Water source pollution monitoring method, device and system, server and storage medium

Abstract

The embodiment of the invention provides a water source pollution monitoring method, device and system, a server and a storage medium, and relates to the technical field of environment monitoring. The server determines a pollution identification result corresponding to the water source monitoring area according to the video data of the water source monitoring area acquired by the video acquisition equipment; when the first pollution probability in the pollution identification result represents that the water source monitoring area is polluted, planning a detection path of the unmanned ship according to the pollution area in the pollution identification result, and controlling the unmanned ship to travel along the detection path so as to obtain water quality detection data returned by water quality detection of the pollution area by the water quality detection sensor; determining a second pollution probability corresponding to the water source monitoring area according to the water quality detection data; and determining whether pollution alarm information is generated according to the first pollution probability and the second pollution probability. The video monitoring and the sensor are combined to perform dual monitoring on water source pollution, so that the monitoring accuracy is improved on the basis of realizing all-weather real-time monitoring and no manual intervention.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to a method, device, system, server and storage medium for monitoring water source pollution. Background Art

[0002] With the continuous development of industry and the continuous improvement of people's living standards, the output of industrial wastewater and domestic sewage is also increasing, leading to serious water pollution. For example, oil pollution caused by oil field exploitation will cause irreparable impact on the environment.

[0003] At present, the main methods of monitoring water pollution include conventional manual detection, video monitoring, and drone monitoring. Conventional manual detection methods are achieved through manual sampling or fixed-position sampling, and then through manual detection, which has poor timeliness; drone monitoring methods are expensive to use and cannot achieve all-weather real-time monitoring due to technical reasons; video monitoring can be effectively monitored in real time, but due to the interference of factors such as weather and shadows on image recognition, although interference can be avoided as much as possible through algorithm optimization, there is still a high false detection rate, which will waste a lot of unnecessary manpower. Therefore, the existing water pollution monitoring methods have the defects of high labor cost, poor timeliness, and insufficient monitoring accuracy. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a water source pollution monitoring method, device, system, server and storage medium to solve the problems of high labor cost, poor timeliness and insufficient monitoring accuracy in current water source pollution monitoring methods.

[0005] In order to achieve the above purpose, the technical solution adopted by the embodiment of the present invention is as follows:

[0006] In a first aspect, the present invention provides a water source pollution monitoring method, which is applied to a server, wherein the server is in communication connection with a video acquisition device and an unmanned boat, wherein the video acquisition device is used to collect video data of a water source monitoring area in real time, and a water quality detection sensor is provided on the unmanned boat; the method comprises:

[0007] Determine the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device; the pollution identification result includes a first pollution probability and a pollution area;

[0008] When the first pollution probability indicates that pollution occurs in the water source monitoring area, planning a detection path for the unmanned boat according to the pollution area;

[0009] Controlling the unmanned boat to travel along the detection path so as to obtain water quality detection data returned by the water quality detection sensor for detecting water quality in the polluted area;

[0010] Determining a second pollution probability corresponding to the water source monitoring area according to the water quality detection data;

[0011] Determine whether to generate pollution warning information according to the first pollution probability and the second pollution probability.

[0012] In an optional implementation manner, determining the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device includes:

[0013] Slicing the video data of the water source monitoring area collected by the video acquisition device to obtain image data;

[0014] The image data is processed for pollution identification to obtain a pollution identification result corresponding to the water source monitoring area.

[0015] In an optional implementation manner, performing pollution identification processing on the image data to obtain a pollution identification result corresponding to the water source monitoring area includes:

[0016] The image data is input into a pre-trained image recognition model, and the image data is processed for pollution recognition through the image recognition model to obtain a pollution recognition result output by the image recognition model; the image recognition model is trained based on a pre-calibrated water source pollution image.

[0017] In an optional implementation manner, determining whether to generate pollution alarm information according to the first pollution probability and the second pollution probability includes:

[0018] Performing weighted calculation on the first contamination probability and the second contamination probability to obtain a third contamination probability;

[0019] When the third pollution probability indicates that pollution occurs in the water source monitoring area, pollution alarm information is generated.

[0020] In a second aspect, the present invention provides a water source pollution monitoring device, which is applied to a server, wherein the server is communicatively connected with a video acquisition device and an unmanned boat, wherein the video acquisition device is used to collect video data of a water source monitoring area in real time, and a water quality detection sensor is provided on the unmanned boat; the device comprises:

[0021] A first pollution identification module, used to determine the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device; the pollution identification result includes a first pollution probability and a pollution area;

[0022] a path planning module, configured to plan a detection path for the unmanned boat according to the polluted area when the first pollution probability indicates that the water source monitoring area is polluted;

[0023] A control module, used for controlling the unmanned boat to travel along the detection path, so as to obtain the water quality detection data returned by the water quality detection sensor for the polluted area;

[0024] A second pollution identification module, used to determine a second pollution probability corresponding to the water source monitoring area according to the water quality detection data;

[0025] A pollution decision module is used to determine whether to generate pollution alarm information according to the first pollution probability and the second pollution probability.

[0026] In a third aspect, the present invention provides a water source pollution monitoring system, including a server, a video acquisition device and an unmanned boat, wherein the server is in communication connection with the video acquisition device and the unmanned boat, and a water quality detection sensor is provided on the unmanned boat;

[0027] The video acquisition device is used to collect video data of the water source monitoring area in real time and send the video data to the server;

[0028] The server is used to determine the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device; the pollution identification result includes a first pollution probability and a pollution area; when the first pollution probability indicates that pollution occurs in the water source monitoring area, the detection path of the unmanned boat is planned according to the pollution area;

[0029] The server is also used to control the unmanned boat to travel along the detection path so as to obtain the water quality detection data returned by the water quality detection sensor for the polluted area; determine the second pollution probability corresponding to the water source monitoring area based on the water quality detection data; and determine whether to generate pollution alarm information based on the first pollution probability and the second pollution probability.

[0030] In an optional embodiment, the unmanned boat includes a main control board and a wireless transmitter, the main control board is electrically connected to the wireless transmitter and the water quality detection sensor, and the wireless transmitter is communicatively connected to the server;

[0031] The main control board is used to receive the control command of the server through the wireless transmitter, and control the unmanned boat to travel along the detection path according to the control command;

[0032] The main control board is also used to control the wireless transmitter to send the water quality detection data to the server after acquiring the water quality detection data returned by the water quality detection sensor.

[0033] In an optional embodiment, the installation position of the water quality detection sensor is flush with the waterline of the unmanned boat.

[0034] In a fourth aspect, the present invention provides a server comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the water source pollution monitoring method as described in any one of the aforementioned embodiments.

[0035] In a fifth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the water source pollution monitoring method as described in any one of the aforementioned embodiments are implemented.

[0036] The water source pollution monitoring method, device, system, server and storage medium provided by the embodiment of the present invention, the server determines the pollution identification result corresponding to the water source monitoring area based on the video data of the water source monitoring area collected by the video acquisition device; when the first pollution probability in the pollution identification result indicates that the water source monitoring area is polluted, the detection path of the unmanned boat is planned according to the polluted area in the pollution identification result, and the unmanned boat is controlled to travel along the detection path, so as to obtain the water quality detection data returned by the water quality detection sensor for water quality detection of the polluted area; according to the water quality detection data, the second pollution probability corresponding to the water source monitoring area is determined; and whether to generate pollution alarm information is determined according to the first pollution probability and the second pollution probability. By combining video monitoring and sensors for dual monitoring of water source pollution, on the basis of achieving all-weather real-time monitoring without human intervention, the monitoring accuracy is also improved, effectively solving the problems of high labor cost, poor timeliness and insufficient monitoring accuracy in the prior art.

[0037] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0039] Figure 1A schematic diagram showing the composition of a water source pollution monitoring system provided by an embodiment of the present invention is shown;

[0040] Figure 2 A schematic diagram of a process of a water source pollution monitoring method provided by an embodiment of the present invention is shown;

[0041] Figure 3 Another schematic diagram of a process of monitoring water pollution provided by an embodiment of the present invention is shown;

[0042] Figure 4 A schematic diagram of a functional module of an unmanned ship is shown;

[0043] Figure 5 A schematic diagram of the structure of an unmanned ship is shown;

[0044] Figure 6 A functional module diagram of a water source pollution monitoring device provided by an embodiment of the present invention is shown;

[0045] Figure 7 A block diagram of a server provided by an embodiment of the present invention is shown.

[0046] Icons: 10-water source pollution monitoring system; 100-server; 110-memory; 120-processor; 130-communication module; 200-video acquisition equipment; 300-unmanned boat; 310-water quality detection sensor; 320-main control board; 330-wireless transmitter; 340-hull; 350-waterline; 600-water source pollution monitoring device; 610-first pollution identification module; 620-path planning module; 630-control module; 640-second pollution identification module; 650-pollution decision module. DETAILED DESCRIPTION

[0047] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0048] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0049] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0050] Based on the problems of high labor cost, poor timeliness and insufficient monitoring accuracy in current water source pollution monitoring methods, the embodiments of the present invention provide a water source pollution monitoring method, device, system, server and storage medium, which perform dual monitoring of water source pollution by combining video monitoring and sensors. On the basis of achieving all-weather real-time monitoring without human intervention, it also improves the monitoring accuracy, effectively solving the problems of high labor cost, poor timeliness and insufficient monitoring accuracy in the prior art.

[0051] Hereinafter, various embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0052] Please refer to Figure 1 , is a schematic diagram of an application scenario applicable to an embodiment of the present invention. Figure 1 As shown, the water source pollution monitoring system 10 includes a server 100, a video acquisition device 200 and an unmanned boat 300. The server 100 is communicatively connected with the video acquisition device 200 and the unmanned boat 300, and a water quality detection sensor 310 is provided on the unmanned boat 300.

[0053] In this embodiment, the video acquisition device 200 is used to collect video data of the water source monitoring area in real time. The monitoring area of ​​the video acquisition device 200 is the water source monitoring area, including the drain outlet and the nearby water source, and the video acquisition device 200 can monitor the water source monitoring area in real time. The video data acquired by the video acquisition device 200 will be sent to the server 100, and the server 100 will perform data processing. Among them, the video acquisition device 200 can be a camera, and the number and arrangement of the video acquisition device 200 can be determined according to the actual location of the water source to be monitored, and this embodiment does not limit this.

[0054] In this embodiment, the video acquisition device 200 and the server 100 can communicate with each other via a wired network or a wireless network; the server 100 and the unmanned boat 300 can communicate with each other via a wireless network.

[0055] In this embodiment, the water quality detection sensor 310 is used to detect the water quality of the water source and obtain water quality detection data. After obtaining the water quality detection data of the water quality detection sensor 310, the unmanned boat 300 will send it to the server 100, and the server 100 will process the data. Among them, the specific installation position of the water quality detection sensor 310 on the unmanned boat 300 can be set according to actual detection needs, for example, it can be set at the tail end of the unmanned boat 300.

[0056] Please refer to Figure 2 , is a schematic diagram of a flow chart of a water source pollution monitoring method provided by an embodiment of the present invention. It should be noted that the water source pollution monitoring method of the present invention is not based on Figure 2 It should be understood that in other embodiments, the order of some steps in the water source pollution monitoring method of the present invention can be interchanged according to actual needs, or some steps can be omitted or deleted. The water source pollution monitoring method can be applied to the above-mentioned server 100. Figure 2 The specific process shown is described in detail.

[0057] Step S201, determining a pollution identification result corresponding to a water source monitoring area according to video data collected by a video acquisition device; the pollution identification result includes a first pollution probability and a pollution area.

[0058] In this embodiment, after the video data collected by the video acquisition device 200 is sent to the server 100, the server 100 processes the video data to identify the pollution situation in the water source monitoring area and obtains the pollution identification result corresponding to the water source monitoring area.

[0059] In this embodiment, the pollution identification result may include a first pollution probability and a pollution area. The first pollution probability is the probability that the server 100 determines that pollution occurs in the water source monitoring area based on the video data; the pollution area can represent the pollution range (i.e., the diffusion range of pollutants on the water surface), which can be a rectangle, and its four vertices can be represented as A (Xmin, Ymin), B (Xmax, Ymin), C (Xmin, Ymax), D (Xmax, Ymax), Xmin represents the minimum value of the horizontal coordinate of the pollution area, Xmax represents the maximum value of the horizontal coordinate of the pollution area, Ymin represents the minimum value of the vertical coordinate of the pollution area, and Ymax represents the maximum value of the vertical coordinate of the pollution area.

[0060] Step S202, when the first pollution probability indicates that pollution occurs in the water source monitoring area, a detection path of the unmanned boat is planned according to the pollution area.

[0061] In this embodiment, when the server 100 determines that the water source monitoring area is polluted based on the first pollution probability, the detection path of the unmanned boat 300 can be planned according to the coordinate information corresponding to the polluted area and the current position of the unmanned boat 300.

[0062] Step S203, controlling the unmanned boat to travel along the detection path, so as to obtain the water quality detection data returned by the water quality detection sensor after performing water quality detection on the polluted area.

[0063] In this embodiment, after generating the detection path of the unmanned boat 300, the server 100 can send a control command to the unmanned boat 300, and the unmanned boat 300 automatically travels along the detection path to the polluted area according to the received control command, and continues to travel along the planned path in the polluted area. When the unmanned boat 300 is traveling in the polluted area, the water quality detection sensor on the unmanned boat 300 detects the water quality of the polluted area, obtains corresponding water quality detection data, and sends the water quality detection data to the server 100 in real time through the unmanned boat 300 for data processing.

[0064] It can be understood that the detection path may include a first driving path from the current position of the unmanned boat 300 to the polluted area, and a second driving path of the unmanned boat 300 within the polluted area. The unmanned boat 300 can accurately reach the polluted area according to the first driving path, and continue to drive within the polluted area according to the second driving path, so that the water quality detection sensor can perform water quality detection on most areas within the polluted area, thereby improving the detection accuracy.

[0065] Step S204: determining a second pollution probability corresponding to the water source monitoring area according to the water quality detection data.

[0066] In this embodiment, after receiving the water quality detection data, the server 100 can obtain a second pollution probability corresponding to the water source monitoring area by analyzing and judging the water quality detection data. The second pollution probability is the probability that the server 100 determines that pollution occurs in the water source monitoring area based on the water quality detection data.

[0067] Step S205: determining whether to generate pollution alarm information according to the first pollution probability and the second pollution probability.

[0068] In this embodiment, the server 100 can make a comprehensive judgment based on the first pollution probability and the second pollution probability, and finally determine whether pollution occurs in the water source monitoring area, and determine whether to generate pollution alarm information according to the final judgment result. When it is determined that pollution alarm information is to be generated, the generated pollution alarm information is sent to the corresponding management personnel so that the management personnel can handle it in time.

[0069] Since the server 100 controls the unmanned boat 300 to conduct water quality testing in the polluted area when it preliminarily determines based on the video data that the water source monitoring area is polluted, unnecessary travel and testing of the unmanned boat 300 is effectively avoided; and when finally determining whether the water source monitoring area is polluted, a comprehensive judgment is made based on the results of video monitoring and sensor detection, so the monitoring accuracy is relatively high. Therefore, the embodiment of the present invention can achieve all-weather real-time monitoring without manual intervention, and can also ensure monitoring accuracy.

[0070] It can be seen that in the water source pollution monitoring method provided by the embodiment of the present invention, the server determines the pollution identification result corresponding to the water source monitoring area based on the video data of the water source monitoring area collected by the video acquisition device; when the first pollution probability in the pollution identification result indicates that the water source monitoring area is polluted, the detection path of the unmanned boat is planned according to the polluted area in the pollution identification result, and the unmanned boat is controlled to travel along the detection path, so as to obtain the water quality detection data returned by the water quality detection sensor for water quality detection of the polluted area; according to the water quality detection data, the second pollution probability corresponding to the water source monitoring area is determined; and according to the first pollution probability and the second pollution probability, it is determined whether to generate pollution alarm information. By combining video monitoring and sensors for dual monitoring of water source pollution, on the basis of achieving all-weather real-time monitoring without human intervention, the monitoring accuracy is also improved, effectively solving the problems of high labor cost, poor timeliness and insufficient monitoring accuracy in the prior art.

[0071] In one implementation, considering that it is not convenient for the server 100 to perform pollution judgment directly based on video data, the embodiment of the present invention can extract images from the video data and perform pollution identification based on the image data. Figure 3 , the above step S201 may include:

[0072] Sub-step S2011, slicing the video data of the water source monitoring area collected by the video acquisition device to obtain image data.

[0073] In this embodiment, the server 100 may perform a slicing operation on the video data by extracting video frames, and may adopt a sliding time window slicing or a linear time slicing method to sample and obtain image data according to actual needs.

[0074] Sub-step S2012, performing pollution identification processing on the image data to obtain pollution identification results corresponding to the water source monitoring area.

[0075] In this embodiment, the server 100 can process the image data obtained after video slicing one by one through an image recognition algorithm to determine whether there is any abnormality in the water source monitoring area shown in the image data, thereby obtaining a pollution identification result corresponding to the water source monitoring area.

[0076] In practical applications, considering the influence of natural conditions such as light and shadow during the shooting process, the sliced ​​images can be preprocessed first, such as contrast enhancement and denoising, and then the preprocessed image data can be subjected to pollution identification processing, thereby avoiding the interference of natural conditions such as light and shadow on image recognition.

[0077] In one embodiment, an image recognition model for performing pollution identification processing may be pre-trained, and the pollution identification result may be generated using the image recognition model. Specifically, the above step S2012 may include: inputting image data into a pre-trained image recognition model, performing pollution identification processing on the image data through the image recognition model, and obtaining the pollution identification result output by the image recognition model; the image recognition model is trained based on a pre-calibrated water source pollution image.

[0078] In this embodiment, the existing water source data can be manually framed to identify the pollution source boundary and annotate its color, shape, distribution and other features. A large number of calibrated water source pollution images can be trained through a neural network through a target recognition algorithm (such as YOLO, etc.), and a specific image recognition model for pollution identification processing can be obtained, that is, the image recognition model has been trained before real-time monitoring, and the pollution situation in the image data can be recognized in real time through the image recognition model. It should be noted that in actual applications, the pollution identification result output by the image recognition model includes not only the first pollution probability and the pollution area, but also information such as the pollution type (pollution type), and the pollution type and other information are carried in the pollution alarm information and sent so that the management personnel know.

[0079] In one embodiment, when the server 100 makes a comprehensive judgment based on the first pollution probability and the second pollution probability, it can obtain the final pollution probability by weighted calculation, and then determine whether to generate pollution alarm information. Specifically, the above step S205 may include: performing weighted calculation on the first pollution probability and the second pollution probability to obtain a third pollution probability; and generating pollution alarm information when the third pollution probability indicates that pollution occurs in the water source monitoring area.

[0080] The server 100 may adopt the formula s=∑Δ i a i +Δj b j , to perform weighted calculation on the first pollution probability and the second pollution probability to obtain the third pollution probability; where s represents the third pollution probability, Δ i , Δ j Respectively represent the weight coefficients corresponding to the first contamination probability and the second contamination probability, a i represents the first contamination probability, b j Represents the second pollution probability. The third pollution probability calculated by weighted summation of the sensor detection results and the image recognition results is used to finally determine whether the water source monitoring area is polluted. For example, when s≥0.5, it can be set to determine that the water source monitoring area is polluted and pollution alarm information needs to be generated.

[0081] In this embodiment, considering that image recognition cannot determine the water quality and has a higher false detection rate than water quality detection sensors, the sensor detection result can be used as the main influencing factor and the image recognition result can be used as the secondary influencing factor when performing weighted calculation, thereby setting Δ i Less than Δ j , or even Δ i Much smaller than Δ j .

[0082] In one embodiment, the water quality detection data returned by the water quality detection sensor may include data on the content of various pollutants in the water. Taking oil pollution as an example, the water quality detection data mainly includes data on the content of petroleum substances such as alkanes, cycloalkanes, aromatic hydrocarbons in water, as well as oxygen content, sulfur content, pH value and other possible data on the content of pollutants in water. After acquiring the water quality detection data, the server 100 performs data processing to obtain the second pollution probability corresponding to the water source monitoring area. Specifically, the pollution threshold can be pre-set according to the type of water quality detection sensor. The server 100 combines the water quality monitoring data and the set pollution threshold, and then normalizes the data to finally obtain a value in the interval [0,1]. This value can characterize the degree of pollution in the water source monitoring area, and the value is used as the second pollution probability for subsequent processing.

[0083] Taking pH data as an example, assuming that the detection value range of the pH detection sensor is 0 to 14, and 7 is set as the pollution threshold (the middle scale indicates no acid or alkalinity), after normalization, 0 to 0.5 indicates acidic water, and 0.5 to 1 indicates alkaline water; after manual measurement, the water source monitoring area is polluted if it is too acidic or too alkaline. Assuming a is the current detection value of the pH detection sensor, the formula Normalization is performed to convert a into a value in the interval [0,1], where 0 represents no pollution and 1 represents a strong acid or a strong base.

[0084] Taking the sulfur content data as an example, assuming that the detection value range of the sulfur content detection sensor is 0 to 200, it is determined based on experience that when the sulfur content value in the water is greater than or equal to 70 (the pollution threshold), the water source is considered polluted. Then 140 (twice the pollution threshold) can be set as the upper limit value (if it exceeds the upper limit value, it will be treated as the upper limit value, that is, when the detection value of the sulfur content detection sensor is greater than or equal to 140, the detection value will be normalized as 140). Assuming b is the detection value of the current sulfur content detection sensor, it can be normalized by the formula Normalization is performed. When b is greater than or equal to the pollution threshold (i.e. 70), the calculated second pollution probability will be greater than or equal to 0.5; when b is less than the pollution threshold, the calculated second pollution probability is less than 0.5; the calculated second pollution probability is weighted with the first pollution probability obtained by image recognition to obtain the final pollution probability, and then determine whether pollution occurs. Other types of sensor detection data are similar, and finally the water quality detection data are converted into values ​​in the [0,1] interval through the normalization formula. 0 means no pollution at all, 1 means serious pollution, and the specific size of the value indicates the degree of pollution.

[0085] In one embodiment, see Figure 4 In order to facilitate the server 100 to receive water quality monitoring data in real time, the unmanned boat 300 may include a main control board 320 and a wireless transmitter 330. The main control board 320 is electrically connected to the wireless transmitter 330 and the water quality detection sensor 310, and the wireless transmitter 330 is communicatively connected to the server 100.

[0086] The main control board 320 is used to receive the control command of the server 100 through the wireless transmitter 330, and control the unmanned boat 300 to travel along the detection path according to the control command; the main control board 320 is also used to control the wireless transmitter 330 to send the water quality detection data to the server 100 after obtaining the water quality detection data returned by the water quality detection sensor 310.

[0087] It can be understood that the main control board 320 is connected to the water quality detection sensor 310, the wireless transmitter 330 and the power system of the unmanned boat 300. The wireless transmitter 330 is a device capable of transmitting radio frequency signals or wireless signals, which can receive the control command sent by the server 100 and send the control command to the main control board 320, which controls the unmanned boat 300 to travel according to the planned detection path, and the water quality detection sensor 310 on the unmanned boat 300 will continuously detect the water pollution status in the polluted area, and send the real-time collected water quality detection data to the main control board 320, which then sends it to the wireless transmitter 330, and the wireless transmitter 330 sends the water quality detection data collected by the water quality detection sensor 310 to the server 100 in real time.

[0088] In one embodiment, see Figure 5 , which is a structural schematic diagram of the unmanned boat 300. The main control board 320 is installed inside the hull 340 (indicated by dotted lines), and the water quality detection sensor 310 is installed at the tail end of the unmanned boat 300 (the dotted line part indicates that it is installed inside the hull 340). In addition to the water quality detection function, the water quality detection sensor 310 also needs to have a waterproof function.

[0089] In the oil pollution scenario, considering that oil pollution always occurs on the water surface, the installation position of the water quality detection sensor 310 can be set flush with the waterline 350 (indicated by a dotted line) of the unmanned boat 300, that is, flush with the water surface. At this time, the water quality detection sensor 310 needs to have a waterproof function and an oil pollution detection function.

[0090] In order to execute the corresponding steps in the above embodiments and various possible methods, a method for implementing a water source pollution monitoring device is provided below. Figure 6 , which is a functional module diagram of a water source pollution monitoring device 600 provided in an embodiment of the present invention. It should be noted that the basic principle and technical effects of the water source pollution monitoring device 600 provided in this embodiment are the same as those of the above-mentioned embodiments. For the sake of brief description, for parts not mentioned in this embodiment, reference can be made to the corresponding contents in the above-mentioned embodiments. The water source pollution monitoring device 600 includes a first pollution identification module 610, a path planning module 620, a control module 630, a second pollution identification module 640 and a pollution decision module 650.

[0091] The first pollution identification module 610 is used to determine the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device; the pollution identification result includes a first pollution probability and a pollution area.

[0092] It can be understood that the first pollution identification module 610 can execute the above step S201.

[0093] The path planning module 620 is used to plan the detection path of the unmanned boat according to the polluted area when the first pollution probability represents that the water source monitoring area is polluted.

[0094] It can be understood that the path planning module 620 can execute the above step S202.

[0095] The control module 630 is used to control the unmanned boat to travel along the detection path so as to obtain the water quality detection data returned by the water quality detection sensor for water quality detection of the polluted area.

[0096] It can be understood that the control module 630 can execute the above step S203.

[0097] The second pollution identification module 640 is used to determine the second pollution probability corresponding to the water source monitoring area according to the water quality detection data.

[0098] It can be understood that the second pollution identification module 640 can execute the above step S204.

[0099] The pollution decision module 650 is used to determine whether to generate pollution alarm information according to the first pollution probability and the second pollution probability.

[0100] It can be understood that the pollution decision module 650 can execute the above step S205.

[0101] Optionally, the first pollution identification module 610 can be used to slice the video data of the water source monitoring area collected by the video acquisition device to obtain image data; perform pollution identification processing on the image data to obtain pollution identification results corresponding to the water source monitoring area.

[0102] Among them, the first pollution identification module 610 inputs the image data into a pre-trained image recognition model, performs pollution identification processing on the image data through the image recognition model, and obtains the pollution identification result output by the image recognition model; the image recognition model is trained based on a pre-calibrated water source pollution image.

[0103] It can be understood that the first pollution identification module 610 can also execute the above sub-steps S2011 and S2012.

[0104] Optionally, the pollution decision module 650 is specifically used to perform weighted calculation on the first pollution probability and the second pollution probability to obtain a third pollution probability; when the third pollution probability indicates that pollution occurs in the water source monitoring area, pollution alarm information is generated.

[0105] It can be seen that the water source pollution monitoring device provided by the embodiment of the present invention includes a first pollution identification module, a path planning module, a control module, a second pollution identification module and a pollution decision module. The first pollution identification module is used to determine the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device; the pollution identification result includes a first pollution probability and a pollution area; the path planning module is used to plan the detection path of the unmanned boat according to the pollution area when the first pollution probability indicates that the water source monitoring area is polluted; the control module is used to control the unmanned boat to travel along the detection path so as to obtain the water quality detection data returned by the water quality detection sensor for water quality detection of the pollution area; the second pollution identification module is used to determine the second pollution probability corresponding to the water source monitoring area according to the water quality detection data; the pollution decision module determines whether to generate pollution alarm information according to the first pollution probability and the second pollution probability. By combining video monitoring and sensors for dual monitoring of water source pollution, on the basis of achieving all-weather real-time monitoring without human intervention, the monitoring accuracy is also improved, which effectively solves the problems of high labor cost, poor timeliness and insufficient monitoring accuracy in the prior art.

[0106] Please refer to Figure 7 , is a block diagram of a server 100 provided in an embodiment of the present invention. The server 100 includes a memory 110, a processor 120, and a communication module 130. The memory 110, the processor 120, and the communication module 130 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0107] The memory 110 is used to store programs or data. The memory 110 may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0108] The processor 120 is used to read / write data or programs stored in the memory 110 and execute corresponding functions. For example, when the computer program stored in the memory 110 is executed by the processor 120, the water source pollution monitoring method disclosed in the above embodiments can be implemented.

[0109] The communication module 130 is used to establish a communication connection between the server 100 and other devices through the network, and to send and receive data through the network.

[0110] It should be understood that Figure 7 The structure shown is only a schematic diagram of the structure of the server 100. The server 100 may also include Figure 7 More or fewer components as shown, or with Figure 7 Different configurations are shown. Figure 7 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0111] The embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by the processor 120, the water source pollution monitoring method disclosed in the above embodiments is implemented.

[0112] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0113] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0114] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0115] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for monitoring water source pollution, characterized in that: Applied to a server, the server is in communication connection with a video acquisition device and an unmanned boat, the video acquisition device is used to collect video data of a water source monitoring area in real time, and a water quality detection sensor is provided on the unmanned boat; the method comprises: Determine the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device; the pollution identification result includes a first pollution probability and a pollution area; When the first pollution probability indicates that pollution occurs in the water source monitoring area, planning a detection path for the unmanned boat according to the pollution area; Controlling the unmanned boat to travel along the detection path so as to obtain water quality detection data returned by the water quality detection sensor for detecting water quality in the polluted area; Determining a second pollution probability corresponding to the water source monitoring area according to the water quality detection data; Determine whether to generate pollution warning information according to the first pollution probability and the second pollution probability.

2. The water source pollution monitoring method according to claim 1, characterized in that: The step of determining the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device includes: Slicing the video data of the water source monitoring area collected by the video acquisition device to obtain image data; The image data is processed for pollution identification to obtain a pollution identification result corresponding to the water source monitoring area.

3. The water source pollution monitoring method according to claim 2, characterized in that: The performing pollution identification processing on the image data to obtain the pollution identification result corresponding to the water source monitoring area includes: The image data is input into a pre-trained image recognition model, and the image data is processed for pollution recognition through the image recognition model to obtain a pollution recognition result output by the image recognition model; the image recognition model is trained based on a pre-calibrated water source pollution image.

4. The water source pollution monitoring method according to claim 1, characterized in that: The determining whether to generate pollution warning information according to the first pollution probability and the second pollution probability includes: Performing weighted calculation on the first contamination probability and the second contamination probability to obtain a third contamination probability; When the third pollution probability indicates that pollution occurs in the water source monitoring area, pollution alarm information is generated.

5. A water source pollution monitoring device, characterized in that: Applied to a server, the server is in communication connection with a video acquisition device and an unmanned boat, the video acquisition device is used to collect video data of a water source monitoring area in real time, and a water quality detection sensor is provided on the unmanned boat; the device comprises: A first pollution identification module, used to determine the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device; the pollution identification result includes a first pollution probability and a pollution area; a path planning module, configured to plan a detection path for the unmanned boat according to the polluted area when the first pollution probability indicates that the water source monitoring area is polluted; A control module, used for controlling the unmanned boat to travel along the detection path, so as to obtain the water quality detection data returned by the water quality detection sensor for the polluted area; A second pollution identification module, used to determine a second pollution probability corresponding to the water source monitoring area according to the water quality detection data; A pollution decision module is used to determine whether to generate pollution alarm information according to the first pollution probability and the second pollution probability.

6. A water source pollution monitoring system, characterized in that: It includes a server, a video acquisition device and an unmanned boat, wherein the server is in communication connection with the video acquisition device and the unmanned boat, and a water quality detection sensor is arranged on the unmanned boat; The video acquisition device is used to collect video data of the water source monitoring area in real time and send the video data to the server; The server is used to determine the pollution identification result corresponding to the water source monitoring area according to the video data collected by the video acquisition device; the pollution identification result includes a first pollution probability and a pollution area; when the first pollution probability indicates that pollution occurs in the water source monitoring area, the detection path of the unmanned boat is planned according to the pollution area; The server is also used to control the unmanned boat to travel along the detection path so as to obtain the water quality detection data returned by the water quality detection sensor for the polluted area; determine the second pollution probability corresponding to the water source monitoring area based on the water quality detection data; and determine whether to generate pollution alarm information based on the first pollution probability and the second pollution probability.

7. The water source pollution monitoring system according to claim 6, characterized in that: The unmanned boat comprises a main control board and a wireless transmitter, the main control board is electrically connected to the wireless transmitter and the water quality detection sensor, and the wireless transmitter is communicatively connected to the server; The main control board is used to receive the control command of the server through the wireless transmitter, and control the unmanned boat to travel along the detection path according to the control command; The main control board is also used to control the wireless transmitter to send the water quality detection data to the server after acquiring the water quality detection data returned by the water quality detection sensor.

8. The water source pollution monitoring system according to claim 6 or 7, characterized in that: The installation position of the water quality detection sensor is flush with the waterline of the unmanned boat.

9. A server, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the water source pollution monitoring method as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the water source pollution monitoring method as described in any one of claims 1 to 4 are implemented.

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