Intelligent adjustment method and system for noise monitoring sensor

Abstract

The present invention relates to the technical field of noise monitoring sensors. Disclosed are an intelligent adjustment method and system for a noise monitoring sensor. The method comprises: obtaining a first target region; obtaining a first noise monitoring submodule; performing noise monitoring sensor calibration adjustment on the first noise monitoring submodule, so as to obtain a second noise monitoring submodule; on the basis of the second noise monitoring submodule, performing noise monitoring sensor test adjustment, so as to obtain a third noise monitoring submodule; on the basis of the third noise monitoring submodule, performing noise monitoring on the first target region, so as to obtain a regional noise monitoring result; and on the basis of the regional noise monitoring result, performing noise monitoring sensor feedback adjustment on the third noise monitoring submodule. Therefore, the problems in the prior art of monitoring data being inaccurate and the real-time performance being poor due to it being impossible to perform intelligent adjustment on a noise monitoring sensor in noise monitoring operations are solved, and rational and precise management and control over noise pollution prevention and control are realized.

Description

Intelligent adjustment method and system for noise monitoring sensor Technical Field

[0001] The present invention relates to the technical field of noise monitoring sensors, and in particular to an intelligent adjustment method and system for noise monitoring sensors. Background Art

[0002] With the acceleration of urbanization and the continuous development of industrial production, noise pollution is becoming increasingly serious. To effectively manage and control noise pollution, accurate noise monitoring and analysis are necessary. Noise monitoring sensors are devices used to measure noise and are widely used in noise monitoring. Traditional noise monitoring methods typically use fixed monitoring stations or sensors. This monitoring method has several problems, such as inability to adapt to environmental changes and inaccurate monitoring data. Therefore, how to achieve intelligent adjustment of noise monitoring sensors and improve the accuracy and reliability of monitoring data is a critical issue that needs to be addressed.

[0003] The existing noise monitoring work in the prior art suffers from inaccurate monitoring data and poor real-time performance due to the inability to intelligently adjust the noise monitoring sensors, which ultimately makes it impossible to rationally and accurately control noise pollution prevention and control.

[0004] Summary of the Invention

[0005] The present application provides an intelligent adjustment method and system for noise monitoring sensors, which solves the problem in the prior art that noise monitoring work cannot intelligently adjust the noise monitoring sensors, resulting in inaccurate monitoring data and poor real-time performance, and realizes rational and precise control of noise pollution prevention and control.

[0006] In view of the above problems, the present application provides an intelligent adjustment method for a noise monitoring sensor.

[0007] In a first aspect, the present application provides an intelligent adjustment method for a noise monitoring sensor, the method comprising: obtaining a first target area; deploying a noise monitoring sensor in the first target area to obtain a first noise monitoring submodule; calibrating and adjusting the noise monitoring sensor in the first noise monitoring submodule to obtain a second noise monitoring submodule; testing and adjusting the noise monitoring sensor based on the second noise monitoring submodule to obtain a third noise monitoring submodule; performing noise monitoring on the first target area based on the third noise monitoring submodule to obtain a regional noise monitoring result; and feedback-adjusting the noise monitoring sensor in the third noise monitoring submodule according to the regional noise monitoring result.

[0008] In second aspect, the present application provides an intelligent adjustment system for a noise monitoring sensor, the system including: a first target area module: obtaining a first target area; a monitoring sensor module: deploying noise monitoring sensors in the first target area to obtain a first noise monitoring submodule; a calibration adjustment module: performing calibration adjustment of the noise monitoring sensor in the first noise monitoring submodule to obtain a second noise monitoring submodule; a test adjustment module: performing test adjustment of the noise monitoring sensor based on the second noise monitoring submodule to obtain a third noise monitoring submodule; a regional noise monitoring module: performing noise monitoring on the first target area based on the third noise monitoring submodule to obtain a regional noise monitoring result; a feedback adjustment module: performing feedback adjustment of the noise monitoring sensor in the third noise monitoring submodule according to the regional noise monitoring result.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] The intelligent adjustment method and system of the noise monitoring sensor provided in the embodiment of the present application obtain a first target area and deploy noise monitoring sensors in the first target area, then obtain a first noise monitoring submodule and perform calibration adjustment of the noise monitoring sensor on the first noise monitoring submodule, further obtain a second noise monitoring submodule, test and adjust the noise monitoring sensor based on the second noise monitoring submodule, obtain a third noise monitoring submodule, and perform noise monitoring on the first target area based on the third noise monitoring submodule to obtain regional noise monitoring results, and finally perform feedback adjustment of the noise monitoring sensor on the third noise monitoring submodule based on the regional noise monitoring results. This solves the problem in the prior art that noise monitoring work is inaccurate and has poor real-time performance due to the inability to intelligently adjust the noise monitoring sensors, and realizes rational and precise control of noise pollution prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] FIG1 is a flow chart of an intelligent adjustment method for a noise monitoring sensor provided by the present application;

[0012] FIG2 is a schematic diagram of the structure of the intelligent adjustment system of the noise monitoring sensor provided in this application.

[0013] Description of reference numerals: first target area module 11 , monitoring sensor module 12 , calibration and adjustment module 13 , test and adjustment module 14 , area noise monitoring module 15 , feedback and adjustment module 16 . DETAILED DESCRIPTION

[0014] The present application provides an intelligent adjustment method and system for noise monitoring sensors, obtains a first target area, and deploys noise monitoring sensors in the first target area, then obtains a first noise monitoring submodule, and performs calibration adjustment on the noise monitoring sensor in the first noise monitoring submodule, further obtains a second noise monitoring submodule, tests and adjusts the noise monitoring sensor based on the second noise monitoring submodule, obtains a third noise monitoring submodule, and performs noise monitoring on the first target area based on the third noise monitoring submodule, obtains regional noise monitoring results, and finally performs feedback adjustment on the noise monitoring sensor in the third noise monitoring submodule based on the regional noise monitoring results. This solves the problem in the prior art that noise monitoring work cannot intelligently adjust noise monitoring sensors, resulting in inaccurate monitoring data and poor real-time performance, and realizes rational and precise control of noise pollution prevention and control.

[0015] Example 1

[0016] As shown in FIG1 , the present application provides an intelligent adjustment method and system for a noise monitoring sensor, the method comprising:

[0017] Obtain the first target area;

[0018] Deploying noise monitoring sensors in the first target area to obtain a first noise monitoring submodule;

[0019] The first target area is the area to be monitored by the noise monitoring sensor. This area is demarcated as a target area. This area can be a major urban road, factory, construction site, or other location requiring noise pollution monitoring. A noise monitoring sensor is a sensor used to measure noise. It primarily consists of an acoustic sensor that receives sound waves, converts them into electrical signals, and processes and analyzes these signals. Based on the first target area, noise monitoring sensors are selected for the first target area and their placement is determined. Appropriate locations within the first target area are selected for sensor placement. These locations can be along roadsides, factory floors, around construction sites, and other locations close to noise sources to accurately monitor noise pollution. The noise monitoring sensors are then placed at their designated locations and verified to be functioning properly. This results in the first noise monitoring submodule, providing the data foundation for subsequent calibration and adjustment of the noise monitoring sensors within the first noise monitoring submodule and the creation of the second noise monitoring submodule.

[0020] performing calibration and adjustment on a noise monitoring sensor of the first noise monitoring submodule to obtain a second noise monitoring submodule;

[0021] Calibrate the noise monitoring sensor of the first noise monitoring submodule to obtain a calibrated first noise monitoring submodule;

[0022] Obtaining a multidimensional noise monitoring scene index, wherein the multidimensional noise monitoring scene index includes noise monitoring time, noise type, and noise source;

[0023] Based on the multi-dimensional noise monitoring scene index, noise monitoring scene parameters are collected for the first target area to obtain noise monitoring scene information;

[0024] The calibrated first noise monitoring submodule is adjusted based on the noise monitoring scenario information to generate the second noise monitoring submodule.

[0025] After obtaining the first noise monitoring submodule, it is necessary to calibrate and adjust the first noise monitoring submodule to improve its adaptability to noise scenarios and enhance data acquisition accuracy. The first noise monitoring submodule is calibrated using a calibration sensor. The calibration function is selected on the sensor and calibration is performed according to the sensor's instructions. During the calibration process, the sensor must be clean and unobstructed. Calibration of the noise monitoring sensor for the first noise monitoring submodule is completed, resulting in a calibrated first noise monitoring submodule. Multidimensional noise monitoring scenario indicators include noise monitoring time, noise type, and noise source. The multidimensional noise monitoring scenario indicators are obtained. Noise monitoring scenario parameters are collected for the first target area based on the multidimensional noise monitoring scenario indicators to obtain noise monitoring scenario information. The noise monitoring scenario information is a set of parameter values ​​for the multidimensional noise monitoring scenario indicators. The calibrated first noise monitoring submodule is adjusted based on the noise monitoring scenario information to obtain multiple noise monitoring adjustment indicators. This generates a second noise monitoring submodule, providing the data foundation for subsequent testing and adjustment of the noise monitoring sensor based on the second noise monitoring submodule to obtain the third noise monitoring submodule.

[0026] Performing testing and adjustment of a noise monitoring sensor based on the second noise monitoring submodule to obtain a third noise monitoring submodule;

[0027] Obtaining a sample noise set having a sample noise feature identifier according to the noise monitoring scene information;

[0028] Testing the second noise monitoring submodule based on the sample noise set to obtain a sample noise monitoring result;

[0029] Comparing the sample noise monitoring result with the sample noise characteristic identifier to obtain a test noise monitoring accuracy rate;

[0030] Determining whether the test noise monitoring accuracy meets the noise monitoring accuracy constraint;

[0031] If the test noise monitoring accuracy satisfies the noise monitoring accuracy constraint, the third noise monitoring submodule is generated according to the second noise monitoring submodule.

[0032] After completing calibration and adjustment of the noise monitoring submodule, before using the noise monitoring submodule to monitor noise in the first target area, the noise monitoring module must be tested and adjusted to determine whether it is functioning properly and accurately recording and analyzing noise. Based on the noise monitoring scenario information, a sample noise set with a sample noise feature identifier is obtained based on big data. The sample noise set with the sample noise feature identifier is referred to as the sample noise set, and the noise monitoring submodule is tested using the samples. Based on the sample noise set, the second noise monitoring submodule is tested to obtain a sample noise monitoring result. The sample noise monitoring result is compared with the sample noise feature identifier, representing a comparison of the noise detection result obtained by the second noise monitoring submodule with the sample standard detection result to determine whether there is any error. A test noise monitoring accuracy is then determined, and it is determined whether the test noise monitoring accuracy meets a noise monitoring accuracy constraint. The noise monitoring accuracy constraint is a threshold for the noise monitoring accuracy. If the test noise monitoring accuracy meets the noise monitoring accuracy constraint, indicating that the second noise monitoring submodule is capable of noise monitoring, a third noise monitoring submodule is generated based on the second noise monitoring submodule. By testing and adjusting the second noise monitoring submodule and setting noise monitoring accuracy constraints, the accuracy of noise monitoring can be improved.

[0033] Performing noise monitoring on the first target area based on the third noise monitoring submodule to obtain regional noise monitoring results;

[0034] The third noise monitoring submodule monitors noise in the first target area at the deployment location to obtain regional noise results for the first target area. The regional noise monitoring results include parameters such as noise intensity, frequency, duration, and noise distribution. By collecting and analyzing these parameters, indicators such as the average noise intensity and noise exceedance rate within the area are calculated. Corresponding charts are drawn based on the indicators and output to obtain regional noise monitoring results. Data processing of the regional noise results to obtain regional noise monitoring results can make the regional noise detection results more intuitive and facilitate corresponding noise processing.

[0035] The third noise monitoring submodule performs feedback adjustment on the noise monitoring sensor according to the regional noise monitoring result.

[0036] Perform an anomaly analysis on regional noise monitoring results, such as noise exceeding the standard, inaccurate noise source positioning, abnormal monitoring data, and other abnormal situations. Determine the abnormal situation and generate corresponding feedback adjustment targets based on the abnormal situation. For example, the feedback adjustment target can be to improve the accuracy of noise source positioning, correct monitoring data anomalies, etc. Generate corresponding adjustment methods based on the feedback adjustment targets. The adjustment methods include hardware adjustment and software adjustment. Hardware adjustment involves adjusting the sensor, such as replacing the sensor or adjusting the sensor position, and software adjustment involves optimizing the noise monitoring adjustment network. Based on the determined adjustment method, feedback adjustment is performed on the third noise monitoring submodule, and the effect after adjustment is verified. The feedback adjustment is repeated to improve the accuracy and reliability of noise monitoring.

[0037] Furthermore, the method further comprises:

[0038] Obtaining regional spatial feature information of the first target area;

[0039] Performing noise spatial domain feature analysis on the first target area based on the regional spatial feature information to obtain regional-noise spatial domain feature information;

[0040] Matching the layout parameters of noise monitoring sensors in the first target area based on the area-noise spatial domain characteristic information to obtain a noise-sensor layout plan;

[0041] Noise monitoring sensors are deployed in the first target area according to the noise-sensor deployment plan to generate the first noise monitoring submodule.

[0042] Regional spatial feature information refers to the regional characteristics of the first target area, such as those of major urban roads, factories, and construction sites. The type of the first target area is determined using big data, and corresponding regional spatial feature information is obtained based on the determined area type. A noise spatial feature analysis of the first target area is performed based on the regional spatial feature information. Noise spatial feature analysis involves analyzing the spatial distribution characteristics of noise, obtaining a correspondence between the regional space and the noise spatial domain of the first target area, and generating regional-noise spatial feature information. A sensor placement plan is then developed based on the regional-noise spatial feature information. For example, sensors are placed according to their sensitivity to noise density in the noise spatial domain characteristics, and the sensor placement plan is matched to obtain a noise-sensor placement plan. Noise monitoring sensors are then placed in the first target area based on the noise-sensor placement plan, generating the first noise monitoring submodule. The first noise monitoring submodule is then placed based on the noise-sensor placement plan, thereby improving the accuracy of noise data acquisition.

[0043] Furthermore, the method further comprises:

[0044] Get the first historical time zone;

[0045] Retrieving regional noise history records of the first target area according to the first historical time zone;

[0046] Performing noise spatial distribution feature analysis based on the regional noise historical records to obtain regional noise spatial distribution feature information;

[0047] Data fusion is performed based on the regional spatial feature information and the regional noise spatial distribution feature information to generate the regional-noise spatial domain feature information.

[0048] The first historical time zone refers to a historical time period. The first historical time zone is obtained by setting the historical time zone of interest. The regional noise monitored within the first historical time zone is the regional noise history record of the first target area. The noise spatial distribution characteristics of the regional noise history record are analyzed. First, noise characteristics are extracted. Noise characteristics include noise intensity, frequency, duration, etc. The noise characteristics are fitted based on spatial characteristics to obtain regional noise spatial distribution characteristic information. The regional spatial characteristic information and the regional noise spatial distribution characteristic information are fused to extract features separately. The extracted features are then feature matched to obtain feature matching results. Data fusion is performed based on the feature matching results to generate regional noise spatial domain characteristic information. Obtaining regional noise spatial distribution characteristic information based on regional noise history records can improve the efficiency of obtaining regional noise spatial domain characteristic information.

[0049] Furthermore, the method further comprises:

[0050] Obtaining a multi-dimensional noise monitoring adjustment index, wherein the multi-dimensional noise monitoring adjustment index includes noise monitoring sensitivity, noise monitoring frequency, and noise monitoring intensity;

[0051] Retrieving a noise monitoring and adjustment record library based on the multi-dimensional noise monitoring and adjustment index;

[0052] Training a noise monitoring and adjustment network according to the noise monitoring and adjustment record library;

[0053] Based on the noise monitoring scenario information, analyzing adjustment parameters of the calibrated first noise monitoring submodule according to the noise monitoring adjustment network to obtain a noise monitoring adjustment solution;

[0054] The calibrated first noise monitoring submodule is adjusted based on the noise monitoring adjustment scheme to obtain the second noise monitoring submodule.

[0055] Multidimensional noise monitoring adjustment indicators are obtained based on multidimensional noise monitoring scenario indicators. These indicators include noise monitoring sensitivity, noise monitoring frequency, and noise monitoring intensity. Noise monitoring sensitivity refers to adjusting the device's sensitivity based on actual needs to accommodate different noise intensities and frequency ranges. Generally speaking, the higher the noise monitoring sensitivity, the lower the noise that can be detected. Noise monitoring frequency refers to selecting an appropriate frequency range to capture and record specific noise types and sources. Noise monitoring intensity refers to setting parameters such as recording time and frequency as needed to ensure sufficient noise data is recorded. Multidimensional noise monitoring adjustment indicator information is retrieved from the noise monitoring record library to obtain a noise monitoring adjustment record library. The noise monitoring adjustment record library is divided into input data and supervision data. The noise monitoring adjustment network is trained using the input data and supervision data to obtain the noise monitoring adjustment network. Based on the noise monitoring scenario information and the noise monitoring adjustment network, adjustment parameters are analyzed for the calibrated first noise monitoring submodule to obtain a noise monitoring adjustment solution. The calibrated first noise monitoring submodule is adjusted according to the noise monitoring adjustment scheme to obtain the second noise monitoring submodule, which provides a data basis for subsequent testing and adjustment of the noise monitoring sensor based on the second noise monitoring submodule to obtain the third noise monitoring submodule.

[0056] Example 2

[0057] Based on the same inventive concept as the intelligent adjustment method of the noise monitoring sensor in the aforementioned embodiment, as shown in FIG2 , the present application provides an intelligent adjustment system for the noise monitoring sensor, the system comprising:

[0058] First target area module 11: The first target area module 11 is used to obtain a first target area;

[0059] Monitoring sensor module 12: The monitoring sensor module 12 is used to deploy noise monitoring sensors in the first target area to obtain a first noise monitoring submodule;

[0060] Calibration and adjustment module 13: The calibration and adjustment module 13 is used to perform calibration and adjustment on the noise monitoring sensor of the first noise monitoring submodule to obtain a second noise monitoring submodule;

[0061] Testing and adjusting module 14: the testing and adjusting module 14 is configured to perform testing and adjusting of the noise monitoring sensor based on the second noise monitoring submodule to obtain a third noise monitoring submodule;

[0062] Regional noise monitoring module 15: The regional noise monitoring module 15 is used to perform noise monitoring on the first target area based on the third noise monitoring submodule to obtain regional noise monitoring results;

[0063] Feedback adjustment module 16: The feedback adjustment module 16 is used to perform feedback adjustment of the noise monitoring sensor of the third noise monitoring submodule according to the regional noise monitoring result.

[0064] Furthermore, the monitoring sensor module 12 includes the following steps:

[0065] Obtaining regional spatial feature information of the first target area;

[0066] Performing noise spatial domain feature analysis on the first target area based on the regional spatial feature information to obtain regional-noise spatial domain feature information;

[0067] Matching the layout parameters of noise monitoring sensors in the first target area based on the area-noise spatial domain characteristic information to obtain a noise-sensor layout plan;

[0068] Noise monitoring sensors are deployed in the first target area according to the noise-sensor deployment plan to generate the first noise monitoring submodule.

[0069] Furthermore, the monitoring sensor module 12 includes the following steps:

[0070] Get the first historical time zone;

[0071] Retrieving regional noise history records of the first target area according to the first historical time zone;

[0072] Performing noise spatial distribution feature analysis based on the regional noise historical records to obtain regional noise spatial distribution feature information;

[0073] Data fusion is performed based on the regional spatial feature information and the regional noise spatial distribution feature information to generate the regional-noise spatial domain feature information.

[0074] Furthermore, the calibration and adjustment module 13 includes the following execution steps:

[0075] Calibrate the noise monitoring sensor of the first noise monitoring submodule to obtain a calibrated first noise monitoring submodule;

[0076] Obtaining a multidimensional noise monitoring scene index, wherein the multidimensional noise monitoring scene index includes noise monitoring time, noise type, and noise source;

[0077] Based on the multi-dimensional noise monitoring scene index, noise monitoring scene parameters are collected for the first target area to obtain noise monitoring scene information;

[0078] The calibrated first noise monitoring submodule is adjusted based on the noise monitoring scenario information to generate the second noise monitoring submodule.

[0079] Furthermore, the calibration and adjustment module 13 includes the following execution steps:

[0080] Obtaining a multi-dimensional noise monitoring adjustment index, wherein the multi-dimensional noise monitoring adjustment index includes noise monitoring sensitivity, noise monitoring frequency, and noise monitoring intensity;

[0081] Retrieving a noise monitoring and adjustment record library based on the multi-dimensional noise monitoring and adjustment index;

[0082] Training a noise monitoring and adjustment network according to the noise monitoring and adjustment record library;

[0083] Based on the noise monitoring scenario information, analyzing adjustment parameters of the calibrated first noise monitoring submodule according to the noise monitoring adjustment network to obtain a noise monitoring adjustment solution;

[0084] The calibrated first noise monitoring submodule is adjusted based on the noise monitoring adjustment scheme to obtain the second noise monitoring submodule.

[0085] Furthermore, the test adjustment module 14 includes the following execution steps:

[0086] Obtaining a sample noise set having a sample noise feature identifier according to the noise monitoring scene information;

[0087] Testing the second noise monitoring submodule based on the sample noise set to obtain a sample noise monitoring result;

[0088] Comparing the sample noise monitoring result with the sample noise characteristic identifier to obtain a test noise monitoring accuracy rate;

[0089] Determining whether the test noise monitoring accuracy meets the noise monitoring accuracy constraint;

[0090] If the test noise monitoring accuracy satisfies the noise monitoring accuracy constraint, the third noise monitoring submodule is generated according to the second noise monitoring submodule.

[0091] Through the detailed description of the intelligent adjustment method of the noise monitoring sensor in the foregoing description, those skilled in the art can clearly understand the intelligent adjustment method of the noise monitoring sensor in this embodiment. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0092] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent adjustment method for a noise monitoring sensor, characterized in that, the method includes: Obtain a first target area; Deploy noise monitoring sensors in the first target area to obtain a first noise monitoring sub-module; Calibrate and adjust the noise monitoring sensors of the first noise monitoring sub-module to obtain a second noise monitoring sub-module; Based on the second noise monitoring sub-module, perform test adjustment on the noise monitoring sensors to obtain a third noise monitoring sub-module; Based on the third noise monitoring sub-module, perform noise monitoring on the first target area to obtain a regional noise monitoring result; According to the regional noise monitoring result, perform feedback adjustment on the noise monitoring sensors of the third noise monitoring sub-module.

2. The method according to claim 1, characterized in that, Deploying noise monitoring sensors in the first target area to obtain a first noise monitoring sub-module includes: Obtain the regional spatial feature information of the first target area; Based on the regional spatial feature information, perform noise spatial domain feature analysis on the first target area to obtain regional-noise spatial domain feature information; Based on the regional-noise spatial domain feature information, perform parameter matching for the deployment of noise monitoring sensors in the first target area to obtain a noise-sensor deployment plan; According to the noise-sensor deployment plan, deploy noise monitoring sensors in the first target area to generate the first noise monitoring sub-module.

3. The method according to claim 2, characterized in that, Based on the regional spatial feature information, performing noise spatial domain feature analysis on the first target area to obtain regional-noise spatial domain feature information includes: Obtain a first historical time zone; According to the first historical time zone, retrieve the regional noise historical record of the first target area; Based on the regional noise historical record, perform noise spatial distribution feature analysis to obtain regional noise spatial distribution feature information; According to the regional spatial feature information and the regional noise spatial distribution feature information, perform data fusion to generate the regional-noise spatial domain feature information.

4. The method according to claim 1, characterized in that, Calibrating and adjusting the noise monitoring sensors of the first noise monitoring sub-module to obtain a second noise monitoring sub-module includes: Calibrate the noise monitoring sensors of the first noise monitoring sub-module to obtain a first noise monitoring sub-module that has completed calibration; Obtain multi-dimensional noise monitoring scenario indicators, where the multi-dimensional noise monitoring scenario indicators include noise monitoring time, noise type, and noise source; Based on the multi-dimensional noise monitoring scenario indicators, collect noise monitoring scenario parameters for the first target area to obtain noise monitoring scenario information; Based on the noise monitoring scenario information, adjust the first noise monitoring sub-module that has completed calibration to generate the second noise monitoring sub-module.

5. The method according to claim 4, characterized in that, Based on the noise monitoring scenario information, adjusting the first noise monitoring sub-module that has completed calibration to generate the second noise monitoring sub-module includes: Obtain multi-dimensional noise monitoring adjustment indicators, where the multi-dimensional noise monitoring adjustment indicators include noise monitoring sensitivity, noise monitoring frequency, and noise monitoring intensity; Based on the multi-dimensional noise monitoring adjustment indicators, retrieve the noise monitoring adjustment record library; Train a noise monitoring adjustment network according to the noise monitoring adjustment record library; Based on the noise monitoring scenario information, analyze the adjustment parameters of the first noise monitoring sub-module that has been calibrated according to the noise monitoring adjustment network to obtain a noise monitoring adjustment plan; Adjust the first noise monitoring sub-module that has been calibrated based on the noise monitoring adjustment plan to obtain the second noise monitoring sub-module.

6. The method according to claim 4, wherein, Based on the second noise monitoring sub-module, perform test adjustment on the noise monitoring sensor to obtain a third noise monitoring sub-module, including: According to the noise monitoring scenario information, obtain a sample noise set with sample noise feature identifiers; Test the second noise monitoring sub-module based on the sample noise set to obtain sample noise monitoring results; Compare the sample noise monitoring results with the sample noise feature identifiers to obtain the test noise monitoring accuracy rate; Judge whether the test noise monitoring accuracy rate meets the noise monitoring accuracy rate constraint; If the test noise monitoring accuracy rate meets the noise monitoring accuracy rate constraint, generate the third noise monitoring sub-module according to the second noise monitoring sub-module.

7. An intelligent adjustment system for a noise monitoring sensor, wherein, The system includes: First target area module: Obtain a first target area; Monitoring sensor module: Arrange noise monitoring sensors in the first target area to obtain a first noise monitoring sub-module; Calibration adjustment module: Calibrate and adjust the noise monitoring sensors of the first noise monitoring sub-module to obtain a second noise monitoring sub-module; Test adjustment module: Perform test adjustment on the noise monitoring sensors based on the second noise monitoring sub-module to obtain a third noise monitoring sub-module; Area noise monitoring module: Perform noise monitoring on the first target area based on the third noise monitoring sub-module to obtain area noise monitoring results; Feedback adjustment module: Perform feedback adjustment on the noise monitoring sensors of the third noise monitoring sub-module according to the area noise monitoring results.

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