Distributed intelligent pest control system and control method thereof

Abstract

The present invention relates to a distributed intelligent pest control system and a control method thereof. The system includes an intelligent pest control device, an antenna module, a wireless communication adapter, an edge computing server, a network adapter and a microcomputer terminal. The intelligent pest control device improves the efficiency and broad spectrum of pest trapping based on a method of combining light trapping with signal molecule trapping. A high-voltage insecticide system and a composite biological trapping plate are used to kill pests. The killed pests themselves are used as signal sources. The high-voltage discharge pulse waveform generated during pest control and the change in capacitance of the composite biological trapping plate are analyzed to count the number of trapped pests and the pest density. A wireless channel method is used to achieve two-way communication with the edge computing server. The edge computing server is used to dynamically control the working status, operation grouping and task queue of the intelligent pest control device in real time, predict the pest density and pest risk in the entire system coverage area, and improve the device operation efficiency and long-term work reliability.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent monitoring and control systems for agricultural pests, and in particular relates to a distributed intelligent pest control system and a control method thereof. Background Art

[0002] my country is a major agricultural producer. Pest monitoring and control is a crucial component of ensuring agricultural safety and food security. It is also a crucial method for improving agricultural production efficiency and the quality of agricultural products, significantly contributing to the realization of efficient and intensive modern agriculture. However, chemical control methods are still the primary method for pest control, resulting in high consumption of various pesticides. This not only increases agricultural production costs, but also poses a significant risk to pesticide residues. The extensive use of pesticides in agricultural production can easily lead to environmental pollution. This pollution is persistent and migratory, causing long-term damage to water sources, the atmosphere, and the soil surrounding agricultural bases. Furthermore, through bioaccumulation and transmission through the food chain, it may eventually enter the human body and pose a threat to health. Therefore, it is necessary to implement a low-pollution, high-efficiency pest control technology. In existing research and practice, physical and biological control methods have gradually been promoted, but both have certain limitations.

[0003] At the same time, there's currently a disconnect between pest control and pest monitoring, often leading to untimely pest control, significant environmental impacts from emergency measures, and high overall costs. Furthermore, traditional monitoring and control methods lack intelligence and rely heavily on manual management and operator experience. These issues ultimately lead to traditional agricultural pest control methods being relatively crude, lacking specificity to specific varieties and regions, and resulting in poor control effectiveness. To address this issue, research and patents have been developed using specialized sensor detection, drone aerial monitoring, and multispectral indirect pest and disease identification. However, these methods primarily test affected plants and indirectly analyze the scale of an infestation based on physiological phenomena, resulting in a certain lag. Furthermore, these methods are complex to apply, have limited effectiveness, and are relatively costly.

[0004] In addition, at the level of pest control methods, existing methods and devices mainly adopt a single-factor pest-luring model, which makes it difficult to balance the relationship among pest control efficiency, environmental impact and application cost. In view of the complex and diverse agricultural environment, the occurrence patterns and biological characteristics of different types of pests vary greatly, and the single-factor method is difficult to cope with. In actual application, poor control effects often occur, affecting the ecological balance and interfering with normal agricultural technical operations. There is a need and necessity for further improvement and optimization. Summary of the Invention

[0005] In response to the above technical problems, the purpose of the present invention is to provide a distributed intelligent pest control system and its control method to solve the technical defects of existing methods, such as the disconnection between pest control and pest monitoring, the limited effect of conventional physical control, the serious environmental damage of chemical control, and the low efficiency of traditional electronic insecticides.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A distributed intelligent pest control system includes an intelligent pest control device 2, an antenna module 4, a wireless communication adapter 5, an edge computing server 6, a network adapter 7 and a microcomputer terminal 8.

[0008] Multiple intelligent pest control devices 2 are deployed in pest control sites, which are used to trap and kill pests and automatically count the number of pests killed and the change in pest density; the pest control sites include fields, orchards, greenhouses, sheds, livestock farms and domestic waste treatment sites; multiple intelligent pest control devices 2 are allocated and combined into different regional groups and task queues by the edge computing server 6; the multiple intelligent pest control devices 2 constitute a pest perception and control array 1.

[0009] The wireless communication adapter 5 is electrically connected to the antenna module 4 and the edge computing server 6 respectively; the antenna module 4 is used to transmit and receive electromagnetic waves, send control instructions to each intelligent pest control device 2 in the pest sensing and control array 1 through the wireless channel 3, and receive the returned pest monitoring information; the pest monitoring information is transmitted in the form of data packets, including high-voltage pest control pulse counts, trapping plate insect capture counts and equipment operation status information.

[0010] The wireless communication adapter 5 is used for fast parallel execution of encoding and modulation transmission of the control instruction stream sent by the edge computing server 6, and decoding of the status and monitoring data stream returned by the intelligent pest control device 2.

[0011] The edge computing server 6 has multiple universal digital signal interfaces, which are electrically connected to the network adapter 7 and the microcomputer terminal 8 respectively; the network adapter 7 is used to enable the edge computing server 6 to access the computer network and provide network data filtering; the microcomputer terminal 8 is used to provide a human-computer interaction interface and realize device management; the edge computing server 6 is used to summarize the statistical information of each intelligent pest control device 2 in each regional group, calculate the amount of pests killed and their change rate in each regional group and in the entire system coverage area, and predict the pest density and pest risk in the entire system coverage area.

[0012] The edge computing server 6 automatically adjusts the working status of each intelligent pest control device 2 in each regional group based on the predicted pest density and pest risk in the entire system coverage area; when the intelligent pest control device 2 in the regional group is unable to kill pests normally due to a malfunction, the edge computing server 6 reallocates the task queue and adjusts the operating parameters of the normal or standby intelligent pest control device 2.

[0013] In the process of the edge computing server 6 automatically adjusting the working status of each intelligent pest control device 2 in each regional group, the edge computing server 6 synchronously adjusts the pest statistics algorithm and the pest statistics correction factor.

[0014] The pest statistics algorithm uses the pest killing amount fed back by each intelligent pest control device 2 in the entire system coverage area as an input variable, obtains the total pest killing amount in the area by accumulation, and combines time information to calculate the change amount and change rate of the pest killing amount over time; based on the normalization method, the relative weight information of the increment of pests killed in the effective area of ​​each intelligent pest control device 2 is obtained, and the working status of the intelligent pest control device 2 is automatically adjusted by feedback.

[0015] The pest statistics correction factor is a dimensionless parameter that assists the correct operation of the pest statistics algorithm and is functionally related to the continuous operation time of the intelligent pest control device 2 to reduce the interference error of the pest statistics caused by changes in the operating efficiency of the intelligent pest control device 2.

[0016] The intelligent pest control device 2 includes an external control unit and an electrical system; the external control unit includes a solar cell 15, a top cover 28, a left support column 29, a right support column 30, a brushless fan bracket 31, a pheromone release module 32, an insect attractant lamp module 33, a collection tray 34, an electrical box 35 and an insect killing net assembly 36.

[0017] The insect-killing net assembly 36 is cylindrical and has a three-layer structure of an inner surface, an interlayer and an outer surface; the insect-killing net assembly 36 includes an insect-killing net electrode 12 and an outer shielding net 38; the insect-killing net electrode 12 includes a grounding electrode, a positive potential electrode 39 and a negative potential electrode 40; the outer shielding net 38 is located on the outer surface of the insect-killing net assembly 36 and is electrically connected to the grounding electrode and then grounded; the positive potential electrode 39 is installed in the interlayer of the insect-killing net assembly 36; the negative potential electrode 40 is installed on the inner surface of the insect-killing net assembly 36; the top cover 28 is fixedly connected to the top of the insect-killing net assembly 36 through the left support column 29 and the right support column 30; the solar cell 15 is fixedly connected to the upper surface of the top cover 28; the pheromone release The release module 32 and the insect attractant lamp module 33 are arranged inside the insect killing net assembly 36; the brushless fan 22 is fixedly connected to the top of the insect killing net assembly 36 through the brushless fan bracket 31, and is used to suck air from the external environment through the insect killing net assembly 36, flow through the pheromone release module 32 and be discharged from the upper part of the brushless fan 22. The discharged airflow is blocked and guided by the top cover 28, and is blown out in the horizontal downward direction of the top cover 28 to promote the diffusion of insect attractant pheromones. At the same time, a negative pressure flow field is formed near the insect killing net assembly 36 to promote insects to enter the insect killing net assembly 36 to achieve killing; the collecting tray 34 is installed at the bottom of the insect killing net assembly 36; the electrical box 35 is fixedly connected to the lower surface of the collecting tray 34 to accommodate the electrical system.

[0018] The electrical system includes a booster 10, a high-voltage controller 11, a pulse counting and control unit 13, an electric energy controller 16, a battery 17, an LED driver 20, an insect trap unit controller 23, a microcontroller 24, an encoding chip 25, a wireless network adapter 26 and an embedded antenna 27.

[0019] The booster 10 has a low-voltage input end, a signal control end and a high-voltage output end; the high-voltage output end of the booster 10 is electrically connected to the high-voltage controller 11; the high-voltage negative electrode of the high-voltage controller 11 is electrically connected to the negative potential electrode 40 of the insect-killing net electrode 12; the high-voltage positive electrode of the high-voltage controller 11 is electrically connected to the positive potential electrode 39 of the insect-killing net electrode 12; the protective grounding electrode of the high-voltage controller 11 is electrically connected to the grounding electrode of the insect-killing net electrode 12.

[0020] The signal control end of the booster 10 and the signal control end of the high-voltage controller 11 are respectively electrically connected to the pulse counting and control unit 13, which is used to adjust the output voltage of the booster 10 and control the on and off of the high-voltage controller 11, thereby controlling the pest killing effect of the insect-killing net electrode 12; at the same time, the pulse counting and control unit 13 is used to count the high-voltage discharge pulses in the insect-killing net electrode 12 during the pest killing process, and then automatically count the amount of pests killed.

[0021] The LED driver 20 is electrically connected to the LED light-emitting chip 19 and is used to drive and control the operation of the LED light-emitting chip 19 to adjust the light intensity and light spectrum.

[0022] The pheromone release module 32 includes multiple insect attracting units 21 consisting of a heating component 43, an insect density sensing electrode 44 and a composite biological trapping plate 45; the insect density sensing electrode 44 is mechanically connected to the heating component 43; the composite biological trapping plate 45 is installed on the upper surface of the insect density sensing electrode 44; the heating component 43 is used to heat the composite biological trapping plate 45 to promote the diffusion of information odor molecules and improve the viscosity of the composite biological trapping plate 45 under low ambient temperature conditions; the composite biological trapping plate 45 adheres to small pests while releasing information odor molecules, thereby achieving an insect extermination function; the distributed capacitance between the insect density sensing electrode 44 and the composite biological trapping plate 45 increases as the number of adhered insects increases.

[0023] The insect attraction unit controller 23 is electrically connected to the insect attraction unit 21, and is used to drive the heating component 43 of the insect attraction unit 21 to heat the composite biological trapping plate 45 to release insect pheromones and adjust the heating power of the heating component 43 to achieve temperature control. At the same time, the distributed capacitance between the insect density sensing electrode 44 and the composite biological trapping plate 45 is automatically measured through the AC small signal method, the capacitive reactance increment of the insect density sensing electrode 44 is determined, and sent to the microcontroller 24.

[0024] The working power supply of the LED driver 20 , the insect attracting unit controller 23 and the brushless fan 22 is a low voltage DC, the negative pole of which is grounded, and the positive potential end is electrically connected in parallel and in parallel with the low voltage input end of the booster 10 .

[0025] The power controller 16 is electrically connected to the solar cell 15 and the battery 17 respectively; based on the MPPT method, the power controller 16 tracks the optimal power point of the solar cell 15 and realizes voltage stabilization and charge and discharge management of the battery 17; the battery 17 is used to store excess power, thereby realizing stable operation of the intelligent pest control device 2 at night and in low light conditions.

[0026] The microcontroller 24 is electrically connected to the pulse counting and control unit 13, the LED driver 20, the insect attracting unit controller 23 and the brushless fan 22, respectively, and is used to realize the working state control and feedback signal processing of the pulse counting and control unit 13, the LED driver 20, the insect attracting unit controller 23 and the brushless fan 22; the encoding chip 25 and the wireless network adapter 26 are electrically connected to the microcontroller 24, and the encoding chip 25 is used for encoding and decoding operations of the communication data stream between the intelligent pest control device 2 and the edge computing server 6, thereby reducing the workload of the microcontroller 24; the wireless network adapter 26 is electrically connected to the embedded antenna 27, and the two work together to connect the microcontroller 24 to the wireless channel 3.

[0027] The insect-killing net assembly 36 kills large-sized pests based on a high-voltage pulse discharge method. When a large-sized pest enters the insect-killing net assembly 36, two high-voltage pulse discharge processes will be triggered: first, the pest body will connect the circuit between the outer shielding net 38 and the positive potential electrode 39. At the same time as the discharge occurs, a rising edge signal appears in the potential of the outer shielding net 38. This signal is captured by the pulse counting and control unit 13, and the recording circuit therein is reset. When the pest further enters the insect-killing net assembly 36, a falling edge signal appears in the potential of the outer shielding net 38. At this time, the recording circuit state value is flipped and locked, and a "trigger signal" is recorded. When the pest enters When the insects enter the area between the positive potential electrode 39 and the negative potential electrode 40, a second high-voltage pulse discharge will be triggered. At this time, a pair of "step signals" with opposite phases appear on the positive potential electrode 39 and the negative potential electrode 40. The signals are collected by the pulse counting and control unit 13, and the killed pests fall onto the collection tray 34, thereby killing the pests. The microcontroller 24 analyzes and predicts the frequency of pest electric shock events by comparing the timing and occurrence frequency of the "trigger signal" and the "step signal" collected by the pulse counting and control unit 13, as well as the return current waveform of the outer shielding net 38 and the output current waveform of the positive potential electrode 39.

[0028] The composite biological trapping plate 45 uses a high-viscosity substrate, and pests are adhered to it when they come into contact with it. At the same time, as the amount of pest adhesion increases, the distributed capacitance between the insect density sensing electrode 44 and the composite biological trapping plate 45 will increase; the insect attractant unit controller 23 automatically measures the distributed capacitance between the insect density sensing electrode 44 and the composite biological trapping plate 45 using an AC small signal method, determines the capacitive reactance of the insect density sensing electrode 44, and sends it to the microcontroller 24; the microcontroller 24 runs a fitting algorithm to calculate the pest density and its change on the surface of the composite biological trapping plate 45.

[0029] The fitting algorithm run by the microcontroller 24 uses the capacitive reactance of the insect density sensing electrode 44 as an input variable, and calculates the density of pests adhered to the surface of the composite biological trapping plate 45 through a calibrated and debugged "capacitive reactance-pest density" working curve, and further obtains the total amount of adhered insects and its change over time.

[0030] The intelligent pest control device 2 cooperates with the edge computing server 6 to operate to realize pest capture statistics, pest density prediction and pest risk prediction; the microcontroller 24 of the intelligent pest control device 2 feeds back the pest density change information on the surface of the composite biological trapping plate 45 and the pest attack statistics of the insect killing net component 36 to the edge computing server 6 through the wireless network adapter 26 and the embedded antenna 27; the edge computing server 6 runs a pest statistics algorithm to integrate the information fed back by multiple intelligent pest control devices 2 in each regional group, and calculates the pest capture amount and its change rate in the corresponding regional group; then, based on the situation of multiple regional groups, the pest capture amount and its change rate in the entire system coverage area are calculated; at the same time, the edge computing server 6 obtains prediction information of pest density and pest risk in the system coverage area based on the enhanced BP algorithm.

[0031] The left support column 29 and the right support column 30 are made of insulating material; insulating support blocks 37 are provided between the left support column 29 and the right support column 30 and the insect-killing net assembly 36, between the brushless fan bracket 31 and the insect-killing net assembly 36, and between the collection tray 34 and the insect-killing net assembly 36.

[0032] The insect attractant lamp module 33 includes a heat sink 41 and an LED chip 42; multiple LED chips 42 are mechanically connected to the outer surface of the heat sink 41, and are electrically connected in parallel to each other to form an LED light-emitting sheet 19; the heat sink 41 is used to buffer and dissipate the heat generated by the LED chip 42, stabilizing the operating temperature of the LED chip 42; the contact surface between the LED chip 42 and the heat sink 41 is filled with high thermal conductivity silicone gel or polished surface treatment; the LED chip 4 is prepared using a voltage-modulated ultraviolet-near-ultraviolet LED device.

[0033] The composite biological trapping plate 45 is prepared by compounding sex pheromone analogues of various pests to trap various pests; or is prepared by using a gel containing pest-sensitive chemical components to trap mosquitoes and flies based on odor molecules.

[0034] The booster 10 adopts a high-frequency PWM driven flyback power supply topology or a bridge excitation topology, realizes voltage conversion based on a mutual inductance transformer, or realizes voltage boosting by using an ultrasonic piezoelectric transformer, or realizes high-voltage DC output by using direct rectification or multiplier rectification.

[0035] A control method for a distributed intelligent pest control system comprises the following steps:

[0036] S1, system preparation stage;

[0037] First, the hardware connection between the edge computing server 6, the network adapter 7, and the microcomputer terminal 8 is completed, and the power is turned on. At this time, the edge computing server 6 starts running, initializes the network adapter 7 and the wireless communication adapter 5 according to the scheduled task program settings, and displays relevant startup information on the microcomputer terminal 8;

[0038] At the same time, the user installs the intelligent pest control device 2 in an agricultural environment. The solar self-powered system 14 in the intelligent pest control device 2 automatically begins to operate, generating photovoltaic power through the solar cell 15 receiving light. The power controller 16 stabilizes the output voltage of the system operating power and charges the battery 17. When the system operating power is established, the microcontroller 24 is powered and operates, performing a hardware self-test on the booster 10, high-voltage controller 11, pulse counting and control unit 13, LED driver 20, brushless fan 22, and insect attractant unit controller 23, and recording the self-test results. The intelligent pest control device 2 then enters a standby state.

[0039] S2, system startup phase;

[0040] After step S1 is completed, the system will execute S2.1 edge computing server startup process and S2.2 intelligent pest control device startup process;

[0041] S2.1, Edge computing server startup process;

[0042] After the system preparation phase of step S1 is completed, the edge computing server automatically starts the node grouping program and the remote control service framework, sends a communication handshake instruction to the intelligent pest control device 2 through the wireless communication adapter 5 and waits for signal feedback. If a normal feedback signal from the node is received within the preset time, the corresponding intelligent pest control device 2 is marked as online. If the response times out or the feedback signal is abnormal, it is marked as abnormal. For the intelligent pest control device 2 in the abnormal state, the edge computing server will retry the handshake multiple times. If it still fails to respond after the retry, the corresponding intelligent pest control device 2 is marked as offline, and the remaining devices that have been retried to connect are automatically recorded in a warning state. At this time, the wireless communication link between the edge computing server and the intelligent pest control device is established, and the step S2.1 process ends;

[0043] S2.2, Intelligent pest control device startup process;

[0044] When the edge computing server 6 sends a communication handshake command via the wireless communication adapter 5, the wireless network adapter 26 in each intelligent pest control device 2 is activated and wakes up the microcontroller 24. At this time, the microcontroller 24 encodes the initialization self-test result in step S1 through the encoding chip 25, modulates it through the wireless network adapter 26, and transmits it via the embedded antenna 27, realizing signal feedback from the intelligent pest control device 2 to the edge computing server 6. The intelligent pest control device 2 then enters a command waiting state, and the process of step S2.2 ends.

[0045] S3, device initialization stage;

[0046] The edge computing server 6 starts the node grouping service program. The user uses the graphical interface provided by the microcomputer terminal 8 to bind the intelligent pest control device 2 to the geographic coordinates and divide the task queue in the lightweight agricultural regional GIS. At this time, the software in the microcomputer terminal 8 automatically generates a node mapping allocation table and submits it to the edge computing server 6. The edge computing server 6 issues a grouping instruction to the intelligent pest control device 2 in the agricultural environment based on the node mapping allocation table. The microcontroller 24 receives and decodes the instruction through the encoding chip 25, wireless network adapter 26 and embedded antenna 27, and records the grouping information corresponding to the device.

[0047] The microcontroller 24 in the intelligent pest control device 2 resets and calibrates the pulse counting and control unit 13 to achieve initialization. The microcontroller 24 then detects and reads the initial capacitance value of the insect density sensing electrode 44 and records it. At this point, the device initialization phase process in step S3 ends.

[0048] S4, pest control and perception process;

[0049] The edge computing server 6 first attempts to connect to the cloud database through the network adapter 7 to download data such as the pest type, average statistical density, and occurrence time of the pest in the area. After making decisions based on this data, it issues corresponding control instructions to the intelligent pest control devices 2 in each group. If there is no relevant recorded data in the application area or the network adapter 7 is not connected to an available network, the user is notified to make settings. In this case, the user can choose to run the system in default mode or make manual settings. After receiving the control instructions, the intelligent pest control device 2 adjusts the output voltage of the booster 10 in the device, the luminous intensity and output spectrum of the LED light-emitting panel 19, the speed of the brushless fan 22, and the operating temperature of the insect attractant unit 21 through the microcontroller 24.

[0050] The LED light-emitting sheet 19 emits UV light of appropriate spectrum and intensity. At the same time, the brushless fan 22 draws air from the insect-killing net assembly 36, passes through the pheromone release module 32, and is discharged from the upper part of the intelligent pest control device 2, causing the signal molecules to diffuse and release. After being stimulated by the light information, sex pheromones, or signal odor molecules, the pests are attracted to the vicinity of the intelligent pest control device 2, thereby attracting the pests.

[0051] Affected by the airflow generated by the brushless fan 22, insect pests enter the insect-killing net assembly 36. For larger insect pests, two high-voltage pulse discharge processes will be triggered: first, the insect body will connect the circuit between the outer shielding net 38 and the positive potential electrode 39. At the same time as the discharge occurs, the outer shielding net 38 potential will show a rising edge signal, which is captured by the pulse counting and control unit 13, and the recording circuit therein is reset. When the insect pest further enters the insect-killing net assembly 36, the outer shielding net 38 potential will show a falling edge signal. At this time, the state value of the recording circuit is flipped and locked, and a trigger signal is recorded. When the insect pest enters the area between the positive potential electrode 39 and the negative potential electrode 40, a second high-voltage pulse discharge will be triggered. At this time, a pair of opposite step signals will appear on the positive potential electrode 39 and the negative potential electrode 40. This signal is collected by the pulse counting and control unit 13, and the killed insect pests will then fall onto the collection tray 34, achieving the pest extermination. The microcontroller 24 predicts the frequency of insect pest electric shock events by comparing the timing and occurrence frequency of the trigger signal and the step signal.

[0052] Smaller insect pests may pass directly through the insect-killing net assembly 36 without generating effective discharge. When the insect pests come into contact with the composite biological trapping plate 45, they become attached. As the amount of insect pest adhesion increases, the distributed capacitance between the insect density sensing electrode 44 and the composite biological trapping plate 45 increases. This change is automatically measured by the microcontroller 24 using an AC small signal method, detecting the increase in the capacitive reactance of the insect density sensing electrode 44 and, based on a built-in fitting algorithm, inferring the change in insect pest density on the surface of the composite biological trapping plate 45.

[0053] The intelligent pest control device 2 transmits information on changes in pest density on the surface of the composite biological trapping plate 45 and pest attack statistics on the insect killing net assembly 36 to the edge computing server 6 via the wireless network adapter 26 and the embedded antenna 27. The edge computing server 6 runs a pest statistics algorithm to integrate the information fed back by the multiple intelligent pest control devices 2 in each regional grouping, and calculates the number of pests captured and their rate of change within the corresponding regional grouping. The information from the multiple regional groups is then combined to calculate the number of pests captured and their rate of change within the entire system working area. Simultaneously, the edge computing server 6 uses an enhanced BP algorithm to predict pest density and pest risk within the system coverage area. This prediction information can be uploaded to the cloud database for reference.

[0054] S5, device self-feedback control process;

[0055] Based on the pest statistical density and pest risk prediction information obtained in step S4, the edge computing server 6 will automatically adjust the working status of the intelligent pest control device 2 in each regional group multiple times to improve its operating efficiency and reduce energy waste; at the same time, during the above-mentioned regulation process, the edge computing server 6 will synchronously adjust the pest statistical algorithm and the pest statistical correction factor to reduce the error introduced by the change in the working efficiency of the intelligent pest control device 2 and improve the long-term operation stability of the system.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. The present invention uses the trapped pests themselves as the trigger signal for pest density statistics. Based on this method, the present invention does not require additional sensors or expensive multispectral-machine vision equipment, and can simultaneously achieve pest trapping and killing, pest counting and statistics, and pest density prediction in situ. This solves the technical problem of the disconnection between pest control and pest monitoring in existing methods, simplifies the workflow, improves the system's operating efficiency, and is more cost-effective than existing intelligent pest monitoring systems.

[0058] 2. This invention uses an edge computing server to dynamically allocate regional groups and task queues for the pest sensing and control array, enabling dynamic allocation and on-demand adjustment of the intelligent pest control device's operating mode, operating power, and operating status. This achieves higher efficiency than traditional electronic pest control devices. Furthermore, this invention offers energy savings, a long operating life, and stable pest trapping.

[0059] 3. The present invention adopts edge computing technology to complete pest statistical analysis, pest risk prediction calculation, node device operation control and other functions in the edge computing server. Compared with conventional "cloud computing" Internet of Things systems, the present invention has lower dependence on wide area networks and cloud servers. In situations where there is no good external network or strict information security requirements, the present invention can achieve purely localized operation, which is convenient for promotion and use in various agricultural application scenarios.

[0060] 3. The present invention adopts a fan device with a "top suction" structure, which draws external airflow inward from the outside of the insect-killing net component, discharges it upward after passing through the pheromone release plate, and after being diverted by the baffle on the top of the device, diffuses and releases information odor molecules around the device. Compared with the traditional insect trapping device with a "downward blowing" structure, the information odor molecules of the present invention have a wider release range and form a negative pressure flow field near the insect-killing net component, which increases the probability of insects entering the device, thereby enhancing the insect pest trapping effect of the present invention.

[0061] 4. The present invention combines high-voltage pulse pest control with physical adhesion pest control to achieve pure physical pest control. Compared with traditional chemical pesticide methods, the present invention does not produce secondary pollution, reduces the impact of pesticides on the environment, and has no drug resistance problem in the prevention and control process, avoiding the problem of attenuation of long-term use effects. In addition, the present invention combines the controllable spectrum light trapping method with the information odor molecule trapping method, and adjusts the trapping spectrum and the composite biological trapping plate components according to different pests, and adopts a composite spectrum and composite component method, which improves the targeted pest trapping while still having strong broad spectrum. Compared with the traditional single trapping method, the method of the present invention has higher trapping efficiency and broad spectrum compatibility with pest types.

[0062] 5. The present invention uses a solar self-powered system to provide power for the intelligent pest control device. The device also has a built-in power management component and a rechargeable battery pack, enabling all-weather operation without relying on external power supply and requiring no power lines. Furthermore, the intelligent pest control device of the present invention uses wireless communication channels with the edge computing server, eliminating the need for communication lines. Based on this approach, the present invention has better environmental compatibility than traditional equipment, a more flexible deployment process, and is convenient for adjusting the installation location based on actual pest control needs. It also avoids the drawbacks of difficult wiring, long construction periods, and high line costs in complex agricultural environments, making it more practical and feasible for large-scale applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a logical diagram of the distributed intelligent pest control system of the present invention;

[0064] Figure 2 Schematic diagram of the mechanical structure of the intelligent pest control device 2 of the present invention;

[0065] Figure 3 is a schematic structural diagram of the insect-killing net assembly 36 of the present invention;

[0066] Figure 4 3 is a schematic structural diagram of the insect trap lamp module 33 of the present invention;

[0067] Figure 5 Schematic diagram of the structure of the pheromone release module 32 of the present invention.

[0068] Figure 6 This is a schematic diagram of the electrical principle of the intelligent pest control device 2 of the present invention;

[0069] The accompanying drawings are as follows:

[0070] 1Pest sensing and control array 2Intelligent pest control device

[0071] 3 wireless channels and 4 antenna modules

[0072] 5 Wireless Communication Adapter 6 Edge Computing Server

[0073] 7 Network adapter 8 Microcomputer terminal

[0074] 9 High-pressure insecticide system 10 Booster

[0075] 11 High voltage controller 12 Insecticide net electrode

[0076] 13 Pulse counting and control unit 14 Solar self-powered electronic system

[0077] 15 Solar cells 16 Power controller

[0078] 17 Battery 18 Insect trapping subsystem

[0079] 19LED light emitting chip 20LED driver

[0080] 21 Insect attractant unit 22 Brushless fan

[0081] 23 insect trap unit controller 24 microcontroller

[0082] 25 encoding chip 26 wireless network adapter

[0083] 27 embedded antenna 28 top cover

[0084] 29 left support column 30 right support column

[0085] 31 Brushless fan bracket 32 ​​Pheromone release module

[0086] 33 insect trap lamp module 34 collection tray

[0087] 35 electrical box 36 insecticide net assembly

[0088] 37 Insulation support block 38 Outer shielding net

[0089] 39 positive potential electrode 40 negative potential electrode

[0090] 41 heat sink 42 LED chip

[0091] 43 heating component 44 insect density sensing electrode

[0092] 45 composite biological trapping board DETAILED DESCRIPTION

[0093] The present invention will be further described below with reference to the accompanying drawings and examples.

[0094] like Figure 1As shown, a distributed intelligent pest control system includes an intelligent pest control device 2, an antenna module 4, a wireless communication adapter 5, an edge computing server 6, a network adapter 7 and a microcomputer terminal 8.

[0095] Multiple intelligent pest control devices 2 are deployed in pest control sites, used to trap and kill pests and automatically calculate pest kill counts and pest density changes. These sites include fields, orchards, greenhouses, sheds, livestock farms, and domestic waste disposal sites. These devices 2 are allocated and organized into different regional groups and task queues by an edge computing server 6. These devices 2 form a pest sensing and control array 1.

[0096] The wireless communication adapter 5 is electrically connected to the antenna module 4 and the edge computing server 6 respectively; the antenna module 4 is used to transmit and receive electromagnetic waves, send control instructions to each intelligent pest control device 2 in the pest sensing and control array 1 through the wireless channel 3, and receive the returned pest monitoring information; the pest monitoring information is transmitted in the form of data packets, including high-voltage pest control pulse counts, trapping plate insect capture counts and equipment operation status information.

[0097] The wireless communication adapter 5 is used for fast parallel execution of encoding and modulation transmission of the control instruction stream sent by the edge computing server 6, and decoding of the status and monitoring data stream returned by the intelligent pest control device 2.

[0098] Preferably, the wireless communication adapter 5 adopts LORA or ZigBee to achieve lower operating power consumption, or adopts Wi-Fi mode to achieve better device compatibility.

[0099] Preferably, when the wireless communication adapter 5 uses the Wi-Fi mode, corresponding wireless routers and AP devices should be deployed at the application site to ensure signal coverage and network stability.

[0100] Preferably, when the wireless communication adapter 5 uses LORA or ZigBee, the Sub-GHz frequency band is used to achieve better signal coverage and obstacle diffraction performance.

[0101] The edge computing server 6 has multiple universal digital signal interfaces, electrically connected to a network adapter 7 and a microcomputer terminal 8. The network adapter 7 is used to connect the edge computing server 6 to a computer network and provide network data filtering. The microcomputer terminal 8 is used to provide a human-computer interface and implement device management. The edge computing server 6 is used to aggregate statistical information from each intelligent pest control device 2 within each regional grouping, calculate the pest capture rate and its rate of change within each regional grouping and within the entire system coverage area, and predict pest density and pest risk within the entire system coverage area.

[0102] The edge computing server 6 automatically adjusts the working state of each intelligent pest control device 2 in each regional group based on the predicted pest density and pest risk in the entire system coverage area to improve its operating efficiency and reduce energy waste. At the same time, during the above-mentioned automatic adjustment process, the edge computing server 6 synchronously adjusts the pest statistical algorithm and the pest statistical correction factor to reduce the error introduced by the change in the working efficiency of the intelligent pest control device 2 and improve the long-term operation stability of the system. Furthermore, when the intelligent pest control device 2 in the regional group is unable to kill pests normally due to a malfunction, the edge computing server 6 reallocates the task queue and adjusts the operating parameters of the normal or standby intelligent pest control device 2 to avoid a significant impact on the pest killing efficiency in the regional group.

[0103] The pest statistics algorithm uses the pest killing amount fed back by each intelligent pest control device 2 in the entire system coverage area as an input variable, obtains the total pest killing amount in the area by accumulation, and combines time information to calculate the change amount and change rate of the pest killing amount over time; based on the normalization method, the relative weight information of the increment of pests killed in the effective area of ​​each intelligent pest control device 2 is obtained, and the working status of the intelligent pest control device 2 is automatically adjusted by feedback.

[0104] As a feasible method, the pest statistics algorithm can be used as a part of the functional program in the edge computing server 6 and written in a programming language such as but not limited to C++, C# or Python.

[0105] The pest statistics correction factor is a dimensionless parameter that assists the correct operation of the pest statistics algorithm and is functionally related to the continuous operation time of the intelligent pest control device 2 to reduce the interference error of the pest statistics caused by changes in the operating efficiency of the intelligent pest control device 2.

[0106] As a feasible method, the insect pest statistical correction factor can be obtained by using a statistical modeling method, and according to experimental test results, a functional relationship of the change with the continuous operation time of the intelligent insect pest control device 2 can be fitted.

[0107] As a feasible method, the pest statistical correction factor can also adopt an artificial intelligence method to automatically obtain an approximate function that changes with the continuous operation time of the intelligent pest control device 2 through multiple rounds of training-calibration process.

[0108] Preferably, the network adapter 7 adopts one or a combination of the following hardware forms: Ethernet (LAN) network card, fiber optic card, high-speed Wi-Fi network card, 4G / 5G network card to achieve network access function.

[0109] Preferably, the microcomputer terminal 8 is an embedded industrial computer, or a terminal device custom-designed for a distributed intelligent pest control system running embedded operating software to achieve better system stability. Alternatively, a general-purpose microcomputer running a conventional operating system and control software can be used to achieve better system cost-effectiveness. Specifically, the microcomputer terminal 8 can use a computer device in a variety of hardware formats, including but not limited to general-purpose laptops, desktop computers, or mobile terminal devices.

[0110] The intelligent pest control device 2 includes an external control unit and an electrical system; Figure 2 As shown, the control unit includes a solar cell 15, a top cover 28, a left support column 29, a right support column 30, a brushless fan bracket 31, a pheromone release module 32, an insect trap module 33, a collection tray 34, an electrical box 35 and an insect killing net assembly 36;

[0111] like Figure 3As shown, the insect-killing net assembly 36 is cylindrical and has a three-layer structure: an inner surface, an interlayer, and an outer surface. The insect-killing net assembly 36 includes an insect-killing net electrode 12 and an outer shielding net 38. The insect-killing net electrode 12 includes a grounding electrode, a positive electrode 39, and a negative electrode 40. The outer shielding net 38 is located on the outer surface of the insect-killing net assembly 36 and is electrically connected to the grounding electrode to shield the external impact of the high-voltage electric field and improve the safety of the device. The positive electrode 39 is installed in the interlayer of the insect-killing net assembly 36, and the negative electrode 40 is installed on the inner surface of the insect-killing net assembly 36. The positive electrode 39 and the negative electrode 40 operate in conjunction, creating a strong electric field between them during operation. When pests enter the insect-killing net assembly 36, a high-voltage pulse discharge is generated between the positive electrode 39 and the negative electrode 40, killing the pests with a transient pulse current. The top cover 28 is fixed to the top of the insecticide net assembly 36 via left and right support columns 29 and 30, providing a shield to prevent rainwater and large debris from entering the device and causing malfunctions. The solar cell 15 is fixed to the upper surface of the top cover 28 to receive sunlight and generate solar power. The pheromone release module 32 and insect attractant light module 33 are located within the insecticide net assembly 36 and are used to attract pests into the device through chemical and optical stimulation of the pheromones, thereby improving the killing efficiency. The brushless fan 22 is fixed to the top of the insecticide net assembly 36 via a brushless fan bracket 31. It draws air from the external environment through the insecticide net assembly 36, passes through the pheromone release module 32, and is discharged from the top of the brushless fan 22. The discharged air is blocked and guided by the top cover 28 and blown horizontally downward from the top cover 28 to promote the diffusion of the insect attractant pheromones. At the same time, a negative pressure flow field is formed near the insecticide net assembly 36, which encourages insects to enter the insecticide net assembly 36 and kill them. The collecting tray 34 is mounted at the bottom of the insect-killing net assembly 36 to collect the remains and debris of the killed insects. The electrical box 35 is fixed to the lower surface of the collecting tray 34 to accommodate the electrical system.

[0112] Preferably, the left support column 29 and the right support column 30 are made of insulating material.

[0113] Insulating support blocks 37 are provided between the left support column 29 , the right support column 30 and the insect-killing net assembly 36 , between the brushless fan bracket 31 and the insect-killing net assembly 36 , and between the collecting tray 34 and the insect-killing net assembly 36 .

[0114] like Figure 4As shown, the insect attractant lamp module 33 includes a heat sink 41 and an LED chip 42; a plurality of LED chips 42 are mechanically connected to the outer surface of the heat sink 41, and are electrically connected in parallel with each other to form an LED light-emitting sheet 19; the heat sink 41 is used to buffer and dissipate the heat generated by the LED chip 42, thereby stabilizing the operating temperature of the LED chip 42.

[0115] Preferably, the contact surface between the LED chip 42 and the heat sink 41 is filled with silicone gel with high thermal conductivity or polished to reduce the thermal resistance between the two and improve the heat dissipation effect.

[0116] Preferably, the LED chip 4 is made of a voltage-modulated violet-near-ultraviolet LED device.

[0117] like Figure 5 As shown, the pheromone release module 32 includes multiple insect trapping units 21, each consisting of a heating assembly 43, an insect density sensing electrode 44, and a composite bio-trapping plate 45. The insect density sensing electrode 44 is mechanically connected to the heating assembly 43; the composite bio-trapping plate 45 is mounted on the upper surface of the insect density sensing electrode 44. The heating assembly 43 is used to heat the composite bio-trapping plate 45 to promote the diffusion of information odor molecules and improve the adhesion of the composite bio-trapping plate 45 under low ambient temperature conditions. While releasing information odor molecules, the composite bio-trapping plate 45 simultaneously adheres to small insect pests, achieving an insecticide function. The distributed capacitance between the insect density sensing electrode 44 and the composite bio-trapping plate 45 increases with the number of adhered insects.

[0118] Preferably, the composite bio-trap plate 45 is prepared using a combination of sex pheromone analogs from multiple pests to trap a variety of pests; or it can be prepared using a gel containing pest-sensitive chemical components to trap mosquitoes and flies based on odor molecules. The composition of the composite bio-trap plate 45 should be selected to avoid conflicting effects of different odor molecules and to prevent the components from reacting with each other and causing failure.

[0119] like Figure 6 As shown, the electrical system includes a booster 10, a high-voltage controller 11, a pulse counting and control unit 13, an electric energy controller 16, a battery 17, an LED driver 20, an insect attractant unit controller 23, a microcontroller 24, an encoding chip 25, a wireless network adapter 26 and an embedded antenna 27.

[0120] The booster 10 has a low-voltage input end, a signal control end and a high-voltage output end; the high-voltage output end of the booster 10 is electrically connected to the high-voltage controller 11; the high-voltage negative electrode of the high-voltage controller 11 is electrically connected to the negative potential electrode 40 of the insect-killing net electrode 12; the high-voltage positive electrode of the high-voltage controller 11 is electrically connected to the positive potential electrode 39 of the insect-killing net electrode 12; the protective grounding electrode of the high-voltage controller 11 is electrically connected to the grounding electrode of the insect-killing net electrode 12.

[0121] Preferably, the booster 10 adopts a high-frequency PWM driven flyback power supply topology or a bridge excitation topology, realizes voltage conversion based on a mutual inductance transformer, or realizes voltage boosting by using an ultrasonic piezoelectric transformer, or realizes high-voltage DC output by using direct rectification or multiplier voltage rectification.

[0122] The signal control end of the booster 10 and the signal control end of the high-voltage controller 11 are respectively electrically connected to the pulse counting and control unit 13, which is used to adjust the output voltage of the booster 10 and control the on and off of the high-voltage controller 11, thereby controlling the pest killing effect of the insect-killing net electrode 12; at the same time, the pulse counting and control unit 13 is used to count the high-voltage discharge pulses in the insect-killing net electrode 12 during the pest killing process, and then automatically count the amount of pests killed.

[0123] The LED driver 20 is electrically connected to the LED light-emitting chip 19 and is used to drive and control the operation of the LED light-emitting chip 19 to adjust the light intensity and light spectrum, thereby improving the pest trapping efficiency and insect species adaptability.

[0124] The insect attraction unit controller 23 is electrically connected to the insect attraction unit 21, and is used to drive the heating component 43 of the insect attraction unit 21 to heat the composite biological trapping plate 45 to release insect pheromones and adjust the heating power of the heating component 43 to achieve temperature control. At the same time, the distributed capacitance between the insect density sensing electrode 44 and the composite biological trapping plate 45 is automatically measured through the AC small signal method, the capacitive reactance increment of the insect density sensing electrode 44 is determined, and sent to the microcontroller 24.

[0125] The working power supply of the LED driver 20 , the insect attracting unit controller 23 and the brushless fan 22 is a low voltage DC, the negative pole of which is grounded, and the positive potential end is electrically connected in parallel and in parallel with the low voltage input end of the booster 10 .

[0126] The power controller 16 is electrically connected to the solar cell 15 and the battery 17 respectively; based on the MPPT method, the power controller 16 tracks the optimal power point of the solar cell 15 and realizes voltage stabilization and charge and discharge management of the battery 17; the battery 17 is used to store excess power, thereby realizing stable operation of the intelligent pest control device 2 at night and in low light conditions.

[0127] The microcontroller 24 is electrically connected to the pulse counting and control unit 13, LED driver 20, insect attractant controller 23, and brushless fan 22, respectively, to control the operating status of these three components and process feedback signals. The encoding chip 25 and wireless network adapter 26 are electrically connected to the microcontroller 24. The encoding chip 25 is responsible for encoding and decoding the communication data stream between the intelligent pest control device 2 and the edge computing server 6, thereby reducing the workload of the microcontroller 24. The wireless network adapter 26 is electrically connected to the embedded antenna 27, and the two work together to connect the microcontroller 24 to the wireless channel 3.

[0128] The insect-killing net assembly 36 kills larger pests using a high-voltage pulse discharge method. When a larger pest enters the net assembly 36, two high-voltage pulse discharge processes are triggered: first, the pest's body connects the circuit between the outer shielding net 38 and the positive electrode 39. Simultaneously with the discharge, a rising edge signal appears in the potential of the outer shielding net 38. This signal is captured by the pulse counting and control unit 13, resetting the recording circuit therein. As the pest further enters the net assembly 36, a falling edge signal appears in the potential of the outer shielding net 38. At this point, the recording circuit state value flips and locks, recording a "trigger signal." When the pest enters the area between the positive electrode 39 and the negative electrode 40, a second high-voltage pulse discharge is triggered. At this point, a pair of "step signals" with opposite phases appear on both the positive and negative electrodes 39, 40. These signals are collected by the pulse counting and control unit 13, and the killed pest then falls onto the collection tray 34, effectively killing the pest. The microcontroller 24 analyzes and predicts the frequency of pest electric shock events by comparing the timing and frequency of the "trigger signal" and "step signal" collected by the pulse counting and control unit 13, as well as the waveform of the return current from the outer shielding mesh 38 and the waveform of the output current from the positive electrode 39. Furthermore, because multiple discharges occur during pest electric shock in practice, the microcontroller 24 employs digital filtering to remove high-frequency signals to reduce prediction errors.

[0129] The composite biological trapping plate 45 uses a high-viscosity substrate, and pests are adhered to it when they come into contact with it. At the same time, as the amount of pest adhesion increases, the distributed capacitance between the insect density sensing electrode 44 and the composite biological trapping plate 45 will increase; the insect attractant unit controller 23 automatically measures the distributed capacitance between the insect density sensing electrode 44 and the composite biological trapping plate 45 using an AC small signal method, determines the capacitive reactance of the insect density sensing electrode 44, and sends it to the microcontroller 24; the microcontroller 24 runs a fitting algorithm to calculate the pest density and its change on the surface of the composite biological trapping plate 45.

[0130] The fitting algorithm run by the microcontroller 24 uses the capacitive reactance of the insect density sensing electrode 44 as an input variable and calculates the density of pests adhered to the surface of the composite biological trapping plate 45 through a calibrated and debugged "capacitive reactance-pest density" working curve. Obviously, for a composite biological trapping plate 45 with a certain geometric size, the total amount of insects adhered thereto and its change over time can be further obtained.

[0131] The intelligent pest control device 2 operates in conjunction with the edge computing server 6 to implement pest capture statistics, pest density prediction, and pest risk prediction. The microcontroller 24 of the intelligent pest control device 2 feeds back information on pest density changes on the surface of the composite biological trapping plate 45 and pest strike statistics from the insect-killing net component 36 to the edge computing server 6 via the wireless network adapter 26 and embedded antenna 27. The edge computing server 6 runs a pest statistics algorithm to synthesize the information fed back by the multiple intelligent pest control devices 2 within each regional grouping, and calculates the pest capture volume and its rate of change within the corresponding regional grouping. The information from multiple regional groups is then combined to calculate the pest capture volume and its rate of change within the entire system coverage area. Simultaneously, the edge computing server 6 uses an enhanced BP algorithm to obtain predicted information on pest density and pest risk within the system coverage area. This predicted information can be uploaded to a cloud database for reference. In addition, for specific situations where confidentiality is required, all statistical and predicted information is stored locally to improve information security.

[0132] The enhanced BP algorithm, based on a back-propagation neural network (BP) model, is optimized using methods such as genetic algorithms (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and their combination to improve model stability and fitting accuracy. Using the total number and increment of insects trapped and killed, the number of installed intelligent pest control devices (2), and their time series as input variables, the algorithm predicts pest density within the area covered by the present invention, thereby achieving pest early warning.

[0133] like Figure 6 As shown, the booster 10, high-voltage controller 11, insect-killing net electrode 12 and pulse counting and control unit 13 together constitute a high-voltage insect-killing subsystem 9; the solar cell 15, power controller 16 and battery 17 together constitute a solar self-powered electronic system 14; the LED light-emitting chip 19, LED driver 20, insect-attracting unit 21, brushless fan 22 and insect-attracting unit controller 23 together constitute an insect-trapping subsystem 18.

[0134] The working process of the present invention is as follows:

[0135] S1, system preparation stage;

[0136] The present invention belongs to a set of software and hardware combined system. In the system preparation stage, the hardware connection between the edge computing server 6, the network adapter 7 and the microcomputer terminal 8 should be completed first, and the power should be turned on. At this time, the edge computing server 6 is turned on and runs, and according to the planned task program settings, the network adapter 7 and the wireless communication adapter 5 are initialized, and the relevant startup information is displayed on the microcomputer terminal 8.

[0137] At the same time, the user installs the intelligent pest control device 2 in an agricultural environment. The solar power system 14 in the intelligent pest control device 2 automatically begins operating, generating photovoltaic power through the solar cells 15 receiving sunlight. The power controller 16 then stabilizes the output voltage of the system operating power and charges the battery 17. Once the system operating power is established, the microcontroller 24 is powered on and begins to perform a hardware self-test on the booster 10, high-voltage controller 11, pulse counting and control unit 13, LED driver 20, brushless fan 22, and insect trap controller 23. The self-test results are recorded, and the intelligent pest control device 2 then enters a standby state.

[0138] S2, system startup phase;

[0139] After step S1 is completed, the system will execute S2.1 edge computing server startup process and S2.2 intelligent pest control device startup process.

[0140] S2.1, Edge computing server startup process;

[0141] After the system preparation phase described in step S1 is completed, the edge computing server automatically starts the node grouping program and remote control service framework, sends a communication handshake instruction to the intelligent pest control device 2 through the wireless communication adapter 5, and waits for signal feedback. If a "node normal" feedback signal is received within the preset time, the corresponding intelligent pest control device 2 is marked as "online state". If the response times out or the feedback signal is abnormal, it is marked as "abnormal state". For the intelligent pest control device 2 in "abnormal state", the edge computing server will retry the handshake multiple times. If it still fails to respond after the retry, the corresponding intelligent pest control device 2 is marked as "offline state". The remaining devices that have been retried to connect are automatically recorded as "warning state". At this time, the wireless communication link between the edge computing server and the intelligent pest control device is completed, and the step S2.1 process ends.

[0142] S2.2, Intelligent pest control device startup process;

[0143] When the edge computing server 6 issues a communication handshake command via the wireless communication adapter 5, the wireless network adapter 26 in each intelligent pest control device 2 is activated, waking up the microcontroller 24. At this point, the microcontroller 24 encodes the initialization self-test result from step S1 via the encoding chip 25, modulates it via the wireless network adapter 26, and transmits it via the embedded antenna 27, thus implementing signal feedback from the intelligent pest control device 2 to the edge computing server 6. The intelligent pest control device 2 then enters a command waiting state, and the process ends at step S2.2.

[0144] The above steps S2.1-S2.2 process describes the method for starting the automatic operation process of the present invention. As a supplement, the user can send an operation instruction to the edge computing server 6 through the microcomputer terminal 8 at any time to manually trigger the execution of the above process.

[0145] S3, device initialization stage;

[0146] The edge computing server 6 starts the "node grouping service" program. Using the graphical interface provided by the microcomputer terminal 8, the user binds the intelligent pest control device 2 to geographic coordinates and assigns a task queue in the lightweight agricultural regional GIS. The software in the microcomputer terminal 8 then automatically generates a "node mapping allocation table" and submits it to the edge computing server 6. Based on the "node mapping allocation table," the edge computing server 6 issues grouping instructions to the intelligent pest control devices 2 in the agricultural environment. The microcontroller 24 receives and decodes the instructions through the encoding chip 25, wireless network adapter 26, and embedded antenna 27, recording the grouping information corresponding to the device.

[0147] The microcontroller 24 in the intelligent pest control device 2 clears and calibrates the pulse counting and control unit 13 to achieve initialization; then the microcontroller 24 detects and reads the initial capacitance value of the insect density sensing electrode 44 and records it. At this time, the device initialization phase process described in step S3 ends.

[0148] S4, pest control and perception process;

[0149] When the system of the present invention is used for the first time after deployment or restarted after long-term inactivity, in order to ensure the efficiency of pest control, the edge computing server 6 first attempts to connect to the cloud database through the network adapter 7 to download data such as the type of pests in the area, the average statistical density of pests, and the time of pest occurrence. After making decisions based on such data, corresponding control instructions are issued to the intelligent pest control devices 2 in each group. If there is no relevant recorded data in the application area or the network adapter 7 is not connected to an available network, the user is notified to make settings. At this time, the user can select the "default mode" to run the system of the present invention, or make manual settings. After receiving the control instructions, the intelligent pest control device 2 adjusts the output voltage of the booster 10 in the device, the luminous intensity and output spectrum of the LED light-emitting sheet 19, the speed of the brushless fan 22, the operating temperature of the insect attractant unit 21 and other parameters through the microcontroller 24.

[0150] LED light sheet 19 emits UV light of an appropriate spectrum and intensity. Simultaneously, brushless fan 22 draws air through insect screen assembly 36, passes through pheromone release module 32, and is discharged from the top of intelligent pest control device 2, causing the signal molecules to diffuse and release. Stimulated by the light, sex pheromones, or signal odor molecules, pests are attracted to the vicinity of intelligent pest control device 2, effectively attracting them.

[0151] Affected by the airflow generated by the brushless fan 22, the pests enter the insect-killing net assembly 36. For larger pests, two high-voltage pulse discharge processes will be triggered: first, the insect body will connect the circuit between the outer shielding net 38 and the positive potential electrode 39. At the same time as the discharge occurs, the potential of the outer shielding net 38 will show a rising edge signal, which is captured by the pulse counting and control unit 13, and the recording circuit therein is reset. When the pests further enter the insect-killing net assembly 36, the potential of the outer shielding net 38 will show a falling edge signal. At this time, the recording circuit state value is flipped and locked, and a "trigger signal" is recorded. When the pests enter the area between the positive potential electrode 39 and the negative potential electrode 40, a second high-voltage pulse discharge will be triggered. At this time, a pair of opposite "step signals" will appear on the positive potential electrode 39 and the negative potential electrode 40. The signal is collected by the pulse counting and control unit 13, and the killed pests then fall onto the collection tray 34, achieving pest extermination. Microcontroller 24 compares the timing and frequency of the "trigger signal" and the "step signal" to predict the frequency of pest electric shock events. Additionally, because multiple discharges occur during pest strikes in practice, microcontroller 24 employs digital filtering to remove high-frequency signals and reduce prediction errors.

[0152] Smaller pests may pass directly through the insect-killing net assembly 36 without generating effective discharge. In this case, the present invention primarily utilizes physical adhesion to capture the pests. The composite bio-trapping plate 45 utilizes a highly viscous substrate, which adheres to the pests upon contact. As the amount of pest adhesion increases, the distributed capacitance between the insect density sensing electrode 44 and the composite bio-trapping plate 45 increases. This change is automatically measured by the microcontroller 24 using an AC small-signal method. This capacitance increment is detected by the insect density sensing electrode 44, and the changes in pest density on the surface of the composite bio-trapping plate 45 are estimated using a built-in fitting algorithm.

[0153] The above process continues continuously during device operation. The intelligent pest control device 2, via the wireless network adapter 26 and embedded antenna 27, transmits information on changes in pest density on the surface of the composite biological trapping plate 45 and statistical information on pest strikes by the insecticide net assembly 36 to the edge computing server 6. The edge computing server 6 runs a pest statistics algorithm, synthesizing the information fed back by the multiple intelligent pest control devices 2 within each regional grouping to calculate the number of pests captured and their rate of change within the corresponding regional grouping. It then aggregates the information from multiple regional groups to calculate the number of pests captured and their rate of change within the entire system's operating area. Simultaneously, the edge computing server 6 uses an enhanced BP algorithm to predict pest density and pest risk within the system's coverage area. This predicted information can be uploaded to a cloud database for reference. Additionally, the user can determine whether this predicted information is automatically uploaded. For situations requiring confidentiality or specific requirements, all statistical and predicted information is stored locally to enhance information security.

[0154] S5, device self-feedback control process;

[0155] Furthermore, during the long-term operation of the device, the edge computing server 6 will automatically adjust the operating status of the intelligent pest control devices 2 within each regional grouping multiple times based on the pest statistical density and pest risk prediction information obtained in step S4 to improve their operating efficiency and reduce energy waste. Furthermore, during this control process, the edge computing server 6 will synchronously adjust the pest statistical algorithm and the pest statistical correction factor to reduce errors introduced by changes in the operating efficiency of the intelligent pest control devices 2, thereby improving the long-term operational stability of the system.

[0156] In addition, when the intelligent pest control device 2 within the regional group cannot kill pests normally due to a malfunction, the edge computing server 6 will reallocate the task queue and adjust the operating parameters of the normal or standby intelligent pest control device 2 to avoid a significant impact on the pest killing efficiency within the regional group.

Claims

1. A distributed intelligent pest control system, characterized in that: The distributed intelligent pest control system comprises an intelligent pest control device (2), an antenna module (4), a wireless communication adapter (5), an edge computing server (6), a network adapter (7) and a microcomputer terminal (8); A plurality of intelligent pest control devices (2) are deployed in pest control sites for trapping and killing pests and automatically calculating the amount of pests killed and pest density change information; the pest control sites include fields, orchards, greenhouses, sheds, livestock and poultry farms, and domestic waste treatment sites; the plurality of intelligent pest control devices (2) are allocated and combined into different regional groups and task queues by an edge computing server (6); the plurality of intelligent pest control devices (2) constitute a pest sensing control array (1); The wireless communication adapter (5) is electrically connected to the antenna module (4) and the edge computing server (6), respectively; the antenna module (4) is used to transmit and receive electromagnetic waves, and to send control instructions to each intelligent pest control device (2) in the pest sensing and control array (1) through the wireless channel (3) and receive returned pest monitoring information; the pest monitoring information is transmitted in the form of data packets, including high-voltage pest killing pulse counts, trapping plate insect capture counts, and equipment operation status information; The wireless communication adapter (5) is used for fast parallel execution of encoding and modulation of the control instruction stream sent by the edge computing server (6), and decoding of the status and monitoring data stream returned by the intelligent pest control device (2); The edge computing server (6) has a plurality of universal digital signal interfaces, which are electrically connected to the network adapter (7) and the microcomputer terminal (8) respectively; the network adapter (7) is used to realize the edge computing server (6) accessing the computer network and providing network data filtering; the microcomputer terminal (8) is used to provide a human-computer interaction interface and realize device management; the edge computing server (6) is used to summarize the statistical information of each intelligent pest control device (2) in each regional group, calculate the pest killing amount and its change rate in each regional group and in the entire system coverage area, and predict the pest density and pest risk in the entire system coverage area; The edge computing server (6) automatically adjusts the working state of each intelligent pest control device (2) in each regional group based on the predicted pest density and pest risk in the entire system coverage area; when the intelligent pest control device (2) in the regional group is unable to kill pests normally due to a fault, the edge computing server (6) reallocates the task queue and adjusts the operating parameters of the normal or standby intelligent pest control device (2).

2. The distributed intelligent pest control system according to claim 1, characterized in that: In the process of the edge computing server (6) automatically adjusting the working state of each intelligent pest control device (2) in each regional group, the edge computing server (6) synchronously adjusts the pest statistical algorithm and the pest statistical correction factor; The pest statistics algorithm uses the pest killing amount fed back by each intelligent pest control device (2) in the entire system coverage area as an input variable, obtains the total pest killing amount in the area by accumulation, and calculates the pest killing amount change and the change rate over time in combination with time information; obtains the relative weight information of the increment of killed pests in the effective area of ​​each intelligent pest control device (2) based on the normalization method, and automatically adjusts the working state of the intelligent pest control device (2) by using the feedback method; The pest statistics correction factor is a dimensionless parameter that assists the correct operation of the pest statistics algorithm and has a functional relationship with the continuous operation time of the intelligent pest control device (2) so as to reduce the interference error of the pest statistics caused by the change of the operation efficiency of the intelligent pest control device (2).

3. The distributed intelligent pest control system according to claim 1, characterized in that: The intelligent pest control device (2) comprises an external control unit and an electrical system; the external control unit comprises a solar cell (15), a top cover (28), a left support column (29), a right support column (30), a brushless fan bracket (31), a pheromone release module (32), an insect trap module (33), a collection tray (34), an electrical box (35) and an insect killing net assembly (36); The insect-killing net assembly (36) is cylindrical and has a three-layer structure of an inner surface, an interlayer and an outer surface; the insect-killing net assembly (36) includes an insect-killing net electrode (12) and an outer shielding net (38); the insect-killing net electrode (12) includes a grounding electrode, a positive potential electrode (39) and a negative potential electrode (40); the outer shielding net (38) is located on the outer surface of the insect-killing net assembly (36) and is electrically connected to the grounding electrode and then grounded; the positive potential electrode (39) is installed in the interlayer of the insect-killing net assembly (36); the negative potential electrode (40) is installed on the inner surface of the insect-killing net assembly (36); the top cover (28) is fixed to the top of the insect-killing net assembly (36) through the left support column (29) and the right support column (30); the solar cell (15) is fixed to the upper surface of the top cover (28); the information The pheromone release module (32) and the insect attracting lamp module (33) are arranged inside the insect killing net assembly (36); the brushless fan (22) is fixed to the top of the insect killing net assembly (36) through the brushless fan bracket (31), and is used to suck air from the external environment through the insect killing net assembly (36), flow through the pheromone release module (32) and be discharged from the upper part of the brushless fan (22), and the discharged air flow is blocked and guided by the top cover (28) and blown out in a horizontal direction below the top cover (28) to promote the diffusion of the insect attracting pheromone, and at the same time, a negative pressure flow field flowing into the device is formed near the insect killing net assembly (36) to promote the insects to enter the insect killing net assembly (36) to achieve killing; the collecting tray (34) is installed at the bottom of the insect killing net assembly (36); the electrical box (35) is fixed to the lower surface of the collecting tray (34) and is used to accommodate the electrical system; The electrical system includes a booster (10), a high-voltage controller (11), a pulse counting and control unit (13), an electric energy controller (16), a battery (17), an LED driver (20), an insect trap unit controller (23), a microcontroller (24), an encoding chip (25), a wireless network adapter (26), and an embedded antenna (27); The booster (10) has a low voltage input terminal, a signal control terminal and a high voltage output terminal; the high voltage output terminal of the booster (10) is electrically connected to a high voltage controller (11); the high voltage negative electrode of the high voltage controller (11) is electrically connected to a negative potential electrode (40) of an insecticide net electrode (12); the high voltage positive electrode of the high voltage controller (11) is electrically connected to a positive potential electrode (39) of an insecticide net electrode (12); and the protective grounding electrode of the high voltage controller (11) is electrically connected to a grounding electrode of an insecticide net electrode (12); The signal control end of the booster (10) and the signal control end of the high-voltage controller (11) are electrically connected to the pulse counting and control unit (13) respectively. The pulse counting and control unit (13) is used to adjust the output voltage of the booster (10) and control the on / off of the high-voltage controller (11), thereby controlling the pest killing effect of the insect-killing net electrode (12); at the same time, the pulse counting and control unit (13) is used to count the high-voltage discharge pulses in the insect-killing net electrode (12) during the pest killing process, thereby automatically counting the amount of pests killed; The LED driver (20) is electrically connected to the LED light-emitting sheet (19) and is used to drive and control the operation of the LED light-emitting sheet (19) to achieve regulation of the luminous intensity and luminous spectrum; The pheromone release module (32) includes a plurality of insect trapping units (21) consisting of a heating assembly (43), an insect density sensing electrode (44) and a composite biological trapping plate (45); the insect density sensing electrode (44) is mechanically connected to the heating assembly (43); the composite biological trapping plate (45) is mounted on the upper surface of the insect density sensing electrode (44); the heating assembly (43) is used to heat the composite biological trapping plate (45) to promote the diffusion of information odor molecules and improve the viscosity of the composite biological trapping plate (45) under low ambient temperature conditions; the composite biological trapping plate (45) adheres to small pests while releasing information odor molecules, thereby achieving an insect extermination function; the distributed capacitance between the insect density sensing electrode (44) and the composite biological trapping plate (45) increases as the amount of adhered insects increases; The insect trap unit controller (23) is electrically connected to the insect trap unit (21) and is used to drive the heating component (43) of the insect trap unit (21) to heat the composite biological trapping plate (45) to release insect pheromones and adjust the heating power of the heating component (43) to achieve temperature control. At the same time, the distributed capacitance between the insect density sensing electrode (44) and the composite biological trapping plate (45) is automatically measured by an AC small signal method, and the capacitive reactance increment of the insect density sensing electrode (44) is determined and sent to the microcontroller (24); The working power supply of the LED driver (20), the insect attracting unit controller (23) and the brushless fan (22) is a low-voltage direct current, the negative electrode of which is grounded, and the positive potential end is electrically connected in parallel and in parallel with the low-voltage input end of the booster (10); The power controller (16) is electrically connected to the solar cell (15) and the storage battery (17) respectively; the power controller (16) tracks the optimal power point of the solar cell (15) based on the MPPT method, and realizes voltage stabilization output and charge and discharge management of the storage battery (17); the storage battery (17) is used to store excess power, thereby realizing stable operation of the intelligent pest control device (2) at night and in low light conditions; The microcontroller (24) is electrically connected to the pulse counting and control unit (13), the LED driver (20), the insect attracting unit controller (23) and the brushless fan (22) respectively, and is used to realize the working state control and feedback signal processing of the pulse counting and control unit (13), the LED driver (20), the insect attracting unit controller (23) and the brushless fan (22); the encoding chip (25) and the wireless network adapter (26) are electrically connected to the microcontroller (24), and the encoding chip (25) is used for encoding and decoding operations of the communication data stream between the intelligent pest control device (2) and the edge computing server (6), thereby reducing the workload of the microcontroller (24); the wireless network adapter (26) is electrically connected to the embedded antenna (27), and the two cooperate to operate and are used to connect the microcontroller (24) to the wireless channel (3).

4. The distributed intelligent pest control system according to claim 3, characterized in that: The insect-killing net assembly (36) kills large-sized pests based on a high-voltage pulse discharge method. When a large-sized pest enters the insect-killing net assembly (36), two high-voltage pulse discharge processes are triggered: first, the pest body connects the circuit between the outer shielding net (38) and the positive potential electrode (39). When the discharge occurs, the outer shielding net (38) generates a rising edge signal, which is captured by the pulse counting and control unit (13). The recording circuit therein is reset. When the pest further enters the insect-killing net assembly (36), the outer shielding net (38) generates a rising edge signal. A falling edge signal is generated, at which time the recorded circuit state value is flipped and locked, and a trigger signal is recorded. When the pest enters the area between the positive potential electrode (39) and the negative potential electrode (40), a second high-voltage pulse discharge is triggered. At this time, a pair of step signals with opposite phases appear on the positive potential electrode (39) and the negative potential electrode (40). The signal is collected by the pulse counting and control unit (13), and the killed pests fall onto the collection plate (34), thereby achieving pest killing. The microcontroller (24) analyzes and predicts the frequency of pest electric shock events by comparing the timing and occurrence frequency of the trigger signal and the step signal collected by the pulse counting and control unit (13), as well as the return current waveform of the outer shielding net (38) and the output current waveform of the positive potential electrode (39); The composite biological trapping plate (45) uses a high-viscosity substrate, and when pests come into contact with it, they are adhered. At the same time, as the amount of pest adhesion increases, the distributed capacitance between the insect density sensing electrode (44) and the composite biological trapping plate (45) increases. The insect trapping unit controller (23) automatically measures the distributed capacitance between the insect density sensing electrode (44) and the composite biological trapping plate (45) by an AC small signal method, determines the capacitive reactance of the insect density sensing electrode (44), and sends it to the microcontroller (24). The microcontroller (24) runs a fitting algorithm to calculate the insect pest density on the surface of the composite biological trapping plate (45) and its change amount. The fitting algorithm run by the microcontroller (24) uses the capacitive reactance of the insect density sensing electrode (44) as an input variable, and calculates the density of pests adhering to the surface of the composite biological trapping plate (45) through a calibrated and debugged capacitive reactance-pest density working curve, and further obtains the total amount of adhering insects and its change over time; The composite biological trapping plate (45) is prepared by compounding sex pheromone analogues of various pests to achieve the trapping of various pests; or is prepared by using a gel containing pest-sensitive chemical components to achieve the trapping of mosquitoes and flies based on odor molecules.

5. The distributed intelligent pest control system according to claim 3, characterized in that: The intelligent pest control device (2) cooperates with the edge computing server (6) to operate, thereby realizing statistics of the amount of trapped pests, prediction of pest density and prediction of pest risk; the microcontroller (24) of the intelligent pest control device (2) feeds back information on the change of pest density on the surface of the composite biological trapping plate (45) and statistical information on the pest attack of the insect killing net component (36) to the edge computing server (6) through the wireless network adapter (26) and the embedded antenna (27); the edge computing server (6) runs a pest statistics algorithm, integrates the information fed back by the multiple intelligent pest control devices (2) in each regional group, and calculates the amount of trapped pests and the rate of change thereof in the corresponding regional group; then, the situation of the multiple regional groups is integrated to calculate the amount of trapped pests and the rate of change thereof in the entire system coverage area; at the same time, the edge computing server (6) obtains prediction information on the pest density and the pest risk in the system coverage area based on the enhanced BP algorithm.

6. The distributed intelligent pest control system according to claim 3, characterized in that: The left support column (29) and the right support column (30) are made of insulating material; insulating support blocks (37) are provided between the left support column (29), the right support column (30) and the insecticide net assembly (36), between the brushless fan bracket (31) and the insecticide net assembly (36), and between the collecting tray (34) and the insecticide net assembly (36).

7. The distributed intelligent pest control system according to claim 3, characterized in that: The insect trap lamp module (33) includes a heat sink (41) and an LED chip (42); a plurality of LED chips (42) are mechanically connected to the outer surface of the heat sink (41) and are electrically connected to each other in parallel to form an LED light-emitting sheet (19); the heat sink (41) is used to buffer and dissipate heat generated by the LED chip (42) to stabilize the operating temperature of the LED chip (42); the contact surface between the LED chip (42) and the heat sink (41) is filled with silicone gel with high thermal conductivity or is polished; the LED chip (4) is prepared using a voltage-modulated ultraviolet-near-ultraviolet LED device.

8. The distributed intelligent pest control system according to claim 3, characterized in that: The booster (10) adopts a high-frequency PWM driven flyback power supply topology or a bridge excitation topology, realizes voltage conversion based on a mutual inductance transformer, or adopts an ultrasonic piezoelectric transformer to realize voltage boosting, or adopts direct rectification or multiplier voltage rectification to realize high-voltage DC output.

9. A control method for a distributed intelligent pest control system according to any one of claims 1 to 8, characterized in that: The control method comprises the following steps: S1, system preparation stage; First, the hardware connection between the edge computing server (6), the network adapter (7) and the microcomputer terminal (8) is completed, and the power is turned on. At this time, the edge computing server (6) is turned on and runs, and the network adapter (7) and the wireless communication adapter (5) are initialized according to the scheduled task program settings, and relevant startup information is displayed on the microcomputer terminal (8); At the same time, the user installs the intelligent pest control device (2) in an agricultural environment. At this time, the solar self-powered system (14) in the intelligent pest control device (2) automatically starts to operate, receives light through the solar cell (15) to generate photovoltaic power, and the power controller (16) outputs the system working power in a stable voltage and charges the battery (17); when the system working power is established, the microcontroller (24) is powered and operates, performs hardware self-test on the booster (10), the high-voltage controller (11), the pulse counting and control unit (13), the LED driver (20), the brushless fan (22) and the insect trap unit controller (23), and records the self-test results, and then the intelligent pest control device (2) enters the standby state; S2, system startup phase; After step S1 is completed, the system will execute S2.1 edge computing server startup process and S2.2 intelligent pest control device startup process; S2.1, Edge computing server startup process; After the system preparation phase of step S1 is completed, the edge computing server automatically starts the node grouping program and the remote control service framework, sends a communication handshake instruction to the intelligent pest control device (2) through the wireless communication adapter (5) and waits for signal feedback. If a normal feedback signal from the node is received within the preset time, the corresponding intelligent pest control device (2) is marked as online. If the response times out or the feedback signal is abnormal, it is marked as abnormal. For the intelligent pest control device (2) in abnormal state, the edge computing server will retry the handshake multiple times. If it still fails to respond after the retry, the corresponding intelligent pest control device (2) is marked as offline, and the remaining devices that have been retried to connect are automatically recorded as warning status. At this time, the wireless communication link between the edge computing server and the intelligent pest control device is completed, and the step S2.1 process ends. S2.2, Intelligent pest control device startup process; When the edge computing server (6) sends a communication handshake instruction through the wireless communication adapter (5), the wireless network adapter (26) in each intelligent pest control device (2) is activated and wakes up the microcontroller (24); at this time, the microcontroller (24) encodes the initialization self-test result in step S1 through the encoding chip (25), modulates it through the wireless network adapter (26), and transmits it based on the embedded antenna (27), thereby realizing signal feedback from the intelligent pest control device (2) to the edge computing server (6); then the intelligent pest control device (2) enters the command waiting state, and the step S2.2 process ends at this time; S3, device initialization stage; The edge computing server (6) starts the node grouping service program. The user binds the intelligent pest control device (2) with the geographic coordinates and divides the task queue in the lightweight agricultural area GIS through the graphical interface provided by the microcomputer terminal (8). At this time, the software in the microcomputer terminal (8) automatically generates a node mapping allocation table and submits it to the edge computing server (6). The edge computing server (6) issues a grouping instruction to the intelligent pest control device (2) in the agricultural environment according to the node mapping allocation table. The microcontroller (24) receives and decodes the instruction through the encoding chip (25), the wireless network adapter (26) and the embedded antenna (27), and records the grouping information corresponding to the device. The microcontroller (24) in the intelligent pest control device (2) clears and calibrates the pulse counting and control unit (13) to achieve initialization; then the microcontroller (24) detects and reads the initial capacitance value of the insect density sensing electrode (44) and records it, and the device initialization phase process of step S3 ends at this time; S4, pest control and perception process; The edge computing server (6) first attempts to connect to the cloud database through the network adapter (7) to download data such as the pest type, average statistical density of pests, and time of pest occurrence in the area. After making decisions based on such data, the server issues corresponding control instructions to the intelligent pest control device (2) in each group. If there is no relevant recorded data in the application area or the network adapter (7) is not connected to an available network, the user is notified to make settings. At this time, the user selects the default mode to run the system or makes manual settings. After receiving the control instructions, the intelligent pest control device (2) adjusts the output voltage of the booster (10), the luminous intensity and output spectrum of the LED light-emitting chip (19), the speed of the brushless fan (22), and the working temperature of the insect attractant unit (21) in the device through the microcontroller (24). The LED light-emitting sheet (19) emits UV light of suitable spectrum and intensity, and at the same time, the brushless fan (22) draws air from the insect-killing net assembly (36), flows through the pheromone release module (32), and is discharged from the upper part of the intelligent pest control device (2), so that the signal molecules are diffused and released; after being stimulated by light information, sex pheromones or signal odor molecules, the pests are attracted to the vicinity of the intelligent pest control device (2), and this process achieves the attraction of the pests; Affected by the airflow generated by the brushless fan (22), the insect pests enter the insect-killing net assembly (36). For larger insect pests, two high-voltage pulse discharge processes will be triggered: first, the insect body will connect the circuit between the outer shielding net (38) and the positive potential electrode (39). At the same time as the discharge occurs, the outer shielding net (38) potential will show a rising edge signal. This signal is captured by the pulse counting and control unit (13), and the recording circuit therein is reset. When the insect pests further enter the insect-killing net assembly (36), the outer shielding net (38) potential will show a falling edge signal. At this time, the recording circuit is reset. The circuit state value is flipped and locked, and a trigger signal is recorded. When the pest enters the area between the positive potential electrode (39) and the negative potential electrode (40), a second high-voltage pulse discharge is triggered. At this time, a pair of opposite step signals appear on the positive potential electrode (39) and the negative potential electrode (40). The signal is collected by the pulse counting and control unit (13), and the killed pests fall onto the collection plate (34), thereby achieving pest killing. The microcontroller (24) predicts the frequency of pest electric shock events by comparing the timing and occurrence frequency of the trigger signal and the step signal. For insect pests of smaller size, they may directly pass through the insect-killing net assembly (36) without generating effective discharge. When the insect pests touch the composite biological trapping plate (45), they will be adhered. At the same time, as the amount of insect pest adhesion increases, the distributed capacitance between the insect density sensing electrode (44) and the composite biological trapping plate (45) will increase. The change is automatically measured by the microcontroller (24) through the AC small signal method, and the capacitance increment of the insect density sensing electrode (44) is detected. Based on the built-in fitting algorithm, the change of the insect pest density on the surface of the composite biological trapping plate (45) is inferred; The intelligent pest control device (2) feeds back pest density change information on the surface of the composite biological trapping plate (45) and pest attack statistics of the insect killing net component (36) to the edge computing server (6) through the wireless network adapter (26) and the embedded antenna (27); the edge computing server (6) runs a pest statistics algorithm to integrate the information fed back by multiple intelligent pest control devices (2) in each regional group, and calculates the pest capture amount and its change rate in the corresponding regional group; then, the situation of multiple regional groups is integrated to calculate the pest capture amount and its change rate in the entire system working area; at the same time, the edge computing server (6) predicts the pest density and pest risk in the system coverage area based on the enhanced BP algorithm, and uploads the predicted information to the cloud database for reference; S5, device self-feedback control process; Based on the pest statistical density and pest risk prediction information obtained in step S4, the edge computing server (6) will automatically adjust the working status of the intelligent pest control device (2) in each regional group multiple times to improve its operating efficiency and reduce energy waste; at the same time, during the above-mentioned regulation process, the edge computing server (6) will synchronously adjust the pest statistical algorithm and the pest statistical correction factor to reduce the error introduced by the change in the working efficiency of the intelligent pest control device (2) and improve the long-term operation stability of the system.

Images