Low-altitude aircraft operation monitoring management system based on AI and Internet of Things

Abstract

The invention relates to the technical field of low-altitude aircraft operation monitoring, and discloses a low-altitude aircraft operation monitoring management system based on AI and Internet of Things, which comprises a bird distribution acquisition module, a division module, an aircraft monitoring module, a flight information module and an analysis module, and is characterized in that bird activity information data is acquired through the bird distribution acquisition module; dividing the target area into a plurality of monitoring area units through a dividing module; acquiring real-time data of the aircraft through the aircraft monitoring module; acquiring flight information data through a flight information module; the safety rating of each monitoring area unit is determined through an analysis module, and then a flight path and a flight path danger index are determined; finally, the aircraft capable of executing the flight line is judged; and comprehensively selecting the aircraft capable of executing the flight route according to multiple dimensions such as the danger degree of the flight route, the distance and the battery state of the aircraft, and ensuring that the selected aircraft can successfully complete the flight route.

Description

Technical Field

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

[0002] An unmanned aerial vehicle (UAV) is a pilotless low-altitude aircraft that can fly flexibly in complex environments such as cities or mountains. Currently, UAVs have been widely used in various fields such as agriculture and logistics distribution.

[0003] Among them, in the agricultural field, UAVs can collect crop pictures in the target area through the equipped sensors and cameras for analyzing the growth conditions of crops and pest information; usually when a UAV executes a task, it determines a flight route and then selects a UAV that can execute this flight route according to the distance of the flight route and the real-time remaining power of the UAV.

[0004] However, in the low-altitude airspace, there are also birds flying. During the flight of a UAV, it needs to avoid birds. If there are many birds, the risk of the UAV is relatively high, which is likely to cause the UAV to crash. Moreover, when the UAV avoids birds, it consumes more power. Therefore, when the UAV enters an airspace with many birds, due to avoiding birds, it consumes a large amount of power and cannot complete this flight route. Summary of the Invention

[0005] The purpose of the present invention is to provide a low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things to solve the above technical problems:

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

[0007] A low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things, the management system includes:

[0008] A bird distribution collection module for collecting data on bird activity information in the low-altitude airspace of the target area;

[0009] A division module for dividing the target area into several monitoring area units;

[0010] An aircraft monitoring module for monitoring the aircraft to obtain real-time data of the aircraft;

[0011] A flight information module for obtaining flight information data;

[0012] An analysis module is used to determine the safety rating of each monitoring area unit according to the bird activity trajectories of each monitoring area unit, determine the flight route and the flight route risk index according to the safety rating results of each monitoring area unit and the flight information data; and then analyze according to the flight route risk index and the real-time data of the aircraft to judge the aircraft that can execute the current flight route.

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

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

[0015] S1: Analyze the number of birds in each monitoring area unit in the past preset time to obtain the flight safety index of each monitoring area unit;

[0016] S2: Analyze the flight safety index of each monitoring area unit to conduct a safety rating on each monitoring area unit;

[0017] S3: Then analyze the safety rating results of each monitoring area unit, the departure location information data and the destination location information data to determine the flight route;

[0018] S4: Analyze according to the flight safety index of each monitoring area passed by the flight route to determine the flight route risk index;

[0019] S5: Analyze according to the flight route, the flight route risk index and the battery status coefficient of each aircraft to obtain the minimum power of each aircraft to execute the current flight;

[0020] S6: Compare the minimum power of each aircraft to execute the current flight with the real-time power of the aircraft to judge the aircraft that can execute the current flight route.

[0021] As a further solution of the present invention: Through the formula:

[0022]

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

[0024] Among them, f(X) is the first judgment function. When X>0, f(X)=1; when X≤0, f(X)=0; Q bn(t) is the change curve of the number of flying birds in the nth monitoring area unit over time, n ∈ N; t d is the current time; Δt is the preset duration; Q 1 is the preset number of flying birds; t nup is the cumulative duration during which the number of flying birds in the nth monitoring area unit exceeds the first preset value within the preset duration after the current time; δ 0 is the first preset ratio.

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

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

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

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

[0029] As a further solution of the present invention: Through the formula:

[0030]

[0031] Calculate the flight route danger index F;

[0032] Among them, A is the number of low-risk areas passed by this flight route, a ∈ A; S a is the route length of this flight route passing through the ath low-risk area; S ALL is the total route length of this flight route; C 1 is the first preset constant.

[0033] As a further solution of the present invention: Through the formula:

[0034]

[0035] Calculate the minimum power B for the mth aircraft to perform this flight mL ;

[0036] Among them, B m (S ALL ) is the basic power consumed by the mth aircraft to perform the flight route; δ mB is the battery state coefficient of the mth aircraft, 0 ≤ δ mB ≤ 1; C 2 is the second preset constant; R m is the mission state coefficient.

[0037] As a further solution of the present invention: The judgment process of whether the current flight route can be executed is as follows:

[0038] Compare the remaining power of the m-th aircraft with the minimum power B required for the m-th aircraft to execute this flight mL Make a comparison;

[0039] When B my ≥ B mL The m-th aircraft can execute this flight;

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

[0041] Advantages of the present invention:

[0042] The present invention collects data on bird activity information in the low-altitude area of the target area through the bird distribution collection module; divides the target area into several monitoring area units through the division module; monitors the real-time data of the aircraft through the aircraft monitoring module; obtains flight information data through the flight information module; and finally determines the safety rating of each monitoring area unit according to the bird activity trajectories of each monitoring area unit, determines the flight route according to the departure location information data, destination location information data, low-risk areas and safe areas, so that the flight route avoids high-risk areas with more birds, reduces the risk of aircraft crashing, determines the flight route and the flight route danger index according to the safety rating results of each monitoring area unit and the flight information data; then analyzes according to the flight route danger index and the real-time data of the aircraft to judge the aircraft that can execute this flight route; comprehensively selects the aircraft that can execute this flight route according to multiple dimensions such as the danger degree, distance of the flight route and the battery status of the aircraft, ensuring that the selected aircraft can successfully complete this flight route. Description of the Drawings

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

[0044] Figure 1 It is a system module framework diagram of an embodiment of the present invention. Detailed Embodiments

[0045] 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 of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] Please refer to Figure 1As shown, in one embodiment, a low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things is provided, including:

[0047] A bird distribution collection module for collecting data on bird activity information in the low-altitude area of the target region;

[0048] A division module for dividing the target region into several monitoring area units;

[0049] An aircraft monitoring module for monitoring the aircraft to obtain real-time data of the aircraft;

[0050] A flight information module for obtaining flight information data;

[0051] An analysis module for determining the safety rating of each monitoring area unit according to the bird activity trajectories of each monitoring area unit, determining the flight route and the flight route risk index according to the safety rating results of each monitoring area unit and the flight information data; and then analyzing according to the flight route risk index and the real-time data of the aircraft to judge the aircraft that can execute this flight route;

[0052] Through the above technical solution, in this embodiment, the bird distribution collection module collects data on bird activity information in the low-altitude area of the target region; specifically, a bird detection radar can be used to collect data on bird activity information; the target region is divided into several monitoring area units through the division module; the aircraft monitoring module monitors the aircraft to obtain real-time data of the aircraft; the flight information module obtains flight information data; finally, the analysis module determines the safety rating of each monitoring area unit according to the bird activity trajectories of each monitoring area unit. The safety rating is divided into high-risk areas, low-risk areas, and safe areas. The flight route is determined according to the departure location information data, the destination location information data, the low-risk areas, and the safe areas, so that the flight route avoids high-risk areas with more birds and reduces the risk of aircraft crashes. If the flight route cannot be determined within the low-risk areas and the safe areas, the execution of this task is cancelled; the flight route and the flight route risk index are determined according to the safety rating results of each monitoring area unit and the flight information data; and then analyzed according to the flight route risk index and the real-time data of the aircraft to judge the aircraft that can execute this flight route; the aircraft that can execute this flight route is comprehensively selected according to multiple dimensions such as the risk degree, distance, and battery status of the flight route, ensuring that the selected aircraft can successfully complete this flight route.

[0053] As an implementation manner of the present invention, the real-time data of the aircraft includes the mission status, real-time power, and battery state coefficient of the aircraft; the flight information data includes the departure location information data and the destination location information data; the bird activity information data includes the number of birds; the flight routes include the flight route from the departure place to the destination and the flight route from the destination back to the departure place.

[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 in the past preset time, obtain the flight safety index of each monitoring area unit;

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

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

[0058] S4: According to the flight safety index of each monitoring area passed by the flight route, determine the flight route risk index;

[0059] S5: According to the flight route, the flight route risk index, and the battery state coefficient of each aircraft, obtain the minimum power required for each aircraft to perform this flight;

[0060] S6: Compare the minimum power required for each aircraft to perform this flight with the real-time power of the aircraft to determine the aircraft that can perform this flight route;

[0061] Through the above technical solution, in this embodiment, first, by analyzing the number of birds in each monitoring area unit in the past preset time, the flight safety index of each monitoring area unit is obtained; then, by analyzing the flight safety index of each monitoring area unit, the safety rating of each monitoring area unit is carried out; then, by analyzing the safety rating results of each monitoring area unit, the departure location information data and the destination location information data, the flight route is determined; the safety rating is divided into high-risk areas, low-risk areas and safe areas, and the flight route is determined according to the departure location information data, the destination location information data, the low-risk areas and the safe areas. Then, according to the flight safety index of each monitoring area passed by the flight route, the flight route risk index is determined; finally, according to the flight route, the flight route risk index and the battery state coefficient of each aircraft, the minimum power of each aircraft to perform this flight is obtained; by comparing the minimum power of each aircraft to perform this flight with the real-time power of the aircraft, the aircraft that can perform this flight route is judged; according to multiple dimensions such as the danger degree, distance of the flight route and the battery state of the aircraft, the aircraft that can perform this flight route is comprehensively selected to ensure that the selected aircraft can successfully complete this flight route.

[0062] As an implementation manner of the present invention, through the formula:

[0063]

[0064] Calculate the flight safety index P of the mth monitoring area unit n ;

[0065] Among them, f(X) is the first judgment function. When X>0, f(X)=1; when X≤0, f(X)=0; Q bn (t) is the change curve of the number of flying birds in the nth monitoring area unit over time, n∈N; t d is the current time; Δt is the preset duration; Q 1 is the preset number of flying birds; t nup is the cumulative duration during which the number of flying birds in the nth monitoring area unit exceeds the first preset value in the past preset duration from the current time; δ 0 is the first preset ratio;

[0066] Through the above technical solution, this embodiment is the average number of flying birds in the nth monitoring area unit in the past preset duration from the current time; is the difference between the average number of flying birds in the nth monitoring area unit in the past preset duration from the current time and the preset number of flying birds; in the formula In, X in the first judgment function f(X) refers to When When it is, it indicates that the average number of flying birds in the nth monitoring area unit in the preset duration past the current time does not exceed the preset number of flying birds. The number of flying birds in the nth monitoring area unit is small, and the impact risk is small. When it is, it indicates that the average number of flying birds in the nth monitoring area unit in the preset duration past the current time exceeds the preset number of flying birds. The number of flying birds in the nth monitoring area unit is large, and the impact risk is large. is the ratio of the cumulative duration during which the number of flying birds in the nth monitoring area unit exceeds the first preset value in the preset duration past the current time to the preset duration; is the difference between the ratio of the cumulative duration during which the number of flying birds in the nth monitoring area unit exceeds the first preset value in the preset duration past the current time to the preset duration and the first preset ratio; In the formula the X in the first judgment function f(X) refers to When it is, it indicates that the cumulative duration during which the number of flying birds in the nth monitoring area unit exceeds the first preset value in the preset duration past the current time is short, so the safety risk is small. When it is, it indicates that the cumulative duration during which the number of flying birds in the nth monitoring area unit exceeds the first preset value in the preset duration past the current time is long, so the safety risk is large.

[0067] It should be noted that the preset duration Δt, the preset number of flying birds Q 1 and the first preset ratio δ 0 are preset values, obtained according to experience, and will not be elaborated here.

[0068] As an implementation manner of the present invention, the safety rating process of the nth monitoring area unit is as follows:

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

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

[0071] When P n = 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 flying birds in the nth monitoring area unit in the preset duration past the current time exceeds the preset number of flying birds and the cumulative duration during which the number of flying birds in the nth monitoring area unit exceeds the first preset value in the preset duration past the current time is long, at this time P n= 2, the nth monitoring area unit is a high-risk area; when the average number of flying birds in the nth monitoring area unit within the preset duration from the current time exceeds the preset number of flying birds or the cumulative duration during which the number of flying birds in the nth monitoring area unit exceeds the first preset value within the preset duration from the current time is long, that is, P n = 1, the nth monitoring area unit is a low-risk area; when the average number of flying birds in the nth monitoring area unit within the preset duration from the current time does not exceed the preset number of flying birds and the cumulative duration during which the number of flying birds in the nth monitoring area unit does not exceed the first preset value within the preset duration from the current time is long, at this time P n = 0, the nth monitoring area unit is a safe area.

[0073] As an implementation manner of the present invention, through the formula:

[0074]

[0075] Calculate the flight route danger index F;

[0076] Among them, A is the number of low-risk areas passed by this flight route, a ∈ A; S a Is the route length of this flight route passing through the ath low-risk area; S ALL Is the total route length of this flight route; C 1 Is the first preset constant;

[0077] Through the above technical solution, this embodiment Is the cumulative length of this flight route passing through all low-risk areas; Is the ratio of the cumulative length of this flight route passing through all low-risk areas to the total route length of this flight route; the ratio of the cumulative length of this flight route passing through all low-risk areas to the total route length of this flight route The larger it is, the larger the flight route danger index F is; the ratio of the cumulative length of this flight route passing through all low-risk areas to the total route length of this flight route The smaller it is, the smaller the flight route danger index F is;

[0078] It should be noted that the first preset constant C 1 Is a preset value, obtained according to experience, and will not be elaborated here.

[0079] As an implementation manner of the present invention, through the formula:

[0080]

[0081] Calculate the minimum power B for the mth aircraft to perform this flight mL ;

[0082] Among them, Bm (S ALL ) is the basic power consumption for the m-th aircraft to execute the flight route; δ mB is the battery state coefficient of the m-th aircraft, 0 ≤ δ mB ≤ 1; C 2 is the second preset constant; R m is the mission state coefficient;

[0083] Through the above technical solution, the mission state of this embodiment is divided into a waiting mission state and an executing mission state. The waiting mission state coefficient is 1, and the executing mission state coefficient is 0; then, by presetting the basic power consumption change curves of various models of aircraft with the flight distance; according to the basic power consumption change curve, obtain the basic power consumption for the distance of S ALL The smaller the battery state coefficient δ mB of the m-th aircraft, the worse the battery state. For the same flight distance, the power consumption speed is faster. Therefore, the minimum power consumption for the m-th aircraft to execute this flight is higher, B mL ; the greater the flight route danger index F, the more risks the aircraft needs to avoid. When the aircraft avoids risks, it also needs to consume more power. Therefore, the minimum power consumption for the m-th aircraft to execute this flight is higher, B mL ; the battery state coefficient δ m of the m-th aircraft is obtained by the prior art and will not be elaborated here;

[0084] It should be noted that the second preset constant C 2 is a preset value obtained according to experience and will not be elaborated here.

[0085] As an implementation manner of the present invention, the judgment process of whether the flight route can be executed is as follows;

[0086] Compare the remaining power of the m-th aircraft with the minimum power consumption B mL for the m-th aircraft to execute this flight;

[0087] When B my ≥ B mL , the m-th aircraft can execute this flight;

[0088] Otherwise, the m-th aircraft cannot execute this flight;

[0089] Through the above technical solution, this embodiment compares the remaining power of the m-th aircraft with the minimum power consumption B mL for the m-th aircraft to execute this flight; when B my ≥ B mL , it indicates that the m-th aircraft is in the waiting mission and the power exceeds the minimum power consumption B mL, so it can perform this flight.

[0090] The above has described an embodiment of the present invention in detail, but the described content is only a preferred embodiment of the present invention and cannot be considered as defining the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the application of the present invention shall still fall within the scope covered by the patent of the present invention.

Claims

1. A low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things, characterized in that: The management system comprises: Bird distribution collection module, used to collect bird activity information data in the low-altitude area of ​​the target area; A division module is used to divide the target area into a number of monitoring area units; Aircraft monitoring module, used to monitor the aircraft and obtain real-time data of the aircraft; Flight information module, used to obtain flight information data; 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 determine the flight route and flight line hazard index based on the safety rating results of each monitoring area unit and the flight information data; and then analyze the flight line hazard index and the real-time data of the aircraft to determine the aircraft that can execute this flight route.

2. According to claim 1, a low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things is characterized in that: The real-time data of the aircraft includes the mission status, real-time power and battery status coefficient of the aircraft; the flight information data includes departure location information data and destination location information data; the bird activity information data includes the number of birds; the flight route includes the flight route from the departure point to the destination and the flight route from the destination back to the departure point.

3. According to claim 2, a low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things is characterized in that: The analysis method of the analysis module comprises the following steps: S1: Analyze the number of birds in each monitoring area unit within the preset time in the past to obtain the flight safety index of each monitoring area unit; S2: Analyze the flight safety index of each monitoring area unit and conduct safety rating for each monitoring area unit; S3: Determine the flight route by analyzing the safety rating results of each monitoring area unit, the departure location information data, and the destination location information data; S4: Analyze the flight safety index of each monitoring area that the flight route passes through to determine the flight route danger index; S5: Analyze the flight route, the flight route risk index, and the battery status coefficient of each aircraft to obtain the minimum power of each aircraft to perform this flight; S6: Determine the aircraft that can execute the current flight route based on the comparison between the minimum power of each aircraft to execute the current flight and the real-time power of the aircraft.

4. According to claim 3, a low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things is characterized in that: By formula: Calculate the flight safety index P of the nth monitoring area unit n ; Wherein, f(X) is the first judgment function, when X>0, f(X)=1; when X≤0, f(X)=0; Q bn (t) is the curve of the number of flying birds in the nth monitoring area unit changing with time, n∈N; t d is the current time; Δt is the preset duration; Q1 is the preset number of flying birds; t nup It is the cumulative time duration during which the number of flying birds exceeds the first preset value within the preset time duration from the current time of the nth monitoring area unit; δ0 is the first preset ratio.

5. According to claim 4, a low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things is characterized in that: The safety rating process of the nth monitoring area unit is: When P n =0, the nth monitoring area unit is a safe area; When P n =1, the nth monitoring area unit is a low-risk area; When P n =2, the nth monitoring area unit is a high-risk area.

6. The low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things according to claim 5 is characterized in that: By formula: Calculate the flight route hazard index F; Where A is the number of low-risk areas that the flight route passes through, a∈A; S a is the length of the flight route passing through the ath low-risk area; S ALL is the total length of the flight route; C1 is the first preset constant.

7. The low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things according to claim 6 is characterized in that: By formula: Calculate the minimum power B required for the mth aircraft to perform this flight mL ; Among them, B m (S ALL ) is the basic power consumed by the mth aircraft to execute the flight route; δ mB is the battery state coefficient of the mth aircraft, 0≤δ mB ≤1; C2 is the second preset constant; R m is the task status coefficient.

8. The low-altitude aircraft operation monitoring and management system based on AI and the Internet of Things according to claim 7 is characterized in that: The judgment process of whether this flight route can be executed is as follows; The remaining power of the mth aircraft and the minimum power B required for the mth aircraft to perform this flight are calculated. mL Make comparisons; When B my ≥B mL When , the mth aircraft can perform this flight; Otherwise, the mth aircraft cannot perform this flight.

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