Intelligent human settlement environment detection and analysis system based on unmanned aerial vehicle vision

Abstract

The invention relates to the technical field of intelligent environment detection and analysis, and particularly discloses an intelligent human settlement environment detection and analysis system based on unmanned aerial vehicle vision. Comprising a human settlement environment region division module, a human settlement environment data acquisition module, an air quality detection and analysis module, a human settlement quality-effect detection and analysis module, a human settlement environment comprehensive detection and analysis module and a human settlement environment quality evaluation module. According to the invention, through the air quality detection and analysis module and the settlement quality-effect detection and analysis module, the air quality evaluation coefficient and the settlement quality-effect evaluation coefficient of each monitoring sub-region are calculated and obtained, and then the human settlement environment quality evaluation index of each monitoring sub-region is analyzed and obtained; by integrating the advanced unmanned aerial vehicle technology, the data processing technology and the intelligent analysis algorithm, various monitoring tasks can be automatically completed, manual intervention and errors are reduced, the monitoring efficiency and accuracy are improved, and powerful support is provided for quality monitoring and improvement of the human settlement environment.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental intelligent detection and analysis, and particularly to an intelligent detection and analysis system for human settlement environment based on unmanned aerial vehicle (UAV) vision. Background Art

[0002] UAV vision refers to a technology that uses image processing and computer vision algorithms to capture real-time images of the surrounding environment through visual sensors such as high-definition cameras carried by UAVs, and performs image recognition, feature extraction and analysis, so as to realize functions such as determination of the UAV position, obstacle recognition, target tracking and map construction.

[0003] The quality of the human settlement environment is a key indicator to measure the comfort and health level of human life. Especially in the context of current social development, its importance has become increasingly prominent. A high-quality human settlement environment can not only ensure that residents enjoy a high level of living comfort and good health, but also is an important cornerstone for promoting the sustainable development of the region.

[0004] Traditional intelligent detection and analysis systems for human settlement environments mainly rely on ground-based fixed monitoring stations and manual inspections. Ground monitoring stations are usually equipped with various environmental sensors, such as air quality monitors, water quality detectors, etc., for real-time collection of environmental data. Manual inspections are carried out by professional personnel to conduct on-site observations and records of the environment to obtain more intuitive environmental information. These data are then transmitted to the data center for storage and analysis to evaluate the overall quality of the human settlement environment.

[0005] Although traditional intelligent detection and analysis systems for human settlement environments have improved the monitoring efficiency, their defects are significant. The system relies too much on manual on-site inspections, which are time-consuming and laborious and difficult to cover large areas and complex terrain regions. The layout of ground monitoring stations is limited, resulting in monitoring blind spots. Manual inspections are also limited by time and energy and it is difficult to achieve comprehensive monitoring. In addition, the construction and maintenance costs of ground monitoring stations are high, and the equipment needs to be calibrated and updated regularly, resulting in a heavy economic burden. Manual inspections also require a large amount of human and material resources, and the overall operation cost of the system is high. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent detection and analysis system for human settlement environment based on UAV vision to solve the problems raised in the above background art.

[0007] To achieve the above object, the present invention provides the following technical solution: An intelligent detection and analysis system for human settlement environment based on UAV vision, including a human settlement environment area division module, a human settlement environment data collection module, an air quality detection and analysis module, a living and traveling quality and efficiency detection and analysis module, a human settlement environment comprehensive detection and analysis module, and a human settlement environment quality evaluation module.

[0008] Residential environment regional division module: used to divide the target residential environment into each monitoring sub-region according to the equal-area division method, and number each monitoring sub-region of the target residential environment;

[0009] Residential environment data collection module: used to collect the residential environment data of each monitoring sub-region of the target residential environment. The residential environment data collection module includes an air quality data collection unit and a residential behavior quality data collection unit, and the residential environment data includes air quality data and residential behavior quality data;

[0010] Air quality detection and analysis module: used to receive the air quality data transmitted by the residential environment data collection module, and calculate the air quality evaluation coefficient of each monitoring sub-region of the target residential environment based on the air quality data collection unit;

[0011] Residential behavior quality detection and analysis module: used to receive the residential behavior quality data transmitted by the residential environment data collection module, and calculate the residential behavior quality evaluation coefficient of each monitoring sub-region of the target residential environment based on the residential behavior quality data collection unit;

[0012] Residential environment comprehensive detection and analysis module: used to obtain the air quality evaluation coefficient and the residential behavior quality evaluation coefficient of each monitoring sub-region of the target residential environment, and conduct comprehensive detection and analysis to obtain the residential environment quality assessment index of each monitoring sub-region of the target residential environment;

[0013] Residential environment quality assessment module: used to obtain the residential environment quality assessment index of each monitoring sub-region of the target residential environment, evaluate the residential environment quality, output the residential environment quality assessment result, and send out a warning message for the data with abnormal assessment results.

[0014] Preferably, the specific division method of the residential environment regional division module is as follows:

[0015] Determine the residential environment as the target detection area, divide the target residential environment into each monitoring sub-region according to the equal-area division method, and number each monitoring sub-region of the target residential environment as 1, 2,..., i,..., n, where i represents the number of the i-th monitoring sub-region.

[0016] Preferably, the specific execution method of the residential environment data collection module is as follows:

[0017] The air quality data collection unit is used to collect the greening coverage rate, ozone concentration, and industrial wastewater discharge volume of each monitoring sub-region of the target residential environment, and mark them as gcr i 、O 3i and wdv i , where i = 1, 2,...n, and i represents the number of the i-th monitoring sub-region;

[0018] The residential environment quality data acquisition unit is used to collect the building volume ratio and road flatness of each monitoring sub-region of the target residential environment, which are respectively marked as far i and rs i .

[0019] Preferably, the method for obtaining the greening coverage rate is as follows:

[0020] According to the size and terrain of each monitoring sub-region, plan the UAV flight route and shooting parameters; control the UAV to fly according to the predetermined route to collect the image data of the target area; use photogrammetry software to splice the collected UAV images into a complete image to form an orthophoto map of the target area, and then perform image splicing, correction and 3D reconstruction; on the reconstructed 3D model or orthophoto, identify the vegetation areas of each monitoring sub-region through visual interpretation or automatic classification algorithms, and calculate the ratio of their areas to the total area of each monitoring sub-region to obtain the vegetation coverage rate gcr of each monitoring sub-region of the target residential environment i ;

[0021] The method for obtaining the industrial wastewater discharge amount is as follows:

[0022] Obtain the total industrial wastewater discharge time and wastewater discharge rate of each monitoring sub-region of the target residential environment, and substitute them into the formula to obtain the industrial wastewater discharge amount wdv of the i-th monitoring sub-region i , where wt i represents the total industrial wastewater discharge time of the i-th monitoring sub-region, and ev i represents the wastewater discharge rate of the i-th monitoring sub-region.

[0023] Preferably, the method for obtaining the building volume ratio is as follows:

[0024] Obtain the total building area and total land area of each monitoring sub-region of the target residential environment through UAVs, and substitute them into the formula to obtain the building volume ratio far of the i-th monitoring sub-region i , where Tba i represents the total building area of the i-th monitoring sub-region, and Tla i represents the total land area of the i-th monitoring sub-region;

[0025] The method for obtaining the road flatness is as follows:

[0026] First step, use a drone equipped with a high-definition camera to fly at a height of 80 meters along the road axis at a constant speed, and take an orthophoto of the road every 0.5 seconds; use image stitching software to stitch the images into a continuous long road map according to the shooting order and overlapping areas, and mark it as the stitched long map;

[0027] Second step, use the edge detection algorithm to identify the uneven areas in the stitched long map, count the number of pixels in the uneven areas, and calculate the road uneven area ua of each monitoring sub-region of the target human settlement environment according to the actual area corresponding to each pixel i ;

[0028] Third step, obtain the total road area ta of each monitoring sub-region of the target human settlement environment i , and obtain the road flatness rs of the i-th monitoring sub-region from the formula i .

[0029] Preferably, the specific implementation method of the air quality detection and analysis module is as follows:

[0030] First step, obtain the greening coverage rate gcr i , ozone concentration O 3i , and industrial waste water discharge wdv i of each monitoring sub-region of the target human settlement environment;

[0031] Second step, calculate the air quality evaluation coefficient of each monitoring sub-region of the target human settlement environment, and the calculation model is as follows:

[0032] Among them, AQC i represents the air quality evaluation coefficient of the i-th monitoring sub-region, O 3i represents the ozone concentration of the i-th monitoring sub-region, O 30 represents the preset safe ozone concentration, wdv i represents the industrial waste water discharge of the i-th monitoring sub-region, wdv 0 represents the preset standard industrial waste water discharge, gcr i represents the greening coverage rate of the i-th monitoring sub-region, and e represents the natural constant.

[0033] Preferably, the specific implementation method of the living and traveling quality and efficiency detection and analysis module is as follows:

[0034] First step, obtain the building volume rate far i of each monitoring sub-region of the target human settlement environment, and at the same time extract the preset standard building volume rate far 0 of each monitoring sub-region of the target human settlement environment from the management database, and substitute them into the formula ​Obtain the building floor area ratio deviation Dpr of the i-th monitored sub-region i ;

[0035] Second, calculate the living and traveling quality evaluation coefficient of each monitored sub-region of the target human settlement environment. The calculation model is as follows:

[0036] Among them, REC i represents the living and traveling quality evaluation coefficient of the i-th monitored sub-region, and Dpr max represents the preset maximum building floor area ratio deviation, and rs i represents the road evenness of the i-th monitored sub-region, and e represents the natural constant.

[0037] Preferably, the specific execution method of the human settlement environment comprehensive detection and analysis module is as follows:

[0038] First, obtain the air quality evaluation coefficient AQC of the i-th monitored sub-region i and the living and traveling quality evaluation coefficient REC of the i-th monitored sub-region i ;

[0039] Second, calculate the human settlement environment quality evaluation index of each monitored sub-region of the target human settlement environment. The calculation model is as follows:

[0040] EQAI i = AQC i ×REC i , where EQAI i represents the human settlement environment quality evaluation index of the i-th monitored sub-region.

[0041] Preferably, the specific execution method of the human settlement environment quality evaluation module is as follows:

[0042] Obtain the human settlement environment quality evaluation index of the i-th monitored sub-region, and evaluate the human settlement environment quality; compare the human settlement environment quality evaluation index of the i-th monitored sub-region with the preset human settlement environment quality evaluation index threshold. If the human settlement environment quality evaluation index of the i-th monitored sub-region is greater than or equal to the preset human settlement environment quality evaluation index threshold, it is determined that the human settlement environment quality of the i-th monitored sub-region is normal. If the human settlement environment quality evaluation index of the i-th monitored sub-region is less than the preset human settlement environment quality evaluation index, it is determined that the human settlement environment quality of the i-th monitored sub-region is abnormal, output the human settlement environment quality evaluation result, and send a warning message for the data with an abnormal evaluation result.

[0043] The technical effects and advantages of the present invention:

[0044] 1. Through the air quality detection and analysis module and the living and traveling quality detection and analysis module, the present invention calculates the air quality evaluation coefficient and the living and traveling quality evaluation coefficient of each monitored sub-region respectively, and then analyzes to obtain the human settlement environment quality evaluation index of each monitored sub-region. Based on the comprehensive evaluation mechanism, it can comprehensively reflect the overall quality status of the human settlement environment. In addition, the human settlement environment quality evaluation module can also send warning messages for data with abnormal evaluation results, timely reminding relevant departments and personnel to take countermeasures, and effectively preventing the occurrence of environmental problems.

[0045] 2. The present invention realizes the full-chain intelligence and automation from data collection, processing, analysis to evaluation. By integrating advanced sensor technology, data processing technology and intelligent analysis algorithms, it can automatically complete various monitoring tasks, reduce manual intervention and errors, and improve the monitoring efficiency and accuracy. At the same time, the intelligent level of the system can be continuously upgraded with the continuous progress of technology, providing strong support for the quality monitoring and improvement of the human settlement environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention will be further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the following drawings without creative efforts.

[0047] Figure 1 It is a schematic structural diagram of an intelligent detection and analysis system for human settlement environment based on unmanned aerial vehicle vision of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0049] Please refer to Figure 1 As shown, the present invention provides an intelligent detection and analysis system for human settlement environment based on unmanned aerial vehicle vision, including a human settlement environment area division module, a human settlement environment data collection module, an air quality detection and analysis module, a living and traveling quality detection and analysis module, a human settlement environment comprehensive detection and analysis module, and a human settlement environment quality evaluation module.

[0050] The human settlement environment regional division module is connected to the human settlement environment data collection module. The human settlement environment data collection module is respectively connected to the air quality detection and analysis module and the living and traveling quality and efficiency detection and analysis module. The air quality detection and analysis module is connected to the human settlement environment comprehensive detection and analysis module. The living and traveling quality and efficiency detection and analysis module is connected to the human settlement environment comprehensive detection and analysis module. The human settlement environment comprehensive detection and analysis module is connected to the human settlement environment quality assessment module.

[0051] Human settlement environment regional division module: It is used to divide the target human settlement environment into each monitoring sub-region according to the equal-area division method, and number each monitoring sub-region of the target human settlement environment.

[0052] In this embodiment, it should be specifically noted that the specific division method of the human settlement environment regional division module is as follows:

[0053] Determine the human settlement environment as the target detection area, divide the target human settlement environment into each monitoring sub-region according to the equal-area division method, and number each monitoring sub-region of the target human settlement environment as 1, 2,..., i,..., n, where i represents the number of the i-th monitoring sub-region.

[0054] Human settlement environment data collection module: It is used to collect the human settlement environment data of each monitoring sub-region of the target human settlement environment. The human settlement environment data collection module includes an air quality data collection unit and a living and traveling quality and efficiency data collection unit. The human settlement environment data includes air quality data and living and traveling quality and efficiency data.

[0055] In this embodiment, it should be specifically noted that the specific execution method of the human settlement environment data collection module is as follows:

[0056] The air quality data collection unit is used to collect the greening coverage rate, ozone concentration, and industrial wastewater discharge amount of each monitoring sub-region of the target human settlement environment, and mark them as gcr i 、O 3i and wdv i , where i = 1, 2,... n, and i represents the number of the i-th monitoring sub-region.

[0057] The living and traveling quality and efficiency data collection unit is used to collect the building floor area ratio and road flatness of each monitoring sub-region of the target human settlement environment, and mark them as far i and rs i .

[0058] In this embodiment, it should be specifically noted that the acquisition method of the greening coverage rate is specifically as follows:

[0059] According to the size and terrain of each monitoring sub-region, plan the flight route and shooting parameters of the UAV; control the UAV to fly according to the predetermined route to collect image data of the target area; use photogrammetry software (such as Agisoft Metashape) to stitch the collected UAV images into a complete image to form an orthophoto map of the target area, and then perform image stitching, correction and 3D reconstruction; on the reconstructed 3D model or orthophoto, identify the vegetation areas of each monitoring sub-region through visual interpretation or automatic classification algorithms, and calculate the ratio of its area to the total area of each monitoring sub-region to obtain the vegetation coverage gcr of each monitoring sub-region of the target human settlement environment i ;

[0060] In this embodiment, it should be specifically noted that the acquisition method of the ozone concentration is as follows:

[0061] Use a UAV equipped with a gas sensor to intelligently collect each monitoring sub-region of the target human settlement environment to obtain the ozone concentration O of each monitoring sub-region of the target human settlement environment 3i 。

[0062] In this embodiment, it should be specifically noted that the acquisition method of the industrial wastewater discharge amount is as follows:

[0063] Obtain the total industrial wastewater discharge time and wastewater discharge rate of each monitoring sub-region of the target human settlement environment, and substitute them into the formula respectively to obtain the industrial wastewater discharge amount wdv of the i-th monitoring sub-region i , where wt i represents the total industrial wastewater discharge time of the i-th monitoring sub-region, and ev i represents the wastewater discharge rate of the i-th monitoring sub-region.

[0064] In this embodiment, it should be specifically noted that the acquisition method of the building floor area ratio is as follows:

[0065] Use a UAV to obtain the total building area and total land area of each monitoring sub-region of the target human settlement environment, and substitute them into the formula respectively to obtain the building floor area ratio far of the i-th monitoring sub-region i , where Tba i represents the total building area of the i-th monitoring sub-region, and Tla i represents the total land area of the i-th monitoring sub-region;

[0066] In this embodiment, it should be specifically noted that the ratio of the floor area to the land area is the building floor area ratio, and the building floor area ratio reflects the land use efficiency and the residential density. A small floor area ratio means that there are relatively few buildings in the community and the population density is low, which helps to improve the comfort and quality of the living environment. A lower floor area ratio can provide more green space for the community, help improve air quality, regulate the microclimate, and provide more leisure and entertainment places for residents.

[0067] In this embodiment, it should be specifically noted that the method for obtaining the road flatness is as follows:

[0068] First step, use a drone equipped with a high-definition camera to fly along the road central axis at a height of 80 meters and at a constant speed (such as 5 m / s), and take a road orthophoto every 0.5 seconds; use image stitching software to stitch the images into a continuous long road image according to the shooting order and overlapping areas, and mark it as the stitched long image;

[0069] Second step, use an edge detection algorithm (such as the Canny algorithm) to identify the uneven areas in the stitched long image, count the number of pixels in the uneven areas, and calculate the road uneven area ua of each monitoring sub-region of the target human settlement environment according to the actual area corresponding to each pixel i ;

[0070] Third step, obtain the total road area ta of each monitoring sub-region of the target human settlement environment i , and obtain the road flatness rs of the i-th monitoring sub-region from the formula i .

[0071] Air quality detection and analysis module: used to receive the air quality data transmitted by the human settlement environment data collection module, and calculate the air quality evaluation coefficient of each monitoring sub-region of the target human settlement environment based on the air quality data collection unit;

[0072] In this embodiment, it should be specifically noted that the specific implementation method of the air quality detection and analysis module is as follows:

[0073] First step, obtain the green coverage rate gcr i , ozone concentration O 3i , and industrial wastewater discharge wdv i of each monitoring sub-region of the target human settlement environment;

[0074] Second step, calculate the air quality evaluation coefficient of each monitoring sub-region of the target human settlement environment, and the calculation model is as follows:

[0075] Among them, AQC iRepresents the air quality evaluation coefficient of the i-th monitoring sub-region, O 3i Represents the ozone concentration of the i-th monitoring sub-region, O 30 Represents the preset safe ozone concentration, wdv i Represents the industrial wastewater discharge of the i-th monitoring sub-region, wdv 0 Represents the preset standard industrial wastewater discharge, gcr i Represents the greening coverage rate of the i-th monitoring sub-region, where e is the natural constant.

[0076] Residential and travel quality and efficiency detection and analysis module: Used to receive the residential and travel quality and efficiency data transmitted by the residential environment data collection module, and calculate the residential and travel quality and efficiency evaluation coefficients of each monitoring sub-region of the target residential environment based on the residential and travel quality and efficiency data collection unit;

[0077] In this embodiment, it should be specifically noted that the specific execution method of the residential and travel quality and efficiency detection and analysis module is as follows:

[0078] First step, obtain the floor area ratio far of each monitoring sub-region of the target residential environment i , and at the same time extract the preset standard floor area ratio far of each monitoring sub-region of the target residential environment from the management database 0 , and substitute them into the formula respectively to obtain the floor area ratio deviation Dpr of the i-th monitoring sub-region i ;

[0079] Second step, calculate the residential and travel quality and efficiency evaluation coefficients of each monitoring sub-region of the target residential environment. The calculation model is specifically as follows:

[0080] Among them, REC i represents the residential and travel quality and efficiency evaluation coefficient of the i-th monitoring sub-region, Dpr max represents the preset maximum floor area ratio deviation, rs i represents the road evenness of the i-th monitoring sub-region, where e is the natural constant.

[0081] Residential environment comprehensive detection and analysis module: Used to obtain the air quality evaluation coefficients and residential and travel quality and efficiency evaluation coefficients of each monitoring sub-region of the target residential environment, and perform comprehensive detection and analysis to obtain the residential environment quality assessment index of each monitoring sub-region of the target residential environment;

[0082] In this embodiment, it should be specifically noted that the specific execution method of the residential environment comprehensive detection and analysis module is as follows:

[0083] First step, obtain the air quality evaluation coefficient AQC of the i-th monitoring sub-region i and the residential and travel quality and efficiency evaluation coefficient REC of the i-th monitoring sub-regioni ;

[0084] In the second step, calculate the human settlement environment quality assessment index for each monitoring sub-region of the target human settlement environment. The calculation model is as follows:

[0085] EQAI i = AQC i × REC i , where EQAI i represents the human settlement environment quality assessment index of the i-th monitoring sub-region.

[0086] Human settlement environment quality assessment module: It is used to obtain the human settlement environment quality assessment index for each monitoring sub-region of the target human settlement environment, evaluate the human settlement environment quality, output the human settlement environment quality assessment result, and send a warning message for data with abnormal assessment results.

[0087] In this embodiment, it should be specifically noted that the specific implementation method of the human settlement environment quality assessment module is as follows:

[0088] Obtain the human settlement environment quality assessment index of the i-th monitoring sub-region and evaluate the human settlement environment quality; compare the human settlement environment quality assessment index of the i-th monitoring sub-region with the preset human settlement environment quality assessment index threshold. If the human settlement environment quality assessment index of the i-th monitoring sub-region is greater than or equal to the preset human settlement environment quality assessment index threshold, it is determined that the human settlement environment quality of the i-th monitoring sub-region is normal. If the human settlement environment quality assessment index of the i-th monitoring sub-region is less than the preset human settlement environment quality assessment index, it is determined that the human settlement environment quality of the i-th monitoring sub-region is abnormal, output the human settlement environment quality assessment result, and send a warning message for data with abnormal assessment results.

[0089] Finally: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

[0090] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, and all should be covered by the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An intelligent detection and analysis system for human settlement environment based on drone vision, characterized in that: include: Human settlement area division module: used to divide the target human settlement into various monitoring sub-areas according to the division method of equal area, and number each monitoring sub-area of ​​the target human settlement environment; Human settlement environment data collection module: used to collect human settlement environment data of each monitoring sub-area of ​​the target human settlement environment, the human settlement environment data collection module includes an air quality data collection unit and a residential quality and efficiency data collection unit, and the human settlement environment data includes air quality data and residential quality and efficiency data; Air quality detection and analysis module: used to receive the air quality data transmitted by the human settlement environment data acquisition module, and calculate the air quality evaluation coefficient of each monitoring sub-area of ​​the target human settlement environment based on the air quality data acquisition unit; Housing quality and efficiency detection and analysis module: used to receive housing quality and efficiency data transmitted by the human settlement environment data acquisition module, and calculate the housing quality and efficiency evaluation coefficient of each monitoring sub-area of ​​the target human settlement environment based on the housing quality and efficiency data acquisition unit; Comprehensive detection and analysis module for human settlement environment: used to obtain the air quality evaluation coefficient and residential quality and efficiency evaluation coefficient of each monitoring sub-area of ​​the target human settlement environment, and conduct comprehensive detection and analysis to obtain the human settlement environment quality evaluation index of each monitoring sub-area of ​​the target human settlement environment; Human settlement environment quality assessment module: used to obtain the human settlement environment quality assessment index of each monitoring sub-area of ​​the target human settlement environment, evaluate the quality of the human settlement environment, output the human settlement environment quality assessment results, and issue early warning information for data with abnormal assessment results.

2. According to claim 1, the intelligent detection and analysis system for human settlement environment based on drone vision is characterized by: The specific division method of the human settlement area division module is as follows: The human settlement environment is determined as the target detection area, and the target human settlement environment is divided into monitoring sub-areas according to an equal area division method, and each monitoring sub-area of ​​the target human settlement environment is numbered 1, 2, ..., i, ..., n, where i represents the number of the i-th monitoring sub-area.

3. The human settlement environment intelligent detection and analysis system based on drone vision according to claim 1 is characterized by: The specific implementation method of the human settlement environment data collection module is as follows: The air quality data collection unit is used to collect the green coverage rate, ozone concentration and industrial wastewater discharge of each monitoring sub-area of ​​the target human settlement environment, which are marked as GCR i , O 3i and wdv i , where i = 1, 2, ... n, i represents the number of the i-th monitoring sub-area; The residential quality and efficiency data collection unit is used to collect the building volume ratio and road flatness of each monitoring sub-area of ​​the target residential environment, which are marked as far i and rs i .

4. The human settlement environment intelligent detection and analysis system based on drone vision according to claim 3 is characterized by: The method for obtaining the green coverage rate is as follows: Plan the flight route and shooting parameters of the drone according to the size and terrain of each monitoring sub-area; control the drone to fly according to the predetermined route to collect image data of the target area; use photogrammetry software to stitch the collected drone images into a complete image to form an orthophoto of the target area, and then stitch, correct and reconstruct the images in three dimensions; on the reconstructed three-dimensional model or orthophoto, identify the vegetation area of ​​each monitoring sub-area through visual interpretation or automatic classification algorithm, and calculate the ratio of its area to the total area of ​​each monitoring sub-area, and obtain the vegetation coverage gcr of each monitoring sub-area of ​​the target human settlement environment. i ; The specific method for obtaining the industrial wastewater discharge volume is as follows: Obtain the total time and rate of industrial wastewater discharge in each monitoring sub-area of ​​the target residential environment, and substitute them into the formula Get the industrial wastewater discharge wdv of the i-th monitoring sub-area i , where wt i It is expressed as the total time of industrial wastewater discharge in the i-th monitoring sub-area, ev i Expressed as the wastewater discharge rate of the i-th monitoring sub-area.

5. The human settlement environment intelligent detection and analysis system based on drone vision according to claim 3 is characterized by: The specific method for obtaining the building volume ratio is as follows: The total building area and total land area of ​​each monitoring sub-area of ​​the target residential environment are obtained by drone, and they are substituted into the formula Get the building volume ratio far of the i-th monitoring sub-area i , among which, Tba i It is expressed as the total building area of ​​the ith monitoring sub-area, Tla i It is expressed as the total land area of ​​the ith monitoring sub-area; The method for obtaining the road smoothness is specifically as follows: The first step is to use a drone equipped with a high-definition camera to fly along the central axis of the road at an altitude of 80 meters and a constant speed, taking an orthophoto of the road every 0.5 seconds; using image stitching software, the images are stitched into a continuous long road map according to the shooting order and overlapping areas, and marked as a stitched long map; In the second step, the edge detection algorithm is used to identify the uneven areas in the spliced ​​long image, count the number of pixels in the uneven areas, and calculate the area ua of the road unevenness area in each monitoring sub-area of ​​the target human settlement environment according to the actual area corresponding to each pixel. i ; The third step is to obtain the total road area ta of each monitoring sub-area of ​​the target human settlement environment. i , according to the formula Get the road roughness rs of the i-th monitoring sub-area i .

6. The human settlement environment intelligent detection and analysis system based on drone vision according to claim 1 is characterized by: The specific implementation method of the air quality detection and analysis module is as follows: The first step is to obtain the green coverage rate gcr of each monitoring sub-area of ​​the target human settlement environment i , ozone concentration O 3i And industrial wastewater discharge wdv i ; The second step is to calculate the air quality evaluation coefficient of each monitoring sub-area of ​​the target human settlement environment. The calculation model is as follows: Among them, AQC i represents the air quality evaluation coefficient of the ith monitoring sub-area, O 3i represents the ozone concentration in the ith monitoring sub-area, O 30 Indicates the preset safe ozone concentration, wdv i represents the industrial wastewater discharge of the ith monitoring sub-area, wdv0 represents the preset standard industrial wastewater discharge, gcr i represents the green coverage rate of the ith monitoring sub-area, and e is a natural constant.

7. The intelligent detection and analysis system for human settlement environment based on drone vision according to claim 1 is characterized by: The specific implementation method of the housing quality and efficiency detection and analysis module is as follows: The first step is to obtain the building volume ratio of each monitoring sub-area of ​​the target human settlement environment far i At the same time, the preset standard building volume ratio far0 of each monitoring sub-area of ​​the target residential environment is extracted from the management database and substituted into the formula Get the building volume ratio deviation Dpr of the i-th monitoring sub-area i ; The second step is to calculate the residential quality and efficiency evaluation coefficient of each monitoring sub-area of ​​the target residential environment. The calculation model is as follows: Among them, REC i represents the residential quality and efficiency evaluation coefficient of the ith monitoring sub-area, Dpr max Indicates the preset maximum building volume ratio deviation, rs i represents the road smoothness of the ith monitoring sub-area, and e is a natural constant.

8. The human settlement environment intelligent detection and analysis system based on drone vision according to claim 1 is characterized by: The specific implementation method of the comprehensive detection and analysis module of the human settlement environment is as follows: The first step is to obtain the air quality evaluation coefficient AQC of the i-th monitoring sub-area i and the residential quality and efficiency evaluation coefficient REC of the ith monitoring sub-area i ; The second step is to calculate the human settlement environment quality assessment index of each monitoring sub-area of ​​the target human settlement environment. The calculation model is as follows: EQAI i =AQC i ×REC i , among which, EQAI i Represents the human settlement environment quality assessment index of the ith monitoring sub-area.

9. The human settlement environment intelligent detection and analysis system based on drone vision according to claim 1 is characterized by: The specific implementation method of the human settlement environment quality assessment module is as follows: Obtain the human settlement environment quality assessment index of the ith monitoring sub-area and assess the human settlement environment quality; compare the human settlement environment quality assessment index of the ith monitoring sub-area with a preset human settlement environment quality assessment index threshold; if the human settlement environment quality assessment index of the ith monitoring sub-area is greater than or equal to the preset human settlement environment quality assessment index threshold, then the human settlement environment quality of the ith monitoring sub-area is judged to be normal; if the human settlement environment quality assessment index of the ith monitoring sub-area is less than the preset human settlement environment quality assessment, then the human settlement environment quality of the ith monitoring sub-area is judged to be abnormal; output the human settlement environment quality assessment result, and issue a warning message for data with abnormal assessment results.

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