Under-forest ginseng protection system

Abstract

The invention relates to the technical field of security and protection monitoring, in particular to an under-forest parameter protection system, which is characterized in that a data acquisition module provides basic data for a target identification module, the target identification module identifies data of the data acquisition module based on a deep learning model, and an identification result guides a decision analysis module to make a strategy; the instruction of the decision analysis module drives the execution control module to perform targeted driving operation, the execution control module executes the driving operation and feeds back the execution state to the monitoring feedback module, and the monitoring feedback module returns optimization information to other modules to promote continuous improvement and optimization of the whole system. According to the system provided by the invention, through efficient cooperation and close interaction of all the modules, precise identification and effective response to damage factors of the growth environment of the ginseng are realized, and the safety of the growth environment of the ginseng is guaranteed.

Description

Technical Field

[0001] This invention belongs to the field of security monitoring technology, and in particular relates to a forest ginseng protection system. Background Technology

[0002] Ginseng has demanding requirements for its growing environment. It thrives in forests with a canopy density of 0.7-0.8, requires fertile, well-drained soil, and has a long growth cycle, generally taking 5-6 years to harvest. During its long growth process, ginseng's growing environment is highly vulnerable to threats such as animal damage and theft.

[0003] Currently, in monitoring animal invasion in ginseng cultivation areas, some growers use physical fences to prevent wild boars and other animals from entering. While physical fences can deter animals to some extent, they have many limitations. In addition, some areas use sound-based animal deterrent devices, which play the sounds of natural predators or irritating noises at regular intervals to drive away animals. However, this method has problems such as a limited range of deterrence and the ease with which animals can adapt, and its effectiveness gradually weakens over time. At the technical monitoring level, early solutions involved using infrared sensors to monitor animal activity. When an animal passed through the infrared sensing area, the device would be triggered and issue an alarm. However, this method could only detect animal activity signals and could not accurately identify the species and behavior of the animal, resulting in a high false alarm rate. Furthermore, it could not provide effective early warning or targeted handling of animal intrusions. To prevent human theft, a common method is to install ordinary surveillance cameras in ginseng planting areas. Growers periodically review the footage to detect anomalies, but this passive monitoring method cannot provide real-time alerts; by the time theft is discovered, losses have often already occurred. Some planting areas have experimented with electronic fence alarm systems, which trigger an alarm when someone illegally climbs over the fence. However, these systems can only monitor boundary intrusions and cannot identify or assess the behavior of individuals entering the planting area. Therefore, they are ineffective in preventing thieves who enter the area without breaching the fence. The existing technical solutions mentioned above have certain shortcomings in preventing threats to ginseng's growth environment, and there is an urgent need for more advanced and intelligent detection and protection methods based on target recognition algorithms. Summary of the Invention

[0004] In view of this, the present invention aims to provide a forest ginseng protection system, which mainly covers five core modules: data acquisition, target identification, decision analysis, execution control, and monitoring feedback. These modules cooperate with each other and work together efficiently to build a complete and intelligent protection system. In addition, the present invention uses a deep learning model to accurately distinguish intrusion targets. By analyzing the shape and movement trajectory of the intrusion target, the intrusion target can be quickly located, avoiding false alarms from infrared sensors and solving the problem that traditional image recognition cannot distinguish the identity of personnel.

[0005] To achieve the above objectives, the technical solution created by this invention is implemented as follows: A ginseng protection system includes: a data acquisition module for acquiring the location and category range of invasive targets in the ginseng planting area, photographing the invasive targets, and collecting environmental information in the ginseng planting area; a target recognition module for receiving the target images acquired by the data acquisition module and recognizing the target images based on a deep learning model, combined with the category range determined by the data acquisition module; a decision analysis module for receiving the recognition results from the target recognition module and providing targeted decisions to drive away the invasive targets based on the recognition results, combined with the environmental information collected by the data acquisition module and the movement trajectory of the invasive targets; an execution control module for executing corresponding driving actions on the invasive targets based on the targeted decisions; and a monitoring feedback module for collecting all information from the data acquisition module, target recognition module, decision analysis module, and execution control module to form a complete log of ginseng protection and adjusting the data acquisition module, target recognition module, decision analysis module, and execution control module based on the complete log.

[0006] Furthermore, the data acquisition module includes a vibrating optical fiber, a camera matrix, sound sensors, and a control unit. The vibrating optical fiber is laid underground in the ginseng planting area and connected to an optical fiber modem. The modem emits incident light into the vibrating optical fiber. When an intruding target enters the ginseng planting area, the target causes the vibrating optical fiber to vibrate, changing the phase of the scattered light within it. The changed beam returns to the modem for demodulation, restoring the vibration signal. This vibration signal is input to the control unit to obtain the target's category, range, and location. The camera matrix includes multiple cameras distributed in a matrix within the ginseng planting area. The control unit controls the cameras at the corresponding locations to capture images of the intruding target, then transmits the captured images to the target recognition module. Sound sensors are distributed in a matrix within the ginseng planting area. These sensors collect sounds generated in the ginseng planting area and transmit the resulting sound signals to the control unit, which then forwards the sound signals to the decision analysis module.

[0007] Furthermore, the control unit has a vibration acoustic signature database. The control unit compares the received vibration information with the vibration information in the vibration acoustic signature database to obtain the category range of the intrusion target.

[0008] Furthermore, the target recognition module calls a YOLOv8-based category recognition model to identify the target image based on the category range: when the category range is human, the target recognition module calls the corresponding category recognition model to identify the items carried by the intruding target; when the category range is animal that damages the ginseng planting area, the target recognition module calls the corresponding category recognition model to identify the eyes of the intruding target.

[0009] Furthermore, the decision analysis module's analysis process includes: when the category is human, the target recognition module identifies the category of the items carried by the intruding target, and combines the location and sound information of the intruding target collected by the data acquisition module: if the category of the items carried by the intruding target belongs to the tools for picking ginseng, and the intruding target's movement trajectory is concentrated in the ginseng planting area, and the sound information is determined to be the sound of digging and damaging ginseng, then the intruding target is determined to be a thief, and a decision is made against the thief; when the category is animal damaging the ginseng planting area, the location information of the intruding target is combined: if the intruding target's position remains unchanged within a preset time, and the sound information is determined to be the sound of digging and damaging ginseng, then the intruding target is determined to be an intruding animal. At this time, the eye position of the intruding animal is calculated based on the eye recognition results of the intruding animal, and a decision is made against the intruding animal based on the eye position.

[0010] Furthermore, the execution control module includes an alarm system, drones, a route prediction unit, and laser cannons arrayed throughout the ginseng planting area. Decisions made by the execution control module regarding thieves include: activating the alarm system to notify guards that thieves have entered the ginseng planting area and are damaging the ginseng; simultaneously, activating drones to track the thieves based on their location and transmitting the captured images to the guards' terminal devices; and transmitting the thieves' location in real-time to the route prediction unit, which predicts the thieves' escape route and transmits the escape route to the terminal devices. Decisions made by the execution control module regarding invasive animals include: activating the alarm system to notify guards that invasive animals have entered the ginseng planting area and are damaging the ginseng; simultaneously, activating the laser cannons in the corresponding area to illuminate the invasive animals' eyes, causing temporary blindness and thus driving them away.

[0011] Compared with the prior art, the present invention can achieve the following beneficial effects: (1) The forest ginseng protection system described in this invention adopts a modular design, clearly dividing functions such as data acquisition, target identification, decision analysis, execution control, and monitoring feedback. Each module has a clear responsibility and works closely together to form a closed-loop collaborative mechanism. This structure avoids functional redundancy, simplifies the overall system architecture, and ensures smooth data flow between modules, improving system response speed and overall operating efficiency. In addition, the system provided by this invention achieves automated operation from data acquisition to target processing, without the need for real-time manual intervention. For example, after target identification, the corresponding strategy is automatically triggered, the execution control module automatically starts the equipment, and the monitoring feedback module automatically records and optimizes the strategy. Staff only need to perform regular equipment maintenance and data viewing, which greatly facilitates operation and reduces labor costs and operational difficulty. (2) The forest ginseng protection system created by this invention reduces reliance on manual patrols and lowers labor costs through automated monitoring and protection mechanisms. In addition, the system has a strategy optimization function, that is, the monitoring feedback module adjusts the data acquisition module, target identification module, decision analysis module and execution control module based on complete logs, which improves equipment utilization efficiency, reduces unnecessary energy consumption and equipment wear and tear, thereby reducing the long-term operating cost of the system. At the same time, accurate target identification and processing reduce resource waste caused by misoperation and further control costs. In addition, the target identification module adopts a high-precision algorithm with an identification accuracy of ≥90%, which can quickly detect potential threats. The decision analysis module can call the corresponding strategy in real time, and the execution control module can quickly start the equipment response, such as laser cannons to quickly drive away invading animals and drones to track thieves in time. The whole process is short from the discovery of the target to the implementation of measures, which greatly improves the protection efficiency of the ginseng growth environment and reduces the risk of loss. Attached Figure Description

[0012] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of the forest ginseng protection system described in an embodiment of the present invention. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not constitute a limitation thereof.

[0014] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0015] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0016] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0017] The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0018] like Figure 1 As shown in the embodiment of the present invention, the forest ginseng protection system includes a data acquisition module, a target identification module, a decision analysis module, an execution control module, and a monitoring feedback module. The data acquisition module acquires the location and category range of invading targets in the ginseng planting area, photographs the invading targets, and collects environmental information from the ginseng planting area. The target identification module receives the target images acquired by the data acquisition module and, based on the category range determined by the data acquisition module, identifies the target images using a deep learning model. The decision analysis module receives the identification results from the target identification module and, based on the identification results, the environmental information collected by the data acquisition module, and the movement trajectory of the invading targets, provides targeted decisions to drive away the invading targets. The execution control module executes corresponding driving actions on the invading targets based on the targeted decisions. The monitoring feedback module collects all information from the data acquisition module, target identification module, decision analysis module, and execution control module to form a complete log of ginseng protection and adjusts the data acquisition module, target identification module, decision analysis module, and execution control module based on the complete log.

[0019] In some embodiments, the data acquisition module includes a vibrating optical fiber, a camera matrix, a sound sensor, and a control unit. The vibrating optical fiber is laid underground in the ginseng cultivation area and connected to an optical fiber modem. The modem emits incident light into the vibrating optical fiber. When an intruder invades the ginseng cultivation area, the intruder causes the vibrating optical fiber to vibrate, changing the phase of the scattered light within it. The changed light beam returns to the modem for demodulation, restoring the vibration signal.

[0020] Specifically, the fiber optic modem emits incident light into the vibrating fiber. As the light propagates through the vibrating fiber, it changes due to the fiber's state and the surrounding environment. External vibrations, such as the movement or collision of an intruding target, cause slight deformations in the fiber, altering its propagation characteristics, such as changes in the phase of scattered light. By connecting the vibrating fiber to the modem, the modem emits incident light. During transmission, the light scatters. When changes in the surrounding environment cause a phase change in the scattered light, it returns to the modem and is reconstructed as a vibration signal.

[0021] The control unit incorporates a vibration acoustic signature database. Since vibration signals generated by different vibration scenarios have their own characteristics, the control unit compares the received vibration information with the vibration information in the database to determine the category range of the intrusion target. Specifically, the process of the control unit determining the location and category range of the intrusion target based on the vibration signal involves two calculations: first, the control unit compares the received vibration signal with the vibration signal in the database to obtain the category range of the intrusion target; then, it determines the location of the intrusion target based on the received vibration signal. In this embodiment of the invention, the vibration acoustic signature database directly adopts an existing open-source vibration acoustic signature database.

[0022] The camera matrix comprises multiple camera devices distributed in a matrix within the ginseng cultivation area. The control unit, based on the location of the intruding target, controls the corresponding camera devices to capture images of the target, and then transmits the captured images to the target recognition module. In this embodiment, Hikvision cameras are preferably used, as they feature low-light performance, high resolution, and wide dynamic range. The camera devices perform 24-hour continuous night vision data acquisition and are distributed in a matrix within the ginseng cultivation area, enabling real-time, comprehensive data collection and ensuring accurate capture of the ginseng cultivation area at any time. Image and video data are then transmitted to the target recognition module in real-time.

[0023] Sound sensors are distributed in a matrix in the ginseng planting area. The sound sensors collect the sounds generated in the ginseng planting area and transmit the generated sound signals to the control unit. The control unit then transmits the sound signals to the decision analysis module.

[0024] In this embodiment of the invention, taking advantage of the relatively fixed growth location of ginseng under forest cover, the coordinates of each ginseng plant or patch are recorded using GPS positioning and stored in the management system database. Simultaneously, concealed RFID electronic tags are placed near the ginseng plants to provide accurate references for subsequent monitoring. In this embodiment, the data acquisition module also includes near-field infrared sensors, arranged in an array within the ginseng planting area to detect whether an intruding target is approaching the ginseng and transmit the sensing signal to the decision analysis module.

[0025] In some embodiments, the target recognition module calls a YOLOv8-based category recognition model to recognize the target image according to the category range: when the category range is human, the target recognition module calls the corresponding category recognition model to recognize the items carried by the intruding target; when the category range is animal that damages the ginseng planting area, the target recognition module calls the corresponding category recognition model to recognize the eyes of the intruding target.

[0026] For example, when the intrusion target is specifically a wild boar, a YOLOv8-based category recognition model is used to identify the wild boar's eyes, automatically extracting features such as shape, color, and texture, and determining the location of the eyes. During the training of the category recognition model for wild boar identification, a large number of wild boar images in different scenarios are collected, including daytime, nighttime, different seasons, different lighting conditions, and wild boars in different postures. The eyes in each image are labeled, including the eye's location and bounding box. The image resolution must be high enough to clearly display the detailed features of the wild boar's eyes, ensuring the model can learn comprehensive and accurate feature information, improving its generalization ability, and enabling it to accurately identify wild boar eyes in various complex environments. Similarly, when the category is humans, i.e., the intrusion target is a human, the target recognition module calls the YOLOv8-based category recognition model to identify items carried by the intrusion target, including tools suitable for digging and loading ginseng, such as small shovels and baskets, carried by the human in the target image. In training a category recognition model to identify items carried by intrusion targets, a large number of tool images in different scenarios are collected, including different types, brands, locations, lighting conditions, and postures of the tools. Each tool in the image is labeled with information such as its category and bounding box. The image resolution must be high enough to clearly display the detailed features of the tools, ensuring that the model can learn comprehensive and accurate feature information, improve the model's generalization ability, and enable it to accurately identify tools in various complex environments.

[0027] In some embodiments, the analysis process of the decision analysis module includes: when the category is human, the target recognition module identifies the category of the items carried by the intruding target, and combines the location information and sound information of the intruding target collected by the data acquisition module: if the category of the items carried by the intruding target belongs to the tools for picking ginseng, and the movement trajectory of the intruding target is concentrated in the ginseng planting area, and the sound information is determined to be the sound of digging and damaging ginseng, then the intruding target is determined to be a thief, and a decision is made against the thief; when the category is animal that damages the ginseng planting area, the location information of the intruding target is combined: if the position of the intruding target remains unchanged within a preset time, and the sound information is determined to be the sound of digging and damaging ginseng, then the intruding target is determined to be an intruding animal. At this time, the eye position of the intruding animal is calculated based on the eye recognition result of the intruding animal, and a decision is made against the intruding animal based on the eye position.

[0028] In this embodiment of the invention, the sensing signal from a near-field infrared sensor and the RFID tag can also be combined to determine the intrusion target. That is, when the category is human, the target identification module identifies the category of the items carried by the intrusion target, and combines the location information and sound information of the intrusion target collected by the data acquisition module: if the category of the items carried by the intrusion target belongs to the tools for picking ginseng, and the intrusion target's movement trajectory is concentrated in the ginseng planting area, and at the same time it is determined that the concealed RFID tag has been triggered, the sensing signal is that the intrusion target is approaching the ginseng, and the sound information is the sound of digging and damaging the ginseng, and the location of the intrusion target matches the management system data. If the coordinates of the ginseng undergrowth in the warehouse are used, the intrusion target is determined to be a thief, and a decision is made against the thief. When the category is animals that damage the ginseng planting area, the location information of the intrusion target is combined: if the location of the intrusion target remains unchanged within a preset time, and it is determined that the concealed RFID tag has been triggered, the sensing signal is that the intrusion target is approaching the ginseng, and the sound information is the sound of digging and damaging the ginseng, and the location of the intrusion target matches the coordinates of the ginseng undergrowth in the management system database, then the intrusion target is determined to be an intrusive animal. At this time, the eye position of the intrusive animal is calculated based on the eye recognition results, and a decision is made against the intrusive animal based on the eye position.

[0029] In some embodiments, the execution control module includes an alarm system, a drone, a route prediction unit, and laser cannons arrayed in the ginseng planting area. The execution control module makes decisions regarding thieves, including: activating the alarm system to notify guards that thieves have entered the ginseng planting area and are damaging the ginseng; simultaneously activating the drone to track the thieves based on their location and transmitting the captured images to the guards' terminal devices; and transmitting the thieves' location in real time to the route prediction unit, which predicts the thieves' escape route and transmits the escape route to the terminal devices. The execution control module also makes decisions regarding invasive animals, including: activating the alarm system to notify guards that invasive animals have entered the ginseng planting area and are damaging the ginseng; simultaneously activating the laser cannons in the corresponding area to illuminate the invasive animals' eyes, causing temporary blindness and driving them away.

[0030] Based on the characteristics of ginseng cultivation under forest cover, the routes available for entering the ginseng cultivation area are often relatively fixed. Therefore, in this embodiment of the invention, it is only necessary to input the predetermined route into the ginseng cultivation area into the route prediction unit. When the execution control module executes the driving-away decision, it is only necessary to transmit the location of the thief to the route prediction unit in real time. The route prediction unit compares the location change of the thief with the predetermined route in the route prediction unit and directly predicts the escape route of the thief.

[0031] Throughout the entire execution process, the monitoring and feedback module plays a crucial role. It monitors the effectiveness of driving away or tracking in real time, recording detailed information such as the time of the event, target characteristics, measures taken, and the final result, forming a complete log for personnel protection. This data is not only used to generate statistical reports but also provides strong support for subsequent strategy optimization. For example, by analyzing multiple failed driving-away cases, laser cannon parameters can be adjusted; based on data from the personnel tracking process, the escape path prediction algorithm can be optimized. Simultaneously, the monitoring and feedback module also feeds back historical data and optimization suggestions to the target recognition and decision analysis modules, helping them continuously improve recognition accuracy and decision precision.

[0032] In the system provided by this invention, the interaction between modules is not unidirectional but forms a tight closed loop. The data acquisition module provides basic data to the target identification module, the results of the target identification module guide the decision analysis module in formulating strategies, the instructions from the decision analysis module drive the operation of the execution control module, the execution status of the execution control module is fed back to the monitoring feedback module, and the monitoring feedback module then transmits optimization information back to other modules, promoting continuous improvement and optimization of the entire system. Through the efficient collaboration and close interaction of the modules, the system provided by this invention achieves accurate identification and effective response to factors that damage the ginseng growth environment, providing reliable technical support for ensuring the safety of the ginseng growth environment and promoting the healthy development of the ginseng industry.

[0033] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0034] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A forest ginseng protection system, characterized in that, include: The data acquisition module acquires the location and category range of invasive targets in the ginseng planting area, photographs the invasive targets, and collects environmental information in the ginseng planting area. The target recognition module receives the target image acquired by the data acquisition module and, in conjunction with the category range determined by the data acquisition module, identifies the target image based on a deep learning model. The decision analysis module receives the identification results from the target identification module and, based on the identification results, combined with the environmental information collected by the data acquisition module and the movement trajectory of the intrusion target, provides targeted decisions to drive away the intrusion target. The execution control module performs corresponding expulsion actions on the intrusion target based on the targeted decision; The monitoring and feedback module collects all information from the data acquisition module, the target identification module, the decision analysis module, and the execution control module to form a complete log for protecting the ginseng, and adjusts the data acquisition module, the target identification module, the decision analysis module, and the execution control module based on the complete log.

2. The forest ginseng protection system according to claim 1, characterized in that, The data acquisition module includes a vibration optical fiber, a camera matrix, a sound sensor, and a control unit, wherein: The vibrating optical fiber is laid underground in the ginseng planting area and connected to an optical fiber modulation and demodulation device. The optical fiber modulation and demodulation device emits incident light into the vibrating optical fiber. When the invading target invades the ginseng planting area, the invading target causes the vibrating optical fiber to vibrate, causing a change in the phase of the scattered light in the vibrating optical fiber. The changed beam returns to the optical fiber modulation and demodulation device for demodulation and is restored to a vibration signal. The vibration signal is input into the control unit to obtain the category range and location of the invading target. The camera matrix includes multiple camera devices, which are distributed in the ginseng planting area in a matrix form. The control unit controls the camera devices at the corresponding positions to take pictures of the intrusion target according to the location of the intrusion target, and then transmits the captured target image to the target recognition module. The sound sensors are distributed in a matrix in the ginseng planting area; the sound sensors collect the sounds generated in the ginseng planting area and transmit the generated sound signals to the control unit, which then transmits the sound signals to the decision analysis module.

3. The forest ginseng protection system according to claim 2, characterized in that, The control unit has a vibration acoustic signature database. The control unit compares the received vibration information with the vibration information in the vibration acoustic signature database to obtain the category range of the intrusion target.

4. The forest ginseng protection system according to claim 2, characterized in that, The target recognition module, based on the category range, invokes a YOLOv8-based category recognition model to recognize the target image: When the category range is human, the target recognition module calls the corresponding category recognition model to identify the items carried by the intruding target; When the category range includes animals that damage the ginseng planting area, the target recognition module calls the corresponding category recognition model to identify the eyes of the invading target.

5. The forest ginseng protection system according to claim 4, characterized in that, The analysis process of the decision analysis module includes: When the category range is human, the target identification module identifies the category of the items carried by the intruding target, and combines the location information and sound information of the intruding target collected by the data acquisition module: if the category of the items carried by the intruding target belongs to the tools for picking ginseng, and the movement trajectory of the intruding target is concentrated in the ginseng planting area, and the sound information is determined to be the sound of digging and damaging ginseng, then the intruding target is determined to be a thief, and a decision is made against the thief. When the category range is animals that damage the ginseng planting area, the location information of the invading target is combined: if the location of the invading target remains unchanged within a preset time, and the sound information is determined to be the sound of digging and damaging ginseng, then the invading target is determined to be an invading animal. At this time, the eye position of the invading animal is calculated based on the eye recognition result of the invading animal, and then the decision is made for the invading animal based on the eye position.

6. The forest ginseng protection system according to claim 5, characterized in that, The execution control module includes an alarm system, drones and route prediction units, as well as laser cannons arrayed in the ginseng planting area; The execution control module makes decisions regarding the thief, including: activating the alarm system to notify the guards that the thief has entered the ginseng planting area and is damaging the ginseng; simultaneously activating the drone to track the thief based on its location and transmitting the captured images to the guards' terminal device; and transmitting the thief's location in real time to the route prediction unit, which predicts the thief's escape route and transmits the escape route to the terminal device. The execution control module makes decisions regarding the invasive animal, including: activating the alarm system to inform the guards that the invasive animal has entered the ginseng planting area and is damaging the ginseng; and simultaneously activating the laser cannon in the corresponding area to irradiate the invasive animal's eyes, causing temporary blindness and thus driving the invasive animal away.

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