Urban noise complaint spatial distribution feature and partition management and control system

Abstract

The invention discloses an urban noise complaint spatial distribution characteristic and partition management and control system, relates to the technical field of data processing, and aims to solve the problems that current urban noise partition management and control research is insufficient, quantitative analysis on noise complaint spatial distribution characteristics is less, and the efficiency is high. The system comprises a noise monitoring module, a data processing module, a noise complaint module, an analysis module, a data storage module, a noise partition management and control unit and a display module, and the noise monitoring module is used for monitoring different functional areas of a city. And the noise complaint module is used for establishing a noise complaint threshold value and automatically making a noise complaint for the monitored noise. According to the method, deep mining and analysis of urban noise complaint data are realized through multi-module collaborative operation and in combination with a multi-source information fusion technology, and the problem of insufficient resident complaint analysis in urban noise management and control is effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and more specifically to a spatial distribution feature of urban noise complaints and a zoning control system. Background Art

[0002] In the process of rapid urban development, the quality of urban living environment has become the focus of urban residents. Through the city-level night noise functional zone division plan, the noise source layout is planned accordingly. However, except for a few cities, the noise zoning control in most cities is still at the district and county level, lacking a comprehensive and effective control strategy.

[0003] In the analysis of urban noise characteristics and control zoning, quantitative analysis is currently mainly used to describe characteristics, evaluate and plan zoning based on the distribution of noise sources and noise recipients. However, quantitative analysis of the spatial distribution characteristics reflected by urban noise complaints is seriously insufficient. Urban noise complaints are directly related to residents' perception of noise. A large amount of noise monitoring data contains rich complaint information. Studying the distribution law of noise complaints is of great significance to analyzing the demand and potential for urban nighttime noise control, and is an indispensable reference indicator for urban noise zoning control.

[0004] At the same time, existing urban noise feature analysis mostly relies on artificial intelligence systems, such as machine learning and deep learning, to analyze objective noise sources. However, such systems have defects in the recognition and analysis of the noise environment actually perceived by residents, and cannot effectively integrate residents' subjective feedback on noise. Urban noise complaints, as a direct channel for reflecting urban noise problems, have not been fully utilized and studied in depth.

[0005] In summary, the current urban noise control has obvious shortcomings in noise complaint analysis and the integration of residents' perception and objective monitoring. In view of this, we propose a spatial distribution feature of urban noise complaints and a zoning control system. Summary of the invention

[0006] The purpose of the present invention is to provide a spatial distribution characteristic of urban noise complaints and a zoning control system to solve the technical problems of insufficient current research on urban noise zoning control, little quantitative analysis of the spatial distribution characteristics of noise complaints, and the inability of artificial intelligence systems to effectively analyze the noise environment actually perceived by residents.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a system for spatial distribution characteristics and zoning control of urban noise complaints, including a noise monitoring module, a data processing module, a noise complaint module, an analysis module, a data storage module, a noise zoning control unit, and a display module; The noise monitoring module is used to monitor different functional areas in the city; The noise complaint module is used to establish a noise complaint threshold, automatically issue noise complaints for monitored noise, and automatically record urban noise complaints; The data processing module is used to classify the urban functional area data and process the noise complaint data; The analysis module is used to count the areas and sites where complaints are recorded, analyze the number and distribution of complaints at each monitoring site and each functional area within the city, and perform multi-attribute analysis and spatial clustering; The data storage module is used to manage and store user data and noise data to ensure the security of the data; The noise zoning control unit is used to identify abnormal noise complaint areas within the city, realize noise monitoring and early warning, and adopt different control parameters for the monitored and early warning areas; The display module is used to display and visualize urban noise information, data on abnormal noise complaint areas in different functional areas of the city obtained by the analysis module, noise prediction targets obtained by the noise zoning control unit, and point control targets.

[0008] Preferably, the noise complaint module comprises a noise value calculation unit, an average sound level calculation unit, a noise complaint threshold calculation unit and a complaint unit; The noise value calculation unit is used to compare the noise monitored by a monitoring site with the noise complaint threshold; The average sound level calculation unit is used to obtain the nighttime sound level value distribution of each monitoring station in the city, construct a nighttime sound level value distribution map of the city, and calculate the average value; The noise complaint threshold calculation unit is used to count the nighttime sound level values ​​of the city monitoring sites and calculate the average value of the sound levels of the city's monitoring sites, which is the noise complaint threshold of the city's noise complaints; The complaint unit is used to issue automatic noise complaints for different areas.

[0009] A method for spatial distribution characteristics and zoning control of urban noise complaints, comprising the following steps: S1: Using the noise monitoring data from various noise monitoring stations in the city, obtain the nighttime sound level values ​​of each monitoring station in the city and construct a nighttime sound level value distribution map; S2: Based on the nighttime sound level distribution data monitored in the set area, the average sound level of urban noise in the target area is calculated, and the nighttime sound level value in the sound level distribution data is compared with the average sound level of urban noise to determine the noise complaint threshold; S3: During the monitoring process, if the nighttime sound level value of any monitoring station in a certain area is greater than the noise complaint threshold, a noise complaint will be automatically issued; S4: Record noise complaints, obtain the number of complaints, count the areas and sites where complaints are recorded, and analyze the number and distribution of complaints at each monitoring site and each functional area within the city; S5: Based on noise complaint records and urban sound level distribution data, identify abnormal noise complaint areas within the city, and conduct multi-attribute analysis and spatial clustering; S6: Establish noise zoning control units based on the urban functional areas and the types of areas with abnormal noise complaints; S7: Based on the different types of functional areas, different classification parameters are used to predict noise, establish a prediction model for urban noise distribution, obtain the distribution of internal spatial noise in different functional areas of the city, and quantify noise prediction targets and point-by-point control targets; Wherein, the noise complaint threshold in step S2 is , the calculation formula is: ; In the formula, is the average sound level of urban noise, is the preset coefficient ( ), is the standard deviation of the nighttime sound level in the target area, .

[0010] Preferably, step S2 further includes the following steps: S201: Obtaining the nighttime sound level values ​​of each monitoring station in the set target area ; S202: Calculate the average nighttime sound level of the target area as the average urban noise level of the target area ; S203: The nighttime sound level value in the target area Average sound level of urban noise in the target area Compare and determine the noise complaint threshold of each monitoring station in the target area .

[0011] Preferably, in step S202, the average nighttime sound level of the target area is calculated as the average urban noise level of the target area, and the calculation formula is: , where is the average sound level of urban noise, Indicates the nighttime sound level value, , is the total number of monitoring sites.

[0012] Preferably, in step S3: Obtaining the nighttime sound level value of a certain area means compressing the noise monitoring time according to the time pattern of the noise peak inside the city to obtain the nighttime sound level value of the monitoring station in the target area; The average sound level of urban noise refers to the average sound level of each monitoring station in the city in the set target area calculated based on the spatial distribution of the monitoring stations, that is, the average sound level of urban noise in each target area, which is used as the noise complaint threshold; The noise complaint threshold refers to the statistical night-time sound level values ​​of urban noise monitoring stations, the calculation of the average night-time sound level values ​​of each monitoring station in the set target area, and the determination of the noise complaint threshold of the noise monitoring station.

[0013] Preferably, the step S5 further comprises the following steps: S501: Statistics on the total number of noise complaints in each district and city , establish a noise complaint frequency distribution map, where , is the number of districts and cities; S502: Classify each functional area of ​​the statistical record, calculate the average value of complaints in each functional area, and establish a distribution map of noise complaints in each functional area; S503: Perform spatial cluster analysis on noise complaints in each functional area.

[0014] Preferably, in step S502, each functional area of ​​the statistical record is classified, and the average complaint value in each functional area is calculated. , the calculation formula is: , where Indicates the functional area number, For the The number of monitoring stations in each functional area, For the A collection of monitoring sites within a functional area. Indicates the number of complaints, Indicates the monitoring site number.

[0015] Preferably, a density-based spatial clustering algorithm is used to perform spatial clustering analysis on noise complaints in each functional area. , defines the total number of complaints within its neighborhood for: , where For monitoring sites The collection of monitoring stations in the neighborhood.

[0016] Preferably, in step S7, a prediction model for urban noise distribution is established, and the following multivariate linear regression model is used for calculation: ; In the formula, represents the noise prediction value, For functional areas The area of For functional areas The population density within For functional areas The nighttime sound level at the last moment, , , , is the regression coefficient, is a random error term.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention realizes in-depth mining and analysis of urban noise complaint data through the collaborative operation of multiple modules. The noise monitoring module is used to obtain noise data from different functional areas of the city, the noise complaint module automatically records the complaints, and the data processing module cooperates with the analysis module to process, count and analyze the noise complaint data. Combined with multi-source information fusion technology, the spatial distribution characteristics of noise complaints are accurately grasped, which not only makes up for the shortcomings of the existing research on the quantitative analysis of the spatial distribution characteristics of urban noise complaints, but also provides a key basis for urban noise zoning control, effectively solves the problem of insufficient analysis of residents' complaints in urban noise control, and improves the scientificity and effectiveness of noise zoning control.

[0018] 2. The present invention also realizes noise monitoring and early warning functions by identifying abnormal areas of noise complaints, and can adopt differentiated control parameters according to the characteristics of different areas. This precise control method, on the basis of the main beneficial effect of solving the problem of noise complaint analysis, further improves the timeliness and pertinence of urban noise management, can quickly respond to abnormal noise situations, implement precise governance in different areas, effectively reduce the impact of noise on residents' lives, further enhance the actual effect of urban noise control, and improve the living environment of urban residents.

[0019] 3. Based on multi-attribute analysis and spatial clustering of noise complaint data, the present invention establishes noise zoning control units in combination with urban functional areas and noise complaint abnormal area types, and uses a multivariate linear regression model to predict noise. This process can not only accurately grasp the current noise distribution, but also predict the trend of noise changes. Based on this, urban management can plan in advance according to the prediction results, optimize the layout of urban functional areas, reasonably arrange the location of noise sources, and reduce noise generation and propagation from the source. This further solves the problem of lack of forward-looking planning in urban noise control, making urban noise control more scientific and efficient, and creating good sound environment conditions for the sustainable development of the city. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the system structure of the present invention; Figure 2 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0021] Embodiment 1: Figure 1 As shown, the present invention relates to a system for spatial distribution characteristics of urban noise complaints and zoning control, including a noise monitoring module, a data processing module, a noise complaint module, an analysis module, a data storage module, a noise zoning control unit, and a display module; Noise monitoring module, used to monitor different functional areas in the city; The noise complaint module is used to establish noise complaint thresholds, automatically issue noise complaints for monitored noise, and automatically record urban noise complaints; The data processing module is used to classify the urban functional area data and process the noise complaint data; The analysis module is used to count the areas and sites where complaints are recorded, analyze the number and distribution of complaints at each monitoring site and each functional area within the city, and conduct multi-attribute analysis and spatial clustering; A data storage module, used for managing and storing user data and noise data to ensure the security of the data; Noise zoning control unit, used to identify abnormal noise complaint areas within the city, realize noise monitoring and early warning, and use different control parameters for the monitoring and early warning areas; The display module is used to display and visualize urban noise information, data on abnormal noise complaint areas in different functional areas of the city obtained by the analysis module, noise prediction targets obtained by the noise zoning control unit, and point control targets.

[0022] In an embodiment of the present invention, the noise complaint module includes a noise value calculation unit, an average sound level calculation unit, a noise complaint threshold calculation unit and a complaint unit; A noise value calculation unit, used to compare the noise monitored at a monitoring station with a noise complaint threshold; The average sound level calculation unit is used to obtain the nighttime sound level value distribution of each monitoring station in the city, construct the nighttime sound level value distribution map of the city, and calculate the average value; The noise complaint threshold calculation unit is used to count the nighttime sound level values ​​of the city's monitoring stations and calculate the average sound level of each monitoring station in the city, which is the noise complaint threshold of the city's noise complaints; Complaint unit for automatic noise complaints for different areas.

[0023] In an embodiment of the present invention, the analysis module is used to count the noise complaints in each functional area and perform spatial cluster analysis on the noise complaints in each functional area; spatial cluster analysis refers to spatial clustering data mining based on multi-attribute data to achieve objective quantification of clustering.

[0024] Embodiment 2: Figure 1 to Figure 2 As shown, a method for spatial distribution characteristics and zoning control of urban noise complaints includes the following steps: S1: Use the noise monitoring data from various noise monitoring stations in the city to obtain the nighttime sound level values ​​of each monitoring station within the city. , construct a nighttime sound level value distribution map; As another embodiment of the present invention, , The total number of monitoring sites is collected to provide basic data support for subsequent analysis by collecting the nighttime sound level values ​​of each monitoring site. The sound level data can directly reflect the noise level of different sites at night; S2: Based on the nighttime sound level distribution data monitored in the set area, the average sound level of urban noise in the target area is calculated, and the nighttime sound level value in the sound level distribution data is compared with the average sound level of urban noise to determine the noise complaint threshold; As another embodiment of the present invention, the step S2 further includes the following steps: S201: Obtaining the nighttime sound level values ​​of each monitoring station in the set target area ; As another embodiment of the present invention, the nighttime sound level values ​​of each monitoring station in the set target area are obtained. , which is the basic data for subsequent calculation of average sound level and determination of complaint threshold; S202: Calculate the average nighttime sound level of the target area as the average urban noise level of the target area; As another embodiment of the present invention, the average nighttime sound level of the target area is calculated as the average urban noise level of the target area. , the calculation formula is: , where is the total number of monitoring sites; S203: comparing the nighttime sound level value in the target area with the average sound level of urban noise in the target area, and determining the noise complaint threshold of noise complaints at each monitoring station in the target area; As another embodiment of the present invention, in step S203, the nighttime sound level value in the target area is Average sound level of urban noise in the target area Compare and determine the noise complaint threshold of each monitoring station in the target area , the calculation formula is: , where is the preset coefficient ( ), used to adjust the sensitivity of the complaint threshold, is the standard deviation of the nighttime sound level in the target area, ; S3: During the monitoring process, if the nighttime sound level value of any monitoring station in a certain area Greater than the noise complaint threshold A noise complaint will be automatically issued when As another embodiment of the present invention, in step S3: Obtaining the nighttime sound level value of a certain area means compressing the noise monitoring time according to the time pattern of the noise peak inside the city to obtain the nighttime sound level value of the monitoring station in the target area; The average sound level of urban noise refers to the average sound level of each monitoring station in the city in the set target area calculated based on the spatial distribution of the monitoring stations, that is, the average sound level of urban noise in each target area, which is used as the noise complaint threshold; The noise complaint threshold refers to the calculation of the nighttime sound level values ​​of the urban noise monitoring stations, the calculation of the nighttime sound level average values ​​of each monitoring station in the set target area, and the determination of the noise complaint threshold of the noise monitoring station; S4: Record noise complaints and obtain the number of complaints ( Indicates the monitoring site number), statistically record the areas and sites of complaints, and analyze the number and distribution of complaints at each monitoring site and each functional area within the city; S5: Based on noise complaint records and urban sound level distribution data, identify abnormal noise complaint areas within the city, and conduct multi-attribute analysis and spatial clustering; The step S5 further comprises the following steps: S501: Count the number of noise complaints in each district and city, and establish a distribution map of the number of noise complaints; As another embodiment of the present invention, the number of noise complaints in each district and city is counted ( , is the number of districts and cities), establish a noise complaint frequency distribution map; S502: Classify each functional area recorded in the statistics, such as residential, road, commercial area, park, etc., calculate the average value of complaints in each functional area, and establish a distribution map of noise complaints in each functional area; As another embodiment of the present invention, each functional area recorded in the statistics, such as residential, road, commercial area, park, etc., is classified, and the average complaint value in each functional area is calculated. ( Indicates the functional area number), the calculation formula is: ; In the formula, For the The number of monitoring stations in each functional area, For the A collection of monitoring sites within a functional area; S503: Perform spatial cluster analysis on noise complaints in each functional area; As another embodiment of the present invention, a density-based spatial clustering algorithm (such as DBSCAN algorithm) is used to perform spatial clustering analysis on noise complaints in each functional area. , defines the total number of complaints within its neighborhood for: ; In the formula, For monitoring sites The collection of monitoring sites in the neighborhood of S6: Establish noise zoning control units based on the urban functional areas and the types of areas with abnormal noise complaints; S7: Based on the different types of functional areas, different classification parameters are used to predict noise, establish a prediction model for urban noise distribution, obtain the distribution of internal spatial noise in different functional areas of the city, and quantify noise prediction targets and point-by-point control targets; As another embodiment of the present invention, in step S7, a prediction model for urban noise distribution is established, and the following multivariate linear regression model is used for calculation: ; In the formula, represents the noise prediction value, For functional areas The area of For functional areas The population density within For functional areas The nighttime sound level at the last moment, , , , is the regression coefficient, is a random error term.

[0025] Specifically, the urban noise prediction includes predicting urban noise according to different types of functional areas and different noise sources; Noise sources refer to different types of facilities in the city, which are the main factors in generating noise; Different types of functional areas within the city refer to different living areas, such as residential areas, commercial areas, transportation areas, and parks and green spaces. Different types of functional areas have different impacts on noise.

[0026] The embodiments of the present invention disclose preferred embodiments, but are not limited thereto. A person skilled in the art can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. However, as long as they do not deviate from the spirit of the present invention, they are all within the protection scope of the present invention.

Claims

1. A spatial distribution characteristics of urban noise complaints and a zoning control system, characterized in that: include: Noise monitoring module, used to monitor different functional areas in the city; The noise complaint module is used to establish noise complaint thresholds, automatically issue noise complaints and automatically record the monitored noise; The data processing module is used to classify the urban functional area data and process the noise complaint data; The analysis module is used to count the areas and sites where complaints are recorded, analyze the number and distribution of complaints at each monitoring site and each functional area within the city, and conduct multi-attribute analysis and spatial clustering; A data storage module, used for managing and storing user data and noise data; Noise zoning control unit, used to identify abnormal noise complaint areas within the city, and implement noise monitoring and early warning based on control parameters; The display module is used to display and visualize urban noise information, data on abnormal noise complaint areas in different functional areas of the city obtained by the analysis module, noise prediction targets obtained by the noise zoning control unit, and point control targets.

2. According to claim 1, a system for spatial distribution characteristics and zoning control of urban noise complaints is characterized in that: The noise complaint module includes: A noise value calculation unit, used to compare the noise monitored at a monitoring station with a noise complaint threshold; The average sound level calculation unit is used to obtain the nighttime sound level value distribution of each monitoring station in the city, construct the nighttime sound level value distribution map of the city, and calculate the average value; The noise complaint threshold calculation unit is used to count the nighttime sound level values ​​of the city's monitoring stations and calculate the average sound level of each monitoring station in the city, which is the noise complaint threshold of the city's noise complaints; Complaint unit for automatic noise complaints for different areas.

3. A method for spatial distribution characteristics and zoning control of urban noise complaints, which is applicable to the spatial distribution characteristics and zoning control system of urban noise complaints as described in any one of claims 1-2, characterized in that: The following steps are involved: S1: Using the noise monitoring data from various noise monitoring stations in the city, obtain the nighttime sound level values ​​of each monitoring station in the city and construct a nighttime sound level value distribution map; S2: Based on the distribution data of nighttime sound level values ​​monitored in the set area, the average sound level of urban noise in the target area is calculated, and the nighttime sound level value is compared with the average sound level of urban noise to determine the noise complaint threshold; S3: During the monitoring process, if the nighttime sound level value of any monitoring station in a certain area is greater than the noise complaint threshold, a noise complaint will be automatically issued; S4: Record noise complaints, obtain the number of complaints, count the areas and sites where complaints are recorded, and analyze the number and distribution of complaints at each monitoring site and each functional area within the city; S5: Based on noise complaint records and urban sound level distribution data, identify abnormal noise complaint areas within the city, and conduct multi-attribute analysis and spatial clustering; S6: Establish noise zoning control units based on the urban functional areas and the types of areas with abnormal noise complaints; S7: Based on the different types of functional areas, different classification parameters are used to predict noise, establish a prediction model for urban noise distribution, obtain the distribution of internal spatial noise in different functional areas of the city, and quantify noise prediction targets and point-by-point control targets; Wherein, the noise complaint threshold in step S2 is , the calculation formula is: ； In the formula, is the average sound level of urban noise, is the preset coefficient ( ), is the standard deviation of the nighttime sound level in the target area, .

4. A method for spatial distribution characteristics and zoning control of urban noise complaints according to claim 3, characterized in that: The step S2 further comprises the following steps: S201: Obtaining the nighttime sound level values ​​of each monitoring station in the set target area ; S202: Calculate the average nighttime sound level of the target area as the average urban noise level of the target area ; S203: The nighttime sound level value in the target area Average sound level of urban noise in the target area Compare and determine the noise complaint threshold of each monitoring station in the target area .

5. According to claim 4, a method for spatial distribution characteristics and zoning control of urban noise complaints is characterized in that: In step S202, the average nighttime sound level of the target area is calculated as the average urban noise level of the target area, and the calculation formula is: , where is the average sound level of urban noise, Indicates the nighttime sound level value, , is the total number of monitoring sites.

6. A method for spatial distribution characteristics and zoning control of urban noise complaints according to claim 5, characterized in that: In step S3: Obtaining the nighttime sound level value of a certain area means compressing the noise monitoring time according to the time pattern of the noise peak inside the city to obtain the nighttime sound level value of the monitoring station in the target area; The average sound level of urban noise refers to the average sound level of each monitoring station in the city in the set target area calculated based on the spatial distribution of the monitoring stations, that is, the average sound level of urban noise in each target area, which is used as the noise complaint threshold; The noise complaint threshold refers to the statistical night-time sound level values ​​of urban noise monitoring stations, the calculation of the average night-time sound level values ​​of each monitoring station in the set target area, and the determination of the noise complaint threshold of the noise monitoring station.

7. A method for spatial distribution characteristics and zoning control of urban noise complaints according to claim 6, characterized in that: The step S5 further comprises the following steps: S501: Statistics on the total number of noise complaints in each district and city , establish a noise complaint frequency distribution map, where , is the number of districts and cities; S502: Classify each functional area of ​​the statistical record, calculate the average value of complaints in each functional area, and establish a distribution map of noise complaints in each functional area; S503: Perform spatial cluster analysis on noise complaints in each functional area.

8. The urban noise complaint spatial distribution characteristics and zoning control method according to claim 7 is characterized in that: In step S502, each functional area of ​​the statistical record is classified, and the average complaint value in each functional area is calculated. , the calculation formula is: , where Indicates the functional area number, For the The number of monitoring sites in each functional area, For the A collection of monitoring sites within a functional area. Indicates the number of complaints, Indicates the monitoring site number.

9. A method for spatial distribution characteristics and zoning control of urban noise complaints according to claim 8, characterized in that: A density-based spatial clustering algorithm is used to perform spatial clustering analysis on noise complaints in each functional area. , defines the total number of complaints within its neighborhood for: , where For monitoring sites The collection of monitoring stations in the neighborhood.

10. A method for spatial distribution characteristics and zoning control of urban noise complaints according to claim 9, characterized in that: In step S7, a prediction model for urban noise distribution is established, and the following multivariate linear regression model is used for calculation: ； In the formula, represents the noise prediction value, For functional areas The area of For functional areas The population density within For functional areas The nighttime sound level at the last moment, , , , is the regression coefficient, is a random error term.

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