Automatic low-altitude remote sensing inspection monitoring system based on unmanned aerial vehicle

Abstract

The invention relates to the technical field of routing inspection monitoring, and particularly discloses an unmanned aerial vehicle-based automatic low-altitude remote sensing routing inspection monitoring system, which comprises a region marking module for marking a key routing inspection region in a remote sensing region based on routing inspection historical data of the remote sensing region; the key polling module is used for regulating and controlling polling periods of the key polling areas based on the importance degree of each key polling area; the combined inspection module is used for combining the key inspection periods based on the inspection time and the inspection period of each key inspection area; according to the method, unnecessary inspection work is reduced and the inspection efficiency is improved by identifying the key inspection areas, and the inspection periods of the key inspection areas are automatically adjusted by calculating the optimization duration of the inspection periods, so that more frequent inspection is performed on the key inspection areas, the inspection quality is improved, the key inspection areas which can be combined are combined, and the inspection efficiency is improved. Therefore, the flight frequency of the unmanned aerial vehicle is reduced and the inspection cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of inspection and monitoring, and particularly to an automatic low-altitude remote sensing inspection and monitoring system based on an unmanned aerial vehicle (UAV). Background Art

[0002] Unmanned aerial vehicle remote sensing (UAVRS), which is the combination of an unmanned aerial vehicle and remote sensing technology, is a new type of aerial remote sensing system that uses an unmanned aerial vehicle as a carrier and obtains high-resolution optical images, videos, lidar point clouds and other data by carrying various remote sensing sensors such as cameras, spectral imagers, and lidar scanners.

[0003] Chinese invention patent with publication number CN117687424A discloses a fully automatic low-altitude remote sensing non-intrusive inspection and monitoring system based on an unmanned aerial vehicle, including a flight path planning device, a remote control device, and a remote sensing UAV; the flight path planning device is used to cut the remote sensing area into multiple local areas and plan remote sensing flight paths for each local area based on the terrain features of each local area; the remote control device is used to control the remote sensing UAV based on the remote sensing flight path so that the remote sensing UAV flies along the remote sensing flight path; the remote sensing UAV is used to perform remote sensing at waypoints on the remote sensing flight path to obtain remote sensing images.

[0004] Traditional UAV inspection methods usually perform uniform inspections on the entire remote sensing area, lacking pertinence, resulting in low inspection efficiency and high inspection costs. Therefore, how to identify key inspection areas based on historical inspection data and perform targeted inspections according to the importance of key inspection areas has become an urgent problem to be solved in the current UAV inspection technology field. Summary of the Invention

[0005] The purpose of the present invention is to provide an automatic low-altitude remote sensing inspection and monitoring system based on an unmanned aerial vehicle to solve the technical problems in the above background.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] The present invention provides an automatic low-altitude remote sensing inspection and monitoring system based on an unmanned aerial vehicle, including:

[0008] An area marking module: based on the inspection historical data of the UAV in the remote sensing area, extracting abnormal marking data generated by the UAV during historical inspections;

[0009] Among them, the abnormal marking data includes: an abnormal marking area, an abnormal degree ratio, and an abnormal marking time;

[0010] Based on the abnormal marking data, determining key inspection areas in the remote sensing area;

[0011] Key inspection module: Regulate the inspection cycle of key inspection areas based on the importance of each key inspection area;

[0012] Combined inspection module: Combine the key inspection cycles based on the inspection time and inspection cycle of each key inspection area.

[0013] As a further solution of the present invention: The process of determining the key inspection areas in the remote sensing area based on the abnormal marking data is as follows:

[0014] Based on any one abnormal marking area in the abnormal marking data, compare and analyze the coincidence of this abnormal marking area with other abnormal marking areas, and mark the areas marked multiple times based on the analysis results;

[0015] Then calculate the multiple abnormal characterization values of each area marked multiple times respectively, analyze the importance of the areas marked multiple times based on the multiple abnormal characterization values, and mark the key inspection areas based on the analysis results.

[0016] As a further solution of the present invention: The process of comparing and analyzing the coincidence of this abnormal marking area with other abnormal marking areas and marking the areas marked multiple times based on the analysis results is as follows:

[0017] Analyze the coincidence degree of the abnormal marking area with other abnormal marking areas respectively, and generate a high coincidence degree signal based on the analysis results;

[0018] Extract the number of times the high coincidence degree signal is generated during the process of comparing and analyzing the coincidence of the abnormal marking area with other abnormal marking areas, add 1 to the number of times the high coincidence degree signal is generated, and calculate the ratio with the total number of abnormal marking areas to obtain the repeated marking ratio;

[0019] Preset a repeated marking ratio threshold, and compare and analyze the repeated marking ratio with the repeated marking ratio threshold;

[0020] If the repeated marking ratio is less than or equal to the repeated marking ratio threshold, generate a less repeated marking signal;

[0021] If the repeated marking ratio is greater than the repeated marking ratio threshold, generate a more repeated marking signal, and mark the overlapping part of this abnormal marking area with all other abnormal marking areas as the areas marked multiple times.

[0022] As a further solution of the present invention: The process of generating the high coincidence degree signal is as follows:

[0023] Mark the abnormal marking area as the area to be analyzed, and mark other abnormal marking areas as the comparison areas;

[0024] Based on any one comparison area, through the formula: Calculate the coincidence degree ratio CH, where SCH is the area of the overlapping part between the area to be analyzed and the comparison area, SFX is the area of the area to be analyzed, and SDB is the area of the comparison area;

[0025] Preset the coincidence degree ratio threshold, and compare and analyze the coincidence degree ratios corresponding to each comparison area with the coincidence degree ratio threshold respectively;

[0026] If the coincidence degree ratio is less than or equal to the coincidence degree ratio threshold, generate a low coincidence degree signal;

[0027] If the coincidence degree ratio is greater than the coincidence degree ratio threshold, generate a high coincidence degree signal.

[0028] As a further solution of the present invention: The process of obtaining multiple abnormal characterization values is as follows:

[0029] Based on any multiple marked area, extract the abnormal marked areas that overlap with the multiple marked area, and mark each abnormal marked area as the 1st abnormal marked area, the 2nd abnormal marked area,..., the nth abnormal marked area according to the time sequence in the historical inspection process, where n is a positive integer;

[0030] Through the formula: Calculate the multiple abnormal characterization value YB, where TK i represents the start time of the abnormal marking of the i-th abnormal marked area, TJ i represents the end time of the abnormal marking of the i-th abnormal marked area, TJ i-1 represents the end time of the abnormal marking of the (i - 1)-th abnormal marked area, the value of i is 1, 2, 3,..., n, CB is the abnormal degree ratio, S is the total area of the remote sensing area, SJ is the area of the multiple marked area, α represents a preset first hyperparameter and is greater than 0, and e is the natural constant.

[0031] As a further solution of the present invention: The process of analyzing the importance of the multiple marked area based on the multiple abnormal characterization value and marking the key inspection area based on the analysis result is as follows:

[0032] Preset the multiple abnormal characterization threshold, and compare and analyze each multiple abnormal characterization value with the multiple abnormal characterization threshold respectively;

[0033] If the multiple abnormal characterization value is less than or equal to the multiple abnormal characterization threshold, generate a low importance signal;

[0034] If the multiple abnormal characterization value is greater than the multiple abnormal characterization threshold, generate a high importance signal and mark the multiple marked area as the key inspection area.

[0035] As a further solution of the present invention: The process of adjusting the inspection cycle of key inspection areas based on the importance of each key inspection area is as follows:

[0036] Extract the multiple abnormal characterization values of the key inspection area and calculate the optimized duration of the inspection cycle;

[0037] Based on the optimized duration of the inspection cycle, adjust the inspection cycle of the key inspection area.

[0038] As a further solution of the present invention: The process of obtaining the optimized duration of the inspection cycle is as follows:

[0039] Through the formula: Calculate to obtain the optimized duration TY of the inspection cycle, where YB is the multiple abnormal characterization value, YBY is the multiple abnormal characterization threshold, and T is the original inspection cycle duration.

[0040] As a further solution of the present invention: The process of merging key inspection cycles is as follows:

[0041] Based on any key inspection area, mark other key inspection areas as key areas to be merged;

[0042] Based on the inspection time and inspection cycle of the key inspection area and the key area to be merged, evaluate whether the inspections can be merged. If the inspections can be merged, then merge the key inspection area and the key area to be merged, and mark the merged area as a new key inspection area. Then continue to evaluate the merged inspections of the newly obtained key inspection area with other key inspection areas until all key inspection areas do not meet the merging requirements.

[0043] As a further solution of the present invention: The merging requirement is:

[0044] If between the key inspection area and the key area to be merged, it satisfies: Then merge the key inspection area and the key area to be merged, where TY1 is the optimized duration of the inspection cycle of the key inspection area, TY2 is the optimized duration of the inspection cycle of the key area to be merged, TX1 is the time taken by the drone to inspect the key inspection area, TX2 is the time taken by the drone to inspect the key area to be merged, TD is the time required for the drone to fly from the key inspection area to the key area to be merged, DW is the maximum battery power of the drone, DX is the total power required for the drone to simultaneously inspect the key inspection area and the key area to be merged, DC is the power required for the drone to fly back and forth to the nearest drone charging point during the process of the drone simultaneously inspecting the key inspection area and the key area to be merged, and V is the drone charging speed.

[0045] The beneficial effects of the present invention:

[0046] (1) The present invention uses historical inspection data to mark key inspection areas in the remote sensing area. The marking process is based on abnormal marking data, including abnormal marking areas, abnormal degree ratios, and abnormal marking times. By performing coincidence comparison analysis and calculating the repeated marking ratio, areas that are marked as abnormal multiple times are identified, i.e., key inspection areas. By identifying key inspection areas, the present invention reduces unnecessary inspection work and improves inspection efficiency.

[0047] (2) The present invention adjusts the inspection cycle according to the importance of key inspection areas. By calculating the optimized duration of the inspection cycle, the inspection cycle of key inspection areas is automatically adjusted, so as to perform more frequent inspections on key inspection areas and improve inspection quality.

[0048] (3) Based on the inspection time and inspection cycle of each key inspection area, the present invention combines key inspection areas that can be combined, thereby reducing the number of drone flights and lowering inspection costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below with reference to the accompanying drawings.

[0050] Figure 1 is a flowchart of the present invention;

[0051] Figure 2 is a system block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The technical solutions in the embodiments of the present invention will be clearly and completely described below 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 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 shall fall within the protection scope of the present invention.

[0053] Embodiment 1:

[0054] Please refer to Figure 1 、 Figure 2 As shown, the automatic low-altitude remote sensing inspection and monitoring system based on drones according to the embodiments of the present invention includes:

[0055] Area marking module: Based on the inspection historical data of the remote sensing area, mark the key inspection areas in the remote sensing area;

[0056] In some embodiments, based on the inspection historical data of the drone in the remote sensing area, extract the abnormal marking data generated by the drone during the historical inspection process;

[0057] Among them, the abnormal marking data includes: the abnormal marking area where the drone marks the area with the abnormal degree exceeding the threshold during the historical inspection of the remote sensing area, the abnormal degree ratio reflecting the abnormal degree of the abnormal marking area, and the abnormal marking time of the abnormal marking area;

[0058] Exemplarily, the preset remote sensing area is an area vulnerable to pollution, the abnormal marking area is the area where the pollution degree exceeds the threshold, the abnormal degree ratio is the ratio between the part where the pollution degree exceeds the threshold and the threshold, and the abnormal marking time includes: the start time, end time, and abnormal marking duration of the abnormal marking area;

[0059] It should be further explained that the above threshold is a critical value for judging the abnormal degree, which is preset by those skilled in the art according to the abnormal degree, and this value is an empirical value;

[0060] Based on the abnormal marking data, determine the key inspection areas in the remote sensing area;

[0061] Specifically, the process of determining the key inspection areas in the remote sensing area based on the abnormal marking data is as follows:

[0062] Based on any abnormal marking area in the abnormal marking data, compare and analyze the coincidence of this abnormal marking area with other abnormal marking areas, and mark the areas marked multiple times based on the analysis results;

[0063] Among them, the process of comparing and analyzing the coincidence of this abnormal marking area with other abnormal marking areas and marking the areas marked multiple times based on the analysis results is as follows:

[0064] Mark this abnormal marking area as the area to be analyzed, and mark other abnormal marking areas as comparison areas;

[0065] Based on any comparison area, through the formula: Calculate the coincidence degree ratio CH, where SCH is the area of the overlapping part between the area to be analyzed and the comparison area, SFX is the area of the area to be analyzed, and SDB is the area of the comparison area;

[0066] Preset the coincidence degree ratio threshold, and compare and analyze the coincidence degree ratios corresponding to each comparison area with the coincidence degree ratio threshold respectively;

[0067] If the coincidence degree ratio is less than or equal to the coincidence degree ratio threshold, it means that the coincidence degree between the comparison area corresponding to this coincidence degree ratio and the area to be analyzed is low, and a low coincidence signal is generated;

[0068] If the coincidence degree ratio is greater than the coincidence degree ratio threshold, it indicates that the coincidence degree between the comparison area corresponding to this coincidence degree ratio and the area to be analyzed is relatively high, and a high coincidence signal is generated;

[0069] Extract the number of times the high coincidence signal is generated during the coincidence comparison analysis based on this abnormal marked area (area to be analyzed) and other abnormal marked areas (comparison areas), and calculate the ratio by adding 1 to the number of times the high coincidence signal is generated and then dividing it by the total number of abnormal marked areas to obtain the repeated marking ratio;

[0070] Preset the repeated marking ratio threshold, and conduct a comparative analysis of the repeated marking ratio and the repeated marking ratio threshold;

[0071] If the repeated marking ratio is less than or equal to the repeated marking ratio threshold, it indicates that the number of times the overlapping part between this abnormal marked area (area to be analyzed) and other abnormal marked areas (comparison areas) is marked as an abnormal marked area is relatively small, and a less repeated marking signal is generated;

[0072] If the repeated marking ratio is greater than the repeated marking ratio threshold, it indicates that the number of times the overlapping part between this abnormal marked area (area to be analyzed) and other abnormal marked areas (comparison areas) is marked as an abnormal marked area is relatively large, and a more repeated marking signal is generated, and the overlapping part between this abnormal marked area (area to be analyzed) and all other abnormal marked areas (comparison areas) is marked as a multiple marked area;

[0073] Then calculate the multiple abnormal characterization values of each multiple marked area respectively, analyze the importance of the multiple marked areas based on the multiple abnormal characterization values, and mark the key inspection areas based on the analysis results;

[0074] Among them, the process of obtaining the multiple abnormal characterization value is as follows:

[0075] Based on any multiple marked area, extract the abnormal marked areas that have overlapping parts with this multiple marked area, and mark each abnormal marked area as the 1st abnormal marked area, the 2nd abnormal marked area,..., the nth abnormal marked area according to the time sequence in the historical inspection process, where n is a positive integer;

[0076] Through the formula: Calculate to obtain the multiple abnormal characterization value YB, where TK i represents the start time of the abnormal marking of the i-th abnormal marked area, TJ i represents the end time of the abnormal marking of the i-th abnormal marked area, TJ i-1 represents the end time of the abnormal marking of the (i - 1)-th abnormal marked area (when i equals 1, i - 1 = 0, and at this time TJ i-1Indicates the start time of the inspection during the historical inspection of the UAV. The value of i is 1, 2, 3, ……, n. CB is the abnormal degree ratio, S is the total area of the remote sensing area, SJ is the area of the marked area multiple times, α represents a preset first hyperparameter and is greater than 0, and e is the natural constant;

[0077] It should be noted that α×(TK i -TJ i-1 ) represents the first product corresponding to the i-th abnormal marked area, represents the first eigenvalue corresponding to the i-th abnormal marked area. Taking the first eigenvalue as the weight value, the larger the time interval between the start time of the abnormal marking of the i-th abnormal marked area and the end time of the abnormal marking of the (i - 1)-th abnormal marked area, the smaller the corresponding weight value;

[0078] It should be further noted that the larger the value of the multiple abnormal characterization value, the higher the abnormal degree or the larger the area occupied by the marked area multiple times, that is, the higher the importance in the subsequent inspection process;

[0079] The process of analyzing the importance of the marked area multiple times based on the multiple abnormal characterization value and marking the key inspection area based on the analysis result is as follows:

[0080] Preset a multiple abnormal characterization threshold, and compare and analyze each multiple abnormal characterization value with the multiple abnormal characterization threshold respectively;

[0081] If the multiple abnormal characterization value is less than or equal to the multiple abnormal characterization threshold, it means that the marked area multiple times corresponding to this multiple abnormal characterization value has a lower importance in the subsequent inspection process, that is, a low importance signal is generated;

[0082] If the multiple abnormal characterization value is greater than the multiple abnormal characterization threshold, it means that the marked area multiple times corresponding to this multiple abnormal characterization value has a higher importance in the subsequent inspection process, that is, a high importance signal is generated, and the marked area multiple times is marked as the key inspection area;

[0083] The technical solution of the embodiment of the present invention is mainly: using historical inspection data to mark the key inspection area in the remote sensing area. The marking process is based on abnormal marking data, including abnormal marked areas, abnormal degree ratios, and abnormal marking times. By coincidence comparison analysis and calculation of the repeated marking ratio, the areas marked as abnormal multiple times are identified, that is, the key inspection areas; the present invention reduces unnecessary inspection work and improves inspection efficiency by identifying the key inspection areas.

[0084] Embodiment 2:

[0085] On the basis of Embodiment 1, please refer to Figure 1 、 Figure 2As shown, the automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to the embodiments of the present invention further includes:

[0086] Key inspection module: Adjust the inspection cycle of key inspection areas based on the importance of each key inspection area;

[0087] In some embodiments, extract multiple abnormal characterization values of the key inspection area, and through the formula: Calculate the optimized inspection cycle duration TY, where YB is the multiple abnormal characterization value, YBY is the multiple abnormal characterization threshold, and T is the original inspection cycle duration;

[0088] Adjust the inspection cycle of the key inspection area based on the optimized inspection cycle duration;

[0089] The technical solution of the embodiments of the present invention is mainly: Regulate the inspection cycle according to the importance of the key inspection area, automatically adjust the inspection cycle of the key inspection area by calculating the optimized inspection cycle duration, so as to conduct more frequent inspections on the key inspection area and improve the inspection quality.

[0090] Embodiment 3:

[0091] Based on Embodiments 1 and 2, please refer to Figure 1 、 Figure 2 As shown, the automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to the embodiments of the present invention further includes:

[0092] Combined inspection module: Combine the key inspection cycles based on the inspection time and inspection cycle of each key inspection area;

[0093] In some embodiments, the process of combining the key inspection cycles is as follows:

[0094] Based on any key inspection area, mark other key inspection areas as key areas to be combined;

[0095] Based on the inspection time and inspection cycle of the key inspection area and the key areas to be combined, evaluate whether the inspections can be combined. If the inspections can be combined, combine the key inspection area and the key areas to be combined, mark the combined area as a new key inspection area, and then continue to evaluate the combined inspections of the newly obtained key inspection area with other key inspection areas until all key inspection areas do not meet the combination requirements;

[0096] Exemplarily, the combination requirements are:

[0097] If between the key inspection area and the key areas to be combined, it satisfies: Then, the key inspection areas and the key inspection areas to be merged are combined. Among them, TY1 is the optimized inspection cycle duration of the key inspection areas, TY2 is the optimized inspection cycle duration of the key inspection areas to be merged, TX1 is the time taken by the UAV to inspect the key inspection areas, TX2 is the time taken by the UAV to inspect the key inspection areas to be merged, TD is the time required for the UAV to fly from the key inspection areas to the key inspection areas to be merged, DW is the maximum power of the UAV, DX is the total power required for the UAV to simultaneously inspect the key inspection areas and the key inspection areas to be merged (including the power required to separately inspect the key inspection areas and the key inspection areas to be merged, and the power required for the UAV to fly from the key inspection areas to the key inspection areas to be merged), DC is the power required for the UAV to travel back and forth to the nearest UAV charging point during the process of the UAV simultaneously inspecting the key inspection areas and the key inspection areas to be merged, and V is the UAV charging speed.

[0098] The working principle of the present invention: Based on the inspection time and inspection cycle of each key inspection area, the key inspection areas that can be merged are combined, thereby reducing the flight times of the UAVs and lowering the inspection costs.

[0099] The above has described in detail an embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application shall still fall within the scope covered by the patent of the present invention.

Claims

1. The automatic low-altitude remote sensing inspection and monitoring system based on drones is characterized by: include: Area marking module: Based on the inspection history data of drones in remote sensing areas, it extracts abnormal marking data generated by drones during historical inspections; The abnormal marking data includes: abnormal marking area, abnormal degree ratio and abnormal marking time; Based on the abnormal marking data, determine the key inspection areas in the remote sensing area; Key inspection module: Based on the importance of each key inspection area, the inspection cycle of the key inspection area is regulated; Merged inspection module: Based on the inspection time and inspection cycle of each key inspection area, the key inspection cycles are merged.

2. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 1 is characterized in that: Based on the abnormal marked data, the process of determining the key inspection areas in the remote sensing area is as follows: Based on any abnormal marked area in the abnormal marked data, performing a coincidence comparison analysis between the abnormal marked area and other abnormal marked areas, and marking multiple marked areas based on the analysis results; Then, the multiple abnormal characterization values ​​of each multiple-marked area are calculated respectively, the importance of the multiple-marked area is analyzed based on the multiple abnormal characterization values, and based on the analysis results, the key inspection areas are marked.

3. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 2 is characterized in that: The abnormal marked area is overlapped and compared with other abnormal marked areas, and based on the analysis results, the process of marking the multiple marked areas is as follows: Performing overlap analysis on the abnormal marked area and other abnormal marked areas respectively, and generating a high overlap signal based on the analysis result; Extract the number of times a high-overlapping signal is generated during the overlap comparison analysis between the abnormally marked area and other abnormally marked areas, and add 1 to the number of times a high-overlapping signal is generated and then calculate the ratio with the total number of abnormally marked areas to obtain the repeated marking ratio; Preset a repeat mark ratio threshold, and compare and analyze the repeat mark ratio with the repeat mark ratio threshold; If the duplicate marking ratio is less than or equal to the duplicate marking ratio threshold, a duplicate marking less signal is generated; If the repeated marking ratio is greater than the repeated marking ratio threshold, a repeated marking multiple signal is generated, and the overlapping portion of the abnormal marking region and all other abnormal marking regions is marked as a multiple marking region.

4. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 3 is characterized in that: The generation process of the high overlap signal is: Mark the abnormal marked area as the area to be analyzed, and mark other abnormal marked areas as comparison areas; Based on any comparison area, by formula: The overlap ratio CH is calculated, where SCH is the overlap area between the region to be analyzed and the comparison region, SFX is the area of ​​the region to be analyzed, and SDB is the area of ​​the comparison region; Preset a threshold value of the overlap ratio, and compare and analyze the overlap ratio corresponding to each comparison area with the overlap ratio threshold value; If the overlap ratio is less than or equal to the overlap ratio threshold, a low overlap signal is generated; If the overlap ratio is greater than the overlap ratio threshold, a high overlap signal is generated.

5. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 2 is characterized in that: The process of obtaining multiple abnormal characterization values ​​is as follows: Based on any multiple marked area, extract the abnormal marked area that overlaps with the multiple marked area, and mark each abnormal marked area as the first abnormal marked area, the second abnormal marked area, ..., the nth abnormal marked area according to the time sequence in the historical inspection process, where n is a positive integer; By formula: Calculate and obtain multiple abnormal characterization values ​​YB, where TK i Indicates the start time of abnormal marking in the i-th abnormal marking area, TJ i Indicates the end time of the abnormal marking of the i-th abnormal marking area, TJ i-1 It represents the end time of the abnormal marking of the i-1th abnormal marking area, the value of i is 1, 2, 3, ..., n, CB is the abnormality degree ratio, S is the total area of ​​the remote sensing area, SJ is the area of ​​the multiple marking area, α is represented as the preset first hyperparameter and is greater than 0, and e is a natural constant.

6. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 1 is characterized in that: The importance of multiple marked areas is analyzed based on multiple abnormal characterization values, and based on the analysis results, the process of marking key inspection areas is as follows: Preset multiple abnormality representation thresholds, and compare and analyze each multiple abnormality representation value with the multiple abnormality representation thresholds; If the multiple abnormality representation value is less than or equal to the multiple abnormality representation threshold, a low importance signal is generated; If the multiple abnormal characterization value is greater than the multiple abnormal characterization threshold, a high importance signal is generated, and the multiple marked area is marked as a key inspection area.

7. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 1 is characterized in that: Based on the importance of each key inspection area, the process of regulating the inspection cycle of the key inspection area is as follows: Extract multiple abnormal characterization values ​​from key inspection areas and calculate the optimized inspection cycle duration; Based on the optimized duration of the inspection cycle, the inspection cycle of key inspection areas is adjusted.

8. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 7 is characterized in that: The process of obtaining the optimized inspection cycle duration is as follows: By formula: The optimized inspection cycle duration TY is calculated, where YB is the multiple abnormality characterization value, YBY is the multiple abnormality characterization threshold, and T is the original inspection cycle duration.

9. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 1 is characterized in that: The process of merging key inspection cycles is as follows: Based on any key inspection area, mark other key inspection areas as key areas to be merged; Based on the inspection time and inspection cycle of the key inspection areas and the key areas to be merged, evaluate whether the inspections can be merged. If the inspections can be merged, merge the key inspection areas and the key areas to be merged, and mark the merged area as a new key inspection area. The newly acquired key inspection area will then continue to be evaluated for merged inspections with other key inspection areas until all key inspection areas do not meet the merger requirements.

10. The automatic low-altitude remote sensing inspection and monitoring system based on unmanned aerial vehicles according to claim 9 is characterized in that: The merge requirements are: If the key inspection areas and the key areas to be merged meet the following conditions: The key inspection areas and the key areas to be merged will be merged, where TY1 is the optimized inspection cycle duration of the key inspection areas, TY2 is the optimized inspection cycle duration of the key areas to be merged, TX1 is the time taken by the drone to inspect the key inspection areas, TX2 is the time taken by the drone to inspect the key areas to be merged, TD is the time required for the drone to fly from the key inspection areas to the key areas to be merged, DW is the maximum power of the drone, DX is the total power required for the drone to simultaneously inspect the key inspection areas and the key areas to be merged, DC is the power required for the drone to travel to and from the nearest drone charging point during the simultaneous inspection of the key inspection areas and the key areas to be merged, and V is the drone charging speed.

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