Urban area atmospheric pollution monitoring method and system based on unmanned aerial vehicle

Abstract

The invention discloses an unmanned aerial vehicle-based urban area air pollution monitoring method and system, and aims to solve the problems that the current unmanned aerial vehicle-based urban area air pollution monitoring method generally uses a sensor to monitor urban area air pollution, the time required by the monitoring method is relatively long, and the monitoring area is limited. The technical problem that the shooting effect is not clear enough due to the light reflection influence of a building glass curtain wall can be solved, and the method comprises the following monitoring steps that S1, an unmanned aerial vehicle is used for carrying an air quality sensor, a laser scanner, an infrared sensor, a large gas detection sensor, an infrared imaging camera and a high-definition camera to lift off; according to the method, the concentration of the particulate matters in the air is determined through an image recognition technology, a monitoring area can be quickly reached, the time required by a traditional monitoring method is shortened, wide areas and places difficult to approach can be covered, and high accuracy and reliability of monitoring data are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of air pollution monitoring, and in particular to an urban area air pollution monitoring method and system based on unmanned aerial vehicle (UAV) technology. Background Art

[0002] To strengthen the rapid monitoring and positioning of pollutant distribution, drones can be well applied to the field of air pollution monitoring with their advantages of intelligence, informationization, automation, small size and high flexibility. Among them, fixed-wing drones have good applications in the field of large-scale atmospheric monitoring due to their advantages of fast flight speed and wide range. However, the current research situation does not have a good monitoring system to determine the location of pollution sources and predict the spread of atmospheric pollutants.

[0003] In the process of realizing the invention, the inventor found that there are at least the following problems in the prior art that have not been solved: during use, the traditional urban area air pollution monitoring method based on drones generally uses sensors to monitor urban area air pollution. The monitoring method takes a long time, the monitoring area is limited, and it can be easily affected by the reflection of the glass curtain wall of the building, making the shooting effect not clear and vivid. Therefore, it is necessary to design a new technical solution to solve it. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for monitoring urban area air pollution based on drones, so as to solve the technical problems that the current method for monitoring urban area air pollution based on drones generally uses sensors to monitor urban area air pollution, the monitoring method requires a relatively long time and the monitored area is limited, and it can be easily affected by the reflection of the glass curtain wall of the building, making the shooting effect not clear and distinct.

[0005] To achieve the above object, the present invention provides the following technical solution: a method and system for monitoring urban area air pollution based on drones, comprising the following monitoring steps:

[0006] S1. First, use a drone to carry an air quality sensor, a laser scanner, an infrared sensor, a large gas detection sensor, an infrared imaging camera and a high-definition camera to launch;

[0007] S2. The drones will then monitor different areas of the city from the air, and monitor the air quality of each area of ​​the city through high-speed flight and rapid sampling functions;

[0008] S3. The laser scanner and high-definition camera carried by the drone are then used to perform three-dimensional modeling;

[0009] S4. Multiple drones collaborate technically, and each drone can work at different times and locations to complete full coverage data collection and transmit the collected data to the terminal for processing;

[0010] S5. In emergency situations, drones can monitor the air quality through air quality sensors, and use high-definition cameras, infrared sensors, and large gas detection sensors to monitor and collect images of pollution sources in real time, dynamically update the concentration and distribution of multiple pollutants in the monitoring area in real time, and quickly lock the suspected location and propagation direction of air pollution sources;

[0011] S6. At night, the drone uses an infrared imaging camera to monitor the atmospheric environment. Through the thermal imager's heat distribution visualization characteristics and temperature measurement-related characteristics, it can accurately find locations where production operations are still ongoing and waste is discharged at night.

[0012] As a preferred embodiment of the present invention, in step S1, polarizing filters are installed on the shooting lens ends of the infrared imaging camera and the high-definition camera.

[0013] As a preferred embodiment of the present invention, the drone monitors different areas of the city in the air, mainly by photographing the target scene with a high-definition camera to obtain original image data, which includes the distribution of particulate matter in the air.

[0014] As a preferred embodiment of the present invention, in step S3, a laser scanner carried by an unmanned aerial vehicle performs three-dimensional modeling, and the laser scanner three-dimensional modeling includes laser radar scanning and photogrammetry:

[0015] LiDAR scanning is to generate ground elevation data by emitting laser beams to the ground and receiving reflected light to calculate the distance to the ground. Then, three-dimensional coordinate information of the ground is obtained by scanning with multiple laser beams.

[0016] Photogrammetry is a method of using drones equipped with high-resolution cameras to capture ground images from different angles and calculate the geometric relationships between these images to achieve three-dimensional modeling of the ground.

[0017] As a preferred embodiment of the present invention, in step S3, a high-definition camera carried by the drone performs three-dimensional modeling, and the high-definition camera three-dimensional modeling includes the following steps:

[0018] M1. First, use a drone equipped with a high-definition camera to shoot from multiple angles, directions, and perspectives to obtain a large amount of high-definition and high-precision image data;

[0019] M2. Preprocess the collected images, including border removal, distortion correction and image segmentation;

[0020] M3. After completing image matching, register the images from different perspectives to ensure that they are accurately aligned;

[0021] M4. Generate a 3D model based on the image data using a 3D reconstruction algorithm;

[0022] M5. Then, the generated 3D model is refined according to specific needs, including texture mapping, surface smoothing and mapping;

[0023] M6. Then, by carrying multiple sensors on the same flight platform and shooting from different angles at the same time, more complete and accurate information can be obtained;

[0024] M7. Finally, based on the image data, any point, line or surface can be measured to obtain centimeter-level measurement accuracy and automatically generate a three-dimensional geographic information model.

[0025] As a preferred implementation of the present invention, the three-dimensional reconstruction algorithm specifically adopts a triangulation method, a voxel-based method or a deep learning-based method.

[0026] As a preferred implementation of the present invention, the transmitting of the collected data to the terminal for processing in step S4 is preprocessing of the collected original image data, including image removal, noise enhancement and segmentation.

[0027] As a preferred embodiment of the present invention, an urban area air pollution monitoring system based on a drone includes the drone platform, an air quality sensor, an infrared sensor, a data acquisition module, a data transmission module, an image preprocessing module, an image registration module, a three-dimensional model generation module, a refinement processing module, a multi-angle information acquisition module, a high-precision measurement module, a ground control station, a visual data analysis module, a drone atmospheric environment monitoring platform, a laser scanner, a large gas detection sensor, an infrared imaging camera and a high-definition camera.

[0028] As a preferred embodiment of the present invention, the UAV platform serves as a carrier of the monitoring system, and the UAV platform is responsible for carrying other monitoring equipment for aerial flight and monitoring;

[0029] Large gas detection sensor: The sensor is installed on the drone to monitor the gas composition in a specific area in real time;

[0030] Data transmission module: responsible for transmitting the monitored data to the ground control station or server in real time for data analysis and processing;

[0031] Ground control station: As the data receiving and processing center, the ground control station is responsible for receiving the data transmitted by the drone and decoding, displaying, processing and reporting;

[0032] Visual data analysis module: used to process and analyze the data transmitted by the drone, generate trend curves and historical data comparison charts;

[0033] UAV atmospheric environment monitoring platform: realizes UAV flight mission management, real-time flight monitoring and historical tracing, and provides comprehensive monitoring and management services through the combination of cloud computing and big data technology.

[0034] As a preferred embodiment of the present invention, the large gas detection sensor includes a PM2.5 sensor, a PM10 sensor, a CO sensor, a SO2 sensor, a NO2 sensor, an O3 sensor, a VOCs sensor and a H2S sensor.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The present invention determines the concentration of particulate matter in the air through image recognition technology, can quickly reach the monitoring area, shortens the time required for traditional monitoring methods, and can cover wide areas and inaccessible places, ensuring high accuracy and reliability of monitoring data, and can avoid the reflection effect of glass curtain walls of buildings, making the shooting effect clearer and more vivid. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0038] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0040] Example 1: See Figure 1 , a method and system for monitoring urban area air pollution based on drones, comprising the following monitoring steps:

[0041] S1. First, use a drone to carry an air quality sensor, a laser scanner, an infrared sensor, a large gas detection sensor, an infrared imaging camera and a high-definition camera to launch;

[0042] S2. The drones will then monitor different areas of the city from the air, and monitor the air quality of each area of ​​the city through high-speed flight and rapid sampling functions;

[0043] S3. The laser scanner and high-definition camera carried by the drone are then used to perform three-dimensional modeling;

[0044] S4. Multiple drones collaborate technically, and each drone can work at different times and locations to complete full coverage data collection and transmit the collected data to the terminal for processing;

[0045] S5. In emergency situations, drones can monitor the air quality through air quality sensors, and use high-definition cameras, infrared sensors, and large gas detection sensors to monitor and collect images of pollution sources in real time, dynamically update the concentration and distribution of multiple pollutants in the monitoring area in real time, and quickly lock the suspected location and propagation direction of air pollution sources;

[0046] S6. At night, the drone uses an infrared imaging camera to monitor the atmospheric environment. Through the thermal imager's heat distribution visualization characteristics and temperature measurement-related characteristics, it can accurately find locations where production operations are still ongoing and waste is discharged at night.

[0047] Specifically, in step S1 , polarizing filters are installed on the shooting lens ends of the infrared imaging camera and the high-definition camera.

[0048] Furthermore, drones monitor different areas of the city from the air, mainly using high-definition cameras to capture target scenes and obtain raw image data, which includes the distribution of particulate matter in the air.

[0049] Furthermore, in step S3, a laser scanner carried by the drone performs 3D modeling. The laser scanner 3D modeling includes laser radar scanning and photogrammetry:

[0050] LiDAR scanning is to generate ground elevation data by emitting laser beams to the ground and receiving reflected light to calculate the distance to the ground. Then, three-dimensional coordinate information of the ground is obtained by scanning with multiple laser beams.

[0051] Photogrammetry is a method of using drones equipped with high-resolution cameras to capture ground images from different angles and calculate the geometric relationships between these images to achieve three-dimensional modeling of the ground.

[0052] It is worth noting that in step S3, the high-definition camera carried by the drone performs three-dimensional modeling, and the high-definition camera three-dimensional modeling includes the following steps:

[0053] M1. First, use a drone equipped with a high-definition camera to shoot from multiple angles, directions, and perspectives to obtain a large amount of high-definition and high-precision image data;

[0054] M2. Preprocess the collected images, including border removal, distortion correction and image segmentation;

[0055] M3. After completing image matching, register the images from different perspectives to ensure that they are accurately aligned;

[0056] M4. Generate a 3D model based on the image data using a 3D reconstruction algorithm;

[0057] M5. Then, the generated 3D model is refined according to specific needs, including texture mapping, surface smoothing and mapping;

[0058] M6. Then, by carrying multiple sensors on the same flight platform and shooting from different angles at the same time, more complete and accurate information can be obtained;

[0059] M7. Finally, based on the image data, any point, line or surface can be measured to obtain centimeter-level measurement accuracy and automatically generate a three-dimensional geographic information model.

[0060] It is worth noting that the 3D reconstruction algorithm specifically uses triangulation, voxel-based methods, or deep learning-based methods.

[0061] It is worth mentioning that the transmission of the collected data to the terminal for processing in step S4 is a preprocessing of the collected original image data, including image removal, noise enhancement and segmentation.

[0062] An urban area air pollution monitoring system based on unmanned aerial vehicles (UAVs), comprising an unmanned aerial vehicle platform, an air quality sensor, an infrared sensor, a data acquisition module, a data transmission module, an image preprocessing module, an image registration module, a three-dimensional model generation module, a refined processing module, a multi-angle information acquisition module, a high-precision measurement module, a ground control station, a visual data analysis module, an unmanned aerial vehicle atmospheric environment monitoring platform, a laser scanner, a large gas detection sensor, an infrared imaging camera and a high-definition camera.

[0063] It is worth emphasizing that the UAV platform is the carrier of the monitoring system, and the UAV platform is responsible for carrying other monitoring equipment for aerial flight and monitoring;

[0064] Large gas detection sensor: The sensor is installed on the drone to monitor the gas composition in a specific area in real time;

[0065] Data transmission module: responsible for transmitting the monitored data to the ground control station or server in real time for data analysis and processing;

[0066] Ground control station: As the data receiving and processing center, the ground control station is responsible for receiving the data transmitted by the drone and decoding, displaying, processing and reporting;

[0067] Visual data analysis module: used to process and analyze the data transmitted by the drone, generate trend curves and historical data comparison charts;

[0068] UAV atmospheric environment monitoring platform: realizes UAV flight mission management, real-time flight monitoring and historical tracing, and provides comprehensive monitoring and management services through the combination of cloud computing and big data technology;

[0069] Large gas detection sensors include PM2.5 sensors, PM10 sensors, CO sensors, SO2 sensors, NO2 sensors, O3 sensors, VOCs sensors and H2S sensors.

[0070] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

[0071] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A method for monitoring urban area air pollution based on drones, characterized in that: The monitoring steps include: S1. First, use a drone to carry an air quality sensor, a laser scanner, an infrared sensor, a large gas detection sensor, an infrared imaging camera and a high-definition camera to launch; S2. The drones will then monitor different areas of the city from the air, and monitor the air quality of each area of ​​the city through high-speed flight and rapid sampling functions; S3. The laser scanner and high-definition camera carried by the drone are then used to perform three-dimensional modeling; S4. Multiple drones collaborate technically, and each drone can work at different times and locations to complete full coverage data collection and transmit the collected data to the terminal for processing; S5. In emergency situations, drones can monitor the air quality through air quality sensors, and use high-definition cameras, infrared sensors, and large gas detection sensors to monitor and collect images of pollution sources in real time, dynamically update the concentration and distribution of multiple pollutants in the monitoring area in real time, and quickly lock the suspected location and propagation direction of air pollution sources; S6. At night, the drone uses an infrared imaging camera to monitor the atmospheric environment. Through the thermal imager's heat distribution visualization characteristics and temperature measurement-related characteristics, it can accurately find locations where production operations are still ongoing and waste is discharged at night.

2. The method for monitoring urban area air pollution based on drone according to claim 1, characterized in that: In step S1, polarizing filters are installed on the shooting lens ends of the infrared imaging camera and the high-definition camera.

3. The method for monitoring urban area air pollution based on drone according to claim 1, characterized in that: The drone monitors different areas of the city in the air, mainly by using a high-definition camera to shoot the target scene and obtain original image data, which includes the distribution of particulate matter in the air.

4. The method for monitoring urban area air pollution based on drone according to claim 1, characterized in that: In step S3, the laser scanner carried by the drone performs three-dimensional modeling, and the laser scanner three-dimensional modeling includes laser radar scanning and photogrammetry: LiDAR scanning is to generate ground elevation data by emitting laser beams to the ground and receiving reflected light to calculate the distance to the ground. Then, three-dimensional coordinate information of the ground is obtained by scanning with multiple laser beams. Photogrammetry is a method of using drones equipped with high-resolution cameras to capture ground images from different angles and calculate the geometric relationships between these images to achieve three-dimensional modeling of the ground.

5. The method for monitoring urban area air pollution based on drone according to claim 1, characterized in that: In step S3, a high-definition camera carried by the drone performs three-dimensional modeling, and the high-definition camera three-dimensional modeling includes the following steps: M1. First, use a drone equipped with a high-definition camera to shoot from multiple angles, directions, and perspectives to obtain a large amount of high-definition and high-precision image data; M2. Preprocess the collected images, including border removal, distortion correction and image segmentation; M3. After completing image matching, register the images from different perspectives to ensure that they are accurately aligned; M4. Generate a 3D model based on the image data using a 3D reconstruction algorithm; M5. Then, the generated 3D model is refined according to specific needs, including texture mapping, surface smoothing and mapping; M6. Then, by carrying multiple sensors on the same flight platform and shooting from different angles at the same time, more complete and accurate information can be obtained; M7. Finally, based on the image data, any point, line or surface can be measured to obtain centimeter-level measurement accuracy and automatically generate a three-dimensional geographic information model.

6. The method for monitoring urban area air pollution based on drone according to claim 5, characterized in that: The three-dimensional reconstruction algorithm specifically adopts a triangulation method, a voxel-based method or a deep learning-based method.

7. The method for monitoring urban area air pollution based on drone according to claim 1, characterized in that: The step S4 of transmitting the collected data to the terminal for processing is to pre-process the collected original image data, including image removal, noise enhancement and segmentation.

8. An urban area air pollution monitoring system based on drones, characterized by: It includes the UAV platform, air quality sensor, infrared sensor, data acquisition module, data transmission module, image preprocessing module, image registration module, three-dimensional model generation module, refined processing module, multi-angle information acquisition module, high-precision measurement module, ground control station, visual data analysis module, UAV atmospheric environment monitoring platform, laser scanner, large gas detection sensor, infrared imaging camera and high-definition camera.

9. The urban area air pollution monitoring system based on drone according to claim 8 is characterized by: The UAV platform serves as a carrier of the monitoring system, and is responsible for carrying other monitoring equipment for aerial flight and monitoring; Large gas detection sensor: The sensor is installed on the drone to monitor the gas composition in a specific area in real time; Data transmission module: responsible for transmitting the monitored data to the ground control station or server in real time for data analysis and processing; Ground control station: As the data receiving and processing center, the ground control station is responsible for receiving the data transmitted by the drone and decoding, displaying, processing and reporting; Visual data analysis module: used to process and analyze the data transmitted by the drone, generate trend curves and historical data comparison charts; UAV atmospheric environment monitoring platform: realizes UAV flight mission management, real-time flight monitoring and historical tracing, and provides comprehensive monitoring and management services through the combination of cloud computing and big data technology.

10. The urban area air pollution monitoring system based on drone according to claim 9, characterized in that: The macro-gas detection sensors include PM2.5 sensors, PM10 sensors, CO sensors, SO2 sensors, NO2 sensors, O3 sensors, VOCs sensors and H2S sensors.

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