A forestry resource protection method, system, terminal and storage medium

Abstract

The present invention relates to a forestry resource protection method, system, terminal and storage medium, including: obtaining environmental image information above the forest in a preset patrol area; judging whether there is a flock of birds escaping according to the comparison between the environmental image information and the preset flock of birds escape model; if there is, determining the flock of birds escape position according to the environmental image information and the flock of birds escape model, and obtaining ground image information at the flock of birds escape position; determining the personnel characteristics and personnel characteristic positions according to the comparison between the ground image information and the preset personnel characteristic database, and scanning the personnel characteristics at the personnel characteristic positions to obtain scanned image information; judging whether the personnel characteristics are illegal felling personnel characteristics according to the comparison between the scanned image information and the preset felling tool database, thereby determining the uploaded personnel characteristic position and issuing an alarm or controlling the preset drone to reset and continue patrolling. The above scheme improves the ability to protect forestry resources.

Description

Technical Field

[0001] The present invention relates to the field of forestry resource protection, and in particular to a forestry resource protection method, system, terminal and storage medium. Background Art

[0002] Forestry resources have economic value, so some lawless elements try to steal forestry resources to seek illegal profits. In order to protect forestry resources, especially precious resources, it is necessary to patrol and monitor the forest area.

[0003] In the existing technology, daily forest patrols mainly rely on forest area monitoring cameras and patrol personnel walking mode. However, the forest environment is relatively complex, and traditional patrols cannot cover all areas. There are patrol blind spots, and forest area monitoring cameras are easily blocked by trees. Manual walking patrols are time-consuming and cannot achieve all-weather, all-round patrols. The patrol efficiency is low and needs to be improved. Summary of the invention

[0004] In order to improve the efficiency of forest inspection when protecting forest resources, the present invention provides a forest resource protection method, system, terminal and storage medium.

[0005] In a first aspect, the present invention provides a forestry resource protection method, which adopts the following technical solution:

[0006] A method for protecting forest resources, comprising:

[0007] Obtain environmental image information above the trees in the preset patrol area;

[0008] Determine whether there is a flock of birds escaping based on the comparison between the environmental image information and the preset flock of birds escaping model;

[0009] If it exists, determine the escape location of the flock of birds according to the environmental image information and the flock of birds escape model, and obtain ground image information at the flock of birds escape location;

[0010] Determine the personnel features and the personnel feature positions according to the comparison between the ground image information and the preset personnel feature database, and scan the personnel features at the personnel feature positions to obtain scanned image information;

[0011] Determine whether the person's characteristics are those of an illegal felling person based on the comparison between the scanned image information and a preset felling tool database;

[0012] If yes, upload the personnel’s characteristic location and issue an alarm;

[0013] If not, the preset drone is controlled to reset and continue patrolling.

[0014] By adopting the above technical scheme, in the prior art, forest patrols are usually carried out by manual patrols, which are inefficient and have blind spots. In this scheme, patrols are carried out by drones, and the drones can analyze the escape of flocks of birds that may occur during the felling process to determine whether there are suspicious persons. Finally, the drones scan the suspicious persons to determine whether they carry felling tools to confirm whether the suspicious persons are illegal fellers. In the above scheme, when an abnormal situation occurs, the drone can quickly reach the designated location, thereby greatly improving the efficiency of forest patrols.

[0015] Optionally, the method for acquiring the ground image information includes:

[0016] Obtain forest growth image information at the location where the flock of birds escapes;

[0017] Rating the lushness of tree leaves according to the tree growth image information and outputting the lushness level;

[0018] Determine whether the luxuriant degree level falls within the preset covering level range;

[0019] If it does not fall into the range, the shooting gap position is obtained according to the forest growth image information;

[0020] Shooting the ground at the shooting gap position and outputting ground image information;

[0021] If it falls into the grid, the forest growth image information is gridded, and the leaf content information in each grid is compared, and the selected grid with the least leaf content information is output and located;

[0022] Determine the descending position in the forest growth image information according to the selected grid;

[0023] At the descending position, a preset lifting camera is controlled to descend and shoot through leaves to output ground image information.

[0024] By adopting the above technical solution, in order to solve the problem that the camera may be blocked by leaves when shooting the ground, this solution uses the lushness of the leaves as the basis for judgment. According to the different lushness of the leaves, the lifting camera can adopt different methods for shooting. The images taken by the camera are not easily affected by the environment and are more efficient.

[0025] Optionally, the control method of the lifting camera includes:

[0026] Get the preset vertical straight-line distance between the drone and the lifting camera;

[0027] Determine the independent power supply type or the UAV power supply type based on the comparison between the vertical straight-line distance and the preset reference distance;

[0028] Based on the power supply type of the drone, the contacts for controlling the lifting camera are connected to the contacts of the base of the drone, so that the drone can supply power to the lifting camera;

[0029] Based on the independent power supply type, before the elevating camera descends, obtain the battery power of the elevating camera;

[0030] According to the comparison between the battery power and the preset low power, it is determined whether to continue charging with the power of the drone or to charge the lifting camera with the preset independent power supply carried by itself and descend for shooting.

[0031] By adopting the above technical solution, the camera adopts two power supply forms, so that the lifting camera can always have sufficient power for shooting, so that the drone can be used for patrolling the forest area, and the camera is not easy to be charged frequently to affect the use of the drone.

[0032] Optionally, the number of the lifting cameras is two, and the method for alternately using the lifting cameras includes:

[0033] Before the lifting cameras descend, respectively obtain the remaining power of the two lifting cameras;

[0034] Compare remaining power to determine working and backup cameras;

[0035] Control the backup camera to continue charging using the drone power supply type, control the working camera to use an independent power supply type and descend to the preset shooting height for shooting, and obtain the available power and camera position of the working camera in real time;

[0036] According to the comparison between the available power and the preset charging power, it is determined whether the working camera continues to shoot or is reset and replaced;

[0037] Based on reset replacement, the working camera is controlled to reset and charge using the drone power supply type, and the backup camera is controlled to be powered by an independent power supply type and moved to the camera position for shooting.

[0038] By adopting the above technical solution, two lifting cameras are set on the drone, and the two lifting cameras can be used interchangeably, so that the drone can operate for a longer time when patrolling the forest area, thereby improving efficiency.

[0039] Optionally, also include:

[0040] Control the lifting camera to lift upward after a preset shooting time, and continuously obtain the traction force of the preset traction line during the rising process;

[0041] The comparison of two consecutive pulling forces is used to determine whether the lift will continue or the tree will be entangled;

[0042] Based on the continued lifting, the lifting camera is controlled to reset and the ground image information is processed;

[0043] Based on the tree entanglement, brute force lifting or adjusted lifting is determined according to the comparison between the pulling force and the preset safety force;

[0044] Based on brute force lifting, the drone is controlled to pull the traction line until the lifting camera is untangled;

[0045] Based on the adjusted lift, the drone is controlled to move horizontally with a preset adjustment path, and the tilt angle of the traction line is obtained in real time;

[0046] Determine whether to continue moving forward or return to the original path according to the comparison relationship between the tilt angle and the preset reference angle;

[0047] Based on continuing to move forward, the lifting camera is controlled to lift upward, and based on the comparison between the traction pulling force and the safety pulling force, it is determined to continue lifting until the entanglement is released or reset and continue to move forward.

[0048] By adopting the above technical scheme, when the lifting camera is entangled by leaves after shooting and recovery, this scheme provides two solutions. By measuring the traction tension of the traction line, while ensuring that the traction line is not broken, the lifting camera can be more efficiently freed from between the branches.

[0049] Optionally, also include:

[0050] After a preset escape time, the extension length of the traction line is obtained;

[0051] Determine whether the extension length of the traction line is greater than the preset escape distance;

[0052] If and only if it is greater than, obtain the landing height between the lifting camera and the ground;

[0053] Control the drone to extend the traction line at the landing height and determine whether the traction force is 0;

[0054] If it is not 0, continue to land;

[0055] If it is 0, control the preset cutting device to cut the traction line, mark the landing position of the lifting camera, and upload the marked position.

[0056] By adopting the above technical solution, a third method for removing the entanglement of the lifting camera by the tree branches is provided. When the entanglement cannot be removed by the lifting method, the lifting camera is lowered to the ground and the traction line is cut. After the lifting camera safely falls on the ground, it can be recovered by manual recovery according to its landing point, thereby avoiding damage to the lifting camera.

[0057] Optionally, also include:

[0058] In the process of obtaining environmental image information in the patrol area, environmental noise information is obtained multiple times simultaneously;

[0059] Determine whether the environmental noise information obtained multiple times is consistent;

[0060] If they are consistent, the circumferential noise intensity is obtained based on the environmental noise information analysis;

[0061] Determine the noise direction based on the circumferential noise intensity;

[0062] Determine whether the direction of the noise is consistent with the direction of the escape location of the flock of birds;

[0063] If they match, the drone is controlled to patrol the location where the flock of birds escaped;

[0064] If they are inconsistent, the drone is controlled to move according to the direction of the noise and locate the noise source.

[0065] By adopting the above technical solution, noise detection is used to assist the system in judging and locating the felling location, thus avoiding the ineffective flight of the drone and improving the inspection efficiency of the drone.

[0066] In the second aspect, the present application provides a forestry resource protection system, which adopts the following technical solution:

[0067] A forestry resource protection system, comprising:

[0068] An acquisition module is used to acquire environmental image information above the trees, ground image information, scanned image information, tree growth image information, vertical straight-line distance, battery power of the lifting camera, remaining power, available power, camera position, traction tension of the traction line, extension length of the traction line, and environmental noise information;

[0069] A memory for storing a program of the above-mentioned forestry resources protection method;

[0070] The program in the processor and the memory can be loaded and executed by the processor to implement the above-mentioned forestry resource protection method.

[0071] In a third aspect, the present application provides a computer storage medium capable of storing corresponding programs, which is convenient for improving the efficiency of forest inspections and adopts the following technical solutions:

[0072] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned forestry resource protection methods.

[0073] In a fourth aspect, the present application provides an intelligent terminal, which adopts the following technical solution:

[0074] An intelligent terminal comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and execute the above-mentioned forestry resource protection method.

[0075] In summary, the present application includes at least one of the following beneficial technical effects:

[0076] 1. The inspection is carried out by drones, and the drones can analyze the possible escape of flocks of birds during the felling process to determine whether there are suspicious persons. Finally, the drones scan the suspicious persons to determine whether they carry felling tools to confirm whether the suspicious persons are illegal fellers, which greatly improves the efficiency of drones in forest patrols;

[0077] 2. When the lifting camera is entangled by branches and cannot be freed, this solution provides three methods to remove the entanglement of the lifting camera, avoiding damage to the lifting camera and improving the inspection efficiency of the drone;

[0078] 3. Noise detection is used to assist the system in determining and locating the felling location, thus avoiding ineffective flight of drones and improving the inspection efficiency of drones. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 is a method flow chart of a forestry resource protection method according to an embodiment of the present invention;

[0080] Figure 2 is a method flow chart of a method for acquiring ground image information according to an embodiment of the present invention;

[0081] Figure 3 is a method flow chart of a method for controlling a lifting camera according to an embodiment of the present invention;

[0082] Figure 4 is a method flow chart of the alternate use method of the lifting camera according to an embodiment of the present invention;

[0083] Figure 5 The method flow of the lifting camera to disentangle the embodiment of the present invention is Figure 1 ;

[0084] Figure 6 The method flow of the lifting camera to disentangle the embodiment of the present invention is Figure 2 ;

[0085] Figure 7 It is a method flow chart of the noise-assisted positioning method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0086] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0087] The embodiment of the present application discloses a forestry resource protection method. A drone is used to patrol the sky above the forest area, and the felling position of the felling personnel is located according to the escape of the flock of birds and the noise situation. At the felling position, the lifting camera adopts different shooting methods according to the lushness of the trees. During the process of the lifting camera completing the shooting and recovering, if the lifting camera is entangled by branches, the system can adopt targeted methods according to different situations to free the lifting camera.

[0088] Reference Figure 1 , a forestry resource protection method includes the following steps.

[0089] S100: Acquire environmental image information above the trees in a preset patrol area.

[0090] The patrol area is the artificially set patrol range of the drone. The forest area is divided into multiple areas, and multiple drones are set up. Each drone patrols within a fixed area to maximize the patrol efficiency and enable the drone to reach the designated location as quickly as possible.

[0091] Environmental image information refers to images above the forest area. The drone patrols back and forth over the forest area and obtains images above the forest area through the drone's built-in camera.

[0092] S101: judging whether there is a flock of birds escaping based on the comparison between the environmental image information and the preset flock of birds escaping model.

[0093] The bird flock escape model is generated by a neural network model, which simulates the image of a flock of birds flying up from the trees and escaping. The bird flock escape model applies existing technology and will not be elaborated here.

[0094] Compare the image of the sky above the trees taken by the drone camera with the bird flock escape model. If there is a flock of birds in the environmental image information, it means that there is a flock of birds escaping. When there is a flock of birds escaping, it means that there may be an abnormal situation at the location where the birds escaped, causing the birds to be startled, for example, someone is cutting down trees and making a lot of noise or there are birds and animals hunting, etc. By capturing the situation of the flock of birds escaping, it is possible to preliminarily determine whether there are people cutting down trees.

[0095] S102: If so, determine the escape location of the flock of birds according to the environmental image information and the flock of birds escape model, and obtain ground image information at the flock of birds escape location.

[0096] The escape position of the flock of birds refers to the original location of the flock of birds. After being frightened, the flock of birds takes off and escapes from the location of the flock of birds. The escape position of the flock of birds can be obtained from the environmental image information.

[0097] After the UAV analyzes the escape location of the flock of birds, the system first controls the UAV to fly to the escape location of the flock of birds, and then checks the escape location of the flock of birds.

[0098] The ground image information is an image of the ground corresponding to the location where the flock of birds escaped. When the drone flies to the location where the flock of birds escaped, it takes a picture of the ground at the location where the flock of birds escaped. If there are people illegally cutting down trees at the location where the flock of birds escaped, the ground image information may contain people who are illegally cutting down trees.

[0099] If there are no birds escaping, the drone will continue its patrol.

[0100] S103: Determine the personnel features and the personnel feature positions according to the comparison between the ground image information and the preset personnel feature database, and scan the personnel features at the personnel feature positions to obtain scanned image information.

[0101] The personnel feature database is a manually set database used for cameras to identify personnel. The personnel feature database is a technology well known to those skilled in the art and will not be described in detail here.

[0102] When there are people who are illegally cutting trees at the location where the flock of birds escapes, by comparing the ground image information with the person feature database, the person features and the person feature position can be obtained from the ground image information. The person feature position is the position where the person is standing and is the precise position of the person within the forest area.

[0103] The scanning image information is the image information obtained by the scanning camera installed on the drone when scanning a person. After determining the person's features and the position of the person's features, the system will control the scanning camera to perform a full body scan of the person's features at the position of the person's features. The scanning image information includes the tools held by the person.

[0104] S104: Determine whether the person's features are those of an illegal felling person based on a comparison between the scanned image information and a preset felling tool database.

[0105] The felling tool database is a manually set database, including images of various felling tools, which will not be described here. By matching and comparing the scanned image information with the felling tool database, the tools carried by the person can be obtained. If the tools carried by the person are felling tools, the person's characteristics can be determined as illegal felling personnel. If the tools carried by the person are mountaineering or other tools, the person's characteristics are ordinary personnel.

[0106] S1041: If yes, upload the personnel's characteristic location and issue an alarm.

[0107] If the personal characteristics are determined to be those of an illegal logger, the system will upload the personal characteristics to the background system at the location of the personal characteristics in the forest area through a drone, and issue an alarm to notify patrol personnel to patrol at the location of the personal characteristics.

[0108] S1042: If not, control the preset UAV to reset and continue patrolling.

[0109] If the individual is determined to be an ordinary person, the drone will return to its initial position and continue patrolling the forest area.

[0110] Reference Figure 2 , the method for obtaining ground image information includes the following steps:

[0111] S200: Acquire forest growth image information at the location where the flock of birds escapes.

[0112] The tree growth image information refers to the image information of the trees at the location where the flock of birds escaped. The tree growth image information is obtained through the camera built into the drone.

[0113] S201: Rating the lushness of tree leaves based on the tree growth image information, and outputting the lushness level.

[0114] When the camera captures ground image information at the location where the flock of birds escapes, the camera's view may be blocked by leaves, making it impossible to obtain ground image information well.

[0115] Whether the camera will be blocked is determined by the tree's lushness level. The higher the lushness level, the more leaves there are on the trees, and the wider the camera will be blocked.

[0116] Before obtaining ground image information, it is necessary to determine the lushness level of the forest to determine how to obtain ground image information.

[0117] S202: Determine whether the luxuriant degree level falls within a preset covering level range.

[0118] The coverage level range is a manually set value used to measure whether trees will affect the camera's shooting of the ground. I will not go into details here. If the lushness level of the forest is within the coverage level range, it means that the lushness of the forest is high, with more leaves, and the camera cannot directly shoot the ground through the leaves.

[0119] If the forest lushness level is not within the coverage level range, it means that the forest lushness level is low and there are fewer leaves, so the camera can directly shoot the ground through the leaves.

[0120] S2021: If it does not fall into the range, the shooting gap position is obtained according to the forest growth image information.

[0121] The shooting gap position refers to the gap between the leaves of the trees, which can be used by the drone's camera to shoot the ground. When the lushness level of the trees is not within the coverage level range, it means that there are more gaps between the leaves of the trees for the camera to shoot. The shooting gap position can be obtained from the tree growth image information. The shooting gap position is the largest gap in the tree growth image information.

[0122] S20211: Photograph the ground at a shooting gap position and output ground image information.

[0123] After determining the shooting gap position, the system can control the drone to descend to the shooting gap position, and control the camera on the drone to shoot the ground through the shooting gap position.

[0124] S2022: If it falls into the range, the forest growth image information is gridded, and the leaf content information in each grid is compared, and the selected grid with the least leaf content information is output and located.

[0125] When the lushness level of the forest falls within the coverage level range, the leaves of the trees are dense and the drone cannot directly shoot the ground. At this time, it is necessary to find a location in the tree with relatively fewer leaves.

[0126] By gridding the forest growth image information and comparing the forest content in each grid, the position with the least leaves in the forest growth image information can be determined. The grid corresponding to the position with the least leaves in the forest growth image is the selected grid.

[0127] S20221: Determine the descending position in the forest growth image information based on the selected grid.

[0128] The descending position is the position with the least leaves in the forest growth image information. The descending position can be determined by selecting the position of the grid in the forest growth image information.

[0129] S20222: Control a preset lifting camera to descend at the descending position and shoot through the leaves to output ground image information.

[0130] When the trees are densely populated and the camera cannot directly shoot, it is necessary to find the location with the least leaves in the forest growth image information. At this location, the drone releases the lifting camera downward through the traction line. The lifting camera can pass through the location with the least leaves to shoot the ground.

[0131] Reference Figure 3 , the control method of the lifting camera includes the following steps:

[0132] S300: Get the preset vertical straight-line distance between the drone and the lifting camera.

[0133] Since the lifting camera is separated from the drone, the battery level of the lifting camera needs to be considered when using it. The vertical straight-line distance is the distance between the drone and the lifting camera, which is measured by the rangefinder set at the bottom of the drone. The vertical straight-line distance can be used to measure whether the lifting camera is connected to the drone.

[0134] S301: Determine the independent power supply type or the UAV power supply type according to the comparison between the vertical straight-line distance and the preset reference distance.

[0135] In this embodiment, the lifting camera has two power supply forms. The first is independent power supply. The lifting camera has its own power supply, and the power supply can power the lifting camera. The second is to power the drone. The drone itself has a power supply. When the lifting camera is connected to the bottom of the drone, the contacts on the top of the lifting camera can contact the contacts at the bottom of the drone, and the drone can charge the lifting camera. In actual use, if the lifting camera is connected to the drone, the drone is powered at this time. If the lifting camera is separated from the drone, it is powered independently at this time.

[0136] The reference distance is a fixed value set manually, which refers to the distance when the lifting camera is connected to the drone. It will not be elaborated here.

[0137] If the vertical straight-line distance is consistent with the reference distance, it means that the elevating camera is connected to the drone, and the elevating camera is now charged through the drone.

[0138] If the vertical straight-line distance is inconsistent with the reference distance, it means that the drone has released the lifting camera and the lifting camera is shooting the ground. At this time, the lifting camera is powered by its own independent power supply.

[0139] S302: Based on the power supply type of the drone, control the contacts of the lifting camera to be connected with the base contacts of the drone, so that the drone can power the lifting camera.

[0140] If the drone needs to charge the lifting camera, the lifting camera needs to be recovered and the contacts of the lifting camera connected to the contacts of the base of the drone. At this time, the lifting camera cannot be released for shooting and can only be connected to the drone for shooting.

[0141] S303: Based on the independent power supply type, before the elevating camera descends, obtain the battery power of the elevating camera.

[0142] When the elevating camera is released and starts shooting, it can only be powered by an independent power supply and cannot be powered by the drone. Before releasing the elevating camera, you need to get the battery power of the elevating camera first. The elevating camera can only shoot when the battery power is sufficient.

[0143] S304: Determine, based on a comparison between the battery power level and a preset low power level, whether to continue charging with power supplied by the drone or to charge the lifting camera with a preset independent power source carried by the drone and lower it for shooting.

[0144] If the battery level is lower than the low level, the lifting camera cannot be released and can only be connected to the drone to continue charging. When the battery level is higher than the low level, the lifting camera can be charged through its own independent power supply and descend to shoot.

[0145] Reference Figure 4 The drone is equipped with two lifting cameras, both of which can be released for shooting. The two lifting cameras are used alternately. During normal operation, only one of the lifting cameras is used, and the other is used as a backup. The method for alternating the use of the lifting cameras includes the following steps:

[0146] S400: Before the elevating cameras are lowered, the remaining power of the two elevating cameras is respectively obtained.

[0147] When it is necessary to release the lifting camera to perform shooting, it is necessary to first determine the remaining power of the two lifting cameras and use the lifting camera with more remaining power to work.

[0148] S401: Compare the remaining power to determine the working camera and the backup camera.

[0149] The remaining power is used to determine which lifting camera to use. The camera with more remaining power is the working camera, which will be used for shooting. The camera with less remaining power is the backup camera, which is used as a backup to replace the working camera when the power is low.

[0150] S402: Control the backup camera to continue charging using the drone power supply type, control the working camera to be powered by an independent power supply type and descend to a preset shooting height for shooting, and obtain the available power and camera position of the working camera in real time.

[0151] Since the backup camera does not need to be released, it is connected to the drone and charged by the drone. The working camera works with an independent power supply. In order to ensure that the working camera works normally and is not prone to sudden power failure during shooting, the available power of the working camera needs to be monitored in real time. When the available power is low, the working camera needs to be replaced by the backup camera, and the backup camera needs to reach the same position as the working camera. In order to ensure that the backup camera can reach the same position as the working camera, the working camera needs to mark its camera position before recycling, and adjust the backup camera according to the camera position.

[0152] S403: Determine whether the working camera should continue shooting or be reset and replaced based on the comparison between the available power and the preset charging power.

[0153] The charging capacity is an artificially set reference value, which is used to measure the standard for the lifting camera to continue working. It will not be elaborated here.

[0154] When the available power is lower than the charging power, the working camera needs to be reset and charged by the drone, and the backup camera replaces the working camera.

[0155] When the available power is not less than the charging power, the working camera can continue to work.

[0156] S404: Based on the reset replacement, the working camera is controlled to be reset and charged using the drone power supply type, and the backup camera is controlled to be powered by an independent power supply type and moved to the camera position for shooting.

[0157] After the working camera and the backup camera are replaced, since the working camera is connected to the drone, the working camera is charged through the drone, while the backup camera is powered by an independent power supply since it is separated from the drone.

[0158] Reference Figure 5 The lifting camera is easily entangled by branches during the recovery process. The method for removing the branches from the lifting camera includes the following steps:

[0159] S500: Control the lifting camera to lift upward after a preset shooting time, and continuously obtain the traction tension of the preset traction line during the lifting process.

[0160] The shooting time is a manually set reference value, and the lifting camera can complete the acquisition of ground image information within the shooting time.

[0161] The lifting camera is connected to the drone via a traction line. By retracting the traction line, the lifting camera can rise and return to the state connected to the drone.

[0162] The traction force refers to the pulling force of the traction line on the lifting camera. By continuously obtaining the traction force and analyzing it, it is possible to determine whether there is a problem with the lifting camera during the ascent process.

[0163] S501: Determine whether to continue lifting or to be entangled in a tree based on a comparison of two adjacent traction forces.

[0164] Under normal conditions, the traction force is equal to the gravity of the lifting camera. At this time, the lifting camera can easily detach from the leaves and return to the state of being connected to the drone. When the traction force is greater than the lifting camera and the traction force gradually increases, it means that the lifting camera may be entangled by branches during the lifting process, making it unable to continue to rise. By comparing whether the two consecutive traction forces are consistent, it can be determined whether the camera is entangled.

[0165] S502: Based on the continued lifting, the lifting camera is controlled to reset and the ground image information is processed.

[0166] When the lifting camera is not entangled by the branches and can successfully get out of the branches in the lowered position, the lifting camera can be reset and connected to the drone. At this time, the system can process the ground image information taken by the lifting camera.

[0167] S503: Based on the tree entanglement, determine brute force lifting or adjusted lifting according to the comparison between the traction tension and the preset safety tension.

[0168] The safety tension is the tension that the traction line can withstand. When the traction line is subjected to a certain amount of tension exceeding the safety tension, the traction line breaks. The safety tension is obtained by artificial measurement of the traction line and will not be described in detail here.

[0169] By comparing the traction force and the safety force, when the drone applies force to the traction line, if the traction force is less than the safety force, the lifting camera can be detached, and the lifting camera is lifted by brute force. If the lifting camera still does not detach when the traction force is increased to the safety force, it cannot be lifted by brute force, but the position of the lifting camera is adjusted to detach the lifting camera.

[0170] S504: Based on brute force lifting, the drone is controlled to pull the traction line until the lifting camera is untangled.

[0171] When lifting by brute force, the traction line is pulled by controlling the drone, and the traction force value is obtained in real time during the pulling process to prevent the traction force from exceeding the safe tension until the camera is untangled.

[0172] S505: Based on the adjusted lift, the drone is controlled to move horizontally according to a preset adjustment path, and the inclination angle of the traction line is obtained in real time.

[0173] The adjustment path is a manually set movement path of the UAV, which will not be described in detail here. When the UAV moves along the adjustment path, if there is no tree blocking the lifting camera, the lifting camera can move synchronously with the UAV under the action of the traction line.

[0174] The tilt angle is the angle of the traction line. When the lifting camera is not blocked, the traction line has a tilt angle of 90° and is in a vertical state. When the lifting camera is blocked, the drone continues to move while the lifting camera stops moving, and the traction line will tilt.

[0175] S506: Determine whether to continue moving forward or return to the original path according to the comparison relationship between the tilt angle and the preset reference angle.

[0176] The reference angle is a standard value set manually, which is 90° in this embodiment and will not be described in detail here.

[0177] During the movement and adjustment process, the drone compares the tilt angle with the reference angle in real time. If the tilt angle is inconsistent with the reference angle, it means that the lifting camera is blocked and the movement direction of the drone cannot free the lifting camera. At this time, the drone returns to the original path and readjusts the direction according to the adjustment path. If the tilt angle is always consistent with the reference angle, it means that the lifting camera is not blocked when moving in that direction and can move in that direction to get out of trouble.

[0178] S507: Based on continuing to move forward, control the lifting camera to lift upward, and determine to continue lifting according to the comparison between the traction pulling force and the safety pulling force until the entanglement is released or reset and continue to move forward.

[0179] When the lifting camera is adjusted, the lifting camera is lifted at the same time. If the lifting camera is not blocked at this time, the winding can be released. If the winding still cannot be released, the lifting camera is reset and the position is adjusted again.

[0180] If the above method still fails to free the lifting camera, use the wire breaking method to untangle it. The wire breaking method will not be described here and will be described in detail in the subsequent steps.

[0181] Reference Figure 6 When the entanglement of the lifting camera cannot be released by adjusting the position of the drone, the method for releasing the entanglement of the branches by the lifting camera also includes the following steps:

[0182] S600: After a preset escape time, obtaining the extension length of the traction line.

[0183] The escape time is an artificially set reference value, which is the time provided by the system for the lifting camera to escape through brute force lifting and adjustment lifting. It will not be elaborated here.

[0184] During the escape time, the lifting camera escapes and rises a certain distance. The extension length is the length of the traction line extending from the drone, which is also the distance between the drone and the lifting camera. The extension length is obtained by measuring the length of the traction line by the drone.

[0185] S601: Determine whether the extension length of the traction line is greater than a preset escape distance.

[0186] The escape distance is a reference value set manually based on the actual distance between the drone and the trees. It will not be elaborated here. The escape distance is used to measure whether the lifting camera is escaped.

[0187] If the extension length of the traction line is greater than the escape distance, it means that the lifting camera is still not entangled. If the extension length of the traction line is not greater than the escape distance, it means that the lifting camera has escaped from the branches of the tree.

[0188] S602: If and only if it is greater than, obtain the landing height between the lifting camera and the ground.

[0189] When the extension length of the traction line is greater than the escape distance, it means that neither brute force lifting nor adjustment lifting can solve the problem. At this time, the traction line is cut to make the lifting camera fall to the ground and the lifting camera is recovered. When using the above method, it is necessary to first obtain the distance between the lifting camera and the ground so that the lifting camera can fall to the ground smoothly and safely.

[0190] The landing height is the distance between the lifting camera and the ground, which is obtained by a rangefinder set on the lifting camera.

[0191] S603: Control the drone to extend the traction line at the landing height, and determine whether the traction force is 0.

[0192] After determining the landing height, the drone extends the traction line according to the landing height, allowing the lifting camera to move downward until the lifting camera lands on the ground.

[0193] By judging the magnitude of the traction force, it can be determined whether the lifting camera has fallen to the ground.

[0194] S6031: If not 0, continue landing.

[0195] If the lifting camera is still suspended in the air, the traction force is still equal to the gravity of the lifting camera, and the traction force is not 0. At this time, the traction line continues to be extended.

[0196] S6032: If it is 0, control the preset cutting device to cut the traction line, mark the landing position of the lifting camera, and upload the marked position.

[0197] The cutting device is arranged on the bottom surface of the UAV, and the UAV can control the cutting device, and the cutting device is used to cut the traction line.

[0198] If the traction force is 0, it means that the lifting camera has fallen on the ground, and the traction line has no pulling force on the lifting camera. At this time, the traction line is cut by the cutting device, and the lifting camera can fall on the ground. When the lifting camera falls on the ground, the system marks the landing point of the lifting camera and uploads it to the system background. The system can prompt the inspection personnel to recycle the lifting camera.

[0199] Reference Figure 7 , by monitoring the noise, the felling position of the felling personnel is assisted in positioning, and the noise assisted positioning method includes the following steps:

[0200] S700: In the process of obtaining environmental image information in the inspection area, environmental noise information is simultaneously obtained multiple times.

[0201] Environmental noise information refers to the noise generated within the forest area. Environmental noise information may include the noise generated when tools cut down trees, or the roar of animals. Environmental noise information is received by the sonar device installed on the drone.

[0202] When receiving the environmental noise information, the form of continuous multiple reception is adopted. If it is the noise generated during felling, the environmental noise information is continuous, and if it is the roar of animals, the environmental noise information is a single noise.

[0203] S701: Determine whether the environmental noise information obtained multiple times is consistent.

[0204] By judging the consistency of the environmental noise information obtained for multiple times, it is determined whether the environmental noise information is the noise during felling.

[0205] S702: If they are consistent, the circumferential noise intensity is obtained according to the environmental noise information analysis.

[0206] If they are inconsistent, it means that the noise may not be the noise generated when cutting down trees. Only when the environmental noise information obtained multiple times is consistent, the environmental noise information is analyzed. The circumferential noise intensity is the intensity of the noise received by the drone. The drone is equipped with sonars around it, which can receive the sound around the drone. If there is noise information, the noise intensity in one direction is larger, and the noise intensity in other directions is smaller. By analyzing the environmental noise information, the circumferential noise intensity can be determined.

[0207] S703: Determine the noise direction according to the circumferential noise intensity.

[0208] The noise direction is the direction corresponding to the position with the maximum sound intensity in the circumferential noise intensity. The direction with the maximum noise intensity can be determined from the circumferential noise intensity, thereby determining the noise direction.

[0209] S704: Determine whether the direction of the noise is consistent with the direction of the escape position of the flock of birds.

[0210] By comparing the noise direction and the location where the flock of birds escaped and judging their consistency, it is possible to determine whether there are people conducting felling activities at the location where the flock of birds escaped.

[0211] S7041: If they match, control the drone to patrol the location where the flock of birds escaped.

[0212] If the two directions are consistent, it means that there is a high probability that illegal personnel are cutting down trees at the location where the birds escaped. At this time, the system controls the drone to patrol the location where the birds escaped.

[0213] S7042: If they are inconsistent, control the drone to move according to the noise direction and locate the noise source.

[0214] If the two directions are inconsistent, it means that there may be no felling at the location where the birds escaped, and other objects may have alarmed the birds. At this time, refer to the noise direction, control the drone to move according to the noise direction and locate the location of the noise source, which may be felling.

[0215] Based on the same inventive concept, an embodiment of the present invention provides a forestry resource protection system, including:

[0216] An acquisition module is used to acquire environmental image information above the trees, ground image information, scanned image information, tree growth image information, vertical straight-line distance, battery power of the lifting camera, remaining power, available power, camera position, traction tension of the traction line, extension length of the traction line, and environmental noise information;

[0217] A memory for storing a program of a forestry resource protection method;

[0218] The program in the memory can be loaded and executed by the processor to implement a forestry resource protection method.

[0219] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0220] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed by a forestry resource protection method.

[0221] Computer storage media include, for example, USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical disks, and other media that can store program codes.

[0222] Based on the same inventive concept, an embodiment of the present invention provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes a forestry resource protection method.

[0223] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0224] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for protecting forest resources, characterized in that: include: Obtain environmental image information above the trees in the preset patrol area; Determine whether there is a flock of birds escaping based on the comparison between the environmental image information and the preset flock of birds escaping model; If it exists, determine the escape location of the flock of birds according to the environmental image information and the flock of birds escape model, and obtain ground image information at the flock of birds escape location; Determine the personnel features and the personnel feature positions according to the comparison between the ground image information and the preset personnel feature database, and scan the personnel features at the personnel feature positions to obtain scanned image information; Determine whether the person's characteristics are those of an illegal felling person based on the comparison between the scanned image information and a preset felling tool database; If yes, then upload the personnel’s characteristic location and issue an alarm; If not, the preset drone is controlled to reset and continue patrolling; The method for acquiring ground image information comprises: Obtain forest growth image information at the location where the flock of birds escapes; Rating the lushness of tree leaves according to the tree growth image information and outputting the lushness level; Determine whether the luxuriant degree level falls within the preset covering level range; If it does not fall into the range, the shooting gap position is obtained according to the forest growth image information; Shooting the ground at the shooting gap position and outputting ground image information; If it falls into the grid, the forest growth image information is gridded, and the leaf content information in each grid is compared, and the selected grid with the least leaf content information is output and located; Determine the descending position in the forest growth image information according to the selected grid; At the descending position, a preset lifting camera is controlled to descend and shoot through leaves to output ground image information; Also includes: Control the lifting camera to lift upward after a preset shooting time, and continuously obtain the traction force of the preset traction line during the rising process; The comparison of two consecutive pulling forces is used to determine whether the lift will continue or the tree will be entangled; Based on the continued lifting, the lifting camera is controlled to reset and the ground image information is processed; Based on the tree entanglement, brute force lifting or adjusted lifting is determined according to the comparison between the pulling force and the preset safety force; Based on brute force lifting, the drone is controlled to pull the traction line until the lifting camera is untangled; Based on the adjusted lift, the drone is controlled to move horizontally with a preset adjustment path, and the tilt angle of the traction line is obtained in real time; Determine whether to continue moving forward or return to the original path according to the comparison relationship between the tilt angle and the preset reference angle; Based on continuing to move forward, the lifting camera is controlled to lift upward, and based on the comparison between the traction pulling force and the safety pulling force, it is determined to continue lifting until the entanglement is released or reset and continue to move forward.

2. A forestry resource protection method according to claim 1, characterized in that: The control method of the lifting camera includes: Get the preset vertical straight-line distance between the drone and the lifting camera; Determine the independent power supply type or the UAV power supply type based on the comparison between the vertical straight-line distance and the preset reference distance; Based on the power supply type of the drone, the contacts for controlling the lifting camera are connected to the contacts of the base of the drone, so that the drone can power the lifting camera; Based on the independent power supply type, before the elevating camera descends, obtain the battery power of the elevating camera; According to the comparison between the battery power and the preset low power, it is determined whether to continue charging with the power of the drone or to charge the lifting camera with the preset independent power supply carried by itself and descend for shooting.

3. A forestry resource protection method according to claim 2, characterized in that: The number of the lifting cameras is two, and the method for alternately using the lifting cameras includes: Before the lifting cameras descend, respectively obtain the remaining power of the two lifting cameras; Compare remaining power to determine working and backup cameras; Control the backup camera to continue charging using the drone power supply type, control the working camera to use an independent power supply type and descend to the preset shooting height for shooting, and obtain the available power and camera position of the working camera in real time; According to the comparison between the available power and the preset charging power, it is determined whether the working camera continues to shoot or is reset and replaced; Based on reset replacement, the working camera is controlled to reset and charge using the drone power supply type, and the backup camera is controlled to be powered by an independent power supply type and moved to the camera position for shooting.

4. A forestry resource protection method according to claim 1, characterized in that: Also includes: After a preset escape time, the extension length of the traction line is obtained; Determine whether the extension length of the traction line is greater than the preset escape distance; If and only if it is greater than, obtain the landing height between the lifting camera and the ground; Control the drone to extend the traction line at the landing height and determine whether the traction force is 0; If it is not 0, continue to land; If it is 0, control the preset cutting device to cut the traction line, mark the landing position of the lifting camera, and upload the marked position.

5. A forestry resource protection method according to claim 1, characterized in that: Also includes: In the process of obtaining environmental image information in the patrol area, environmental noise information is obtained multiple times simultaneously; Determine whether the environmental noise information obtained multiple times is consistent; If they are consistent, the circumferential noise intensity is obtained based on the environmental noise information analysis; Determine the noise direction based on the circumferential noise intensity; Determine whether the direction of the noise is consistent with the direction of the escape location of the flock of birds; If they match, the drone is controlled to patrol the location where the flock of birds escaped; If they are inconsistent, the drone is controlled to move according to the direction of the noise and locate the noise source.

6. A forestry resource protection system, characterized in that: include: An acquisition module is used to acquire environmental image information above the trees, ground image information, scanned image information, tree growth image information, vertical straight-line distance, battery power of the lifting camera, remaining power, available power, camera position, traction tension of the traction line, extension length of the traction line, and environmental noise information; A memory for storing a program of a forestry resource protection method according to any one of claims 1 to 5; The program in the processor and the memory can be loaded and executed by the processor to implement a forestry resource protection method as described in any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and executes a forestry resource protection method as claimed in any one of claims 1 to 5.

8. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes a forestry resource protection method as claimed in any one of claims 1 to 5.

Images