Tobacco beetle monitoring system, tobacco beetle monitoring method and storage medium

Abstract

The invention discloses a cigarette beetle monitoring system, a cigarette beetle monitoring method and a storage medium, the cigarette beetle monitoring system comprises at least one trapping intelligent terminal and an intelligent identification subsystem, a first communication processing module of the trapping intelligent terminal is used for preprocessing an original image to obtain a target image; and combining the currently set first position information, the target image and the current system timestamp to obtain target information, and transmitting the target information to the intelligent identification subsystem, a second communication processing module of the intelligent identification subsystem being used for storing the received target information, performing cigarette beetle identification on the target image in the target information, and sending the cigarette beetle identification information to the intelligent identification subsystem. And determining second position information and counting information of the cigarette beetles, and marking the target image according to the second position information and the counting information to obtain a target result image. The trapping result image of the trapping intelligent terminal is automatically and accurately identified, the corresponding position information and counting information are output, and reliable reference information is provided for monitoring the cigarette beetles.

Description

Technical Field

[0001] This application relates to the field of automation technology. Specifically, it relates to a cigarette beetle monitoring system, a cigarette beetle monitoring method, and a storage medium. Background Art

[0002] Since the adults and larvae of tobacco beetles can burrow into tobacco or other grains, devouring the germ and endosperm, resulting in a decline in quality, nutrient loss, mildew, etc. In addition, they may also spread bacteria and fungi, contaminating grain or tobacco products, leading to the destruction of the entire production batch. Therefore, preventing and controlling cigarette beetles is of crucial importance. By monitoring cigarette beetles, pests can be detected and dealt with in a timely manner, thus ensuring the quality and safety of tobacco or grain products. However, in the prior art, there is usually a cigarette beetle trapping device, but it requires manual identification and counting of cigarette beetles, increasing labor costs and having a large implementation difficulty, and it is unable to achieve good monitoring of cigarette beetles.

[0003] In view of the above problems, there is an urgent need for an effective technical solution at present. Summary of the Invention

[0004] The purpose of this application is to provide a cigarette beetle monitoring system, a cigarette beetle monitoring method, and a storage medium, which can solve the problems in the prior art that manual identification and counting of cigarette beetles are required, increasing labor costs and having a large implementation difficulty, and being unable to achieve good monitoring of cigarette beetles. It realizes that by deploying at least one trapping intelligent terminal, cigarette beetles in different regions can be trapped and accurate trapping result images can be provided. By deploying an intelligent recognition subsystem, the trapping result images of at least one trapping intelligent terminal can be automatically and accurately recognized, and the corresponding position information and counting information can be output, providing reliable reference information for monitoring cigarette beetles.

[0005] In a first aspect, this application provides a cigarette beetle monitoring system, which includes: at least one trapping intelligent terminal and an intelligent recognition subsystem, and the trapping intelligent terminal is connected to the intelligent recognition subsystem through a wireless network;

[0006] The trapping intelligent terminal is provided with a trapping module, a camera module and a first communication processing module. Among them, the trapping module includes a trapping plate and a trapping core arranged on the trapping plate, and is used to capture cigarette beetles. The camera module is connected to the first communication processing module. The first communication processing module is used to transmit a picture-taking command to the camera module when a preset picture-taking trigger condition is met. The camera module is used to capture the original image of the trapping plate when receiving the picture-taking command, and transmit the original image to the first communication processing module. The first communication processing module is also used to preprocess the original image to obtain a target image, combine the currently set first position information, the target image and the current system timestamp to obtain target information, and transmit the target information to the intelligent recognition subsystem;

[0007] The intelligent recognition subsystem includes a second communication processing module and a result display module. The second communication processing module is connected to the result display module. The second communication processing module is used to store the received target information, identify cigarette beetles in the target image of the target information, determine the second position information and the counting information of the cigarette beetles, perform annotation processing on the target image according to the second position information and the counting information to obtain a target result image, and transmit the target result image to the result display module. The result display module is used to display the target result image.

[0008] Optionally, the second communication processing module is further used to generate a quantity distribution map and a quantity change curve according to the recorded received first position information, system timestamp, and the determined counting information corresponding to the target image, and transmit the quantity distribution map and the quantity change curve to the result display module. The result display module is further used to display the quantity distribution map and the quantity change curve.

[0009] Optionally, the second communication processing module is further used to perform early warning analysis on the quantity distribution map and the quantity change curve, generate corresponding early warning information, and transmit the early warning information to the result display module. The result display module is further used to display the early warning information.

[0010] Optionally, the second communication processing module is further configured to send a status confirmation request to the first communication processing module of the at least one trapping intelligent terminal. The first communication processing module is further configured to, upon receiving the status confirmation request, reply with the current status information to the second communication processing module. The second communication processing module is further configured to, upon receiving at least one piece of current status information, determine the status summary information of the trapping intelligent terminal according to the at least one piece of current status information, and transmit the status summary information to the result display module. The result display module is further configured to display the device status of each trapping intelligent terminal according to the status summary information.

[0011] Optionally, the satisfaction of the preset image capture trigger condition includes:

[0012] Reaching a preset time node or receiving a trigger image capture command sent by the intelligent recognition subsystem.

[0013] Optionally, the trapping intelligent terminal further includes a fill light module. The fill light module is connected to the first communication processing module. The first communication processing module is further configured to, before transmitting the image capture command to the camera module, transmit a turn-on fill light command to the fill light module. The fill light module is further configured to turn on the fill light when receiving the turn-on fill light instruction.

[0014] Optionally, the trapping intelligent terminal further includes a mobile power supply module. The mobile power supply module is respectively connected to the camera module and the first communication processing module. The mobile power supply module is used to supply power to the camera module and the first communication processing module.

[0015] Optionally, the trapping intelligent terminal is further provided with a two-dimensional code. The camera module can also be used to collect the two-dimensional code image corresponding to the two-dimensional code, and transmit the two-dimensional code image to the first communication processing module. The first communication processing module is further configured to identify the two-dimensional code image to obtain the first position information.

[0016] In a second aspect, the present application provides a tobacco beetle monitoring method, which is applied to the tobacco beetle monitoring system provided in the embodiments of the present application. The method includes:

[0017] When the preset image capture trigger condition is satisfied, the first communication processing module transmits an image capture command to the camera module. When the camera module receives the image capture command, it captures the original image of the trapping board, and transmits the original image to the first communication processing module. The first communication processing module preprocesses the original image to obtain a target image, combines the currently set first position information, the target image, and the current system timestamp to obtain target information, and transmits the target information to the intelligent recognition subsystem;

[0018] The second communication processing module stores the received target information, identifies the tobacco beetles in the target image of the target information, determines the second position information and the counting information of the tobacco beetles, and sends the position information, the counting information, and the target image to the result display module. The result display module performs annotation processing on the target image according to the position information and the counting information to obtain a target result image, and displays the target result image.

[0019] In a third aspect, the present application provides a computer-readable storage medium, which includes a program for the tobacco beetle monitoring method. When the program for the tobacco beetle monitoring method is executed by a processor, the steps of the tobacco beetle monitoring method are implemented.

[0020] As can be seen from the above, the tobacco beetle monitoring system, the tobacco beetle monitoring method, and the storage medium provided by the present application. The system includes: at least one trapping intelligent terminal and an intelligent recognition subsystem. The trapping intelligent terminal is connected to the intelligent recognition subsystem through a wireless network. The trapping intelligent terminal is provided with a trapping module, a camera module, and a first communication processing module. Among them, the trapping module includes a trapping board and a trapping core arranged on the trapping board, which is used to trap tobacco beetles. The camera module is connected to the first communication processing module. The first communication processing module is used to transmit a picture-taking command to the camera module when a preset picture-taking trigger condition is met. The camera module is used to collect the original image of the trapping board when the picture-taking command is received, and transmit the original image to the first communication processing module. The first communication processing module is also used to preprocess the original image to obtain a target image, combine the currently set first position information, the target image, and the current system timestamp to obtain target information, and transmit the target information to the intelligent recognition subsystem. The intelligent recognition subsystem includes a second communication processing module and a result display module. The second communication processing module is connected to the result display module. The second communication processing module is used to store the received target information, identify the tobacco beetles in the target image of the target information, determine the second position information and the counting information of the tobacco beetles, perform annotation processing on the target image according to the second position information and the counting information to obtain a target result image, and transmit the target result image to the result display module. The result display module is used to display the target result image. This system realizes that by deploying at least one trapping intelligent terminal, tobacco beetles in different regions can be trapped, and an accurate trapping result image can be provided. By deploying the intelligent recognition subsystem, the trapping result images of at least one trapping intelligent terminal can be automatically and accurately recognized, and the corresponding position information and counting information can be output, providing reliable reference information for monitoring tobacco beetles.

[0021] Other features and advantages of the present application will be described in the subsequent specification. Moreover, they will be partially obvious from the specification or understood by implementing the embodiments of the present application. The objectives and other advantages of the present application can be achieved and obtained through the structures specifically pointed out in the written specification, claims, and drawings. Description of the Drawings

[0022] To more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application and should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other relevant drawings can also be obtained based on these drawings.

[0023] Figure 1 Schematic diagram of the cigarette beetle monitoring system provided for the embodiments of the present application;

[0024] Figure 2 Schematic diagram of the structure of the trapping intelligent terminal provided for the embodiments of the present application;

[0025] Figure 3 Schematic diagram of the intelligent recognition subsystem provided for the embodiments of the present application;

[0026] Figure 4 Target result image obtained by performing annotation processing on the target image provided for the embodiments of the present application;

[0027] Figure 5 Flowchart of the cigarette beetle monitoring method provided for the embodiments of the present application. Detailed Embodiments

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of them. The components of the embodiments of the present application usually described and illustrated in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application claimed, but only represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0029] It should be noted that similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first" and "second" are only used for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0030] Please refer to Figure 1 , which is a schematic diagram of a tobacco beetle monitoring system in some embodiments of the present application. The tobacco beetle monitoring system includes at least one trapping intelligent terminal 110 and an intelligent recognition subsystem 120, and the trapping intelligent terminal 110 is connected to the intelligent recognition subsystem 120 through a wireless network.

[0031] It should be noted that the trapping intelligent terminal can be deployed in a specific area of a warehouse storing tobacco, and the number thereof can be one or more. The intelligent recognition subsystem can be deployed on an edge server, and can be specifically set in a factory area, a storage area, a warehouse, a headquarters computer room or a cloud computer room, etc. The wireless network can be a 4G network, a 5G network, etc., and the present application does not make a limitation here.

[0032] Please refer to Figure 2 , which is a schematic structural diagram of a trapping intelligent terminal in some embodiments of the present application. The trapping intelligent terminal 110 is provided with a trapping module 111, a camera module 112 and a first communication processing module 113. Among them, the trapping module 111 includes a trapping board 1111 and a trapping core 1112 arranged on the trapping board 1111, and is used for trapping tobacco beetles. The camera module 112 is connected to the first communication processing module 113. The first communication processing module 113 is used to transmit a picture-taking command to the camera module 112 when a preset picture-taking trigger condition is met. The camera module 112 is used to collect an original image of the trapping board 1111 when receiving the picture-taking command, and transmit the original image to the first communication processing module 113. The first communication processing module 113 is further used to preprocess the original image to obtain a target image, combine the currently set first position information, the target image and the current system timestamp to obtain target information, and transmit the target information to the intelligent recognition subsystem 120;

[0033] It should be noted that the trapping board can be used to trap and kill pests. By taking advantage of the pests' preference for certain colors, shapes, or materials, the pests are attracted to fly towards or stay on the trapping board, thereby achieving the purpose of trapping and killing. The lure core can attract the target organism to approach by using specific features such as specific odors, colors, shapes, etc. The first communication processing module can be provided with a processor and a communication module. The communication module can be provided with a communication antenna for data inter - transmission with the intelligent recognition subsystem. Among them, meeting the preset image - taking trigger conditions includes: reaching a preset time node, or receiving a trigger image - taking command sent by the intelligent recognition subsystem. For example, the trapping intelligent terminal is set to trigger at fixed time points or at fixed time intervals. Another example is that the intelligent recognition system individually triggers a certain trapping intelligent terminal to take pictures, or the intelligent recognition system triggers all online trapping intelligent terminals to take pictures with one key. The pre - processing of the original image can be filtering processing or enhancement processing of the original image. The filtering processing can be mean filtering, Gaussian filtering, median filtering, or bilateral filtering, etc. The enhancement processing can be histogram equalization, normalization, wavelet transform, edge enhancement, or dilation and erosion, etc. This application does not make a limitation here. By combining the currently set first position information, the target image, and the current system timestamp to obtain the target information, and transmitting the target information to the intelligent recognition subsystem, the specific geographical location of the trapping intelligent terminal, the captured image of the cigarette beetle, and the specific capture time can be provided to the intelligent recognition subsystem.

[0034] Please refer to Figure 3 , which is a schematic diagram of the intelligent recognition subsystem in some embodiments of this application. The intelligent recognition subsystem 120 includes a second communication processing module 121 and a result display module 122. The second communication processing module 121 is connected to the result display module 122. The second communication processing module 121 is used to store the received target information, identify the cigarette beetle in the target image of the target information, determine the second position information and the counting information of the cigarette beetle, perform annotation processing on the target image according to the second position information and the counting information to obtain the target result image, and transmit the target result image to the result display module 122. The result display module 122 is used to display the target result image.

[0035] It should be noted that the first communication processing module can be provided with a processor and a communication module for data inter - transmission with the trapping intelligent terminal. The result display module can be used to visually display the processing results such as images and messages output by the first communication processing module, specifically, it can be a display, an interactive panel, etc. For the target image for tobacco beetle recognition, the specific process can be as follows: using an image segmentation method to separate the tobacco beetles in the image from the background for more accurate recognition. Then, feature extraction in different dimensions is performed on the image. For example, color information in the image such as RGB values, HSV values, etc. is extracted to distinguish tobacco beetles from other objects. Another example is to extract shape information in the image such as contours, edges, corner points, etc. to identify the morphology of tobacco beetles. Next, different image recognition algorithms can be used. For example, a template image of tobacco beetles is pre - stored, and then the part similar to the template image is searched in the image to be recognized. Another example is to use machine learning algorithms such as support vector machines and neural networks to train and learn the image, and train a model to recognize tobacco beetles by extracting features in the image. Another example is to use deep learning algorithms such as convolutional neural networks to train and recognize the image, which can automatically extract features in the image and perform classification and recognition. Finally, the first position information of the recognized tobacco beetles is determined, and this first position information can be coordinate information, and the counting information of the tobacco beetles is determined, and this counting information can be the serial number of the tobacco beetles and the number of tobacco beetles. In addition, the tobacco beetles can be marked in the target image according to the second position information and the counting information. Please refer to Figure 4 , which is the target result image obtained by performing annotation processing on the target image provided by the embodiment of the present application.

[0036] As described above, by deploying at least one trapping intelligent terminal, tobacco beetles in different regions can be trapped, and an accurate trapping result image can be provided. By deploying the intelligent recognition subsystem, the trapping result images of at least one trapping intelligent terminal can be automatically and accurately recognized, and the corresponding position information and counting information can be output, providing reliable reference information for monitoring tobacco beetles.

[0037] According to the embodiment of the present invention, the second communication processing module is further configured to generate a quantity distribution map and a quantity change curve according to the recorded received first position information, system timestamp, and the determined counting information corresponding to the target image, and transmit the quantity distribution map and the quantity change curve to the result display module, and the result display module is further configured to display the quantity distribution map and the quantity change curve.

[0038] It should be noted that the second communication processing module can record the information sent by different trapping intelligent terminals multiple times. Among them, the first location information can be the specific geographical location of the trapping intelligent terminal, the system timestamp can be the time when the trapping intelligent terminal reports the statistical result of tobacco beetles, and the counting information can be the number of tobacco beetles identified and counted this time. The quantity distribution map can be a map recording the total number of tobacco beetles trapped by trapping intelligent terminals located at different geographical locations, and the quantity change curve can be a curve representing the change in the total number of tobacco beetles trapped by the same trapping intelligent terminal over time.

[0039] According to an embodiment of the present invention, the second communication processing module is further configured to perform early warning analysis on the quantity distribution map and the quantity change curve, generate corresponding early warning information, and transmit the early warning information to the result display module, and the result display module is further configured to display the early warning information.

[0040] It should be noted that potential risks or abnormal situations can be identified based on preset thresholds, historical data comparison, trend prediction or other algorithms. For example, when the data of a certain trapping intelligent terminal reaches or exceeds the early warning threshold, corresponding early warning information is generated. Another example is that when the duration of the continuous increase in the number of tobacco beetles trapped by a certain trapping intelligent terminal exceeds the early warning threshold, corresponding early warning information is generated. Another example is that when the year-on-year or month-on-month change in the number of tobacco beetles trapped by a certain trapping intelligent terminal exceeds a certain range, corresponding early warning information is generated. The result display module can correspondingly display the specific text content of the early warning information.

[0041] According to an embodiment of the present invention, the second communication processing module is further configured to send a status confirmation request to the first communication processing module of at least one trapping intelligent terminal, and the first communication processing module is further configured to, in the case of receiving the status confirmation request, reply with the current status information to the second communication processing module. The second communication processing module is further configured to, in the case of receiving at least one current status information, determine the status summary information of the trapping intelligent terminal according to the at least one current status information, and transmit the status summary information to the result display module, and the result display module is further configured to display the device status of each trapping intelligent terminal according to the status summary information.

[0042] It should be noted that the second communication processing module can send a status confirmation request to the trapping intelligent terminal to determine whether the trapping intelligent terminals located at different positions are in an online state or an offline state. If the second communication processing module does not receive feedback information from the trapping intelligent terminal, it can be regarded that the trapping intelligent terminal is in an offline state. When the first communication processing module receives the status confirmation request, it can reply with the current status information. For example, whether the current device can normally execute the trapping function and whether it can normally collect images, etc. The second communication processing module can summarize the current status information provided by different trapping intelligent terminals it receives, determine the operating status of each set trapping intelligent terminal, so as to obtain status summary information, and this status summary information can include the identifiers and current statuses of different trapping intelligent terminals.

[0043] According to an embodiment of the present invention, the trapping intelligent terminal further includes a fill light module. The fill light module is connected to the first communication processing module. The first communication processing module is further configured to send a fill light turn-on command to the fill light module before transmitting an image acquisition command to the camera module. The fill light module is further configured to turn on the fill light when receiving the fill light turn-on instruction.

[0044] It should be noted that when the fill light module receives the fill light turn-on instruction and turns on the fill light, it can start and emit light to ensure that high-quality images can be captured even in an environment with insufficient light, and it can be adapted to trapping intelligent terminals that work under different light conditions.

[0045] According to an embodiment of the present invention, the trapping intelligent terminal further includes a mobile power supply module. The mobile power supply module is respectively connected to the camera module and the first communication processing module. The mobile power supply module is used to supply power to the camera module and the first communication processing module.

[0046] It should be noted that the mobile power supply module can supply power to the camera module and the first communication processing module to ensure the normal operation of the camera module and the first communication processing module.

[0047] According to an embodiment of the present invention, the trapping intelligent terminal is further provided with a two-dimensional code. The camera module can also be used to collect a two-dimensional code image corresponding to the two-dimensional code and transmit the two-dimensional code image to the first communication processing module. The first communication processing module is further used to identify the two-dimensional code image to obtain first position information.

[0048] It should be noted that the trapping intelligent terminal can be provided with a two-dimensional code. This two-dimensional code can be that developers pre-mark the position of the trapping intelligent terminal on the drawing and number it, generate a two-dimensional code for each point, and paste it on the trapping intelligent terminal. The camera module determines the first position information by collecting the two-dimensional code image corresponding to the two-dimensional code and transmitting it to the first communication processing module for identification. This first position information is the positioning information of the trapping intelligent terminal.

[0049] Please refer to Figure 5 , which is a flowchart of the tobacco beetle monitoring method in some embodiments of this application. This tobacco beetle monitoring method is applied to a tobacco beetle monitoring system, and specifically includes the following steps:

[0050] S101. When the first communication processing module meets the preset image acquisition trigger condition, it transmits an image acquisition command to the camera module. When the camera module receives the image acquisition command, it acquires the original image of the trapping board, and transmits the original image to the first communication processing module. The first communication processing module preprocesses the original image to obtain a target image, combines the currently set first position information, the target image, and the current system timestamp to obtain target information, and transmits the target information to the intelligent recognition subsystem;

[0051] S102. The second communication processing module stores the received target information, identifies tobacco beetles in the target image of the target information, determines the second position information and counting information of the tobacco beetles, and sends the position information, counting information, and the target image to the result display module. The result display module performs annotation processing on the target image according to the position information and counting information to obtain a target result image, and displays the target result image.

[0052] It should be noted that the trapping intelligent terminal can be deployed in a specific area of the warehouse storing tobacco, and the number thereof can be one or more. The intelligent recognition subsystem can be deployed on an edge server, and can be specifically set in a factory area, a storage area, a warehouse, a headquarters computer room, a cloud computer room, etc. The wireless network can be a 4G network, a 5G network, etc., and is not limited herein in this application. Among them, the satisfaction of the preset image acquisition trigger condition includes: reaching a preset time node, or receiving a trigger image acquisition command sent by the intelligent recognition subsystem. For example, the trapping intelligent terminal is set to be triggered regularly according to a fixed time point or a fixed time interval. Another example is that the intelligent recognition system separately triggers a certain trapping intelligent terminal to acquire an image, or the intelligent recognition system triggers all online trapping intelligent terminals to acquire images with one key. The preprocessing of the original image can be filtering processing or enhancement processing of the original image. The filtering processing can be mean filtering, Gaussian filtering, median filtering, bilateral filtering, etc. The enhancement processing can be histogram equalization, normalization, wavelet transform, edge enhancement, dilation and erosion, etc., and is not limited herein in this application. By combining the currently set first position information, the target image, and the current system timestamp to obtain the target information, and transmitting the target information to the intelligent recognition subsystem, the specific geographical location of the trapping intelligent terminal, the acquired image of the tobacco beetle, and the specific acquisition time can be provided to the intelligent recognition subsystem. In addition, for the recognition of the tobacco beetle in the target image, the specific process can be to use an image segmentation method to separate the tobacco beetle in the image from the background for more accurate recognition. Then, feature extraction in different dimensions is performed on the image. For example, color information in the image, such as RGB values, HSV values, etc., is extracted to distinguish the tobacco beetle from other objects. Another example is to extract shape information in the image, such as contours, edges, corner points, etc., to identify the morphology of the tobacco beetle. Next, different image recognition algorithms can be adopted. For example, a template image of the tobacco beetle is pre-stored, and then the part similar to the template image is searched in the image to be recognized. Another example is to use machine learning algorithms such as support vector machines and neural networks to train and learn the image, and the model is trained to recognize the tobacco beetle by extracting features in the image. Another example is to use deep learning algorithms such as convolutional neural networks to train and recognize the image, which can automatically extract features in the image and perform classification and recognition. Finally, the first position information of the recognized tobacco beetle is determined. The first position information can be coordinate information, and the counting information of the tobacco beetle is determined. The counting information can be the serial number of the tobacco beetle and the number of tobacco beetles.

[0053] As described above, by deploying at least one trapping intelligent terminal, tobacco beetles in different areas can be trapped, and an accurate trapping result image can be provided. By deploying the intelligent recognition subsystem, the trapping result images of at least one trapping intelligent terminal can be automatically and accurately recognized, and the corresponding position information and counting information can be output, providing reliable reference information for monitoring tobacco beetles.

[0054] The present invention also provides a computer-readable storage medium, which includes a program for a cigarette beetle monitoring method. When the program for the cigarette beetle monitoring method is executed by a processor, the steps of the cigarette beetle monitoring method are implemented.

[0055] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces. The indirect coupling or communication connection of devices or units can be electrical, mechanical, or other forms.

[0056] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units; they can be located in one place or distributed to multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0057] In addition, in each embodiment of the present invention, the various functional units can all be integrated in one processing unit, or each unit can be separately used as a unit, or two or more units can be integrated in one unit; the above-mentioned integrated units can be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0058] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a readable storage medium. When the program is executed, it executes the steps including the above method embodiments; and the foregoing storage medium includes: various media such as removable storage devices, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0059] Alternatively, if the above integrated units of the present invention are implemented in the form of software functional modules and sold or used as independent products, they can also be stored in a readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as removable storage devices, ROM, RAM, magnetic disks, or optical discs.

Claims

1. A smoke beetle monitoring system, characterized in that: The system comprises: at least one trapping intelligent terminal and an intelligent identification subsystem, wherein the trapping intelligent terminal is connected to the intelligent identification subsystem via a wireless network; The trapping intelligent terminal is provided with a trapping module, a camera module and a first communication processing module, wherein the trapping module includes a trapping plate and a trapping core arranged on the trapping plate, and is used to capture smoke beetles; the camera module is connected to the first communication processing module; the first communication processing module is used to transmit a picture acquisition command to the camera module when a preset picture acquisition trigger condition is met; the camera module is used to collect an original image of the trapping plate when receiving the picture acquisition command, and transmit the original image to the first communication processing module; the first communication processing module is also used to pre-process the original image to obtain a target image, combine the currently set first position information, the target image and the current system timestamp to obtain target information, and transmit the target information to the intelligent identification subsystem; The intelligent identification subsystem includes a second communication processing module and a result display module. The second communication processing module is connected to the result display module. The second communication processing module is used to store the received target information, and identify the target image in the target information as a smoke beetle, determine the second position information and counting information of the smoke beetle, and annotate the target image according to the second position information and the counting information to obtain a target result image, and transmit the target result image to the result display module. The result display module is used to display the target result image.

2. The smoke beetle monitoring system according to claim 1, characterized in that: The second communication processing module is also used to generate a quantity distribution map and a quantity change curve based on the recorded received first position information, system timestamp, and counting information corresponding to the determined target image, and transmit the quantity distribution map and the quantity change curve to the result display module, and the result display module is also used to display the quantity distribution map and the quantity change curve.

3. The smoke beetle monitoring system according to claim 2, characterized in that: The second communication processing module is also used to perform early warning analysis on the quantity distribution map and the quantity change curve, generate corresponding early warning information, and transmit the early warning information to the result display module, and the result display module is also used to display the early warning information.

4. The smoke beetle monitoring system according to claim 1, characterized in that: The second communication processing module is also used to send a status confirmation request to the first communication processing module of at least one trapped smart terminal. The first communication processing module is also used to reply current status information to the second communication processing module when receiving the status confirmation request. The second communication processing module is also used to determine status summary information of the trapped smart terminal based on at least one current status information when receiving at least one current status information, and transmit the status summary information to the result display module. The result display module is also used to display the device status of each trapped smart terminal based on the status summary information.

5. The smoke beetle monitoring system according to claim 1, characterized in that: The preset image acquisition triggering condition is met, including: Arrives at the preset time node, or receives the trigger image acquisition command sent by the intelligent recognition subsystem.

6. The tobacco beetle monitoring system according to claim 1, characterized in that: The trapping intelligent terminal also includes a fill light module, which is connected to the first communication processing module. The first communication processing module is also used to transmit a fill light start command to the fill light module before transmitting a picture acquisition command to the camera module. The fill light module is also used to turn on the fill light when receiving the fill light start command.

7. The smoke beetle monitoring system according to claim 1, characterized in that: The trapping intelligent terminal also includes a mobile power module, which is connected to the camera module and the first communication processing module respectively, and is used to supply power to the camera module and the first communication processing module.

8. The smoke beetle monitoring system according to claim 1, characterized in that: The trapping intelligent terminal is also provided with a QR code, and the camera module can also be used to collect the QR code image corresponding to the QR code and transmit the QR code image to the first communication processing module, and the first communication processing module is also used to identify the QR code image to obtain the first location information.

9. A method for monitoring tobacco beetles, characterized in that: Applied to the beetle monitoring system of claim 1, the method comprising: The first communication processing module transmits a picture acquisition command to the camera module when a preset picture acquisition trigger condition is met. The camera module, upon receiving the picture acquisition command, acquires an original image of the trapping plate and transmits the original image to the first communication processing module. The first communication processing module pre-processes the original image to obtain a target image, combines the currently set first position information, the target image and the current system timestamp to obtain target information, and transmits the target information to the intelligent recognition subsystem. The second communication processing module stores the received target information, identifies the target image in the target information as a smoke beetle, determines the second position information and count information of the smoke beetle, and sends the position information, the count information and the target image to the result display module. The result display module annotates the target image according to the position information and the count information to obtain a target result image, and displays the target result image.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a smoke beetle monitoring method program, and when the smoke beetle monitoring method program is executed by a processor, the steps of the smoke beetle monitoring method as described in claim 9 are implemented.

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