A Low-Altitude Aircraft Operation Monitoring and Management System Based on AI and IoT

Abstract

This invention relates to the field of low-altitude aircraft operation monitoring technology, and discloses a low-altitude aircraft operation monitoring and management system based on AI and IoT. The system includes a bird distribution collection module, a segmentation module, an aircraft monitoring module, a flight information module, and an analysis module. The bird distribution collection module collects bird activity information data; the segmentation module divides the target area into several monitoring area units; the aircraft monitoring module acquires real-time aircraft data; the flight information module acquires flight information data; the analysis module determines the safety rating of each monitoring area unit, then determines the flight route and flight path hazard index; finally, it determines the aircraft capable of executing the flight route; based on multiple dimensions such as the hazard level of the flight route, distance, and the aircraft's battery status, it comprehensively selects the aircraft capable of executing the flight route, ensuring that the selected aircraft can successfully complete the flight route.

Description

Technical Field

[0001] This invention relates to the field of low-altitude aircraft operation monitoring technology, specifically to a low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things. Background Art

[0002] A drone is an unmanned, low-altitude aircraft that can fly flexibly in complex environments such as cities or mountains. Currently, drones are widely used in various fields such as agriculture and logistics distribution.

[0003] In the agricultural field, drones can use onboard sensors and cameras to collect images of crops in a target area for analysis of crop growth and pest and disease information. Typically, when a drone is performing a mission, it determines its flight path and then selects the drone capable of executing the flight path based on the distance of the flight path and the drone's real-time remaining battery power.

[0004] However, birds also fly in low-altitude airspace. During flight, drones need to avoid birds. If there are many birds, the drone is at greater risk and may crash. In addition, drones consume more power when avoiding birds. Therefore, when a drone enters an airspace with many birds, it will consume more power due to bird avoidance and will be unable to complete the flight route. Summary of the Invention

[0005] The purpose of this invention is to provide a low-altitude aircraft operation monitoring and management system based on AI and IoT, thereby solving the above-mentioned technical problems:

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

[0007] A low-altitude aircraft operation monitoring and management system based on AI and IoT, the management system comprising:

[0008] The bird distribution data collection module is used to collect data on bird activity in the low-altitude airspace of the target area.

[0009] The partitioning module is used to divide the target area into several monitoring area units;

[0010] The aircraft monitoring module is used to monitor the aircraft and acquire its real-time data.

[0011] The flight information module is used to acquire flight information data;

[0012] The analysis module is used to determine the safety rating of each monitoring area unit based on the bird activity trajectory of each monitoring area unit, and to determine the flight route and flight path hazard index based on the safety rating results and flight information data of each monitoring area unit; then, based on the flight path hazard index and the real-time data of the aircraft, it analyzes and judges which aircraft can execute the current flight route.

[0013] As a further aspect of the present invention: the real-time data of the aircraft includes the aircraft's mission status, real-time battery level, and battery status coefficient; the flight information data includes departure location information data and destination location information data; the bird activity information data includes the number of birds; and the flight route includes a flight route from the departure point to the destination and a flight route from the destination back to the departure point.

[0014] As a further aspect of the present invention: the analysis method of the analysis module includes the following steps:

[0015] S1: By analyzing the number of birds in each monitoring area unit within a preset time period in the past, the flight safety index of each monitoring area unit is obtained;

[0016] S2: By analyzing the flight safety index of each monitoring area unit, a safety rating is given for each monitoring area unit;

[0017] S3: Then, by analyzing the safety rating results, departure location information data, and destination location information data of each monitoring area unit, the flight route is determined;

[0018] S4: Analyze the flight safety index of each monitoring area along the flight route to determine the flight route hazard index;

[0019] S5: Based on the flight route, the flight route hazard index, and the battery state coefficient of each aircraft, the minimum charge level required for each aircraft to perform this flight is obtained.

[0020] S6: Based on the comparison between the minimum battery level required for each aircraft to execute this flight and the real-time battery level of the aircraft, determine which aircraft can execute this flight route.

[0021] As a further aspect of the present invention: through the formula:

[0022]

[0023] Calculate the flight safety index P of the nth monitoring area unit. n ;

[0024] Where f(X) is the first judgment function, f(X) = 1 when X > 0; and f(X) = 0 when X ≤ 0; Q bn(t) represents the curve showing the change in the number of birds in the nth monitoring area unit over time, where n∈N; t d t is the current time; Δt is the preset duration; Q1 is the preset number of birds; t nup δ0 is the cumulative duration during which the number of birds exceeds a first preset value within the current time of the nth monitoring area unit; δ0 is the first preset ratio.

[0025] As a further aspect of the present invention: the safety rating process for the nth monitoring area unit is as follows:

[0026] When P n When = 0, the nth monitoring area unit is a safe area;

[0027] When P n When the value is 1, the nth monitoring area unit is a low-risk area;

[0028] When P n When the value is 2, the nth monitoring area unit is a high-risk area.

[0029] As a further aspect of the present invention: through the formula:

[0030]

[0031] Calculate the flight path hazard index F;

[0032] Where A is the number of low-risk areas traversed by the flight route, a∈A; S a S is the length of the flight path passing through the a-th low-risk area; ALL C1 is the total length of the flight path; C2 is the first preset constant.

[0033] As a further aspect of the present invention: through the formula:

[0034]

[0035] Calculate the minimum battery power B required for the m-th aircraft to perform this flight. mL ;

[0036] Among them, B m (S ALL ) represents the basic electrical energy consumed by the m-th aircraft during its flight path; δ mB Let δ be the battery state coefficient of the m-th aircraft, 0 ≤ δ mB ≤1; C2 is the second preset constant; R m This represents the task status coefficient.

[0037] As a further aspect of the present invention: the process for determining whether the current flight route can be executed is as follows;

[0038] The remaining battery power of the m-th aircraft is compared with the minimum battery power B required for the m-th aircraft to perform this flight. mL Compare;

[0039] When B my ≥B mL At that time, the m-th aircraft is able to perform this flight;

[0040] Otherwise, the m-th aircraft cannot perform this flight.

[0041] The beneficial effects of this invention are:

[0042] This invention collects bird activity data in the low-altitude airspace of a target area using a bird distribution collection module; divides the target area into several monitoring area units using a segmentation module; monitors the aircraft using an aircraft monitoring module to obtain real-time data; acquires flight information data using a flight information module; and finally, uses an analysis module to determine the safety rating of each monitoring area unit based on bird activity trajectories. It also determines flight routes based on origin and destination location data, low-risk areas, and safe areas, ensuring that the flight routes avoid high-risk areas with high bird populations, reducing the risk of aircraft crashes. Based on the safety rating results of each monitoring area unit and the flight information data, it determines the flight path and flight path hazard index. Further analysis of the flight path hazard index and the aircraft's real-time data determines which aircraft can execute the flight path. Finally, based on multiple dimensions including the hazard level of the flight path, distance, and the aircraft's battery status, it comprehensively selects aircraft capable of executing the flight path, ensuring that the selected aircraft can successfully complete the flight path. Attached Figure Description

[0043] The invention will now be further described with reference to the accompanying drawings.

[0044] Figure 1 This is a system module framework diagram of one embodiment of the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Please see Figure 1 As shown, in one embodiment, a low-altitude aircraft operation monitoring and management system based on AI and IoT is provided, including:

[0047] The bird distribution data collection module is used to collect data on bird activity in the low-altitude airspace of the target area.

[0048] The partitioning module is used to divide the target area into several monitoring area units;

[0049] The aircraft monitoring module is used to monitor the aircraft and acquire its real-time data.

[0050] The flight information module is used to acquire flight information data;

[0051] The analysis module is used to determine the safety rating of each monitoring area unit based on the bird activity trajectory of each monitoring area unit, and to determine the flight route and flight path hazard index based on the safety rating results and flight information data of each monitoring area unit; then, based on the flight path hazard index and the real-time data of the aircraft, it analyzes the data to determine which aircraft can execute the current flight route.

[0052] Through the above technical solution, this embodiment collects bird activity information data in the low-altitude airspace of the target area using a bird distribution collection module; specifically, bird detection radar can be used to collect bird activity information data; the target area is divided into several monitoring area units using a segmentation module; the aircraft monitoring module monitors the aircraft and obtains real-time data; the flight information module obtains flight information data; finally, the analysis module determines the safety rating of each monitoring area unit based on the bird activity trajectory of each monitoring area unit. The safety rating is divided into high-risk areas, low-risk areas, and safe areas, based on the departure location information data and destination location information data, low-risk areas, and safe areas. Flight routes are determined across the entire area to avoid high-risk areas with abundant bird populations, reducing the risk of aircraft crashes. If a flight route cannot be determined within low-risk or safe areas, the mission is cancelled. Flight routes and hazard indices are determined based on safety ratings and flight information data from each monitoring area unit. Further analysis of the hazard indices and real-time aircraft data is conducted to identify aircraft capable of executing the flight route. Finally, a comprehensive selection of aircraft is made, considering factors such as the hazard level of the flight route, distance, and the aircraft's battery status, ensuring the selected aircraft can successfully complete the flight route.

[0053] In one embodiment of the present invention, the real-time data of the aircraft includes the aircraft's mission status, real-time battery level, and battery status coefficient; the flight information data includes departure location information data and destination location information data; the bird activity information data includes the number of birds; and the flight route includes a flight route from the departure point to the destination and a flight route from the destination back to the departure point.

[0054] The analysis method of the analysis module includes the following steps:

[0055] S1: By analyzing the number of birds in each monitoring area unit within a preset time period in the past, the flight safety index of each monitoring area unit is obtained;

[0056] S2: By analyzing the flight safety index of each monitoring area unit, a safety rating is given for each monitoring area unit;

[0057] S3: Then, by analyzing the safety rating results, departure location information data, and destination location information data of each monitoring area unit, the flight route is determined;

[0058] S4: Analyze the flight safety index of each monitoring area along the flight route to determine the flight route hazard index;

[0059] S5: Based on the flight route, the flight route hazard index, and the battery state coefficient of each aircraft, the minimum charge level required for each aircraft to perform this flight is obtained.

[0060] S6: Based on the comparison between the minimum battery level of each aircraft for this flight and the real-time battery level of the aircraft, determine which aircraft can execute this flight route;

[0061] Through the above technical solution, this embodiment first analyzes the number of birds in each monitoring area unit within a preset time period to obtain the flight safety index of each monitoring area unit; then, it analyzes the flight safety index of each monitoring area unit to conduct a safety rating of each monitoring area unit; next, it analyzes the safety rating results of each monitoring area unit, departure location information data, and destination location information data to determine the flight route; the safety rating is divided into high-risk areas, low-risk areas, and safe areas. The flight route is determined based on the departure location information data, destination location information data, low-risk areas, and safe areas. Then, it analyzes the flight safety index of each monitoring area passed through by the flight route to determine the flight route hazard index; finally, it analyzes the flight route, the flight route hazard index, and the battery status coefficient of each aircraft to obtain the minimum power required for each aircraft to perform this flight; it compares the minimum power required for each aircraft to perform this flight with the real-time power of the aircraft to determine which aircraft can perform this flight route; based on multiple dimensions such as the hazard level of the flight route, distance, and the battery status of the aircraft, it comprehensively selects the aircraft that can perform this flight route to ensure that the selected aircraft can successfully complete this flight route.

[0062] As one embodiment of the present invention, the formula is as follows:

[0063]

[0064] Calculate the flight safety index P of the m-th monitoring area unit. n ;

[0065] Where f(X) is the first judgment function, f(X) = 1 when X > 0; and f(X) = 0 when X ≤ 0; Q bn (t) represents the curve showing the change in the number of birds in the nth monitoring area unit over time, where n∈N; t d t is the current time; Δt is the preset duration; Q1 is the preset number of birds; t nup δ0 is the cumulative duration during which the number of birds exceeds a first preset value within the current time of the nth monitoring area unit; δ0 is the first preset ratio.

[0066] Through the above technical solution, this embodiment The average number of birds in flight within a preset time period past the current time for the nth monitoring area unit; The difference between the average number of birds in the nth monitoring area unit over the past preset time and the preset number of birds; in the formula In the first judgment function f(X), X refers to... when This indicates that the average number of birds in the nth monitoring area unit over the past preset time period has not exceeded the preset number of birds, meaning the number of birds in the nth monitoring area unit is relatively low, and the risk of collision is low. when If the number of birds exceeds the preset number of birds over the past preset time period, it indicates that the number of birds in the nth monitoring area unit is relatively high, and the risk of collision is greater. It is the ratio of the cumulative duration during which the number of birds in the nth monitoring area unit exceeds the first preset value within the current time to the preset duration; The ratio of the cumulative duration during which the number of birds exceeds a first preset value within a preset time period in the current monitoring area unit to the preset duration itself, and the first preset ratio, is the difference between these two values. (In the formula...) In the first judgment function f(X), X refers to... when This indicates that the cumulative duration during which the number of birds in the nth monitoring area unit exceeds the first preset value within the past preset time is relatively short, therefore the safety risk is relatively low. when This indicates that the cumulative duration for which the number of birds in the nth monitoring area unit has exceeded the first preset value within the past preset time is relatively long, thus posing a significant safety risk.

[0067] It should be noted that the preset duration Δt, preset number of birds Q1, and first preset ratio δ0 are preset values ​​obtained based on experience, and will not be described in detail here.

[0068] As one embodiment of the present invention, the safety rating process for the nth monitoring area unit is as follows:

[0069] When P n When = 0, the nth monitoring area unit is a safe area;

[0070] When P n When the value is 1, the nth monitoring area unit is a low-risk area;

[0071] When P n When the value is 2, the nth monitoring area unit is a high-risk area;

[0072] Through the above technical solution, in this embodiment, when the average number of birds in the nth monitoring area unit exceeds the preset number of birds within the current time and the cumulative time for the number of birds in the nth monitoring area unit to exceed the first preset value is relatively long, then P... n =2, the nth monitoring area unit is a high-risk area; when the average number of birds in the nth monitoring area unit over the past preset time exceeds the preset number of birds, or when the cumulative time for the number of birds in the nth monitoring area unit to exceed the first preset value over the past preset time is relatively long, i.e., P n When P = 1, the nth monitoring area unit is a low-risk area; when the average number of birds in the nth monitoring area unit over the past preset time does not exceed the preset number of birds and the cumulative time over the past preset time of the nth monitoring area unit does not exceed the first preset value is relatively long, then P n =0, the nth monitoring area unit is a safe area.

[0073] As one embodiment of the present invention, the formula is as follows:

[0074]

[0075] Calculate the flight path hazard index F;

[0076] Where A is the number of low-risk areas traversed by the flight route, a∈A; S a S is the length of the flight path passing through the a-th low-risk area; ALL C1 is the total length of the flight path; C2 is the first preset constant.

[0077] Through the above technical solution, this embodiment This is the cumulative length of the flight route through all low-risk areas. This is the ratio of the cumulative length of the flight route passing through all low-risk areas to the total length of the flight route; the ratio of the cumulative length of the flight route passing through all low-risk areas to the total length of the flight route. The larger the value, the greater the flight route hazard index F; the ratio of the cumulative length of the flight route through all low-risk areas to the total length of the flight route. The smaller the value, the lower the flight path hazard index F;

[0078] It should be noted that the first preset constant C1 is a preset value obtained based on experience, and will not be described in detail here.

[0079] As one embodiment of the present invention, the formula is as follows:

[0080]

[0081] Calculate the minimum battery power B required for the m-th aircraft to perform this flight. mL ;

[0082] Among them, B m (S ALL ) represents the basic electrical energy consumed by the m-th aircraft during its flight path; δ mB Let δ be the battery state coefficient of the m-th aircraft, 0 ≤ δ mB ≤1; C2 is the second preset constant; R m For task status coefficients;

[0083] Through the above technical solution, the task status in this embodiment is divided into a waiting task status and an executing task status, with a waiting task status coefficient of 1 and an executing task status coefficient of 0; then, by using preset basic power consumption curves of various types of aircraft as a function of flight distance; the distance S is obtained based on the basic power consumption curves. ALL Basic power consumption; battery state coefficient δ of the m-th spacecraft mB The smaller the value, the worse the battery condition; for the same flight distance, the battery drains faster. Therefore, the minimum battery level required for the m-th aircraft to perform this flight is higher. mL The higher the flight path hazard index F, the more risks the aircraft needs to avoid, and the more power the aircraft needs to consume to avoid these risks. Therefore, the minimum power required for the m-th aircraft to perform this flight is higher, B. mL The battery state coefficient δ of the m-th spacecraft m The method of obtaining x is based on existing technology and will not be detailed here;

[0084] It should be noted that the second preset constant C2 is a preset value obtained based on experience, and will not be described in detail here.

[0085] As one embodiment of the present invention, the process for determining whether the current flight route can be executed is as follows:

[0086] The remaining battery power of the m-th aircraft is compared with the minimum battery power B required for the m-th aircraft to perform this flight. mL Compare;

[0087] When B my ≥B mL At that time, the m-th aircraft is able to perform this flight;

[0088] Otherwise, the m-th spacecraft cannot perform this flight;

[0089] Using the above technical solution, this embodiment combines the remaining battery power of the m-th aircraft with the minimum battery power B required for the m-th aircraft to perform this flight. mL Compare; when B my ≥B mL When this occurs, it indicates that the m-th aircraft is in a waiting state and its battery level exceeds the minimum battery level B required for the m-th aircraft to perform this flight. mL Therefore, it was able to carry out this flight.

[0090] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A low-altitude aircraft operation monitoring and management system based on AI and IoT, characterized in that, The management system includes: The bird distribution data collection module is used to collect data on bird activity in the low-altitude airspace of the target area. The partitioning module is used to divide the target area into several monitoring area units; The aircraft monitoring module is used to monitor the aircraft and acquire its real-time data. The flight information module is used to acquire flight information data; The analysis module is used to determine the safety rating of each monitoring area unit based on bird activity information data, determine the flight route and flight path hazard index based on the safety rating results and flight information data of each monitoring area unit, and then analyze the flight path hazard index and the real-time data of the aircraft to determine which aircraft can execute the current flight route. The real-time data of the aircraft includes the aircraft's mission status, real-time battery level, and battery status coefficient; the flight information data includes departure location information and destination location information; the bird activity information data includes the number of birds; the flight route includes the flight route from departure to destination and the flight route from destination back to departure. The analysis method of the analysis module includes the following steps: S1: By analyzing the number of birds in each monitoring area unit within a preset time period in the past, the flight safety index of each monitoring area unit is obtained; S2: By analyzing the flight safety index of each monitoring area unit, a safety rating is given for each monitoring area unit; S3: Then, by analyzing the safety rating results, departure location information data, and destination location information data of each monitoring area unit, the flight route is determined; S4: Analyze the flight safety index of each monitoring area along the flight route to determine the flight route hazard index; S5: Based on the flight route, the flight route hazard index, and the battery state coefficient of each aircraft, the minimum charge level required for each aircraft to perform this flight is obtained. S6: Based on the comparison between the minimum battery level of each aircraft for this flight and the real-time battery level of the aircraft, determine which aircraft can execute this flight route; Through the formula: ； Calculate the first Flight safety index of each monitoring area unit ; in, As the first judgment function, when hour, ;when hour, ; For the first The curve showing the change in the number of birds over time in each monitoring area unit. ; The current time; Preset duration; Preset the number of flying birds; For the first The cumulative duration during which the number of birds in a monitoring area unit exceeds a first preset value within the current time of the preset duration. This is the first preset ratio; No. The safety rating process for each monitoring area unit is as follows: when At that time, the first Each monitoring area unit is a safe zone; when At that time, the first Each monitoring area unit is a low-risk area; when At that time, the first Each monitoring area unit is a high-risk area; Through the formula: ； Calculate the flight path hazard index ; in, The number of low-risk areas that the flight route passes through. ; The flight route passes through the first The route length for each low-risk area; This is the total length of the flight path; This is the first preset constant; Through the formula: ； Calculate the first The minimum battery power required for the aircraft to perform this flight. ; in, For the first The basic amount of electricity consumed by an aircraft when executing its flight path; For the first The battery state coefficient of an aircraft ; This is the second preset constant; This represents the task status coefficient.

2. The low-altitude aircraft operation monitoring and management system based on AI and IoT as described in claim 1, characterized in that, The process for determining whether this flight route can be executed is as follows: The first The remaining power of the aircraft With the The minimum battery power required for the aircraft to perform this flight. Compare; when At that time, the first One aircraft is capable of performing this flight; Otherwise, the first The aircraft is unable to perform this flight.

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