Environmental pollutant monitoring method and system

Abstract

The invention provides an environmental pollutant monitoring method and device and electronic equipment, and the method comprises the steps: detecting a plurality of Raman peaks of a to-be-detected water area through a Raman spectrometer based on a preset time period; respectively inputting the plurality of Raman peaks into a preset organic matter content detection model, and outputting the content and type of the organic solvent corresponding to each Raman peak in the plurality of Raman peaks; an organic matter content detection model construction step: detecting a preset type and a preset content of an organic solvent through a Raman spectrometer, and outputting an experimental Raman peak; training the initial organic matter content detection model based on the solvent information and the experimental Raman peak corresponding to the solvent information to obtain an organic matter content detection model; and sending the content and the type of the organic solvent corresponding to each Raman peak to a specified cloud, and monitoring the content and the type of the organic solvent corresponding to each Raman peak through the specified cloud. The method increases the accuracy of identification and quantification.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to a method and system for monitoring environmental pollutants. Background Art

[0002] At present, the main type of pollutants in waters near some organic solvent processing units are organic solvents, such as coatings, detergents or paints. Furthermore, organic solvents in water bodies are generally tested by operators in laboratories. Due to the uneven level of operators and the variety of organic solvents, the detection machine has low accuracy and poor accuracy of the test results.

[0003] Furthermore, the type and content of organic solvents in water bodies can also be monitored by Raman spectrometers. However, since the concentration of organic solvents in water samples is very low or the molecular structures of the solvents are similar, their Raman peaks may overlap, which increases the difficulty of identification and quantification.

[0004] Overall, the existing environmental pollutant monitoring still suffers from low monitoring accuracy. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for monitoring environmental pollutants, so as to alleviate the technical problem of low monitoring accuracy in the prior art of environmental pollutant monitoring and improve the monitoring accuracy.

[0006] In a first aspect, an embodiment of the present invention provides an environmental pollutant monitoring method, comprising: based on a preset time period, detecting multiple Raman peaks of a water area to be detected by a Raman spectrometer; inputting the above-mentioned multiple Raman peaks into a preset organic matter content detection model respectively, and outputting the content and type of the organic solvent corresponding to each Raman peak in the above-mentioned multiple Raman peaks; the above-mentioned organic matter content detection model is constructed based on the following steps: detecting organic solvents of preset types and preset contents by a Raman spectrometer, and outputting experimental Raman peaks; training an initial organic matter content detection model based on solvent information of the above-mentioned preset types and preset contents of organic solvents, and the above-mentioned experimental Raman peaks corresponding to the above-mentioned solvent information until a preset training standard is reached to obtain the above-mentioned organic matter content detection model; sending the content and type of the organic solvent corresponding to the above-mentioned each Raman peak to a designated cloud, and monitoring the content and type of the organic solvent corresponding to the above-mentioned each Raman peak through the above-mentioned designated cloud.

[0007] In a preferred embodiment of the present invention, the above-mentioned initial organic matter content detection model is constructed based on the LSTM model; the initial organic matter content detection model is trained based on the solvent information of the above-mentioned preset type and preset content of organic solvent, and the above-mentioned experimental Raman peak corresponding to the above-mentioned solvent information until the preset training standard is reached, and before the step of obtaining the above-mentioned organic matter content detection model, the above-mentioned method includes: standardizing the above-mentioned solvent information and the above-mentioned experimental Raman peak corresponding to the above-mentioned solvent information to obtain a standardized case set; training the above-mentioned LSTM model based on the above-mentioned standardized case set until the above-mentioned training standard is reached to obtain the above-mentioned organic matter content detection model.

[0008] In a preferred embodiment of the present invention, the above-mentioned LSTM model includes six neural network layers, and the above-mentioned six neural network layers include five LSTM layers and a fully connected layer; the first four LSTM layers among the above-mentioned five LSTM layers each contain 128 neurons; each LSTM layer randomly discards 30% of the neurons during the calculation process; the fifth layer among the above-mentioned five LSTM layers contains 64 neurons; the above-mentioned fully connected layer is used to output a single prediction value; and each layer uses a preset bias weight.

[0009] In a preferred embodiment of the present invention, the step of detecting a preset type and a preset content of organic solvents by a Raman spectrometer and outputting an experimental Raman peak comprises: based on a preset sampling period, detecting a preset type and a preset content of organic solvents by a Raman spectrometer and outputting an initial experimental Raman peak; according to the above sampling period, adding a timing label to the above initial experimental Raman peak to obtain the above experimental Raman peak.

[0010] In a preferred embodiment of the present invention, the step of training the initial organic content detection model based on the solvent information of the preset type and preset content of the organic solvent, and the experimental Raman peak corresponding to the solvent information until the preset training standard is reached to obtain the organic content detection model comprises: taking the experimental Raman peak as the input of the initial organic content detection model, taking the solvent information of the preset type and preset content of the organic solvent as the output of the initial organic content detection model, setting a sliding time window according to the time series label, training the initial organic content detection model until the preset training standard is reached to obtain the organic content detection model; after the step of detecting multiple Raman peaks of the water area to be detected by a Raman spectrometer based on a preset time period, the method further comprises: obtaining the predicted time of the organic solvent content of the water area to be detected; respectively inputting the multiple Raman peaks into the preset organic content detection model, and outputting the content and type of the organic solvent corresponding to each of the multiple Raman peaks, comprises: respectively inputting the multiple Raman peaks into the preset organic content detection model, and outputting the predicted value of the organic solvent in the water area to be detected at the predicted time of the organic solvent content.

[0011] In a preferred embodiment of the present invention, before the step of detecting a preset type and a preset content of organic solvent by a Raman spectrometer and outputting an experimental Raman peak, the method includes: shaking the preset type and the preset content of organic solvent by a vibration device until the state of the solution no longer changes, thereby obtaining a uniform solution; the step of detecting a preset type and a preset content of organic solvent by a Raman spectrometer and obtaining an experimental Raman peak includes: detecting the uniform solution by a Raman spectrometer and outputting the experimental Raman peak.

[0012] In a preferred embodiment of the present invention, the step of monitoring the content and type of the organic solvent corresponding to each of the above Raman peaks through the above-mentioned designated cloud comprises: determining through the above-mentioned designated cloud whether the content and type of the organic solvent corresponding to each of the above Raman peaks is greater than a preset type of solvent content threshold; if so, generating a warning signal, and sending the above-mentioned warning signal to the designated terminal.

[0013] In a preferred embodiment of the present invention, the types of the above-mentioned organic solvents include: organic phosphides, polycyclic aromatic hydrocarbons, phenolic compounds and esters.

[0014] In a second aspect, an embodiment of the present invention further provides an environmental pollutant monitoring device, comprising: a data acquisition module, used to detect multiple Raman peaks of a water area to be detected through a Raman spectrometer based on a preset time period; an output module, used to input the above-mentioned multiple Raman peaks into a preset organic matter content detection model respectively, and output the content and type of the organic solvent corresponding to each of the above-mentioned multiple Raman peaks; the above-mentioned organic matter content detection model is constructed based on the following steps: detecting organic solvents of preset types and preset contents through a Raman spectrometer, and outputting experimental Raman peaks; training an initial organic matter content detection model based on solvent information of the above-mentioned preset types and preset contents of organic solvents, and the above-mentioned experimental Raman peaks corresponding to the above-mentioned solvent information until a preset training standard is reached to obtain the above-mentioned organic matter content detection model; a monitoring module, used to send the content and type of the organic solvent corresponding to each of the above-mentioned Raman peaks to a designated cloud, and monitor the content and type of the organic solvent corresponding to each of the above-mentioned Raman peaks through the above-mentioned designated cloud.

[0015] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the environmental pollutant monitoring method of any one of claims 1 to 8.

[0016] The embodiments of the present invention have the following beneficial technical effects:

[0017] The embodiments of the present invention provide an environmental pollutant monitoring method, device and electronic device, comprising: based on a preset time period, detecting multiple Raman peaks of a water area to be detected by a Raman spectrometer; inputting the multiple Raman peaks into a preset organic matter content detection model respectively, and outputting the content and type of the organic solvent corresponding to each of the multiple Raman peaks; the organic matter content detection model is constructed based on the following steps: detecting organic solvents of preset types and preset contents by a Raman spectrometer, and outputting experimental Raman peaks; training an initial organic matter content detection model based on solvent information of the organic solvents of preset types and preset contents, and the experimental Raman peaks corresponding to the solvent information, until a preset training standard is reached, thereby obtaining the organic matter content detection model; sending the content and type of the organic solvent corresponding to each Raman peak to a designated cloud, and monitoring the content and type of the organic solvent corresponding to each Raman peak through the designated cloud. This method detects standard organic solvents through a Raman spectrometer, outputs experimental Raman peaks, and then trains an organic matter content detection model based on the solvent information of the above organic solvents. Based on the above organic matter content detection model, the content and type of organic solvents corresponding to the Raman peaks are detected, thereby avoiding the technical problem that the concentration of organic solvents in water samples is very low, or the solvent molecular structures are similar, and their Raman peaks may overlap, which increases the difficulty of identification and quantification. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 A schematic diagram of a process for monitoring environmental pollutants provided by an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of the structure of an environmental pollutant monitoring device provided by an embodiment of the present invention;

[0021] Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0023] The existing environmental pollutant monitoring still has the problem of low monitoring accuracy.

[0024] Based on this, an embodiment of the present invention provides an environmental pollutant monitoring method, device and electronic device. For ease of understanding, the environmental pollutant monitoring method is first described in detail.

[0025] Example 1

[0026] In this embodiment, Figure 1 A schematic flow chart of a method for monitoring environmental pollutants provided in an embodiment of the present invention.

[0027] Depend on Figure 1 As can be seen, the method includes:

[0028] Step S101: Based on a preset time period, a plurality of Raman peaks of the water area to be detected are detected by a Raman spectrometer.

[0029] Step S102: respectively input the above-mentioned multiple Raman peaks into a preset organic matter content detection model, and output the content and type of the organic solvent corresponding to each Raman peak in the above-mentioned multiple Raman peaks; the above-mentioned organic matter content detection model is constructed based on the following steps: detecting organic solvents of preset types and preset contents by a Raman spectrometer, and outputting experimental Raman peaks; training the initial organic matter content detection model based on the solvent information of the above-mentioned preset types and preset contents of organic solvents, and the above-mentioned experimental Raman peaks corresponding to the above-mentioned solvent information, until the preset training standard is reached, thereby obtaining the above-mentioned organic matter content detection model.

[0030] Step S103: sending the content and type of the organic solvent corresponding to each Raman peak to a designated cloud, and monitoring the content and type of the organic solvent corresponding to each Raman peak through the designated cloud.

[0031] In one embodiment, the initial organic matter content detection model is constructed based on an LSTM model; the initial organic matter content detection model is trained based on the solvent information of the preset type and preset content of the organic solvent, and the experimental Raman peak corresponding to the solvent information, until the preset training standard is reached, and before the step of obtaining the organic matter content detection model, the method includes: standardizing the solvent information and the experimental Raman peak corresponding to the solvent information to obtain a standardized case set; training the LSTM model based on the standardized case set until the training standard is reached to obtain the organic matter content detection model.

[0032] Furthermore, the above-mentioned LSTM model includes six neural network layers, and the above-mentioned six neural network layers include five LSTM layers and a fully connected layer; the first four LSTM layers among the above-mentioned five LSTM layers each contain 128 neurons; each LSTM layer randomly discards 30% of the neurons during the calculation process; the fifth layer among the above-mentioned five LSTM layers contains 64 neurons; the above-mentioned fully connected layer is used to output a single prediction value; and each layer uses a preset bias weight.

[0033] Furthermore, the step of detecting a preset type and a preset content of organic solvents by a Raman spectrometer and outputting an experimental Raman peak includes: based on a preset sampling period, detecting a preset type and a preset content of organic solvents by a Raman spectrometer and outputting an initial experimental Raman peak; according to the above sampling period, adding a timing label to the above initial experimental Raman peak to obtain the above experimental Raman peak.

[0034] Further, based on the solvent information of the above-mentioned preset type and preset content of organic solvent, and the above-mentioned experimental Raman peak corresponding to the above-mentioned solvent information, the initial organic content detection model is trained until the preset training standard is reached to obtain the above-mentioned organic content detection model, including: using the above-mentioned experimental Raman peak as the input of the above-mentioned initial organic content detection model, using the above-mentioned solvent information of the preset type and preset content of organic solvent as the output of the above-mentioned initial organic content detection model, setting a sliding time window according to the above-mentioned time series label, and training the initial organic content detection model until the preset training standard is reached to obtain the above-mentioned organic content detection model; after the step of detecting multiple Raman peaks of the water area to be detected by Raman spectrometer based on a preset time period, the above-mentioned method also includes: obtaining the predicted time of the organic solvent content of the above-mentioned water area to be detected; the step of inputting the above-mentioned multiple Raman peaks into the preset organic content detection model respectively, and outputting the content and type of the organic solvent corresponding to each of the above-mentioned multiple Raman peaks, including: inputting the above-mentioned multiple Raman peaks into the preset organic content detection model respectively, and outputting the predicted value of the organic solvent in the above-mentioned water area to be detected at the above-mentioned organic solvent content prediction time.

[0035] Furthermore, before the step of detecting a preset type and a preset content of organic solvent by a Raman spectrometer and outputting an experimental Raman peak, the method includes: shaking the preset type and the preset content of organic solvent by a vibration device until the state of the solution no longer changes, thereby obtaining a uniform solution; the step of detecting a preset type and a preset content of organic solvent by a Raman spectrometer and obtaining an experimental Raman peak includes: detecting the uniform solution by a Raman spectrometer and outputting the experimental Raman peak.

[0036] Furthermore, the step of monitoring the content and type of the organic solvent corresponding to each of the above Raman peaks through the above designated cloud comprises: judging through the above designated cloud whether the content and type of the organic solvent corresponding to each of the above Raman peaks is greater than a preset solvent content threshold; if so, generating a warning signal, and sending the warning signal to the designated terminal.

[0037] Furthermore, the types of the above-mentioned organic solvents include: organic phosphides, polycyclic aromatic hydrocarbons, phenolic compounds and esters.

[0038] An embodiment of the present invention provides an environmental pollutant monitoring method, comprising: based on a preset time period, detecting multiple Raman peaks of a water area to be detected by a Raman spectrometer; inputting the multiple Raman peaks into a preset organic matter content detection model respectively, and outputting the content and type of the organic solvent corresponding to each of the multiple Raman peaks; the organic matter content detection model is constructed based on the following steps: detecting organic solvents of preset types and preset contents by a Raman spectrometer, and outputting experimental Raman peaks; training an initial organic matter content detection model based on solvent information of the organic solvents of preset types and preset contents, and the experimental Raman peaks corresponding to the solvent information, until a preset training standard is reached, thereby obtaining the organic matter content detection model; sending the content and type of the organic solvent corresponding to each Raman peak to a designated cloud, and monitoring the content and type of the organic solvent corresponding to each Raman peak through the designated cloud. This method detects standard organic solvents through a Raman spectrometer, outputs experimental Raman peaks, and then trains an organic matter content detection model based on the solvent information of the above organic solvents. Based on the above organic matter content detection model, the content and type of organic solvents corresponding to the Raman peaks are detected, thereby avoiding the technical problem that the concentration of organic solvents in water samples is very low, or the solvent molecular structures are similar, and their Raman peaks may overlap, which increases the difficulty of identification and quantification.

[0039] Example 2

[0040] Based on the above embodiments, Figure 2 A schematic diagram of the structure of an environmental pollutant monitoring device provided in an embodiment of the present invention.

[0041] Depend on Figure 2 As can be seen, the device includes:

[0042] The data acquisition module 31 is used to detect multiple Raman peaks of the water area to be detected by using a Raman spectrometer based on a preset time period.

[0043] The output module 32 is used to input the above-mentioned multiple Raman peaks into a preset organic matter content detection model respectively, and output the content and type of the organic solvent corresponding to each Raman peak in the above-mentioned multiple Raman peaks; the above-mentioned organic matter content detection model is constructed based on the following steps: detecting organic solvents of preset types and preset contents by a Raman spectrometer, and outputting experimental Raman peaks; training the initial organic matter content detection model based on the solvent information of the above-mentioned preset types and preset contents of organic solvents, and the above-mentioned experimental Raman peaks corresponding to the above-mentioned solvent information, until the preset training standard is reached, so as to obtain the above-mentioned organic matter content detection model.

[0044] The monitoring module 33 is used to send the content and type of the organic solvent corresponding to each Raman peak to a designated cloud, and monitor the content and type of the organic solvent corresponding to each Raman peak through the designated cloud.

[0045] The data acquisition module 31, the output module 32 and the monitoring module 33 are connected in sequence.

[0046] The environmental pollutant monitoring device provided in the embodiment of the present invention has the same implementation principle and technical effects as those in the aforementioned environmental pollutant monitoring method embodiment. For the sake of brief description, for parts not mentioned in the embodiment of the above-mentioned environmental pollutant monitoring device, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0047] The embodiment of the present invention further provides an electronic device, such as Figure 3 As shown, it is a schematic diagram of the structure of the electronic device, wherein the electronic device includes a processor 41 and a memory 42, the memory 42 stores machine executable instructions that can be executed by the processor 41, and the processor 41 executes the machine executable instructions to implement the above-mentioned environmental pollutant monitoring method.

[0048] exist Figure 3 In the illustrated embodiment, the electronic device further includes a bus 43 and a communication interface 44 , wherein the processor 41 , the communication interface 44 and the memory 42 are connected via the bus.

[0049] The memory 42 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 44 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used. The bus may be an ISA bus, a PCI bus, or an EISA bus, etc. The above-mentioned bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0050] The processor 41 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 41. The above processor 41 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiments of the present invention can be directly embodied as a hardware decoding processor to be executed, or the hardware and software modules in the decoding processor can be executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor 41 reads the information in the memory 42 and completes the steps of the environmental pollutant monitoring method of the above embodiment in combination with its hardware.

[0051] An embodiment of the present invention also provides a machine-readable storage medium, which stores machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions prompt the processor to implement the above-mentioned environmental pollutant monitoring method. The specific implementation can be found in the aforementioned method embodiment, which will not be repeated here.

[0052] The computer program products of the environmental pollutant monitoring method, environmental pollutant monitoring device and electronic device provided in the embodiments of the present invention include a computer-readable storage medium storing program code. The instructions included in the above program code can be used to execute the above-mentioned environmental pollutant monitoring method in the previous method embodiment. The specific implementation can be referred to the method embodiment, which will not be repeated here.

[0053] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0054] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that can be executed by a processor. 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 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 above methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0055] Finally, it should be noted that the above-mentioned embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention rather than to limit it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-mentioned embodiments, ordinary technicians in this field should understand that any technician familiar with this technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed by the present invention, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the protection scope of the present invention.

Claims

1. A method for monitoring environmental pollutants, characterized in that: include: Based on a preset time period, a plurality of Raman peaks of the water area to be detected are detected by a Raman spectrometer; The multiple Raman peaks are respectively input into a preset organic matter content detection model, and the content and type of the organic solvent corresponding to each Raman peak in the multiple Raman peaks are output; the organic matter content detection model is constructed based on the following steps: detecting organic solvents of preset types and preset contents by a Raman spectrometer, and outputting experimental Raman peaks; training the initial organic matter content detection model based on the solvent information of the organic solvents of preset types and preset contents, and the experimental Raman peaks corresponding to the solvent information, until a preset training standard is reached, thereby obtaining the organic matter content detection model; The content and type of the organic solvent corresponding to each Raman peak are sent to a designated cloud, and the content and type of the organic solvent corresponding to each Raman peak are monitored through the designated cloud.

2. The environmental pollutant monitoring method according to claim 1, characterized in that: The initial organic matter content detection model is constructed based on the LSTM model; the initial organic matter content detection model is trained based on the solvent information of the preset type and preset content of the organic solvent, and the experimental Raman peak corresponding to the solvent information, until the preset training standard is reached, and before the step of obtaining the organic matter content detection model, the method includes: Standardizing the solvent information and the experimental Raman peaks corresponding to the solvent information to obtain a standardized case set; The LSTM model is trained based on the standardized case set until the training standard is reached to obtain the organic matter content detection model.

3. The environmental pollutant monitoring method according to claim 2, characterized in that: The LSTM model includes six neural network layers, which include five LSTM layers and a fully connected layer; the first four LSTM layers of the five LSTM layers each include 128 neurons; each LSTM layer randomly discards 30% of the neurons during the calculation process; the fifth layer of the five LSTM layers includes 64 neurons; the fully connected layer is used to output a single prediction value; each layer uses a preset bias weight.

4. The environmental pollutant monitoring method according to claim 1, characterized in that: The steps of detecting a preset type and a preset content of an organic solvent by a Raman spectrometer and outputting an experimental Raman peak include: Based on a preset sampling period, a preset type and a preset content of organic solvent are detected by a Raman spectrometer, and an initial experimental Raman peak is output; According to the sampling period, a time sequence label is added to the initial experimental Raman peak to obtain the experimental Raman peak.

5. The environmental pollutant monitoring method according to claim 4, characterized in that: The step of training an initial organic matter content detection model based on the solvent information of the preset type and preset content of the organic solvent and the experimental Raman peak corresponding to the solvent information until a preset training standard is reached to obtain the organic matter content detection model comprises: The experimental Raman peak is used as the input of the initial organic matter content detection model, the solvent information of the preset type and preset content of the organic solvent is used as the output of the initial organic matter content detection model, a sliding time window is set according to the time series label, and the initial organic matter content detection model is trained until a preset training standard is reached to obtain the organic matter content detection model; After the step of detecting multiple Raman peaks of the water area to be detected by a Raman spectrometer based on a preset time period, the method further includes: Obtaining the predicted time of the organic solvent content in the water area to be tested; The step of inputting the plurality of Raman peaks into a preset organic matter content detection model respectively and outputting the content and type of the organic solvent corresponding to each of the plurality of Raman peaks comprises: The multiple Raman peaks are respectively input into a preset organic matter content detection model, and a predicted value of the organic solvent in the water area to be detected at the organic solvent content prediction time is output.

6. The environmental pollutant monitoring method according to claim 1, characterized in that: Before the step of detecting an organic solvent of a preset type and a preset content by a Raman spectrometer and outputting an experimental Raman peak, the method includes: Shaking the organic solvent of the preset type and content by a vibration device until the state of the solution no longer changes, thereby obtaining a uniform solution; The step of detecting a preset type and a preset content of an organic solvent by a Raman spectrometer to obtain an experimental Raman peak comprises: The uniform solution is detected by a Raman spectrometer to output an experimental Raman peak.

7. The environmental pollutant monitoring method according to claim 1, characterized in that: The step of monitoring the content and type of the organic solvent corresponding to each Raman peak through the designated cloud comprises: Determining, through the designated cloud, whether the content and type of the organic solvent corresponding to each Raman peak is greater than a preset solvent content threshold; If yes, a warning signal is generated and sent to a designated terminal.

8. The environmental pollutant monitoring method according to claim 1, characterized in that: The types of organic solvents include: organic phosphides, polycyclic aromatic hydrocarbons, phenolic compounds and esters.

9. An environmental pollutant monitoring device, characterized in that: include: A data acquisition module, used for detecting multiple Raman peaks of the water area to be detected by a Raman spectrometer based on a preset time period; An output module is used to input the multiple Raman peaks into a preset organic matter content detection model respectively, and output the content and type of the organic solvent corresponding to each Raman peak in the multiple Raman peaks; the organic matter content detection model is constructed based on the following steps: detecting organic solvents of preset types and preset contents by a Raman spectrometer, and outputting experimental Raman peaks; training an initial organic matter content detection model based on solvent information of the organic solvents of preset types and preset contents, and the experimental Raman peaks corresponding to the solvent information, until a preset training standard is reached, thereby obtaining the organic matter content detection model; The monitoring module is used to send the content and type of the organic solvent corresponding to each Raman peak to a designated cloud, and monitor the content and type of the organic solvent corresponding to each Raman peak through the designated cloud.

10. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the environmental pollutant monitoring method according to any one of claims 1 to 8.

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