Forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors

Abstract

The invention discloses a forest fire prevention unmanned aerial vehicle automatic inspection system based on meteorological factors. The forest fire prevention unmanned aerial vehicle automatic inspection system comprises a meteorological data acquisition device, an unmanned aerial vehicle field and edge calculation device, a remote data analysis and flight management system and an unmanned aerial vehicle. The meteorological data acquisition device is used for acquiring meteorological factor data of different meteorological conditions, special festivals and holidays or different seasons in real time; the unmanned aerial vehicle field and edge computing device is used for receiving the meteorological factor data, cleaning and processing the meteorological factor data to obtain processed data, and controlling the unmanned aerial vehicle to cruise the inspection area; the remote data analysis and flight management system is used for analyzing the processed data, judging forest fire danger meteorological levels under different conditions, formulating cruise tasks of different unmanned aerial vehicles and sending the cruise tasks of the unmanned aerial vehicles; the unmanned aerial vehicle automatically executes a cruising task according to the control command; the system can automatically increase the forest fire prevention inspection frequency of the unmanned aerial vehicle according to the special nodes, meets the actual inspection requirements, and enables the forest fire prevention to be more efficient and intelligent.

Description

Technical Field

[0001] The present invention relates to the technical field of forest fire prevention unmanned aerial vehicle inspection, and in particular to an automatic forest fire prevention unmanned aerial vehicle inspection system based on meteorological factors. Background Art

[0002] Traditional drone inspection systems generally patrol according to pre-set inspection tasks and fixed patrol frequencies, without taking into account the probability of fires in different seasons and under different weather conditions. As a result, the frequency of drone forest fire inspections cannot meet actual inspection needs. Alternatively, inspectors set special dates, special seasons and real-time weather conditions, and manually adjust patrol plans and frequencies, which requires a lot of manpower and material resources, and is not very timely, resulting in a waste of human resources and reduced inspection efficiency. Summary of the invention

[0003] The present invention provides an automatic forest fire prevention UAV patrol system based on meteorological factors to overcome the technical problem that the existing UAV forest fire prevention patrol system needs the patrol personnel to set and adjust the patrol plan and patrol frequency in advance when performing patrol tasks, which consumes a lot of manpower and material resources, is inefficient, and does not take into account the different probabilities of fire under different meteorological conditions, special holidays or seasons, resulting in the UAV forest fire prevention patrol frequency being unable to meet actual patrol needs.

[0004] In order to achieve the above object, the technical solution of the present invention is:

[0005] An automatic inspection system for forest fire prevention drones based on meteorological factors, comprising: a meteorological data collection device, a drone airport and edge computing device, a remote data analysis and flight management system, and a drone;

[0006] The meteorological data acquisition device is used to collect meteorological factor data of different meteorological conditions, special holidays or different seasons in real time, and the meteorological factor data includes but is not limited to temperature, air humidity, wind speed, rainfall and snow thickness;

[0007] The unmanned aerial vehicle airport and edge computing device include an edge computing unit and an unmanned aerial vehicle airport unit. The edge computing unit is used to receive meteorological factor data and clean and process the meteorological factor data to obtain processed data; the unmanned aerial vehicle airport unit is used to control the unmanned aerial vehicle to cruise the inspection area;

[0008] The remote data analysis and flight management system is used to receive the processed data, analyze the processed data, determine the forest fire risk meteorological level under different meteorological conditions, special holidays or different seasons, formulate different UAV cruise missions according to the forest fire risk meteorological level, and send the UAV cruise missions to the UAV airport unit;

[0009] The UAV automatically performs the cruise mission according to the control command of the UAV airport unit, and completes the automatic cruise of the inspection area.

[0010] Further, the remote data analysis and flight management system includes a data communication module, a data storage module, a flight mission calculation module, a flight mission manual correction module and a route planning module;

[0011] The data communication module is used to receive processed data sent by the edge computing unit and control command data sent to the flight mission computing module, the flight mission manual correction module and the route planning module;

[0012] The data storage module is used to store the cruise mission obtained by the flight mission calculation module;

[0013] The flight mission calculation module is used to determine the forest fire risk weather level in different weather conditions, special holidays or different seasons according to the processed data received by the data communication module every day, and formulate the cruise mission of the UAV according to the forest fire risk weather level;

[0014] The flight mission manual correction module is used to manually correct the flight mission;

[0015] The route planning module is used to set the inspection route of the drone.

[0016] Furthermore, the edge computing unit includes a data receiving module, a data caching module and a data cleaning and processing module;

[0017] The data receiving module is connected to the meteorological collection device and is used to receive the meteorological factor data collected by the meteorological collection device;

[0018] The data cache module is connected to the data receiving module and is used to store the meteorological factor data received by the data receiving module;

[0019] The data cleaning and processing module is connected to the data cache module and is used to clean and process the stored meteorological factor data to obtain processed data.

[0020] Further, the UAV airport unit includes a flight command communication module, a flight control module and a UAV airport device;

[0021] The flight command communication module is used to receive data from the data cache module and control commands and data synchronization commands from the remote data analysis and flight management system;

[0022] The flight control module is used to control the drone airport and drone operations;

[0023] The UAV airport device is used to provide an intelligent airport for UAVs.

[0024] Furthermore, the flight mission calculation module is used to determine the forest fire risk weather level under different weather conditions, special holidays or different seasons according to the processed data received by the data communication module every day, and formulate the cruise mission of the UAV according to the forest fire risk weather level, including:

[0025] S21: Extract the processed data, which are the temperature T and relative humidity r at 14:00 on the day before the inspection. RH and wind speed value V;

[0026] S22: determining the number of consecutive days M in which the precipitation is less than the precipitation threshold from the processed data;

[0027] S23: Calculate the precipitation R within 24 hours on the inspection day and the previous day t ;

[0028] S24: Calculate the minimum snow thickness H within 24 hours of the inspection day and the previous day t ;

[0029] S25: Calculate the forest fire weather index FFDI based on the data obtained from S41-S44, as shown in formula (1):

[0030] I FFDI =(f(V)+f(T)+f(r RH )+f(M))×C t ×C h (1)

[0031] Among them, I FFDI represents the forest fire risk meteorological index, f(V) represents the wind speed factor meteorological index function, f(T) represents the temperature factor meteorological index function, f(M) represents the drought meteorological factor index function, C t Represents the precipitation correction factor, R t When C is greater than or equal to the preset value t is 0; R t When C is less than the preset value t =1; C h Denotes the snow correction factor, H t When C is greater than or equal to the preset value h =0; H t When C is less than the preset value h is 1;

[0032] The forest fire weather is divided into five levels, and the calculated forest fire weather index I is used to determine the forest fire weather index. FFDI The level to which the value belongs;

[0033] S26: According to the forest fire weather index I FFDI and the date D of the inspection day, calculate the number of inspections per day, the number of inspections X t As shown in formula (2),

[0034] X t =f I +f h +f s (2)

[0035] f I There are five inspection frequencies set according to the level of forest fire risk weather;

[0036] f h is the number of inspections calculated based on whether it is a special holiday, as shown in formula (3),

[0037]

[0038] f s is the number of inspections calculated based on whether it is a special season, as shown in formula (4),

[0039]

[0040] S27: Calculate the inspection time point according to the number of inspections;

[0041] S28: Formulate a cruise mission according to the flight mission parameters preset by the route planning module;

[0042] S29: The cruise mission is stored in the data storage module, and at the same time, the flight mission is sent to the flight control module of the UAV airport unit through the data communication module.

[0043] Furthermore, the inspection time point is calculated according to the number of inspections, including:

[0044] S271: Set the inspection start time T s Point, inspection deadline T e point;

[0045] S272: Calculate the inspection time, as shown in formula (5):

[0046]

[0047] Among them, K represents the Kth inspection, T s Indicates the start inspection time point, T e Indicates that as of the inspection time, X t Represents the number of inspections, Round is the rounding function, and f(K) represents the time point of the Kth inspection.

[0048] Furthermore, the flight control module sets a timer according to the set cruise mission. When the timer is reached, the UAV flight control module controls the UAV to cruise according to the following steps:

[0049] S41, extracting real-time meteorological factor data from a data cache module of a meteorological data acquisition device;

[0050] S42: Determine whether the current conditions for the drone to take off are met based on the meteorological factor data. The take-off conditions require that the wind speed and 24-hour rainfall are both less than the threshold. The take-off determination is as shown in formula (6):

[0051]

[0052] Where V represents the current wind speed value in meters per second, v represents the set wind speed threshold, t represents the current time, accurate to minutes, R represents the set rainfall threshold, and R t Indicates 24-hour rainfall; fly indicates take-off conditions. When fly=1, it means take-off is possible; when fly=0, it means take-off is not possible.

[0053] S43. When the meteorological factor data meets the take-off conditions, the UAV is controlled to take off and perform the cruise mission according to the set cruise mission and cruise route.

[0054] Furthermore, the step of the data cleaning and processing module cleaning and processing the meteorological factor data includes:

[0055] S31, extracting meteorological factor data, and using a limited symbol filtering algorithm to denoise the meteorological factor data, as shown in formula (7),

[0056]

[0057] Wherein, Y represents the sampling value, k represents the k-th data extracted, Y(k) represents the k-th sampling value, Y(k-1) represents the previous sampling value, and ΔY represents the sampling deviation threshold;

[0058] S32, calculate the average sampling value per minute after denoising, as shown in formula (8),

[0059]

[0060] Where T represents the average sampling value per minute, and n represents the number of data extracted within 1 minute;

[0061] S33. Send the calculated data to the remote data analysis and flight management system, and the data format is ID, meteorological factor type name, meteorological factor type symbol, meteorological factor collection time, and meteorological factor value.

[0062] The present invention provides a forest fire prevention UAV automatic patrol system based on meteorological factors. A meteorological collection device, a UAV airport and an edge computing device and a remote data analysis and flight management system are deployed at forest fire detection points. The edge computing unit is used to clean and process the collected meteorological factor data of different meteorological conditions, special holidays or different seasons. According to the remote data analysis and flight management system, the meteorological data is processed and analyzed again, and these data are used to automatically generate UAV cruise missions for different meteorological conditions, special holidays or different seasons, so as to achieve the purpose of controlling the automatic cruise of the UAV, eliminating the trouble of manual intervention, and being able to automatically increase the frequency of UAV forest fire prevention patrols in view of special holidays or seasons, meet actual patrol needs, and make forest fire prevention more efficient and intelligent. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0064] Figure 1 A system block diagram of a forest fire prevention UAV automatic inspection system based on meteorological factors provided by the present invention. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] This embodiment provides a forest fire prevention drone automatic inspection system based on meteorological factors, such as Figure 1 As shown, it includes: meteorological data collection device, UAV airport and edge computing device, remote data analysis and flight management system and UAV;

[0067] The meteorological data acquisition device is used to collect meteorological factor data of different meteorological conditions, special holidays or different seasons in real time, and the meteorological factor data includes but is not limited to temperature, air humidity, wind speed, rainfall and snow thickness;

[0068] The unmanned aerial vehicle airport and edge computing device include an edge computing unit and an unmanned aerial vehicle airport unit. The edge computing unit is used to receive meteorological factor data and clean and process the meteorological factor data to obtain processed data; the unmanned aerial vehicle airport unit is used to control the unmanned aerial vehicle to cruise the inspection area;

[0069] The remote data analysis and flight management system is used to receive the processed data, analyze the processed data, determine the forest fire risk meteorological level under different meteorological conditions, special holidays or different seasons, formulate different UAV cruise missions according to the forest fire risk meteorological level, and send the UAV cruise missions to the UAV airport unit;

[0070] The UAV automatically performs the cruise mission according to the control command of the UAV airport unit, and completes the automatic cruise of the inspection area.

[0071] Specifically, the meteorological data is a small meteorological station, which integrates sensors such as temperature, air humidity, wind speed, rainfall and snow thickness ultrasonic detectors, and is electrically connected to the edge computing unit to collect data on various meteorological factors. The meteorological factor data of different meteorological conditions, special holidays or different seasons that can be collected can provide more inspection conditions for drone cruises; the drone airport and edge computing device include an edge computing unit and a drone airport unit, and the edge computing unit is used to receive meteorological factor data and clean and process the meteorological factor data to obtain processed data; the drone airport unit is used to control the opening and closing of the drone airport door, the loosening and clamping of the push rod, the charging of the drone, and the provision of network and live streaming services; the drone airport and edge computing device can process the collected data The data is cleaned to remove noise from the data and make the data more accurate; the remote data analysis and flight management system is used to receive the processed data, analyze the processed data, formulate the cruise mission of the UAV according to the analysis results, and send the cruise mission of the UAV to the UAV airport unit. The remote data analysis and flight management system is set up to formulate the cruise mission of the UAV according to the data, eliminating the trouble of manual intervention, meeting the actual inspection needs, and making forest fire prevention more efficient and intelligent; the UAV automatically performs the cruise mission according to the control command of the UAV airport unit, and completes the automatic cruise of the inspection area. The UAV is a small multi-rotor UAV, carrying wide-angle, telephoto and thermal imaging function cameras, and automatically cruises the inspection area under the control of the flight control module.

[0072] In a specific embodiment, the remote data analysis and flight management system includes a data communication module, a data storage module, a flight mission calculation module, a flight mission manual correction module, and a route planning module;

[0073] The data communication module is respectively connected to the data cleaning and processing module of the edge computing unit and the flight command communication module of the unmanned aerial vehicle airport unit for receiving the processed data sent by the edge computing unit and the control command data sent to the flight mission calculation module, the flight mission manual correction module and the route planning module;

[0074] The data storage module is used to store the cruise mission obtained by the flight mission calculation module;

[0075] The flight mission manual correction module is used to manually correct the flight mission;

[0076] The route planning module is used to set the inspection route of the drone:

[0077] The flight mission calculation module is used to determine the forest fire risk weather level in different weather conditions, special holidays or different seasons according to the processed data received by the data communication module every day, and formulate the cruise mission of the UAV according to the forest fire risk weather level:

[0078] S21: Extract the processed data, which are the temperature T and relative humidity r at 14:00 on the day before the inspection. RH and wind speed value V;

[0079] S22: Determine the number of days M during which the continuous precipitation is less than the precipitation threshold from the processed data. In this embodiment, the precipitation threshold is 1 mm and is calculated according to the method prescribed by the state;

[0080] S23: Calculate the precipitation R within 24 hours on the inspection day and the previous day t ;

[0081] S24: Calculate the minimum snow thickness H within 24 hours of the inspection day and the previous day t ;

[0082] S25: Calculate the forest fire weather index FFDI based on the data obtained from S21-S24, as shown in formula (9):

[0083] I FFDI =(f(V)+f(T)+f(r RH )+f(M))×C t ×C h (9)

[0084] Among them, I FFDI represents the forest fire risk meteorological index, f(V) represents the wind speed meteorological factor index function, f(r RH ) represents the meteorological factor index function of rainfall, f(T) represents the meteorological factor index function of temperature, and f(M) represents the meteorological factor index function of drought. The meteorological factor index functions are all nationally set values.

[0085] C t Represents the precipitation correction factor, R t When C is greater than or equal to the preset value t is 0; R t When C is less than the preset value t =1; C h Denotes the snow correction factor, H t When C is greater than or equal to the preset value h =0; H t When C is less than the preset value h is 1; in this embodiment, 24h precipitation R t When ≥1mm, C t =0; R t When <1mm, C t =1; 24h snow thickness H t When ≥1mm, C h =0; H t When <1mm, C h =1;

[0086] The forest fire weather is divided into five levels, as shown in Table 1.

[0087] Table 1 Forest fire risk weather levels

[0088] FFDI Forest fire weather level [0，38) Low risk [38，47) Lower risk [47，66) Higher risk [66，73) High risk [73，47) Very high risk

[0089] S26: Determine the calculated forest fire risk meteorological index I FFDI The value of the level belongs to, according to the forest fire weather index I FFDI and the date D of the inspection day, calculate the number of inspections per day, the number of inspections X t As shown in formula (10),

[0090] X t =f I +f h +f s (10)

[0091] f I are five inspection times set according to the level of forest fire weather, as shown in formula (11).

[0092]

[0093] f h is the number of inspections calculated based on whether it is a special holiday, as shown in formula (12),

[0094]

[0095] Special holidays such as Qingming Festival, Zhongyuan Festival, Spring Festival, etc.;

[0096] f s is the number of inspections calculated based on whether it is a special season, as shown in formula (13),

[0097]

[0098] Special seasons such as spring and autumn;

[0099] S27: Calculate the inspection time point according to the number of inspections;

[0100] S271: Set the inspection start time T s Point, inspection deadline T e In this embodiment, it is from 4 am to 8 pm;

[0101] S272: Calculate the inspection time, as shown in formula (14),

[0102]

[0103] Among them, K represents the Kth inspection, T s Indicates the start inspection time point, T e Indicates that as of the inspection time, X t represents the number of inspections, Round is the rounding function, and f(K) represents the time point of the Kth inspection;

[0104] S28: Formulate a cruise mission according to the flight mission parameters preset by the route planning module, such as inspecting the route, inspecting the equipment, and returning conditions;

[0105] S29: The cruise mission is stored in the data storage module, and at the same time, the flight mission is sent to the flight control module of the UAV airport unit through the data communication module.

[0106] In this embodiment, the manual correction module for flight missions is a management function based on the B / S architecture, through which the controller can manually correct the inspection mission and synchronize the UAV airport unit; the route planning module is a management function based on the B / S architecture, through which the controller can manually pre-set the UAV flight route based on GIS, satellite map images, elevation data and three-dimensional map models, and send the inspection route to the flight control module; the data storage module is a Mysql relational database, which stores the processed and analyzed meteorological factor data, route data and inspection mission data;

[0107] The remote data analysis and flight management system also includes a special date and season setting module, through which special dates that need to increase inspection efforts, such as the Spring Festival, Qingming Festival, etc., and special seasons such as spring and autumn, are set, and the set dates are sent to the data storage module for formulating inspection tasks;

[0108] A remote data analysis and flight management system is set up to process and analyze the meteorological data again, and use these data to automatically generate UAV cruise missions under different meteorological conditions or in different seasons, so as to achieve the purpose of controlling the automatic cruise of the UAV. In special seasons and holidays, the intensity of the cruise can be automatically increased to meet actual inspection requirements, making forest fire prevention more efficient and intelligent.

[0109] In a specific embodiment, the edge computing unit includes a data receiving module, a data caching module, and a data cleaning and processing module;

[0110] The data receiving module is connected to the meteorological collection device and is used to receive the meteorological factor data collected by the meteorological collection device;

[0111] The data cache module is connected to the data receiving module and is used to store the meteorological factor data received by the data receiving module;

[0112] The data cleaning and processing module is connected to the data cache module and is used to clean and process the stored meteorological factor data to obtain processed data:

[0113] S31, extracting meteorological factor data, and using a limited symbol filtering algorithm to denoise the meteorological factor data, as shown in formula (15),

[0114]

[0115] Wherein, Y represents the sampling value, k represents the K-th data extracted, Y(k) represents the k-th sampling value, Y(k-1) represents the previous sampling value, and ΔY represents the sampling deviation threshold;

[0116] The limit filter subtracts two adjacent sampling values ​​to find the absolute value increment, and then compares it with the sampling deviation threshold ΔY. If it is less than or equal to the sampling deviation ΔY, the current adopted value Y(k) is taken; if it is greater than the sampling deviation threshold ΔY, the previous sampling value Y(k-1) is taken as the current sampling value, and the cache data is updated;

[0117] S32, every hour, the data cleaning and processing module extracts the meteorological factor data temperature T, atmospheric relative humidity r RH , wind speed V, rainfall R t and snow thickness H t , k = 1, 2, 3, ... 60;

[0118] S33, calculate the average sampling value per minute after denoising, as shown in formula (16),

[0119]

[0120] Where T represents the average sampling value per minute, and n represents the number of data extracted within 1 minute;

[0121] S34. Send the calculated data to the remote data analysis and flight management system. The data format is ID, meteorological factor type name, meteorological factor type symbol, meteorological factor collection time, and meteorological factor value (retain 1 decimal place).

[0122] In this embodiment, the data receiving module is electrically connected to the meteorological data acquisition device, and collects meteorological factor data every 1 minute using the RS485 protocol and saves it in the data cache module; the data cache module uses Redis as the data cache database; the data cache module is connected to the data cleaning and processing module; an edge computing unit is set up to save and denoise the collected data to obtain more accurate data.

[0123] In a specific embodiment, the UAV airport unit includes a flight command communication module, a flight control module, and a UAV airport device;

[0124] The flight command communication module is connected to the data cache module and the remote data analysis and flight management system, and is used to receive data from the data cache module and control commands and data synchronization commands from the remote data analysis and flight management system;

[0125] The flight control module is used to control the drone airport and drone operations. A timer is set according to the set cruise mission. When the timer is reached, the drone flight control module controls the drone to cruise according to the following steps:

[0126] S41, extracting real-time meteorological factor data from a data cache module of a meteorological data acquisition device;

[0127] S42. Determine whether the current conditions for the drone to take off are met based on the meteorological factor data. The take-off conditions require that the wind speed and 24-hour rainfall are both less than the threshold. The take-off determination is as shown in formula (17):

[0128]

[0129] Where V represents the current wind speed value in meters per second, v represents the set wind speed threshold, t represents the current time, accurate to minutes, R represents the set rainfall threshold, and R tIndicates the 24-hour rainfall; fly indicates the take-off condition. When fly=1, it indicates that the aircraft can take off; when fly=0, it indicates that the aircraft cannot take off. In this embodiment, the wind speed is below 12 meters per second and the 24-hour rainfall does not exceed 100 mm.

[0130] S43, when the meteorological factor data meets the take-off conditions, the UAV is controlled to take off and perform the cruise mission according to the set cruise mission and cruise route;

[0131] The UAV airport device is used to provide an intelligent airport for UAVs.

[0132] In this embodiment, the flight command communication module is used to receive control commands and data synchronization commands from the remote data analysis and flight management system. Control commands include the operation control of the UAV airport and the operation control of the UAV; data synchronization commands mainly include route data synchronization, flight plan data synchronization, etc.

[0133] The flight control module mainly includes two parts of work. One part is to control the opening and closing of the UAV airport door, the clamping and loosening of the push rod, the charging and shutting down of the UAV, the take-off, landing, hovering, flight and camera gimbal control of the UAV according to the control command; the other part is to synchronize the route data and flight plan data to the UAV remote control according to the data synchronization command;

[0134] The drone airport device mainly includes a drone airport and its attached drone remote controller and router, etc., which are used to control drones and provide network.

[0135] A UAV airport unit is set up to receive flight commands from the UAV and control the UAV to achieve cruise missions.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A forest fire prevention drone automatic inspection system based on meteorological factors, characterized in that: include: Meteorological data collection devices, drone airports and edge computing devices, remote data analysis and flight management systems and drones; The meteorological data acquisition device is used to collect meteorological factor data of different meteorological conditions, special holidays or different seasons in real time, and the meteorological factor data includes but is not limited to temperature, air humidity, wind speed, rainfall and snow thickness; The unmanned aerial vehicle airport and edge computing device include an edge computing unit and an unmanned aerial vehicle airport unit. The edge computing unit is used to receive meteorological factor data and clean and process the meteorological factor data to obtain processed data; the unmanned aerial vehicle airport unit is used to control the unmanned aerial vehicle to cruise the inspection area; The remote data analysis and flight management system is used to receive the processed data, analyze the processed data, determine the forest fire risk meteorological level under different meteorological conditions, special holidays or different seasons, formulate different UAV cruise missions according to the forest fire risk meteorological level, and send the UAV cruise missions to the UAV airport unit; The UAV automatically performs the cruise mission according to the control command of the UAV airport unit, and completes the automatic cruise of the inspection area.

2. The automatic inspection system for forest fire prevention drones based on meteorological factors according to claim 1 is characterized in that: The remote data analysis and flight management system includes a data communication module, a data storage module, a flight mission calculation module, a flight mission manual correction module and a route planning module; The data communication module is used to receive processed data sent by the edge computing unit and control command data sent to the flight mission computing module, the flight mission manual correction module and the route planning module; The data storage module is used to store the cruise mission obtained by the flight mission calculation module; The flight mission calculation module is used to determine the forest fire risk weather level in different weather conditions, special holidays or different seasons according to the processed data received by the data communication module every day, and formulate the cruise mission of the UAV according to the forest fire risk weather level; The flight mission manual correction module is used to manually correct the flight mission; The route planning module is used to set the inspection route of the drone.

3. The automatic inspection system for forest fire prevention drones based on meteorological factors according to claim 1 is characterized in that: The edge computing unit includes a data receiving module, a data caching module and a data cleaning and processing module; The data receiving module is connected to the meteorological collection device and is used to receive the meteorological factor data collected by the meteorological collection device; The data cache module is connected to the data receiving module and is used to store the meteorological factor data received by the data receiving module; The data cleaning and processing module is connected to the data cache module and is used to clean and process the stored meteorological factor data to obtain processed data.

4. The automatic inspection system for forest fire prevention drones based on meteorological factors according to claim 1 is characterized in that: The unmanned aerial vehicle airport unit includes a flight command communication module, a flight control module and an unmanned aerial vehicle airport device; The flight command communication module is used to receive data from the data cache module and control commands and data synchronization commands from the remote data analysis and flight management system; The flight control module is used to control the drone airport and drone operations; The UAV airport device is used to provide an intelligent airport for UAVs.

5. The automatic inspection system for forest fire prevention drones based on meteorological factors according to claim 2 is characterized in that: The flight mission calculation module is used to determine the forest fire risk weather level under different weather conditions, special holidays or different seasons according to the processed data received by the data communication module every day, and formulate the cruise mission of the UAV according to the forest fire risk weather level, including: S21: Extract the processed data, which are the temperature T and relative humidity r at 14:00 on the day before the inspection. RH and wind speed value V; S22: determining the number of consecutive days M in which the precipitation is less than the precipitation threshold from the processed data; S23: Calculate the precipitation R within 24 hours on the inspection day and the previous day t ; S24: Calculate the minimum snow thickness H within 24 hours of the inspection day and the previous day t ; S25: Calculate the forest fire weather index FFDI based on the data obtained from S21-S24, as shown in formula (1): I FFDI =(f(V)+f(T)+f(r RH )+f(M))×C t ×C h (1) Among them, I FFDI represents the forest fire risk meteorological index, f(V) represents the wind speed factor meteorological index function, f(T) represents the temperature factor meteorological index function, f(M) represents the drought meteorological factor index function, C t Represents the precipitation correction factor, R t When C is greater than or equal to the preset value t is 0; R t When C is less than the preset value t =1; C h Denotes the snow correction factor, H t When C is greater than or equal to the preset value h =0; H t When C is less than the preset value h is 1; The forest fire weather is divided into five levels, and the calculated forest fire weather index I is used to determine the forest fire weather index. FFDI The level to which the value belongs; S26: According to the forest fire weather index I FFDI and the date D of the inspection day, calculate the number of inspections per day, the number of inspections X t As shown in formula (2), X t =f I +f h +f s (2) f I There are five inspection frequencies set according to the level of forest fire risk weather; f h is the number of inspections calculated based on whether it is a special holiday, as shown in formula (3), f s is the number of inspections calculated based on whether it is a special season, as shown in formula (4), S27: Calculate the inspection time point according to the number of inspections; S28: Formulate a cruise mission according to the flight mission parameters preset by the route planning module; S29: The cruise mission is stored in the data storage module, and at the same time, the flight mission is sent to the flight control module of the UAV airport unit through the data communication module.

6. The automatic inspection system for forest fire prevention drones based on meteorological factors according to claim 5 is characterized in that: The inspection time points calculated based on the number of inspections include: S271: Set the inspection start time T s Point, inspection deadline T e point; S272: Calculate the inspection time, as shown in formula (5): Among them, K represents the Kth inspection, T s Indicates the start inspection time point, T e Indicates that as of the inspection time, X t Represents the number of inspections, Round is the rounding function, and f(K) represents the time point of the Kth inspection.

7. The automatic inspection system for forest fire prevention drones based on meteorological factors according to claim 3 is characterized in that: The flight control module sets a timer according to the set cruise mission. When the timer is reached, the UAV flight control module controls the UAV to cruise according to the following steps: S41, extracting real-time meteorological factor data from a data cache module of a meteorological data acquisition device; S42: Determine whether the current conditions for the drone to take off are met based on the meteorological factor data. The take-off conditions require that the wind speed and 24-hour rainfall are both less than the threshold. The take-off determination is as shown in formula (6): Where V represents the current wind speed value in meters per second, v represents the set wind speed threshold, t represents the current time, accurate to minutes, R represents the set rainfall threshold, and R t Indicates 24-hour rainfall; fly indicates take-off conditions. When fly=1, it means take-off is possible; when fly=0, it means take-off is not possible. S43. When the meteorological factor data meets the take-off conditions, the UAV is controlled to take off and perform the cruise mission according to the set cruise mission and cruise route.

8. The automatic inspection system for forest fire prevention drones based on meteorological factors according to claim 2 is characterized in that: The step of cleaning and processing the meteorological factor data by the data cleaning and processing module includes: S31, extracting meteorological factor data, and using a limited symbol filtering algorithm to denoise the meteorological factor data, as shown in formula (7), Wherein, Y represents the sampling value, k represents the k-th data extracted, Y(k) represents the k-th sampling value, Y(k-1) represents the previous sampling value, and ΔY represents the sampling deviation threshold; S32, calculate the average sampling value per minute after denoising, as shown in formula (8), Where T represents the average sampling value per minute, and n represents the number of data extracted within 1 minute; S33. Send the calculated data to the remote data analysis and flight management system, and the data format is ID, meteorological factor type name, meteorological factor type symbol, meteorological factor collection time, and meteorological factor value.

Images