Atmospheric dust monitoring system based on GPS

Abstract

The invention discloses an atmospheric dust monitoring system based on a GPS (Global Positioning System), which relates to the technical field of atmospheric dust monitoring and comprises the following modules: a feedback model building module for building a dust monitoring environment model by utilizing a GIS (Geographic Information System) space model through geographic information; the vehicle-mounted cruise monitoring module is used for acquiring atmospheric dust vehicle monitoring concentration and vehicle monitoring positioning information through driving and moving of a dust monitoring vehicle according to a monitoring route; the unmanned aerial vehicle cruise monitoring module is used for acquiring atmospheric dust machine monitoring concentration and machine monitoring positioning information; the model data integration module is used for correcting the weak signal area according to the marking result and the flying picture; therefore, the dust monitoring data can be conveniently displayed in the dust monitoring environment model, the monitored scattered dust concentration data can be conveniently visualized, a subsequent dust monitoring vehicle can conveniently and movably monitor the dust concentration according to a monitoring route, and the accuracy and authenticity of dust concentration monitoring are further facilitated.

Description

Technical Field

[0001] The invention relates to the technical field of atmospheric dust monitoring, and in particular to an atmospheric dust monitoring system based on GPS. Background Art

[0002] Atmospheric dust refers to tiny particles suspended in the atmosphere. It comes from a wide range of sources, including natural factors such as wind and sand, volcanic eruptions, forest fires, etc., as well as human factors such as industrial emissions, transportation, construction, etc. The particle size of atmospheric dust varies, ranging from a few nanometers to tens of microns. Smaller particles can penetrate deep into the human lungs, causing harm to human health and causing respiratory diseases. At the same time, atmospheric dust can also affect the visibility of the atmosphere, causing inconvenience to transportation and daily life. In terms of the environment, it may also have an impact on the ecosystem, such as affecting the photosynthesis of plants. In addition, atmospheric dust will also participate in atmospheric chemical processes and have a certain impact on the climate.

[0003] Monitoring stations mostly choose fixed-point sampling methods in the process of monitoring atmospheric dust. The dust concentration at the sampling point is obtained through dust concentration sensors, filter membrane weighing method, natural dust accumulation method and other means, and then the dust concentration of the entire monitoring area is estimated based on the dust concentration of multiple sampling points. However, this fixed-point sampling method is not only easy to affect the dust concentration monitoring results of the overall monitoring area due to inaccurate sampling results at the sampling points, but also errors will occur in the process of deducing the dust concentration of the entire monitoring area through the sampling points. Therefore, it is easy to lack authenticity and accuracy in the process of atmospheric dust monitoring, and it is difficult to effectively monitor atmospheric dust in an intelligent and precise manner. For this reason, we propose an atmospheric dust monitoring system based on GPS. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the deficiencies of the prior art, the present invention provides an atmospheric dust monitoring system based on GPS to solve the above problems in the prior art.

[0005] (II) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: A GPS-based atmospheric dust monitoring system, comprising the following modules: Feedback model building module, obtain geographic information within the monitoring range, use GIS spatial model to establish dust monitoring environment model through geographic information, and formulate monitoring route according to dust monitoring environment model; The vehicle cruise monitoring module obtains the atmospheric dust concentration and vehicle monitoring positioning information by driving the dust monitoring vehicle along the monitoring route, obtains the weak signal area through the dust monitoring vehicle, and obtains the release area through the weak signal area and the monitoring route; The drone cruise monitoring module releases the dust monitoring drone mounted on the monitoring vehicle in the release area. The dust monitoring drone flies with the dust monitoring vehicle in the release area to obtain the atmospheric dust concentration and positioning information. The dust monitoring drone takes a bird's-eye view of the environment to obtain the release picture. The model data integration module marks and displays the atmospheric dust vehicle-monitored concentration in the dust monitoring environment model according to the vehicle-monitored positioning information, and marks and displays the atmospheric dust machine-monitored concentration in the dust monitoring environment model according to the machine-monitored positioning information, and corrects the weak signal area based on the marking results and the release pictures.

[0006] Preferably, in the feedback model building module, a monitoring route is formulated according to the dust monitoring environment model, specifically: Step 1: Obtain a road map within the monitoring range through the dust monitoring environment model, obtain the location information of all factories, schools, hospitals and shopping malls, and mark the locations of all factories, schools, hospitals and shopping malls on the road map to obtain a primary road map; Step 2: Obtain the location information of the monitoring station, and mark the location of the monitoring station on the primary route map to obtain an intermediate route map; Step 3: Using the monitoring station as the starting point and the end point, passing through all the factories, schools, hospitals and shopping malls, three monitoring paths are formulated using genetic algorithms. The distances of the three monitoring paths are measured respectively, and the one with the shortest distance is selected as the monitoring route.

[0007] Preferably, in the vehicle cruise monitoring module, the dust monitoring vehicle moves along the monitoring route to obtain the atmospheric dust vehicle monitoring concentration and vehicle monitoring positioning information, specifically: Step 1: Set the recording interval to 5 minutes, obtain the moving speed of the dust monitoring vehicle, and obtain the moving distance of the dust monitoring vehicle by multiplying the moving speed of the dust monitoring vehicle by the 5-minute recording interval; Step 2: Determine whether the dust monitoring vehicle has moved a distance greater than 1 kilometer. If the dust monitoring vehicle has moved a distance greater than or equal to 1 kilometer, record the current atmospheric dust concentration once and mark it as the atmospheric dust vehicle monitoring concentration and send it to the monitoring station. Record the current vehicle GPS location information once and mark it as the vehicle monitoring positioning information and send it to the monitoring station. If the dust monitoring vehicle has moved a distance less than 1 kilometer, execute step 1.

[0008] Preferably, in the vehicle cruise monitoring module, the weak signal area is obtained by using a dust monitoring vehicle, specifically: Step 1: Set the signal verification time interval to 10 seconds. Use the signal verification time interval as the standard to send a verification signal to the monitoring station through the dust monitoring vehicle and receive the feedback signal from the monitoring station. Determine whether the dust monitoring vehicle receives the feedback signal. If no feedback signal is received, the signal verification result is marked as 0. If a feedback signal is received, the signal verification result is marked as 1. Step 2: Obtain three signal verification results, and get the final signal result by summing the three signal verification results. Determine whether the final signal result is greater than 2. If the final signal result is greater than 2, execute step 1. If the final signal result is less than or equal to 2, obtain the current vehicle GPS location information and mark it as a weak signal area.

[0009] Preferably, in the vehicle cruise monitoring module, the release area is obtained through the weak signal area and the monitoring route, specifically: Step 1: Obtain the location information of the weak signal area, mark the location of the weak signal area in the dust monitoring environment model to obtain a comparison map, obtain a monitoring route map, and overlap the comparison map with the monitoring route map based on the road to obtain a reference map; Step 2: Determine whether the coordinates of the weak signal area in the reference map are on the monitoring route. If the weak signal area is on the monitoring route, mark the weak signal area as the release area. If the weak signal area is not on the monitoring route, notify the dust monitoring vehicle to deviate from the monitoring route.

[0010] Preferably, in the drone cruise monitoring module, the dust monitoring drone mounted on the monitoring vehicle is released in the release area, specifically: Step 1: Set the judgment interval time, and use the judgment interval time as a period to judge whether the current position is a release area. If the current position is a release area, execute step 2; Step 2: Use the camera on the roof of the dust monitoring vehicle to take a photo of the environment from an upward perspective, process the grayscale of the environment photo, mark the unobstructed area and the obstructed area by the difference in brightness, measure the area of ​​the unobstructed area, measure the area of ​​the obstructed area, and obtain the hazard value by dividing the area of ​​the obstructed area by the area of ​​the unobstructed area; Step 3: Set the preset threshold of the danger value and determine whether the danger value is less than the preset threshold of the danger value. If the danger value is less than or equal to the preset threshold of the danger value, release the dust monitoring drone. If the danger value is greater than the preset threshold of the danger value, execute step 2.

[0011] Preferably, in the drone cruise monitoring module, the dust monitoring drone is flown with the dust monitoring vehicle in the release area to obtain the atmospheric dust monitoring concentration and monitoring positioning information, specifically: Step 1: Set the safe flight altitude and safe flight speed. The dust monitoring drone will fly vertically to the safe flight altitude at the safe flight speed. Step 2: Obtain the positioning information of the dust monitoring vehicle, obtain the monitoring route, obtain the moving direction of the dust monitoring vehicle through the monitoring route and the positioning information of the dust monitoring vehicle, obtain the current moving speed of the dust monitoring vehicle, set the moving speed of the dust monitoring drone to be the same as the moving speed of the dust monitoring vehicle, and set the moving direction of the dust monitoring drone to be the same as the moving direction of the dust monitoring vehicle; Step 3: Set the recording time interval to 2 minutes, obtain the moving speed of the dust monitoring drone, and obtain the moving distance of the dust monitoring drone by multiplying the moving speed of the dust monitoring drone by the 2-minute recording time interval; Step 4: Determine whether the dust monitoring drone has moved more than 200 meters. If the dust monitoring drone has moved more than or equal to 200 meters, record the current atmospheric dust concentration and mark it as the atmospheric dust machine-monitored concentration and send it to the monitoring station. Record the current drone GPS location information and mark it as the machine-monitored positioning information and send it to the monitoring station. If the dust monitoring drone has moved less than 200 meters, execute step 3.

[0012] Preferably, in the model data integration module, the atmospheric dust vehicle monitoring concentration is marked and displayed in the dust monitoring environment model according to the vehicle monitoring positioning information, and the atmospheric dust machine monitoring concentration is marked and displayed in the dust monitoring environment model according to the machine monitoring positioning information, specifically: Step 1: Obtain all vehicle monitoring positioning information, mark the vehicle positioning points in the dust monitoring environment model according to all vehicle monitoring positioning information, and mark the corresponding atmospheric dust vehicle monitoring concentration at all vehicle positioning points; Step 2: Obtain all machine monitoring positioning information, mark the machine positioning points in the dust monitoring environment model according to all machine monitoring positioning information, and mark the corresponding atmospheric dust machine monitoring concentration at all machine positioning points; Step 3: Mark the points where the vehicle positioning point and the machine positioning point overlap as the overlap points.

[0013] Preferably, the weak signal area is corrected in the model data integration module according to the marking results and the released image, specifically: Step 1: Obtain the position information of the coincidence point, obtain the release picture of the coincidence point according to the position information of the coincidence point, mark it as the coincidence release picture, grayscale the coincidence release picture, mark the occlusion area and the unocclusion area by the difference in brightness, measure the area of ​​the unocclusion area, measure the area of ​​the occlusion area, and obtain the occlusion value by dividing the area of ​​the occlusion area by the area of ​​the unocclusion area; Step 2: Set the preset threshold of the occlusion value, and determine whether the occlusion value is less than the preset threshold of the occlusion value. If the occlusion value is less than or equal to the preset threshold of the occlusion value, then define the overlap point as a non-weak signal area, and remove the area from the weak signal area. If the occlusion value is greater than the preset threshold of the occlusion value, then define the overlap point as a signal unstable area, and mark the signal unstable area in the weak signal area.

[0014] (III) Beneficial effects The present invention provides an atmospheric dust monitoring system based on GPS, which has the following beneficial effects: (1) In the feedback model building module, this scheme uses geographic information to use the GIS spatial model to establish a dust monitoring environment model, and formulates a monitoring route based on the dust monitoring environment model, so as to facilitate the subsequent display of dust monitoring data in the dust monitoring environment model, and then facilitate the visualization of the monitored scattered dust concentration data. By formulating a monitoring route, it is convenient for the subsequent dust monitoring vehicle to monitor the dust concentration along the monitoring route, which is beneficial to the accuracy and authenticity of dust concentration monitoring.

[0015] (2) In the model data integration module, this scheme marks and displays the dust concentration monitored by the dust monitoring vehicle and the dust monitoring drone in the dust monitoring environment model, so as to facilitate the visualization of the monitored scattered dust concentration data. The weak signal area is corrected according to the marking results and the release pictures, so as to facilitate the subsequent control of the dust monitoring vehicle and the dust monitoring drone to reasonably monitor the dust concentration. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a structural schematic diagram of an atmospheric dust monitoring system based on GPS according to the present invention; Figure 2 The present invention is a principle block diagram of an atmospheric dust monitoring system based on GPS. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1-Figure 2 The present invention provides an atmospheric dust monitoring system based on GPS, comprising the following modules: The feedback model building module obtains geographic information within the monitoring range, uses the GIS spatial model through the geographic information to establish a dust monitoring environment model, and formulates a monitoring route based on the dust monitoring environment model; in this scheme, in the feedback model building module, the GIS spatial model is used to establish a dust monitoring environment model through geographic information, and a monitoring route is formulated based on the dust monitoring environment model, so as to facilitate the subsequent display of dust monitoring data in the dust monitoring environment model, and then facilitate the visualization of the monitored scattered dust concentration data. By formulating the monitoring route, it is convenient for the subsequent dust monitoring vehicle to monitor the dust concentration in a mobile manner along the monitoring route, which is beneficial to the accuracy and authenticity of the dust concentration monitoring; The vehicle-mounted cruise monitoring module obtains the atmospheric dust vehicle monitoring concentration and vehicle monitoring positioning information by having the dust monitoring vehicle move along the monitoring route, obtains the weak signal area through the dust monitoring vehicle, and obtains the release area through the weak signal area and the monitoring route; in the vehicle-mounted cruise monitoring module, this solution obtains the atmospheric dust vehicle monitoring concentration and vehicle monitoring positioning information by having the dust monitoring vehicle move along the monitoring route, thereby facilitating mobile monitoring of dust concentration, which is beneficial to the accuracy and authenticity of dust concentration monitoring, and the vehicle monitoring positioning information facilitates the subsequent positioning and display of the monitored dust vehicle monitoring concentration in the dust monitoring environment model, which is convenient for visualizing the monitored scattered dust concentration data, and the release area is obtained through the weak signal area and the monitoring route, so as to facilitate the release of dust monitoring drones in areas with poor signals to monitor the environment, which is beneficial to avoid the loss of dust monitoring data in some areas due to unstable GPS signals, and further beneficial to the accuracy and authenticity of dust concentration monitoring; The drone cruise monitoring module releases the dust monitoring drone carried on the monitoring vehicle in the release area, and obtains the atmospheric dust monitoring concentration and monitoring positioning information by the dust monitoring drone flying with the dust monitoring vehicle in the release area, and obtains the release picture by taking the environmental photos from a bird's-eye view; in the drone cruise monitoring module, this scheme monitors the area with weak GPS signals by releasing the dust monitoring drone, and obtains the atmospheric dust monitoring concentration and monitoring positioning information by the dust monitoring drone flying with the dust monitoring vehicle in the release area, so as to facilitate the subsequent positioning and display of the atmospheric dust monitoring concentration in the dust monitoring environment model according to the monitoring positioning information, which is further beneficial to the accuracy and authenticity of dust concentration monitoring, and obtains the release picture by taking the environmental photos from a bird's-eye view by the dust monitoring drone, so as to facilitate the subsequent correction of the weak signal area according to the marking results and the release picture, so as to facilitate the control of the dust monitoring vehicle and the dust monitoring drone to reasonably monitor the dust concentration; The model data integration module marks and displays the atmospheric dust vehicle-monitored concentration in the dust monitoring environment model according to the vehicle monitoring positioning information, and marks and displays the atmospheric dust machine-monitored concentration in the dust monitoring environment model according to the aircraft monitoring positioning information, and corrects the weak signal area according to the marking results and the release pictures; In the model data integration module, this scheme marks and displays the dust concentration monitored by the dust monitoring vehicle and the dust concentration monitored by the dust monitoring drone in the dust monitoring environment model, so as to facilitate the visualization of the monitored scattered dust concentration data, and corrects the weak signal area according to the marking results and the release pictures, so as to facilitate the subsequent control of the dust monitoring vehicle and the dust monitoring drone to reasonably monitor the dust concentration.

[0019] It is worth mentioning that in this scheme, the dust monitoring environment model is established by using the GIS spatial model through geographic information, which can be generated through GIS spatial model training. The GIS spatial model is an existing technology, and its specific training and generation steps are not described in detail here. Both the dust monitoring vehicle and the dust monitoring drone are equipped with dust concentration sensors, and the dust concentration information in the current environment can be directly obtained through the dust concentration sensor.

[0020] In the feedback model building module, a monitoring route is formulated according to the dust monitoring environment model, specifically: Step 1: Obtain a road map within the monitoring range through the dust monitoring environment model, obtain the location information of all factories, schools, hospitals and shopping malls, and mark the locations of all factories, schools, hospitals and shopping malls on the road map to obtain a primary road map; Step 2: Obtain the location information of the monitoring station, and mark the location of the monitoring station on the primary route map to obtain an intermediate route map; Step 3: Using the monitoring station as the starting point and the end point, passing through all the factories, schools, hospitals and shopping malls, three monitoring paths are formulated using genetic algorithms. The distances of the three monitoring paths are measured respectively, and the one with the shortest distance is selected as the monitoring route.

[0021] In this embodiment, the three-dimensional space model is two-dimensionalized through the bird's-eye view of the dust monitoring environment model to obtain a road map within the monitoring range, and then factories, schools, hospitals and shopping malls with dense crowds of people are marked on the road map, so as to facilitate the key monitoring of dust concentration in crowded places. The monitoring path is formulated through a genetic algorithm and the shortest distance is selected as the monitoring route, which is beneficial to improving the mobile monitoring efficiency of the dust monitoring vehicle. It is worth mentioning that formulating and selecting the optimal path through a genetic algorithm is an existing technology, and its specific operating steps will not be described in detail here.

[0022] In the vehicle cruise monitoring module, the dust monitoring vehicle moves along the monitoring route to obtain the atmospheric dust vehicle monitoring concentration and vehicle monitoring positioning information, specifically: Step 1: Set the recording interval to 5 minutes, obtain the moving speed of the dust monitoring vehicle, and obtain the moving distance of the dust monitoring vehicle by multiplying the moving speed of the dust monitoring vehicle by the 5-minute recording interval; Step 2: Determine whether the dust monitoring vehicle has moved a distance greater than 1 kilometer. If the dust monitoring vehicle has moved a distance greater than or equal to 1 kilometer, record the current atmospheric dust concentration once and mark it as the atmospheric dust vehicle monitoring concentration and send it to the monitoring station. Record the current vehicle GPS location information once and mark it as the vehicle monitoring positioning information and send it to the monitoring station. If the dust monitoring vehicle has moved a distance less than 1 kilometer, execute step 1.

[0023] In this embodiment, the recording interval is set, and the moving distance of the dust monitoring vehicle is obtained by multiplying the moving speed of the dust monitoring vehicle by the recording interval. Finally, the moving distance and time of the dust monitoring vehicle are judged to determine whether the dust monitoring vehicle should record the current environmental dust concentration information once. This is beneficial to avoid the dust monitoring vehicle repeatedly monitoring useless information when there is a traffic jam in the city, and it is also convenient for the subsequent monitored dust concentration to be sent to the monitoring station for display in the dust monitoring environment model.

[0024] In the vehicle cruise monitoring module, the weak signal area is obtained through the dust monitoring vehicle, specifically: Step 1: Set the signal verification time interval to 10 seconds. Use the signal verification time interval as the standard to send a verification signal to the monitoring station through the dust monitoring vehicle and receive the feedback signal from the monitoring station. Determine whether the dust monitoring vehicle receives the feedback signal. If no feedback signal is received, the signal verification result is marked as 0. If a feedback signal is received, the signal verification result is marked as 1. Step 2: Obtain three signal verification results, and get the final signal result by summing the three signal verification results. Determine whether the final signal result is greater than 2. If the final signal result is greater than 2, execute step 1. If the final signal result is less than or equal to 2, obtain the current vehicle GPS location information and mark it as a weak signal area.

[0025] In this embodiment, the dust monitoring vehicle and the monitoring station send and receive signals to verify whether the current GPS signal is normal, so that dust monitoring drones can be released in areas with weak GPS signals to replace the dust monitoring vehicle to monitor dust concentration. This makes it easier for the dust monitoring drone to monitor the dust concentration information and send it directly to the monitoring station, avoiding the situation where the dust monitoring vehicle is unable to send the dust concentration information to the monitoring station in real time due to GPS signal problems, and marking it in the dust monitoring environment model, which is further beneficial to the accuracy and authenticity of dust concentration monitoring.

[0026] In the vehicle cruise monitoring module, the release area is obtained through the weak signal area and the monitoring route, specifically: Step 1: Obtain the location information of the weak signal area, mark the location of the weak signal area in the dust monitoring environment model to obtain a comparison map, obtain a monitoring route map, and overlap the comparison map with the monitoring route map based on the road to obtain a reference map; Step 2: Determine whether the coordinates of the weak signal area in the reference map are on the monitoring route. If the weak signal area is on the monitoring route, mark the weak signal area as the release area. If the weak signal area is not on the monitoring route, notify the dust monitoring vehicle to deviate from the monitoring route.

[0027] In this embodiment, by judging whether the position coordinates of the weak signal area in the reference map are on the monitoring route, it is convenient to mark the weak signal area as a release area or notify the dust monitoring vehicle to deviate from the monitoring route according to the judgment result, thereby facilitating the dust monitoring vehicle to efficiently perform dust monitoring tasks.

[0028] In the drone cruise monitoring module, the dust monitoring drone mounted on the monitoring vehicle is released in the release area, specifically: Step 1: Set the judgment interval time, and use the judgment interval time as a period to judge whether the current position is a release area. If the current position is a release area, execute step 2; Step 2: Use the camera on the roof of the dust monitoring vehicle to take a photo of the environment from an upward perspective, process the grayscale of the environment photo, mark the unobstructed area and the obstructed area by the difference in brightness, measure the area of ​​the unobstructed area, measure the area of ​​the obstructed area, and obtain the hazard value by dividing the area of ​​the obstructed area by the area of ​​the unobstructed area; Step 3: Set the preset threshold of the danger value and determine whether the danger value is less than the preset threshold of the danger value. If the danger value is less than or equal to the preset threshold of the danger value, release the dust monitoring drone. If the danger value is greater than the preset threshold of the danger value, execute step 2.

[0029] In this embodiment, a dust monitoring drone is released in the launch area to monitor dust information. By analyzing the environmental photos, it is convenient to judge whether the current location is suitable for the drone to take off, so that the dust monitoring drone can take off safely to monitor the dust concentration. It is worth mentioning that calculating the area of ​​different regions by identifying the different brightness of grayscale images is an existing technology, and its specific operating steps will not be described in detail here.

[0030] In the UAV cruise monitoring module, the dust monitoring UAV is used to fly with the dust monitoring vehicle in the release area to obtain the atmospheric dust monitoring concentration and positioning information, specifically: Step 1: Set the safe flight altitude and safe flight speed. The dust monitoring drone will fly vertically to the safe flight altitude at the safe flight speed. Step 2: Obtain the positioning information of the dust monitoring vehicle, obtain the monitoring route, obtain the moving direction of the dust monitoring vehicle through the monitoring route and the positioning information of the dust monitoring vehicle, obtain the current moving speed of the dust monitoring vehicle, set the moving speed of the dust monitoring drone to be the same as the moving speed of the dust monitoring vehicle, and set the moving direction of the dust monitoring drone to be the same as the moving direction of the dust monitoring vehicle; Step 3: Set the recording time interval to 2 minutes, obtain the moving speed of the dust monitoring drone, and obtain the moving distance of the dust monitoring drone by multiplying the moving speed of the dust monitoring drone by the 2-minute recording time interval; Step 4: Determine whether the dust monitoring drone has moved more than 200 meters. If the dust monitoring drone has moved more than or equal to 200 meters, record the current atmospheric dust concentration and mark it as the atmospheric dust machine-monitored concentration and send it to the monitoring station. Record the current drone GPS location information and mark it as the machine-monitored positioning information and send it to the monitoring station. If the dust monitoring drone has moved less than 200 meters, execute step 3.

[0031] In the model data integration module, the atmospheric dust vehicle monitoring concentration is marked and displayed in the dust monitoring environment model according to the vehicle monitoring positioning information, and the atmospheric dust machine monitoring concentration is marked and displayed in the dust monitoring environment model according to the machine monitoring positioning information, specifically: Step 1: Obtain all vehicle monitoring positioning information, mark the vehicle positioning points in the dust monitoring environment model according to all vehicle monitoring positioning information, and mark the corresponding atmospheric dust vehicle monitoring concentration at all vehicle positioning points; Step 2: Obtain all machine monitoring positioning information, mark the machine positioning points in the dust monitoring environment model according to all machine monitoring positioning information, and mark the corresponding atmospheric dust machine monitoring concentration at all machine positioning points; Step 3: Mark the points where the vehicle positioning point and the machine positioning point overlap as the overlap points.

[0032] In this embodiment, by marking and displaying the GPS vehicle positioning points and the drone positioning points in the dust monitoring environment model, it is convenient to capture the overlapping points of the simultaneous monitoring of the dust monitoring vehicle and the dust monitoring drone, and then facilitate the subsequent correction of the weak signal area according to the overlapping points, which is beneficial for the dust monitoring drone to reasonably monitor the dust concentration in a suitable environment.

[0033] In the model data integration module, the weak signal area is corrected according to the marking results and the release pictures, specifically: Step 1: Obtain the position information of the coincidence point, obtain the release picture of the coincidence point according to the position information of the coincidence point, mark it as the coincidence release picture, grayscale the coincidence release picture, mark the occlusion area and the unocclusion area by the difference in brightness, measure the area of ​​the unocclusion area, measure the area of ​​the occlusion area, and obtain the occlusion value by dividing the area of ​​the occlusion area by the area of ​​the unocclusion area; Step 2: Set the preset threshold of the occlusion value, and determine whether the occlusion value is less than the preset threshold of the occlusion value. If the occlusion value is less than or equal to the preset threshold of the occlusion value, then define the overlap point as a non-weak signal area, and remove the area from the weak signal area. If the occlusion value is greater than the preset threshold of the occlusion value, then define the overlap point as a signal unstable area, and mark the signal unstable area in the weak signal area.

[0034] In this embodiment, the release picture is combined with the overlap point to capture the release picture of the overlap point, and then the overlap point position is judged whether it is really an area with weak GPS signal according to the environmental occlusion of the release picture of the overlap point, and the weak signal area is proofread and corrected according to the judgment result, which is beneficial for the dust monitoring drone to reasonably monitor the dust concentration in a suitable environment.

[0035] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0036] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0037] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A GPS-based atmospheric dust monitoring system, characterized in that: Includes the following modules: Feedback model building module, obtain geographic information within the monitoring range, use GIS spatial model to establish dust monitoring environment model through geographic information, and formulate monitoring route according to dust monitoring environment model; The vehicle cruise monitoring module obtains the atmospheric dust concentration and vehicle monitoring positioning information by driving the dust monitoring vehicle along the monitoring route, obtains the weak signal area through the dust monitoring vehicle, and obtains the release area through the weak signal area and the monitoring route; The drone cruise monitoring module releases the dust monitoring drone mounted on the monitoring vehicle in the release area. The dust monitoring drone flies with the dust monitoring vehicle in the release area to obtain the atmospheric dust concentration and positioning information. The dust monitoring drone takes a bird's-eye view of the environment to obtain the release picture. The model data integration module marks and displays the atmospheric dust vehicle-monitored concentration in the dust monitoring environment model according to the vehicle-monitored positioning information, and marks and displays the atmospheric dust machine-monitored concentration in the dust monitoring environment model according to the machine-monitored positioning information, and corrects the weak signal area based on the marking results and the release pictures.

2. The GPS-based atmospheric dust monitoring system according to claim 1, characterized in that: In the feedback model building module, a monitoring route is formulated according to the dust monitoring environment model, specifically: Step 1: Obtain a road map within the monitoring range through the dust monitoring environment model, obtain the location information of all factories, schools, hospitals and shopping malls, and mark the locations of all factories, schools, hospitals and shopping malls on the road map to obtain a primary road map; Step 2: Obtain the location information of the monitoring station, and mark the location of the monitoring station on the primary route map to obtain an intermediate route map; Step 3: Using the monitoring station as the starting point and the end point, passing through all the factories, schools, hospitals and shopping malls, three monitoring paths are formulated using genetic algorithms. The distances of the three monitoring paths are measured respectively, and the one with the shortest distance is selected as the monitoring route.

3. The GPS-based atmospheric dust monitoring system according to claim 1, characterized in that: In the vehicle cruise monitoring module, the dust monitoring vehicle moves along the monitoring route to obtain the atmospheric dust vehicle monitoring concentration and vehicle monitoring positioning information, specifically: Step 1: Set the recording interval to 5 minutes, obtain the moving speed of the dust monitoring vehicle, and obtain the moving distance of the dust monitoring vehicle by multiplying the moving speed of the dust monitoring vehicle by the 5-minute recording interval; Step 2: Determine whether the dust monitoring vehicle has moved a distance greater than 1 kilometer. If the dust monitoring vehicle has moved a distance greater than or equal to 1 kilometer, record the current atmospheric dust concentration once and mark it as the atmospheric dust vehicle monitoring concentration and send it to the monitoring station. Record the current vehicle GPS location information once and mark it as the vehicle monitoring positioning information and send it to the monitoring station. If the dust monitoring vehicle has moved a distance less than 1 kilometer, execute step 1.

4. The GPS-based atmospheric dust monitoring system according to claim 1, characterized in that: In the vehicle cruise monitoring module, the weak signal area is obtained through the dust monitoring vehicle, specifically: Step 1: Set the signal verification time interval to 10 seconds. Use the signal verification time interval as the standard to send a verification signal to the monitoring station through the dust monitoring vehicle and receive the feedback signal from the monitoring station. Determine whether the dust monitoring vehicle receives the feedback signal. If no feedback signal is received, the signal verification result is marked as 0. If a feedback signal is received, the signal verification result is marked as 1. Step 2: Obtain three signal verification results, and get the final signal result by summing the three signal verification results. Determine whether the final signal result is greater than 2. If the final signal result is greater than 2, execute step 1. If the final signal result is less than or equal to 2, obtain the current vehicle GPS location information and mark it as a weak signal area.

5. The GPS-based atmospheric dust monitoring system according to claim 1, characterized in that: In the vehicle cruise monitoring module, the release area is obtained through the weak signal area and the monitoring route, specifically: Step 1: Obtain the location information of the weak signal area, mark the location of the weak signal area in the dust monitoring environment model to obtain a comparison map, obtain a monitoring route map, and overlap the comparison map with the monitoring route map based on the road to obtain a reference map; Step 2: Determine whether the coordinates of the weak signal area in the reference map are on the monitoring route. If the weak signal area is on the monitoring route, mark the weak signal area as the release area. If the weak signal area is not on the monitoring route, notify the dust monitoring vehicle to deviate from the monitoring route.

6. The GPS-based atmospheric dust monitoring system according to claim 1, characterized in that: In the drone cruise monitoring module, the dust monitoring drone mounted on the monitoring vehicle is released in the release area, specifically: Step 1: Set the judgment interval time, and use the judgment interval time as a period to judge whether the current position is a release area. If the current position is a release area, execute step 2; Step 2: Use the camera on the roof of the dust monitoring vehicle to take a photo of the environment from an upward perspective, process the grayscale of the environment photo, mark the unobstructed area and the obstructed area by the difference in brightness, measure the area of ​​the unobstructed area, measure the area of ​​the obstructed area, and obtain the hazard value by dividing the area of ​​the obstructed area by the area of ​​the unobstructed area; Step 3: Set the preset threshold of the danger value and determine whether the danger value is less than the preset threshold of the danger value. If the danger value is less than or equal to the preset threshold of the danger value, release the dust monitoring drone. If the danger value is greater than the preset threshold of the danger value, execute step 2.

7. The GPS-based atmospheric dust monitoring system according to claim 1, characterized in that: In the UAV cruise monitoring module, the dust monitoring UAV is used to fly with the dust monitoring vehicle in the release area to obtain the atmospheric dust monitoring concentration and monitoring positioning information, specifically: Step 1: Set the safe flight altitude and safe flight speed. The dust monitoring drone will fly vertically to the safe flight altitude at the safe flight speed. Step 2: Obtain the positioning information of the dust monitoring vehicle, obtain the monitoring route, obtain the moving direction of the dust monitoring vehicle through the monitoring route and the positioning information of the dust monitoring vehicle, obtain the current moving speed of the dust monitoring vehicle, set the moving speed of the dust monitoring drone to be the same as the moving speed of the dust monitoring vehicle, and set the moving direction of the dust monitoring drone to be the same as the moving direction of the dust monitoring vehicle; Step 3: Set the recording time interval to 2 minutes, obtain the moving speed of the dust monitoring drone, and obtain the moving distance of the dust monitoring drone by multiplying the moving speed of the dust monitoring drone by the 2-minute recording time interval; Step 4: Determine whether the dust monitoring drone has moved more than 200 meters. If the dust monitoring drone has moved more than or equal to 200 meters, record the current atmospheric dust concentration and mark it as the atmospheric dust machine-monitored concentration and send it to the monitoring station. Record the current drone GPS location information and mark it as the machine-monitored positioning information and send it to the monitoring station. If the dust monitoring drone has moved less than 200 meters, execute step 3.

8. The GPS-based atmospheric dust monitoring system according to claim 1, characterized in that: In the model data integration module, the atmospheric dust vehicle monitoring concentration is marked and displayed in the dust monitoring environment model according to the vehicle monitoring positioning information, and the atmospheric dust machine monitoring concentration is marked and displayed in the dust monitoring environment model according to the machine monitoring positioning information, specifically: Step 1: Obtain all vehicle monitoring positioning information, mark the vehicle positioning points in the dust monitoring environment model according to all vehicle monitoring positioning information, and mark the corresponding atmospheric dust vehicle monitoring concentration at all vehicle positioning points; Step 2: Obtain all machine monitoring positioning information, mark the machine positioning points in the dust monitoring environment model according to all machine monitoring positioning information, and mark the corresponding atmospheric dust machine monitoring concentration at all machine positioning points; Step 3: Mark the points where the vehicle positioning point and the machine positioning point overlap as the overlap points.

9. The GPS-based atmospheric dust monitoring system according to claim 8, characterized in that: In the model data integration module, the weak signal area is corrected according to the marking results and the release pictures, specifically: Step 1: Obtain the position information of the coincidence point, obtain the release picture of the coincidence point according to the position information of the coincidence point, mark it as the coincidence release picture, grayscale the coincidence release picture, mark the occlusion area and the unocclusion area by the difference in brightness, measure the area of ​​the unocclusion area, measure the area of ​​the occlusion area, and obtain the occlusion value by dividing the area of ​​the occlusion area by the area of ​​the unocclusion area; Step 2: Set the preset threshold of the occlusion value, and determine whether the occlusion value is less than the preset threshold of the occlusion value. If the occlusion value is less than or equal to the preset threshold of the occlusion value, then define the overlap point as a non-weak signal area, and remove the area from the weak signal area. If the occlusion value is greater than the preset threshold of the occlusion value, then define the overlap point as a signal unstable area, and mark the signal unstable area in the weak signal area.

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