaries or uniformly distributed discontinuous regular areas for carrying out real-time dynamic information characteristic extraction, the embodiment considers the risk of boundary interference and information superposition, temporarily does not consider the overlapping condition of the divided areas, the default divided regular areas are rectangular frames with a plurality of sizes, the area is certain, the frames are continuously and uniformly distributed, and the situation of boundary overlapping does not exist.
The analysis module is arranged to realize the integration of the water area distribution state and the non-water area distribution state and the refinement analysis of the ecological state, specifically, the water area distribution state and the non-water area distribution state information obtained by the image recognition module are analyzed, then the early warning strategies are obtained according to analysis results, the real-time monitoring and detection process of the ecology of the flowing river and lake is realized by analyzing the early warning strategies of different monitoring areas, and the real-time performance and the accuracy of the optimization and the updating of the environment monitoring model are realized.
And an early warning module is further arranged, an area ecological environment result is obtained by analyzing an early warning strategy of the monitoring area, the early warning module is arranged to realize early warning treatment on the result which does not meet the requirement, and the real-time ecological damage probability of the environment is reduced.
Finally, a data visualization service platform is further arranged, the ecological monitoring data are visually expressed, the user service end and the environment detection staff dynamically acquire real-time information of the served area or the monitoring area, visual presentation effect of environmental results of the ecological area is achieved, and real-time recording accuracy of the ecological monitoring data is improved.
As an embodiment of the present invention, the image recognition module specifically includes:
s1, carrying out gray processing on an ecological image, extracting amphibious features and boundary lines thereof in the ecological image by adopting a Canny algorithm, and dividing the ecological image into a water area and a non-water area;
s2, setting a key frame according to the distribution position characteristics of the water area and the non-water area;
s3, acquiring the water surface gray value of a water area in the key frame in real time, and judging a first state of the key frame according to the water surface gray value;
s4, judging the distribution state of the water area according to the first state information of the corresponding key frame.
According to the technical scheme, the ecological information is extracted through the image recognition module, specifically, the method comprises the steps of firstly carrying out gray processing on an ecological image, extracting land and water features and boundary lines of the land and water features in the ecological image by adopting a Canny algorithm, and dividing the ecological image into a water area and a non-water area; in order to facilitate the analysis and refinement of the regional state and the refinement of the monitoring target, a key frame is arranged, wherein the key frame is a regular monitoring region with a rectangular shape or a polygonal shape, the key frame is arranged to ensure that the distribution position characteristics according to the water area and the non-water area are fully distinguished, and the monitoring accuracy is ensured; then, acquiring the water surface gray value of a water area in the key frame in real time, and judging a first state of the key frame according to the water surface gray value, wherein the water surface of the water area has fluidity, the gray system value is acquired in real time according to the brightness of the water surface, namely the image color depth degree in the graying treatment, by acquiring the water surface information in real time; and finally, judging the distribution state of the water area according to the first state information of the corresponding key frames, wherein the corresponding key frames are matched in the monitoring process because the water area sizes and the distribution area sizes of the different key frames are different.
As an embodiment of the present invention, the image recognition module further includes:
SS1, collecting standard images of non-water areas in a key frame;
SS2, identifying green block RGB color values and soil distribution RGB color values of preset points of a standard image of the non-water area, and judging a second state of the key frame through the green block RGB color values and the soil distribution RGB color values;
and SS3, judging the distribution state of the non-water area according to the second state information of the corresponding key frame.
Through the technical scheme, besides the identification of the distribution state information of the water area, the non-water area distribution state information is also required to be identified, and the specific identification steps are as follows: firstly, collecting standard images of non-water areas in a key frame; and then, recognizing green block RGB color values and soil distribution RGB color values of preset points of a standard image of the non-water area in a key frame, judging a second state of the key frame through the green block RGB color values and the soil distribution RGB color values, particularly, considering the influence of greening distribution areas and greening coverage rates of surrounding water areas on the ecological environment in the analysis of the non-water area, wherein the green block distribution and the certain soil color values of the environment meeting the preset monitoring area river and lake ecological health standard under a certain greening coverage rate can enable the environment to reach the optimal state, and the condition that the damage to the ecological environment is irreversible under the critical state or over the critical state is judged by comprehensively analyzing the green block RGB color values and the soil distribution RGB color values, so that the current non-water area is distributed and analyzed, and finally, the non-water area distribution state is judged according to the corresponding second state information of the key frame.
As an embodiment of the present invention, the method is represented by the formulaObtain->The->Distribution coefficient of time->And according to the distribution coefficient->Generating an early warning strategy according to the pre-setThe warning strategy carries out early warning treatment on the regional ecological environment;
wherein,、/>is a weight coefficient, and->、/>Are all greater than 0; />Is->In the individual region->Green quantity distribution state coefficient of time, +.>Is->In the individual region->Soil distribution condition coefficients at the moment; />Is->In the individual region->A time-of-day water level gray value; />The gray value is a standard water surface gray value; />Is->In the individual region->Green blocks and soil distribution influencing functions of the non-water area at moment; />Is->In the individual region->Green block coverage size of the non-water area at the moment.
According to the technical scheme, in order to realize accurate analysis of the water area distribution state and the non-water area distribution state by the analysis module, the embodiment provides the distribution coefficients of different monitoring areas at specific moments, and the distribution coefficients are physical quantities used for describing the distribution capacity of chemical substances in two different phases; the analysis is specifically performed through the distribution condition coefficient of the green amount of the area, the distribution condition coefficient of the soil of the area and the gray level value of the water surface, wherein the distribution condition coefficient is obtained by fitting in the actual measuring and calculating process according to the green amount and the distribution state value of the soil, and the calculation process is not repeated in the prior art.
By the formulaObtain->The->Distribution coefficient of time->Distribution coefficient->Can reflect the distribution characteristics of static non-water area and dynamic water area, wherein +.>The method is used for judging the rationality of the ecological feature distribution of the non-water area according to the function obtained by the average value of the green block and soil distribution relation of the non-water area in different monitoring areas as a distribution influence function, so that the judgment accuracy of the distribution coefficient in the specific time of the monitoring area is improved.
In addition, the weight coefficient、/>The method is characterized in that the method is respectively provided with empirical data obtained by respectively setting the influence degree of plant distribution and soil property factors, which are judged by actual empirical analysis and affect the ecological environment of a specific region, on the characteristic distribution coefficient and considering the influence of the gray value of the water surface on the distribution coefficient in the actual measurement and calculation process.
As one embodiment of the invention, the distribution coefficient isAnd standard threshold [ ]>，/>]Comparison is performed:
if it is＜/>Generating regional ecological environment early warning information;
if it is≤/>≤/>The current state is maintained;
if it is＞/>And analyzing the ecological environment monitoring data.
Through the technical scheme, the early warning strategy is obtained according to the analysis result of the analysis module on the water area distribution state and the non-water area distribution state, and further, the distribution coefficient is obtainedDetermining the distribution state of the comprehensive river and lake environment area, and adding the distribution coefficient +.>Comparing the size with the standard threshold value to determine when +.>＜/>Generating regional ecological environment early warning information when +.>≤/>≤/>The current state is maintained; when->＞/>And further analyzing the monitored ecological environment monitoring data.
As one embodiment of the present invention, the analysis process of the ecological environment monitoring data is:
SSS1, acquiring water environment information of a water area and soil environment information of a non-water area according to real-time acquisition ecological environment monitoring data;
SSS2, inputting historical ecological environment monitoring data of different areas into a convolutional neural network for training and constructing an area detection model, and calculating to obtain environment prediction parameters;
SSS3, inputting environment prediction parameters and water environment information of the water area and soil environment information of the non-water area into the area detection model to update and obtain an ecological area real-time monitoring model;
and SSS4, generating water flow distribution information of the water area and soil distribution information of the non-water area according to the data analysis result of the step SSS 3.
Through the above technical scheme, the method for updating the detection model of the preset area by analyzing the ecological environment monitoring data in the embodiment comprises the following specific processes: firstly, acquiring water environment information of a water area and soil environment information of a non-water area according to real-time acquisition ecological environment monitoring data; then, inputting the historical ecological environment monitoring data of different areas into a convolutional neural network for training and constructing an area detection model, and calculating to obtain environment prediction parameters; then, inputting environmental prediction parameters and water environment information of the water area and soil environment information of the non-water area into an area detection model to update and obtain an ecological area real-time monitoring model; finally, generating water flow distribution information of the water area and soil distribution information of the non-water area according to the analysis result of the last step; and updating the ecological area real-time monitoring model according to the existing area detection model, realizing the training of the historical ecological environment monitoring data according to the combination of the historical ecological environment monitoring data and the convolutional neural network, and completing the construction and the timely updating of the area detection model.
As one implementation mode of the invention, the information acquisition module receives monitoring points through the sensor to collect ecological environment monitoring data in real time.
By the technical scheme, the information acquisition module in the embodiment receives monitoring points through the sensors to collect ecological environment monitoring data in real time, acquires various data of river and lake ecological areas of the monitoring points through the sensors, completes the transmission process of the acquired data through ZigBee, and finally manages different servers according to the acquired data; the detection data comprise illumination intensity, air humidity, soil temperature, electrolyte content in the soil and the like.
As an embodiment of the present invention, the analysis module is further configured to monitor a water surface environment of the water area:
acquiring the number of plankton in the area of the historical collection water area, and according to a time-varying curve of the number of plankton in the area of the historical collection water area；
Acquiring a time-dependent change curve of plankton number in a water area region in the same time period acquired in real time；
Calculating a curve over a period of timeAnd curve->Corresponding area difference->；
Will beAnd a preset threshold->Comparing, if->≤/>Judging that the water surface environment is good; if->＞/>And judging that the water surface environment is poor.
Through the above technical scheme, the method for monitoring the water surface environment of the water area by the analysis module of the embodiment further comprises the following steps: firstly, acquiring the number of plankton in a historical acquisition water area, and according to a time-varying curve of the number of plankton in the historical acquisition water areaThe method comprises the steps of carrying out a first treatment on the surface of the Then, the time-dependent curve of the plankton number in the water area within the same time period acquired in real time is acquired +.>The method comprises the steps of carrying out a first treatment on the surface of the Then, calculate the curve for a period of time +.>And curve->Corresponding area difference->The method comprises the steps of carrying out a first treatment on the surface of the Finally, will->And a preset threshold->Comparing, if->≤/>Judging that the water surface environment is good; if->＞/>And judging that the water surface environment is poor.
The invention also designs an ecological monitoring method based on image recognition, which is applied to the ecological monitoring system based on image recognition, and referring to fig. 2, the specific method comprises the following steps:
the method comprises the steps of firstly, collecting ecological image information in a monitoring red line in real time, and receiving ecological environment monitoring data corresponding to the image information in real time through a sensor;
step two, identifying the water area distribution state and the non-water area distribution state in the ecological image information;
analyzing the water area distribution state and the non-water area distribution state, and acquiring an early warning strategy according to an analysis result;
fourthly, carrying out regional ecological environment early warning treatment according to an early warning strategy, and monitoring the water surface environment of the water area;
and fifthly, constructing a data visualization service platform to realize the visualization expression of the ecological monitoring data.
The foregoing is merely illustrative and explanatory of the principles of the invention, as various modifications and additions may be made to the specific embodiments described, or similar thereto, by those skilled in the art, without departing from the principles of the invention or beyond the scope of the appended claims.
Claims (9)
1. An ecological monitoring system based on image recognition, comprising:
the information acquisition module is used for acquiring ecological image information in the monitoring red line and ecological environment monitoring data corresponding to the image information in real time;
the image recognition module is used for recognizing the water area distribution state and the non-water area distribution state in the ecological image information;
the analysis module is used for analyzing the water area distribution state and the non-water area distribution state and acquiring an early warning strategy according to an analysis result;
the early warning module is used for carrying out regional ecological environment early warning treatment according to an early warning strategy;
and the data visualization service platform is used for carrying out visual expression on the ecological monitoring data.
2. The image recognition-based ecological monitoring system according to claim 1, wherein the specific steps of the image recognition module are:
s1, carrying out gray processing on an ecological image, extracting amphibious features and boundary lines thereof in the ecological image by adopting a Canny algorithm, and dividing the ecological image into a water area and a non-water area;
s2, setting a key frame according to the distribution position characteristics of the water area and the non-water area;
s3, acquiring a water surface gray value of a preset water area in the key frame in real time, and judging a first state of the key frame according to the water surface gray value;
s4, judging the distribution state of the water area according to the first state information of the corresponding key frame.
3. The image recognition-based ecological monitoring system of claim 2, wherein the image recognition module further comprises:
SS1, collecting standard images of non-water areas in a key frame;
SS2, identifying green block RGB color values and soil distribution RGB color values of preset points of a standard image of the non-water area, and judging a second state of the key frame through the green block RGB color values and the soil distribution RGB color values;
and SS3, judging the distribution state of the non-water area according to the second state information of the corresponding key frame.
4. The image recognition-based ecological monitoring system of claim 1, wherein the image recognition-based ecological monitoring system is characterized by the formulaObtain->The->Distribution coefficient of time->And according to the distribution coefficient->Generating an early warning strategy, and carrying out early warning treatment on the regional ecological environment according to the early warning strategy;
wherein,、/>is a weight coefficient, and->、/>Are all greater than 0; />Is->In the individual region->Green quantity distribution state coefficient of time, +.>Is->In the individual region->Soil distribution condition coefficients at the moment; />Is->In the individual region->A time-of-day water level gray value; />The gray value is a standard water surface gray value; />Is->In the individual region->Green blocks and soil distribution influencing functions of the non-water area at moment; />Is->In the individual region->Green block coverage size of the non-water area at the moment.
5. The image recognition based ecological monitoring system of claim 4, wherein the distribution coefficients are calculated byAnd standard threshold [ ]> ，/>]Comparison is performed:
if it is＜/>Generating regional ecological environment early warning information;
if it is≤/>≤/>The current state is maintained;
if it is＞/>And analyzing the ecological environment monitoring data.
6. The image recognition-based ecological monitoring system of claim 5, wherein the analysis process of the ecological environment monitoring data is:
SSS1, acquiring water environment information of a water area and soil environment information of a non-water area according to real-time acquisition ecological environment monitoring data;
SSS2, inputting historical ecological environment monitoring data of different areas into a convolutional neural network for training and constructing an area detection model, and calculating to obtain environment prediction parameters;
SSS3, inputting environment prediction parameters and water environment information of the water area and soil environment information of the non-water area into the area detection model to update and obtain an ecological area real-time monitoring model;
and SSS4, generating water flow distribution information of the water area and soil distribution information of the non-water area according to the data analysis result of the step SSS 3.
7. The image recognition-based ecological monitoring system of claim 1, wherein the information acquisition module receives monitoring points through sensors to collect ecological environment monitoring data in real time.
8. The image recognition-based ecological monitoring system of claim 1, wherein the analysis module is further configured to monitor a water surface environment of a water area:
acquiring the number of plankton in the area of the historical collection water area, and according to a time-varying curve of the number of plankton in the area of the historical collection water area；
Acquiring a time-dependent change curve of plankton number in a water area region in the same time period acquired in real time；
Calculating a curve over a period of timeAnd curve->Corresponding area difference->；
Will beAnd a preset threshold->Comparing, if->≤/>Judging that the water surface environment is good; if->＞/>And judging that the water surface environment is poor.
9. An image recognition-based ecological monitoring method, which is applied to the image recognition-based ecological monitoring system as claimed in any one of claims 1 to 8, and comprises the following steps:
the method comprises the steps of firstly, collecting ecological image information in a monitoring red line in real time, and receiving ecological environment monitoring data corresponding to the image information in real time through a sensor;
step two, identifying the water area distribution state and the non-water area distribution state in the ecological image information;
analyzing the water area distribution state and the non-water area distribution state, and acquiring an early warning strategy according to an analysis result;
fourthly, carrying out regional ecological environment early warning treatment according to an early warning strategy, and monitoring the water surface environment of the water area;
and fifthly, constructing a data visualization service platform to realize the visualization expression of the ecological monitoring data.
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