CN113673970B

CN113673970B - Distributed node-based water quality report generation method and electronic equipment

Info

Publication number: CN113673970B
Application number: CN202111219181.3A
Authority: CN
Inventors: 全绍军; 林格; 陈小燕; 梁少玲
Original assignee: Longse Technology Co ltd
Current assignee: Longse Technology Co ltd
Priority date: 2021-10-20
Filing date: 2021-10-20
Publication date: 2022-02-22
Anticipated expiration: 2041-10-20
Also published as: CN113673970A; WO2023065622A1; ZA202305525B

Abstract

The invention is suitable for the technical field of data processing, and provides a method for generating a water quality report based on distributed nodes and electronic equipment, wherein the method comprises the following steps: receiving real-time water condition videos fed back by all distributed nodes deployed in a target drainage basin; acquiring water quality index information associated with the target basin; importing the real-time water condition video into a water quality index analysis algorithm associated with the water quality index information, and outputting water quality index parameters corresponding to the water quality indexes of the target basin determined based on the distributed nodes; calculating the water quality grade of the target basin according to the confidence coefficient weights, the weighting weights and the water quality index parameters of all the real-time water condition videos; and generating a water quality report of the target basin based on the water quality grade. By adopting the method and the device, the contribution of the real-time water condition video at the position with higher confidence coefficient in the water quality grade calculation can be improved, and the accuracy of the water quality grade is further improved.

Description

Distributed node-based water quality report generation method and electronic equipment

Technical Field

The invention belongs to the technical field of data processing, and particularly relates to a distributed node-based water quality report generation method and electronic equipment.

Background

In recent years, with the rapid development of society, the use demand of human beings for natural resources is increasing, and the water resource demand amount which is closely related to human beings is particularly prominent. However, due to the intervention of human activities, the quality of water resources is always deteriorated, the health of the masses is affected and damaged, and the sustainable development of the economy and the society is not facilitated. Therefore, the work of preventing and controlling water resource pollution is urgent. The water quality monitoring is an important link of water pollution prevention and treatment work, and plays an important role in water pollution early warning, pollutant monitoring, treatment, evaluation and prevention.

The existing water quality report generation technology generally carries out water quality assessment on collected water body samples through the manual work of experts after water resources are sampled, and generates corresponding water quality reports. Therefore, the existing water quality report generation method can be completed by a large number of experts with professional knowledge, the labor cost is high, and the report generation efficiency is low.

Disclosure of Invention

In view of this, embodiments of the present invention provide a method for generating a water quality report based on distributed nodes and an electronic device, so as to solve the problems that the existing water quality report generation technology needs a large amount of experts with professional knowledge to complete, the labor cost is high, and the report generation efficiency is low.

The first aspect of the embodiments of the present invention provides a method for generating a water quality report based on distributed nodes, including:

receiving real-time water condition videos fed back by all distributed nodes deployed in a target drainage basin; each real-time water condition video is configured with a corresponding confidence coefficient weight;

acquiring water quality index information associated with the target basin; the water quality index information comprises at least one water quality index and a weighting weight related to the water quality index;

importing the real-time water condition video into a water quality index analysis algorithm associated with the water quality index information, and outputting water quality index parameters corresponding to the water quality indexes of the target basin determined based on the distributed nodes;

calculating the water quality grade of the target basin according to the confidence coefficient weights, the weighting weights and the water quality index parameters of all the real-time water condition videos;

and generating a water quality report of the target basin based on the water quality grade.

A second aspect of the embodiments of the present invention provides a device for generating a water quality report based on distributed nodes, including:

the real-time water condition video receiving unit is used for receiving real-time water condition videos fed back by all distributed nodes deployed in a target basin; each real-time water condition video is configured with a corresponding confidence coefficient weight;

a water quality index information acquisition unit for acquiring water quality index information associated with the target basin; the water quality index information comprises at least one water quality index and a weighting weight related to the water quality index;

a water quality index parameter determination unit, configured to import the real-time water condition video into a water quality index analysis algorithm associated with the water quality index information, and output a water quality index parameter corresponding to each water quality index of the target basin determined based on the distributed nodes;

the water quality grade calculation unit is used for calculating the water quality grade of the target basin according to the confidence coefficient weights, the weighting weights and the water quality index parameters of all the real-time water condition videos;

and the water quality report generating unit is used for generating a water quality report of the target basin based on the water quality grade.

A third aspect of embodiments of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the first aspect when executing the computer program.

A fourth aspect of embodiments of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, performs the steps of the first aspect.

The embodiment of the invention provides a method for generating a water quality report based on distributed nodes and an electronic device, which have the following beneficial effects:

the embodiment of the invention deploys corresponding distributed nodes at a plurality of positions of a target basin and collects corresponding real-time water condition videos, so that the water quality of the whole target basin can be detected through the real-time water condition videos, before the water quality detection is carried out, the water quality index information corresponding to the target basin is determined, the real-time water condition videos are analyzed through a water quality index analysis algorithm associated with the water quality index information, the water quality index parameters corresponding to a plurality of water quality index dimensions of the real-time water condition videos are determined, the water quality grade corresponding to the target basin can be calculated according to the confidence weight corresponding to the real-time water condition videos, the weighting weight associated with the water quality index and the water quality index parameters, and the water quality report is generated based on the water quality grade, so that the purpose of automatically generating the water quality report is realized. Compared with the existing water quality report generation technology, the embodiment of the application does not depend on experts to perform water quality detection on a water body sample, but can analyze the real-time water condition videos through a water quality index analysis algorithm associated with water quality index information of a target basin, determine water quality index parameters corresponding to the real-time water condition videos, determine corresponding confidence weights according to the deployment positions of the real-time water condition videos, improve the contribution of the real-time water condition videos at the positions with higher confidence degrees in water quality level calculation, further improve the accuracy of the water quality level, configure different weighting weights for different water quality indexes of the target basin according to different focuses of the target basin, realize the matching of the water quality level and the detection content of the target basin, and improve the accuracy and flexibility of water quality report generation.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions 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 it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

Fig. 1 is a flow chart of an implementation of a method for generating a water quality report based on distributed nodes according to a first embodiment of the present invention;

fig. 2 is a flowchart of a specific implementation of a method for generating a water quality report based on distributed nodes according to a second embodiment of the present invention;

FIG. 3 is a schematic diagram illustrating a multi-angle acquisition of real-time water condition video according to an embodiment of the present application;

FIG. 4 is a schematic structural diagram of a confidence level recognition network according to an embodiment of the present application;

fig. 5 is a flowchart of a detailed implementation of a method S201 for generating a water quality report based on distributed nodes according to a third embodiment of the present invention;

fig. 6 is a flowchart of a specific implementation of the method S104 for generating a water quality report based on distributed nodes according to a fourth embodiment of the present invention;

fig. 7 is a flowchart of a concrete implementation of the method S102 for generating a water quality report based on distributed nodes according to a fifth embodiment of the present invention;

fig. 8 is a flowchart of a concrete implementation of the method S105 for generating a water quality report based on distributed nodes according to a fifth embodiment of the present invention;

fig. 9 is a flowchart of a concrete implementation of a method S101 for generating a water quality report based on distributed nodes according to a fifth embodiment of the present invention;

fig. 10 is a block diagram of a device for generating a water quality report based on distributed nodes according to an embodiment of the present invention;

fig. 11 is a schematic diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

In recent years, with the rapid development of society, the use demand of human beings for natural resources is increasing, and the water resource demand amount which is closely related to human beings is particularly prominent. However, due to the intervention of human activities, the quality of water resources is always deteriorated, the health of the masses is affected and damaged, and the sustainable development of the economy and the society is not facilitated. Therefore, the work of preventing and controlling water resource pollution is urgent. The water quality monitoring is an important link of water pollution prevention and treatment work, and plays an important role in water pollution early warning, pollutant monitoring, treatment, evaluation and prevention. The water quality evaluation sets a weight for each water quality index through various means, and the quantification of the water resource quality is realized, so that the purpose of water quality supervision is achieved. The existing main means is to determine the weight of the parameter according to its environmental importance and the guidance value suggested by experts. But often the weights for the same parameter vary widely between different approaches, indicating that assigning appropriate weight values is difficult. On the whole, a large amount of professional knowledge is needed to balance the water quality indexes, the labor cost is high, and the popularization rate is low.

The embodiment of the invention deploys corresponding distributed nodes at a plurality of positions of a target basin and collects corresponding real-time water condition videos, can carry out water quality detection on the whole target basin through the real-time water condition videos, determines water quality index information corresponding to the target basin before carrying out water quality detection, analyzes the real-time water condition videos through a water quality index analysis algorithm associated with the water quality index information, determines water quality index parameters corresponding to a plurality of water quality index dimensions of the real-time water condition videos, can calculate the water quality grade corresponding to the target basin according to the confidence weight corresponding to the real-time water condition videos, the weighting weight associated with the water quality indexes and the water quality index parameters, and generates a water quality report based on the water quality grade, thereby realizing the purpose of automatically generating the water quality report, solving the problem that the existing generation technology of the water quality report can be completed only by a large number of experts with professional knowledge, the labor cost is high, and the report generation efficiency is low.

In the embodiment of the present invention, the main execution body of the process is an electronic device, and the electronic device includes but is not limited to: the device comprises a server, a computer, a smart phone, a notebook computer, a tablet computer and the like, and can execute the generation process of the water quality report. Fig. 1 shows an implementation flowchart of a method for generating a water quality report based on distributed nodes according to a first embodiment of the present invention, which is detailed as follows:

in S101, receiving real-time water condition videos fed back by all distributed nodes deployed in a target drainage basin; each of the real-time water condition videos is configured with a corresponding confidence weight.

In this embodiment, the target watershed may be an area with a certain amount of water, such as a river, a stream, a river, a lake, or a sea outlet. In the watershed of the type, because the water body flows, the water quality is in a dynamic state, and therefore, the water quality of the watershed needs to be detected regularly or in real time to determine the water quality condition of the watershed.

In this embodiment, due to the mobility of water, in order to improve the accuracy of water quality detection, the electronic device may establish a communication connection with a plurality of distributed nodes, and obtain real-time water condition videos fed back by different distributed nodes, so that water quality monitoring may be performed at a plurality of monitoring points (i.e., positions where the distributed nodes are placed), and more comprehensive water quality assessment may be obtained. Each distributed node can acquire the real-time water condition video of the corresponding position, and feeds back the acquired real-time water condition video to the electronic equipment through communication connection between the distributed node and the electronic equipment.

In this embodiment, the distributed node is configured with a camera module, and the camera module may be specifically located in the target watershed, and may acquire a real-time water condition video of the target watershed. Optionally, the distributed node may be configured with a video optimization algorithm, and before sending the real-time water condition video to the electronic device, the distributed node may optimize the original video through the video optimization algorithm and send the optimized video (i.e., the real-time water condition video) to the electronic device. For example, the distributed node may determine an environmental compensation coefficient according to the collection time and the average pixel mean value of the collected original video, and adjust the pixel value of each pixel in the original video and the contrast of each video image frame in the original video based on the environmental compensation coefficient, so as to generate the corresponding real-time water condition video.

In a possible implementation manner, the distributed node may adjust the working mode of the camera module according to the acquisition time, for example, during daytime acquisition, the camera module may be set to a full-color working mode; if gather at night, then can set up camera module into night mode.

In a possible implementation manner, the electronic device may send a video feedback instruction to the distributed nodes when the water quality analysis report needs to be generated. After receiving the video feedback instruction, the distributed node can send the acquired real-time water quality video to the electronic equipment. The distributed nodes can set effective feedback time, and the distributed nodes can acquire videos from a certain time before the distributed nodes receive the video feedback instructions to the time when the distributed nodes receive the video feedback instructions and feed the videos back to the electronic equipment as real-time water condition videos; and the difference value between the certain moment and the moment when the video feedback instruction is received is the effective feedback time.

In a possible implementation manner, a long connection may be established between the distributed node and the electronic device, the distributed node may send a video (i.e., a real-time water condition video) acquired in real time to the electronic device through the long connection, and the electronic device may configure corresponding video databases for different distributed nodes and store the received real-time water condition video in the associated video database.

In S102, acquiring water quality index information associated with the target basin; the water quality index information includes at least one water quality index and a weighting weight associated with the water quality index.

In this embodiment, different target basins are focused differently, and different water quality index information may be associated with different target basins in order to perform water quality detection on different basins according to actual conditions and generate corresponding water quality reports. The types and the numbers of the water quality indexes contained in different water quality index information are different, and the weighting weights associated with different water quality indexes can also be different.

For example, for the first target basin, the associated water quality indicator information may include: water temperature, pH value and suspended solid density, the corresponding weighting weight is respectively: 0.3, 0.5 and 0.2; for the second target basin, the associated water quality index information may include: ph, turbidity and suspended solids density, corresponding to a weight of 0.4, 0.2 and 0.4, respectively. As can be seen, the target basins have different points of interest, and the included water quality indicators may be different, and even if the same water quality indicator exists, the corresponding weighting weights may be different.

In this embodiment, the electronic device may store a corresponding relationship between the target watershed and the water quality index information, and the electronic device may query the corresponding relationship according to the watershed identifier of the target watershed to determine the water quality index information corresponding to the target watershed.

In S103, the real-time water condition video is imported into a water quality index analysis algorithm associated with the water quality index information, and water quality index parameters corresponding to the water quality indexes of the target basin determined based on the distributed nodes are output.

In this embodiment, the water quality index analysis algorithms are different depending on the water quality index information. After the water quality index information of the target basin is determined, the electronic equipment can acquire a water quality index analysis algorithm associated with the water quality execution information, and analyze the real-time water condition video through the water quality index algorithm to determine water quality index parameters corresponding to different water quality index dimensions.

In a possible implementation manner, the electronic device may identify the water quality index included in the water quality index information, and obtain an analysis algorithm associated with different water quality indexes, where the analysis algorithm associated with the water quality index is used to output a water quality index parameter corresponding to a corresponding water quality index dimension. Illustratively, the water quality index information of a certain target basin includes the following three water quality indexes: temperature, pH value and suspended solid density, when the electronic equipment analyzes the real-time water condition video, three types of water quality index analysis algorithms can be obtained, namely a first analysis algorithm corresponding to a temperature dimension, a second analysis algorithm corresponding to the pH value and a third analysis algorithm corresponding to the suspended solid density, and then water quality index parameters corresponding to different dimensions of the real-time water condition video are respectively determined through the three types of analysis algorithms.

In S104, the water quality level of the target basin is calculated according to the confidence weights, the weighted weights and the water quality index parameters of all the real-time water condition videos.

In this embodiment, since different real-time water condition videos correspond to different confidence weights and different water quality indexes correspond to different weighting weights, after the water quality index parameters are obtained through calculation, the electronic device needs to convert the water quality index parameters based on the confidence weights and the weighting weights, and superimpose all the converted water quality index parameters corresponding to all the real-time water condition videos, so as to calculate the water quality level of the target basin.

In the embodiment, the water quality grade is used for determining the degree of cleanness of the water body of the target basin; if the numerical value of the water quality grade is larger, the higher the cleanness degree of the water body of the target basin is represented; conversely, the smaller the value of the water quality grade, the lower the degree of crystallization of the water body of the target basin.

In a possible implementation manner, the manner of calculating the water quality grade may be: the electronic device may store a conversion network of water quality grades, and may generate the water quality grades by introducing, into the conversion network, the confidence weight corresponding to each real-time water condition video, and the weight weights corresponding to the plurality of water quality index parameters determined based on the real-time water condition video.

In S105, a water quality report of the target basin is generated based on the water quality level.

In this embodiment, the electronic device may store a corresponding report template, and after the water quality level corresponding to the target basin is determined, may generate a water quality report regarding the target basin by introducing the water quality level and the water quality index parameters of the water quality indexes into the report template.

In a possible implementation manner, after S105, the method may further include: if the water quality grade of the target basin is detected to be lower than the preset grade threshold value, corresponding water quality early warning information can be generated so as to inform a user to process the abnormal condition.

In one possible implementation manner, each distributed node may be configured with a corresponding water quality regulation module, for example, corresponding detergent, acid-base neutralizer and the like may be put into the target drainage basin to perform corresponding water quality exception handling. In this case, when detecting that the water quality level of the target basin is lower than the level threshold, the electronic device may determine, according to the abnormal water quality index parameter, a corresponding water quality abnormality treatment, and send an adjustment instruction corresponding to the water quality abnormality treatment to the distributed node, and after receiving the adjustment instruction, the distributed node may execute a corresponding water quality abnormality treatment operation through the water quality adjustment module, so as to process the water quality abnormality of the target basin.

As can be seen from the above, the method for generating a water quality report based on distributed nodes according to the embodiments of the present invention deploys corresponding distributed nodes at a plurality of locations of a target basin, and corresponding real-time water condition videos are collected, the water quality of the whole target basin can be detected through the real-time water condition videos, before water quality detection is carried out, water quality index information corresponding to a target basin is determined, a real-time water condition video is analyzed through a water quality index analysis algorithm associated with the water quality index information, water quality index parameters corresponding to a plurality of water quality index dimensions of the real-time water condition video are determined, according to the confidence weighting corresponding to the real-time water condition video, the weighting associated with the water quality index and the water quality index parameter, the water quality grade corresponding to the target basin can be calculated, and a water quality report is generated based on the water quality grade, so that the purpose of automatically generating the water quality report is achieved. Compared with the existing water quality report generation technology, the embodiment of the application does not depend on experts to perform water quality detection on a water body sample, but can analyze the real-time water condition videos through a water quality index analysis algorithm associated with water quality index information of a target basin, determine water quality index parameters corresponding to the real-time water condition videos, determine corresponding confidence weights according to the deployment positions of the real-time water condition videos, improve the contribution of the real-time water condition videos at the positions with higher confidence degrees in water quality level calculation, further improve the accuracy of the water quality level, configure different weighting weights for different water quality indexes of the target basin according to different focuses of the target basin, realize the matching of the water quality level and the detection content of the target basin, and improve the accuracy and flexibility of water quality report generation.

Fig. 2 shows a flowchart of a specific implementation of a method for generating a water quality report based on distributed nodes according to a second embodiment of the present invention. Referring to fig. 2, with respect to the embodiment shown in fig. 1, before receiving the real-time water condition videos fed back by the distributed nodes deployed in the target drainage basin, the method for generating a distributed node-based water quality report according to this embodiment further includes: S201-S206, detailed details are as follows:

furthermore, each distributed node comprises a plurality of shooting angles, and each shooting angle corresponds to one real-time water condition video;

before the receiving the real-time water condition videos fed back by the distributed nodes deployed in the target drainage basin, the method further comprises the following steps:

in S201, an initial confidence of the training water condition video corresponding to each of the shooting angles is determined.

In this embodiment, a plurality of shooting angles may be configured in one distributed node, and a camera module may be configured at a position corresponding to a different shooting angle, so as to obtain a real-time water condition video corresponding to the shooting angle through the camera module. Illustratively, fig. 3 shows a schematic diagram of a multi-angle acquisition real-time water condition video provided by an embodiment of the present application. Referring to fig. 3, a distributed node includes 3 shooting angles, which are respectively used to obtain real-time water condition videos of three areas, i.e., water surface, water bottom and water surface. Because the difference of pollutant, its buoyancy can have the difference, for example partial plastic refuse can float on the surface of water, and other solid pollutants then can exist in aquatic, and some heavier pollutant then can subside in the bottom of water, on this basis, through acquireing the real-time water condition video that different shooting angles correspond, can have an holistic understanding to the quality of water condition that the position that the distributed node corresponds.

In this embodiment, the electronic device may configure corresponding confidence weights for different distributed nodes, and may also configure corresponding confidence weights for different shooting angles. For example, if the part of the target basin is located, the wind wave of the water surface is large, and the water is calm, the real-time water condition video acquired by the water surface is difficult to identify and detect the water quality, and the real-time water condition video in the water can accurately determine the water quality of the target basin due to the calmness of the water. Therefore, the electronic equipment can configure different confidence coefficient weights according to different positions, and can also perform adaptive adjustment on the confidence coefficient weights according to different shooting angles, so that the accuracy of water quality detection of the target basin is greatly improved.

In this embodiment, the electronic device may generate a network configured with confidence weights in a training learning manner, so as to output confidence weights corresponding to different distributed nodes. Based on this, the electronic device may configure corresponding initial confidence levels for different shooting angles of a certain distributed node. The initial confidence level can be manually configured based on a user, and can also be automatically identified according to the position corresponding to the distributed node.

In S202, a preset three-dimensional analysis network identifies the training water condition video obtained from the shooting angle to perform three-dimensional video visual analysis, and generates three-dimensional feature data corresponding to the training water condition video.

In this embodiment, the network for determining the confidence weight includes at least two parts, which are a three-dimensional analysis network for performing three-dimensional analysis on the video and a fully-connected network for determining the confidence weight based on the feature data. Both networks contain adjustable learning parameters. Based on this, the electronic device may import the training water condition video obtained at the corresponding shooting angle into a preset three-dimensional analysis network, perform three-dimensional video visual analysis on the training water condition video, recognize and obtain a shooting object included in the training water condition video, and generate three-dimensional feature data corresponding to the shooting object and the video background feature based on all the recognized shooting objects and the video background feature, where the three-dimensional feature data is specifically data obtained by encoding the training water condition video.

In S203, the three-dimensional feature data is imported into a preset fully-connected network, and a confidence to be verified corresponding to the shooting angle is calculated.

In this embodiment, after generating the three-dimensional feature data corresponding to the training water condition video, the electronic device may import the three-dimensional feature data into the full-connection network, and may analyze the three-dimensional feature data through the full-connection network to output the confidence to be verified corresponding to the training water condition video obtained at a certain shooting angle. Because the fully-connected network and the three-dimensional analysis network are obtained without learning and training, a certain deviation exists between the output confidence coefficient to be verified and the actual confidence coefficient, and therefore, the two networks need to be trained and learned according to the confidence coefficient to be verified.

In a possible implementation manner, after the fully connected network, a corresponding normalization network may be further configured, where the normalization network is specifically a softmax function, and may perform a logical regression process on data output by the fully connected network, and a normalized value is used as the confidence to be verified.

In S204, the initial confidence and the confidence to be verified are introduced into a preset algorithm loss calculation function, and loss values corresponding to the three-dimensional analysis network and the fully-connected network are calculated; the loss calculation function is specifically:

wherein the content of the first and second substances,

in order to be said loss value, the loss value,

the initial confidence for the ith shooting angle;

the confidence to be verified for the ith shooting angle;

is the total number of the shooting angles.

In this embodiment, the electronic device may introduce the initial confidence level corresponding to the training water condition video and the confidence level to be verified output by the two networks into a preset loss calculation function, so as to determine the loss values corresponding to the two networks, and if the loss value is larger, the distortion degree is larger; conversely, a smaller loss value indicates a smaller distortion factor.

In S205, training the three-dimensional analysis network and the fully-connected network based on the loss value, and generating a confidence recognition network; the confidence recognition network is constructed when the loss values corresponding to the three-dimensional analysis network and the fully-connected network are smaller than a preset loss threshold value; the confidence identification network is used to determine the confidence weight for each of the real-time water condition videos.

In this embodiment, the electronic device may train and learn the three-dimensional analysis network and the fully-connected network according to the loss values, adjust parameters in the two networks, and determine the confidence weights corresponding to the subsequent real-time water condition videos by using the confidence recognition network, where the two networks are trained completely when the loss values corresponding to the confidences to be verified output by the two networks converge, and the trained two networks are used as the confidence recognition networks.

Illustratively, fig. 4 shows a schematic structural diagram of a confidence level recognition network provided by an embodiment of the present application. Referring to fig. 4, the confidence level identification network specifically includes at least three parts, which are a three-dimensional analysis network for encoding the real-time water condition video, a fully-connected network for analyzing the encoded data, and a softmax function for normalizing the values of the fully-connected network.

In the embodiment of the application, the initial confidence degrees corresponding to the training water condition videos are determined, and the three-dimensional analysis network and the full-connection network are trained and learned based on the initial confidence degrees, so that a confidence degree identification network capable of automatically determining the confidence degree weight can be generated, the automation degree of generation of the water quality report and the accuracy of identification are improved, manual confidence degree configuration is not needed, and the labor cost is reduced.

Fig. 5 shows a flowchart of a specific implementation of a method S201 for generating a water quality report based on distributed nodes according to a third embodiment of the present invention. Referring to fig. 5, with respect to the embodiment described in fig. 2, in the method for generating a water quality report based on distributed nodes according to this embodiment, S201 includes: S2011-S2014, which is specifically detailed as follows:

in S2011, the deployment position of the distributed node is obtained, and the inflection angle of the deployment position in the target flow domain is queried to obtain a position confidence factor.

In S2012, the rotational speed of the gear placed at the position corresponding to the photographing angle is identified, and the flow rate of the water current associated with the photographing angle is determined.

In S2013, based on any one of the reference water condition images in the training water condition video acquired at the shooting angle, the obstacle included in the reference water condition image is identified, and based on the distance values between all the obstacles and the camera modules corresponding to the shooting angle, a shooting confidence factor is determined.

In this embodiment, the electronic device may determine the initial confidence levels of the training water condition videos corresponding to different shooting angles in an automatic identification manner, where the factors affecting the initial confidence levels include at least three factors, which are a position factor related to the degree of curvature of the watershed in the position, a flow rate factor related to the flow rate of the water flow in the watershed, and a shooting confidence factor related to the distance between obstacles in the target watershed.

Based on this, the electronic device may obtain factors corresponding to the above three aspects, respectively. The location factor can be determined by the deployment position of the distributed nodes, each distributed node can be configured with a corresponding location sensor, or the electronic device can mark the deployment position of each distributed node on a preset map, and after deployment of the distributed nodes is completed, the distributed nodes are generally fixed and unchangeable, so that the deployment position corresponding to each distributed node can be determined by querying a pre-generated map, the bending degree of the watershed corresponding to the location can be determined according to the deployment position and the watershed trend of the target watershed, the bending degree can be represented by a corner angle, and a location confidence factor corresponding to the bending degree is generated based on the corner angle.

For the water flow velocity, under the shooting angle corresponding to each distributed node, a gear for measuring the water flow velocity can be placed, the distributed nodes can determine the rotating speed corresponding to the motor through the numerical value fed back by the motor associated with the gear, and the water flow velocity corresponding to the position can be determined based on the rotating speed.

For the shooting confidence factor related to the obstacle, the closer the distance between the obstacle and the camera module in the shooting process is, the greater the degree of the shielded picture is, and the content related to the water quality cannot be accurately represented.

In S2014, the position confidence factor, the shooting confidence factor and the water flow rate are led to a preset confidence conversion model, and an initial confidence corresponding to the shooting angle is calculated; the confidence conversion model specifically comprises:

wherein the content of the first and second substances,

the initial confidence corresponding to the ith shooting angle;

is the location confidence factor;

a preset compensation angle;

is the water flow rate;

the shooting confidence is obtained;

is a preset reference distance; a and

is a preset coefficient.

In this embodiment, the electronic device may introduce the factors of the above three aspects into the confidence conversion model, so as to calculate and obtain an initial confidence corresponding to the training water condition video obtained by the shooting angle.

In the embodiment of the application, the initial confidence corresponding to the training water condition video is automatically determined by acquiring factors of multiple aspects, so that the purpose of automatically setting the confidence label of the training water condition video can be realized, and the automation degree of generating the water quality report is further improved.

Fig. 6 shows a flowchart of a specific implementation of the method S104 for generating a water quality report based on distributed nodes according to the fourth embodiment of the present invention. Referring to fig. 6, compared with the embodiment of fig. 1, in the method for generating a water quality report based on distributed nodes provided in this embodiment, S104 specifically includes S1041 to S1043, which are specifically detailed as follows:

in S1041, a weighting parameter corresponding to the water quality index parameter is calculated according to the weighting weight associated with the water quality index parameter.

In S1042, according to the confidence weight of the real-time water condition video, a weighting operation is performed on each weighting parameter, and a water quality indicator factor corresponding to the real-time water condition video is calculated.

In S1043, calculating a water quality level of the target basin based on the water quality index factors of all the real-time water condition videos of all the distributed nodes; wherein, the water quality grade specifically is:

wherein the content of the first and second substances,

the water quality grade is obtained;

the confidence coefficient weight corresponding to the jth real-time water condition video;

the weighting parameter is the ith water quality index factor in the jth real-time water condition video;

the ith water quality factor in the jth real-time water condition video;

the total number of the water quality indexes is shown;

is the total number of the real-time water condition videos.

In this embodiment, after obtaining each water quality index parameter through calculation, the electronic device may perform weighting adjustment on the water quality index parameter by using the weighting weight corresponding to the water quality index parameter, so as to obtain the weighted water quality index parameter through calculation, that is, the weighting parameter, then adjust the weighting parameter according to the confidence weight of the real-time water condition video corresponding to the water quality index parameter, and superimpose all the adjusted weighting parameters corresponding to the real-time water condition video, so as to obtain the water quality index parameter corresponding to the real-time water condition video through calculation. Because a target basin comprises a plurality of different distributed nodes, the different distributed nodes can have a plurality of different shooting angles, and the different shooting angles can correspond to a real-time water condition video, the water quality index factors corresponding to the real-time water condition videos obtained by all the distributed nodes at all the shooting angles can be superposed, and the water quality grade can be calculated.

In the embodiment of the application, the water quality index factors determined by the real-time water condition videos are adjusted through the weighting weight and the confidence coefficient weight, so that the water quality grade is obtained through calculation, and the accuracy of the water quality grade can be improved.

Fig. 7 shows a flowchart of a specific implementation of the method S102 for generating a water quality report based on distributed nodes according to the fifth embodiment of the present invention. Referring to fig. 7, compared with the embodiment of fig. 1, in the method for generating a water quality report based on distributed nodes according to the present embodiment, S102 specifically includes S1021 to S1023, which is specifically described as follows:

in S1021, a basin event corresponding to the target basin is obtained, and the basin type of the target basin is determined based on the basin event.

In this embodiment, the electronic device may determine a watershed event of the target watershed, where the watershed event is specifically an event that a human engages in the target watershed, such as ship sailing, breeding, fishing, ship berthing, and the like, and the electronic device may determine a watershed type corresponding to the target watershed according to the watershed event occurring in the target watershed, and determine an effect of the target watershed in human activities, where different watershed types have different emphasis on water quality, so that different water quality index information may be configured.

In S1022, if the basin type is a ship shipping type, using first index information as the water quality index information; the water quality index of the first index information comprises turbidity, pH value, buoyancy coefficient and suspended solid density.

In S1023, if the watershed type is a fishery breeding type, using second index information as the water quality index information; and the water quality indexes of the second index information comprise turbidity, temperature, pH value, suspended solid density and dissolved oxygen concentration.

In this embodiment, the basin type may include a ship shipping type, that is, the target basin is a canal; the aforementioned types of watershed may also comprise types of fishery farming, i.e. the target watershed is specifically used for fishery farming activities. Based on this, the electronic equipment can configure the water quality index information corresponding to the water quality index according to the attention focus of different basin types.

In the embodiment of the application, the basin type of the target basin is determined, and the corresponding water quality index information is configured, so that the matching degree between the water quality report and the target basin can be improved.

Fig. 8 shows a flowchart of a specific implementation of the method S105 for generating a water quality report based on distributed nodes according to the sixth embodiment of the present invention. Referring to fig. 8, compared with the embodiments of fig. 1 to 7, in the method for generating a water quality report based on distributed nodes according to this embodiment, S105 specifically includes S1051 to S1054, which are specifically detailed as follows:

in S1051, a report template associated with the water quality grade is obtained; the report template includes a plurality of report items associated with the water quality ratings.

In S1052, a description phrase of each report item is determined based on the magnitude of the water quality level.

In S1053, a key video segment is intercepted from the real-time water situation video of the distributed node.

In S1054, the description language segment and the key video segment are imported into the report template to generate the water quality report

In this embodiment, after determining the water quality grade corresponding to the target basin, the electronic device may acquire a report template corresponding to the water quality grade, where the report template may be divided into the following types based on the numerical value of the water quality grade:

1) excellence (WQI = 90-100)

2) Liang (WQI = 70-89)

3) Middle (WQI = 50-69)

4) Bad (WQI = 25-49)

5) Range difference (WQI = 0-24)

The method can be used for corresponding to different report templates and corresponding report items according to different water quality grades, for example, when the water quality is bad, the method can need to include a corresponding item of a treatment mode, and when the water quality is medium or good, the method can include a corresponding item of optimizing the water quality. Therefore, if the report items corresponding to different water quality grades are different, the corresponding report templates are also different. The electronic device can determine a corresponding description language segment according to the water quality grade corresponding to the target basin, and can intercept a corresponding key video segment from the real-time water condition video and add the key video segment into the report template so as to generate a corresponding water quality report in order to improve the readability of the water quality report.

In the embodiment of the application, the report templates corresponding to different water quality grades are associated, the corresponding description language segments are determined according to the numerical values of the water quality grades, and the key video segments are led into the report templates, so that the accuracy of the water quality templates can be improved, and the readability is further improved.

Fig. 9 shows a flowchart of a specific implementation of the method S101 for generating a water quality report based on distributed nodes according to the seventh embodiment of the present invention. Referring to fig. 9, compared with the embodiments of fig. 1 to 7, in the method for generating a water quality report based on distributed nodes according to the present embodiment, S101 specifically includes S1011 to S1013, and the following details are specifically described as follows:

in S1011, if a trigger instruction fed back by any distributed node is received, the event type corresponding to the trigger instruction is analyzed.

In S1012, if the event type is within a preset water quality change event, a video feedback instruction is sent to each distributed node.

In S1013, the real-time water condition video sent by each distributed node based on the video feedback instruction is received.

In this embodiment, the electronic device may be capable of monitoring the water quality condition of the target basin in real time, that is, determining the water quality level in real time, and may also trigger the generation process of the water quality report in an event-triggered manner, where the event-triggered detection is completed by the distributed nodes, and when detecting that the target basin has a corresponding detection trigger event, the distributed nodes may generate a trigger instruction and send the trigger instruction to the electronic device. For example, when it is detected that a large number of ships sail on the target watershed or a large-area fishing behavior of the target watershed exists, the distributed nodes may generate corresponding trigger instructions, and add the trigger events to the trigger instructions, so that the electronic device determines whether a generation flow of a water quality report needs to be started according to event types. If the electronic device detects that the event type is within a preset water quality change event, that is, it is determined that the water quality of the target basin is affected by activities performed by humans on the target basin, a video feedback instruction may be sent to each distributed node, so that each distributed video sends a real-time water condition video to the electronic device, and a generation process of a water quality report is executed.

In the embodiment of the application, whether the event of water quality change exists or not is detected through the distributed nodes, and the timeliness of water quality change identification can be improved.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

Fig. 10 is a block diagram illustrating a configuration of an apparatus for generating a water quality report based on distributed nodes according to an embodiment of the present invention, where the electronic device includes units for executing steps in the embodiment corresponding to fig. 1. Please refer to fig. 1 and fig. 1 for the corresponding description of the embodiment. For convenience of explanation, only the portions related to the present embodiment are shown.

Referring to fig. 10, the apparatus for generating a distributed node-based water quality report includes:

the real-time water condition video receiving unit 11 is configured to receive real-time water condition videos fed back by distributed nodes deployed in a target basin; each real-time water condition video is configured with a corresponding confidence coefficient weight;

a water quality index information obtaining unit 12 configured to obtain water quality index information associated with the target basin; the water quality index information comprises at least one water quality index and a weighting weight related to the water quality index;

a water quality index parameter determination unit 13, configured to import the real-time water condition video into a water quality index analysis algorithm associated with the water quality index information, and output a water quality index parameter corresponding to each water quality index of the target basin determined based on the distributed nodes;

a water quality grade calculation unit 14, configured to calculate a water quality grade of the target basin according to the confidence weights, the weighted weights, and the water quality index parameters of all the real-time water condition videos;

and a water quality report generation unit 15 for generating a water quality report of the target basin based on the water quality grade.

Optionally, each distributed node includes a plurality of shooting angles, and each shooting angle corresponds to one real-time water condition video;

the device for generating the water quality report based on the distributed nodes further comprises:

the initial confidence coefficient determining unit is used for determining the initial confidence coefficient of the training water condition video corresponding to each shooting angle;

the three-dimensional characteristic data generating unit is used for identifying the training water condition video acquired by the shooting angle through a preset three-dimensional analysis network to perform three-dimensional video visual analysis so as to generate three-dimensional characteristic data corresponding to the training water condition video;

a confidence determining unit to be verified, configured to import the three-dimensional feature data into a preset full-connection network, and calculate a confidence to be verified corresponding to the shooting angle;

a loss value calculation unit, configured to introduce the initial confidence level and the confidence level to be verified into a preset algorithm loss calculation function, and calculate loss values corresponding to the three-dimensional analysis network and the fully-connected network; the loss calculation function is specifically:

wherein the content of the first and second substances,

in order to be said loss value, the loss value,

the initial confidence for the ith shooting angle;

the confidence to be verified for the ith shooting angle;

the total number of the shooting angles is;

the training learning unit is used for training the three-dimensional analysis network and the full-connection network based on the loss value to generate a confidence recognition network; training the three-dimensional analysis network and the fully-connected network based on the loss value to generate a confidence recognition network; the confidence recognition network is constructed when the loss values corresponding to the three-dimensional analysis network and the fully-connected network are smaller than a preset loss threshold value; the confidence identification network is used for determining the confidence weight of each real-time water condition video; the confidence identification network is used to determine the confidence weight for each of the real-time water condition videos.

Optionally, the initial confidence determining unit includes:

the position confidence factor determining unit is used for acquiring the deployment positions of the distributed nodes and inquiring the inflection angle of the deployment positions in the target flow domain to obtain position confidence factors;

the water flow velocity determining unit is used for identifying the rotating speed of a gear placed at a position corresponding to a shooting angle and determining the water flow velocity related to the shooting angle;

the shooting confidence factor determining unit is used for identifying obstacles contained in the reference water condition images based on any reference water condition image in the training water condition videos acquired by the shooting angle and determining the shooting confidence factor based on the distance values between all the obstacles and the camera modules corresponding to the shooting angle;

the initial confidence coefficient calculation unit is used for guiding the position confidence factor, the shooting confidence factor and the water flow velocity into a preset confidence coefficient conversion model and calculating an initial confidence coefficient corresponding to the shooting angle; the confidence conversion model specifically comprises:

the confidence conversion model specifically comprises:

wherein the content of the first and second substances,

the initial confidence corresponding to the ith shooting angle;

is the location confidence factor;

a preset compensation angle;

is the water flow rate;

the shooting confidence is obtained;

is a preset reference distance; a and

is a preset coefficient

Wherein the content of the first and second substances,

the initial confidence corresponding to the ith shooting angle;

is the location confidence factor;

a preset compensation angle;

is the water flow rate;

the shooting confidence is obtained;

is a preset reference distance; a and

is a preset coefficient.

Optionally, the water quality grade calculating unit 13 includes:

the weighting parameter calculation unit is used for calculating a weighting parameter corresponding to the water quality index parameter according to the weighting weight associated with the water quality index parameter;

the water quality index factor calculation unit is used for performing weighting operation on each weighting parameter according to the confidence coefficient weight of the real-time water condition video and calculating a water quality index factor corresponding to the real-time water condition video;

the weighted superposition unit is used for calculating the water quality grade of the target basin based on the water quality index factors of all the real-time water condition videos of all the distributed nodes; wherein, the water quality grade specifically is:

wherein the content of the first and second substances,

the water quality grade is obtained;

the ith water quality factor in the jth real-time water condition video;

the total number of the water quality indexes is shown;

is the total number of the real-time water condition videos.

Optionally, the water quality index information obtaining unit 12 includes:

a basin type determining unit, configured to obtain a basin event corresponding to the target basin, and determine a basin type of the target basin based on the basin event;

the first type response unit is used for taking the first index information as the water quality index information if the basin type is a ship shipping type; the water quality indexes of the first index information comprise turbidity, pH value, buoyancy coefficient and suspended solid density;

the second type response unit is used for taking second index information as the water quality index information if the basin type is a fishery breeding type; and the water quality indexes of the second index information comprise turbidity, temperature, pH value, suspended solid density and dissolved oxygen concentration.

Optionally, the water quality report generating unit 15 includes:

a report template determination unit for acquiring a report template associated with the water quality grade; the report template comprises a plurality of report items related to the water quality grades;

a description language segment determining unit, configured to determine a description language segment of each report item based on the magnitude of the water quality grade;

a key video segment intercepting unit, configured to intercept a key video segment from the real-time water condition video of the distributed node;

and the information importing unit is used for importing the description language segment and the key video segment into the report template to generate the water quality report.

Optionally, the real-time water condition video receiving unit 11 includes:

the distributed triggering unit is used for analyzing an event type corresponding to a triggering instruction if the triggering instruction fed back by any distributed node is received;

the video feedback instruction sending unit is used for sending a video feedback instruction to each distributed node if the event type is within a preset water quality change event;

and the real-time water condition video feedback unit is used for receiving the real-time water condition video sent by each distributed node based on the video feedback instruction.

Therefore, the electronic device provided by the embodiment of the invention does not depend on experts to perform water quality detection on a water body sample, but can analyze the real-time water condition videos through a water quality index analysis algorithm associated with water quality index information of a target basin, determine water quality index parameters corresponding to the real-time water condition videos, and determine corresponding confidence weights according to the deployment positions of the real-time water condition videos, so that the contribution of the real-time water condition videos at positions with higher confidence degrees in water quality level calculation can be improved, the accuracy of the water quality level is further improved, different weighting weights can be configured for different water quality indexes of the target basin according to different focused points of the target basin, the matching of the water quality level and the detection content of the target basin can be realized, and the accuracy and flexibility of water quality report generation are improved.

Fig. 11 is a schematic diagram of an electronic device according to another embodiment of the invention. As shown in fig. 11, the electronic apparatus 11 of this embodiment includes: a processor 110, a memory 111 and a computer program 112 stored in said memory 111 and executable on said processor 110, such as a generation program of water quality reports based on distributed nodes. The processor 110 executes the computer program 112 to implement the steps in the above-mentioned embodiments of the method for generating a distributed node-based water quality report, such as S101 to S105 shown in fig. 1. Alternatively, the processor 110 executes the computer program 112 to implement the functions of the units in the device embodiments, such as the functions of the modules 11 to 15 shown in fig. 10.

Illustratively, the computer program 112 may be divided into one or more units, which are stored in the memory 111 and executed by the processor 110 to accomplish the present invention. The one or more units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 112 in the electronic device 11.

The electronic device may include, but is not limited to, a processor 110, a memory 111. Those skilled in the art will appreciate that fig. 11 is merely an example of an electronic device 11 and does not constitute a limitation of electronic device 11 and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the electronic device may also include input-output devices, network access devices, buses, etc.

The Processor 110 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The storage 111 may be an internal storage unit of the electronic device 11, such as a hard disk or a memory of the electronic device 11. The memory 111 may also be an external storage device of the electronic device 11, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 11. Further, the memory 111 may also include both an internal storage unit and an external storage device of the electronic device 11. The memory 111 is used for storing the computer program and other programs and data required by the electronic device. The memory 111 may also be used to temporarily store data that has been output or is to be output.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims

1. A method for generating a water quality report based on distributed nodes is characterized by comprising the following steps:

generating a water quality report for the target basin based on the water quality rating;

each distributed node comprises a plurality of shooting angles, and each shooting angle corresponds to one real-time water condition video;

determining the initial confidence of the training water condition video corresponding to each shooting angle;

identifying the training water condition video obtained by the shooting angle through a preset three-dimensional analysis network to perform three-dimensional video visual analysis, and generating three-dimensional characteristic data corresponding to the training water condition video;

importing the three-dimensional characteristic data into a preset full-connection network, and calculating a confidence coefficient to be verified corresponding to the shooting angle;

importing the initial confidence coefficient and the confidence coefficient to be verified into a preset algorithm loss calculation function, and calculating loss values corresponding to the three-dimensional analysis network and the full-connection network; the loss calculation function is specifically:

wherein the content of the first and second substances,

in order to be said loss value, the loss value,

the initial confidence for the ith shooting angle;

the confidence to be verified for the ith shooting angle;

the total number of the shooting angles is;

training the three-dimensional analysis network and the fully-connected network based on the loss value to generate a confidence recognition network; the confidence recognition network is constructed when the loss values corresponding to the three-dimensional analysis network and the fully-connected network are smaller than a preset loss threshold value; the confidence identification network is used to determine the confidence weight for each of the real-time water condition videos.

2. The method according to claim 1, wherein the determining the initial confidence level of the training water condition video corresponding to each shooting angle comprises:

acquiring the deployment position of the distributed node, and inquiring the inflection angle of the deployment position in the target flow domain to obtain a position confidence factor;

identifying the rotating speed of a gear placed at a position corresponding to a shooting angle, and determining the water flow velocity associated with the shooting angle;

based on any reference water condition image in the training water condition video acquired by the shooting angle, recognizing obstacles contained in the reference water condition image, and determining a shooting confidence factor based on distance values between all the obstacles and the camera module corresponding to the shooting angle;

leading the position confidence factor, the shooting confidence factor and the water flow velocity into a preset confidence conversion model, and calculating an initial confidence corresponding to the shooting angle; the confidence conversion model specifically comprises:

wherein the content of the first and second substances,

the initial confidence corresponding to the ith shooting angle;

is the location confidence factor;

a preset compensation angle;

is the water flow rate;

the shooting confidence is obtained;

is a preset reference distance; a and

is a preset coefficient.

3. The generation method according to claim 1, wherein the calculating a water quality level of the target basin from the confidence weights, the weighted weights, and the water quality index parameters of all the real-time water condition videos includes:

calculating a weighting parameter corresponding to the water quality index parameter according to the weighting weight associated with the water quality index parameter;

according to the confidence coefficient weight of the real-time water condition video, performing weighting operation on each weighting parameter, and calculating a water quality index factor corresponding to the real-time water condition video;

calculating the water quality grade of the target basin based on the water quality index factors of all the real-time water condition videos of all the distributed nodes; wherein, the water quality grade specifically is:

wherein the content of the first and second substances,

the water quality grade is obtained;

the ith water quality factor in the jth real-time water condition video;

the total number of the water quality indexes is shown;

is the total number of the real-time water condition videos.

4. The generation method according to claim 1, wherein the acquiring of the water quality index information associated with the target basin includes:

acquiring a basin event corresponding to the target basin, and determining the basin type of the target basin based on the basin event;

if the river basin type is a ship shipping type, taking first index information as the water quality index information; the water quality indexes of the first index information comprise turbidity, pH value, buoyancy coefficient and suspended solid density;

if the watershed type is a fishery breeding type, using second index information as the water quality index information; and the water quality indexes of the second index information comprise turbidity, temperature, pH value, suspended solid density and dissolved oxygen concentration.

5. The method according to any one of claims 1 to 4, wherein the generating a water quality report of the target basin based on the water quality class includes:

acquiring a report template associated with the water quality grade; the report template comprises a plurality of report items related to the water quality grades;

determining a description language segment of each report item based on the numerical value of the water quality grade;

intercepting a key video segment from the real-time water condition video of the distributed node;

and importing the description language segment and the key video segment into the report template to generate the water quality report.

6. The generation method according to any one of claims 1 to 4, wherein the receiving of the real-time water condition video fed back by each distributed node deployed in the target basin comprises:

if a triggering instruction fed back by any distributed node is received, analyzing an event type corresponding to the triggering instruction;

if the event type is within a preset water quality change event, sending a video feedback instruction to each distributed node;

and receiving the real-time water condition video sent by each distributed node based on the video feedback instruction.

7. A control device for generation of a water quality report based on distributed nodes, comprising:

a water quality report generation unit for generating a water quality report of the target basin based on the water quality grade;

wherein the content of the first and second substances,

in order to be said loss value, the loss value,

the initial confidence for the ith shooting angle;

the confidence to be verified for the ith shooting angle;

the total number of the shooting angles is;

the training learning unit is used for training the three-dimensional analysis network and the full-connection network based on the loss value to generate a confidence recognition network; training the three-dimensional analysis network and the fully-connected network based on the loss value to generate a confidence recognition network; the confidence recognition network is constructed when the loss values corresponding to the three-dimensional analysis network and the fully-connected network are smaller than a preset loss threshold value; the confidence identification network is used to determine the confidence weight for each of the real-time water condition videos.

8. An electronic device, characterized in that the electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, the processor executing the computer program with the steps of the method according to any of claims 1 to 6.

9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.