Crop monitoring method, device, equipment and storage medium

Abstract

The application provides a crop monitoring method, device and equipment and a storage medium, and relates to the field of artificial intelligence. The method comprises the following steps: in response to receiving at least one user-triggered crop monitoring request, obtaining monitoring basic requirement information included in the request; determining farmland information to be merged and downloaded according to position information of a farmland in a monitoring task corresponding to at least one user and a preset image map download size, and downloading a corresponding farmland remote sensing image based on the farmland information to be merged and downloaded; cropping the farmland remote sensing image according to the position information of the farmland and a monitored crop type, so as to obtain a target farmland remote sensing image of at least one monitoring task; monitoring the crops in the at least one user monitoring task based on the target farmland remote sensing image, the position information of the farmland, the monitored crop type and a monitored growth condition type; and generating a monitoring report of the corresponding monitoring task based on a monitoring task identifier and a monitoring result. The method provided by the application improves the download efficiency and improves the diversity of monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of artificial intelligence, and in particular to a crop monitoring method and device, equipment and storage medium. BACKGROUND

[0002] With the continuous development of satellite remote sensing technology and artificial intelligence technology, intelligent agriculture has also developed continuously. Monitoring crops is a crucial part of intelligent agriculture.

[0003] Currently, before monitoring crops, farmland remote sensing images need to be downloaded very frequently from a server storing farmland remote sensing images based on the needs of each user, resulting in low efficiency in downloading farmland remote sensing images. And when monitoring crops, only single monitoring can be performed, resulting in that the user cannot timely understand the growth of crops based on the single monitoring result, and the multiple needs of the user for monitoring crops cannot be met. SUMMARY

[0004] The present application provides a crop monitoring method, device, equipment and storage medium to solve the technical problem of low efficiency in downloading farmland remote sensing images and only single monitoring, resulting in that the user cannot timely understand the growth of crops, and the multiple needs of the user for monitoring crops cannot be met.

[0005] In a first aspect, the present application provides a crop monitoring method, comprising: in response to receiving a crop monitoring request triggered by at least one user through an operation interface, obtaining monitoring basic requirement information included in the crop monitoring request; the monitoring basic requirement information includes: a monitoring task identifier, location information of at least one farmland, a monitored crop type, and a monitored growth condition type; the monitored growth condition type is any one or more of drought, flood, pest, and yield;

[0006] Determine the farmland information to be downloaded based on the location information of the farmland in the monitoring task corresponding to the at least one user and the preset image download size, and download the corresponding farmland remote sensing image based on the farmland information to be downloaded;

[0007] According to the location information of the farmland and the monitored crop type, the farmland remote sensing image is cropped to obtain a target farmland remote sensing image corresponding to the monitoring task corresponding to the at least one user;

[0008] Based on the target farmland remote sensing image, the location information of the farmland, the monitored crop type and the monitored growth condition type, the crops in the monitoring task of the at least one user are monitored to obtain a monitoring result;

[0009] generate a monitoring report of a monitoring task corresponding to the monitoring task identification based on the monitoring result.

[0010] In a second aspect, the present application provides a crop monitoring device, comprising: an acquisition module, configured to acquire monitoring basic requirement information included in a crop monitoring request triggered by at least one user through an operation interface in response to receiving the crop monitoring request; the monitoring basic requirement information comprises: a monitoring task identification, location information of at least one farmland, a monitoring crop type, and a monitoring growth condition type; the monitoring growth condition type is any one or more of drought, flood, pest, and yield;

[0011] A determination module is configured to determine farmland information to be downloaded based on location information of the farmland in the monitoring task corresponding to the at least one user and a preset image map download size.

[0012] A download module is configured to download a corresponding farmland remote sensing image based on the farmland information to be downloaded.

[0013] A cropping module is configured to crop the farmland remote sensing image based on the location information of the farmland and the monitoring crop type, so as to obtain a target farmland remote sensing image corresponding to the monitoring task corresponding to the at least one user.

[0014] A monitoring module is configured to monitor crops in the monitoring task of the at least one user based on the target farmland remote sensing image, the location information of the farmland, the monitoring crop type, and the monitoring growth condition type, so as to obtain a monitoring result.

[0015] A generation module is configured to generate a monitoring report of a monitoring task corresponding to the monitoring task identification based on the monitoring result.

[0016] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory connected to the processor in communication;

[0017] The memory stores computer execution instructions.

[0018] The processor executes the computer execution instructions stored in the memory to implement the method of the first aspect.

[0019] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to implement the method of the first aspect.

[0020] In a fifth aspect, the present application provides a computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the method of the first aspect.

[0021] The crop monitoring method, apparatus, equipment, and storage medium provided in this application, in response to receiving a crop monitoring request triggered by at least one user through an operating interface, acquires basic monitoring requirement information included in the crop monitoring request; the basic monitoring requirement information includes: a monitoring task identifier, location information of at least one farmland, type of monitored crop, and type of monitored growth condition; the type of monitored growth condition is any one or more of drought, flood, pests, and yield; determines the farmland information to be merged and downloaded based on the location information of the farmland in the monitoring task corresponding to at least one user and a preset image download size, and downloads the corresponding farmland remote sensing image based on the farmland information to be merged and downloaded; crops the farmland remote sensing image are cropped according to the location information of the farmland and the type of monitored crop to obtain a target farmland remote sensing image corresponding to the monitoring task corresponding to at least one user; the crops in the monitoring task of at least one user are monitored based on the target farmland remote sensing image, the location information of the farmland, the type of monitored crop, and the type of monitored growth condition to obtain monitoring results; and a monitoring report corresponding to the monitoring task identifier is generated based on the monitoring results. Because the monitoring task identifier, the location information of at least one farmland, the type of crop to be monitored, and the type of growth condition to be monitored are pre-stored in the user-triggered crop monitoring request, and the growth condition type is further subdivided into any one or more of drought, flood, pest, and yield, when a user triggers a crop monitoring request, by obtaining the location information of at least one farmland in the request and the pre-set image download size, the farmland information to be merged and downloaded can be determined, and the farmland remote sensing images can be downloaded accordingly. Furthermore, by obtaining the location information of each farmland and the type of crop to be monitored, the downloaded farmland remote sensing images can be cropped to obtain the target farmland remote sensing images corresponding to at least one crop that the user needs to monitor, without having to frequently download the original farmland remote sensing images based on each user's needs, thus improving the efficiency of farmland remote sensing image download. Furthermore, after acquiring remote sensing images of the target farmland, by obtaining the location information of the farmland corresponding to each user, the type of crop to be monitored, and the type of growth status to be monitored, the crops in the corresponding monitoring tasks of each user can be monitored based on the remote sensing images of the target farmland. This allows for the acquisition of monitoring results for each monitoring task, and the generation of monitoring reports for each monitoring task. This makes the monitoring results more comprehensive, enabling users to promptly learn about the growth status of crops and meeting the needs of each user for monitoring crops. Attached Figure Description

[0022] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0023] Figure 1This is an application scenario diagram of a crop monitoring method provided in one embodiment of this application;

[0024] Figure 2 A flowchart illustrating a crop monitoring method provided in an embodiment of this application;

[0025] Figure 3 A flowchart of a crop monitoring method provided in another embodiment of this application;

[0026] Figure 4 A flowchart illustrating a crop monitoring method provided in yet another embodiment of this application;

[0027] Figure 5 This is a schematic diagram of the structure of a crop monitoring device provided in one embodiment of this application;

[0028] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0029] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0030] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0031] It should be noted that the crop monitoring methods, devices, equipment, and storage media of this application can be used in the field of artificial intelligence, or in any field other than artificial intelligence. The application fields of the crop monitoring methods, devices, equipment, and storage media of this application are not limited.

[0032] To clearly understand the technical solution of this application, the solutions of the prior art will be described in detail first.

[0033] Currently, crop monitoring typically involves each user downloading remote sensing images of farmland according to their specific monitoring needs, and then using these images to assess crop growth. Specifically, when a user needs to know about crop growth, they trigger a component to download the remote sensing image on their client's interface. In response to each user's trigger, the system downloads the required image from a server storing these images and then sends them to each user's client. This process requires downloading the original remote sensing image each time a user triggers the component. Furthermore, these original images often cover the entire detectable area of ​​farmland, resulting in large file sizes and low download efficiency. Additionally, after obtaining the image, users can only assess the current crop growth based on the specific image acquired, lacking a comprehensive understanding and failing to meet the diverse monitoring needs of different users.

[0034] Therefore, to improve the efficiency of downloading farmland remote sensing images, in the face of technical problems in existing technologies, instead of downloading the original farmland remote sensing image every time a user triggers the component, the task identifier, farmland location, crop type, and growth status of the user's farmland monitoring request are pre-stored in the user's triggered image download request. In response to multiple users having farmland monitoring needs, the system simultaneously identifies the needs of multiple users and obtains all the aforementioned information. Then, based on overlapping farmland locations, all farmland is integrated, and the integrated farmland remote sensing images of all farmland are downloaded from the server storing the farmland remote sensing images. Based on the location of farmland corresponding to different crop types, the above farmland remote sensing images are cropped to form farmland remote sensing images corresponding to each crop type. Finally, based on the user's corresponding crop type and farmland location, the user's corresponding farmland remote sensing image is obtained.

[0035] Meanwhile, in order to comprehensively understand the growth status of crops and meet the different needs of different users for monitoring crops, the crop growth status type is also stored in the image download request triggered by the user. After obtaining the remote sensing image of the farmland corresponding to the user, the monitoring is carried out according to the location of the farmland corresponding to the crop type and the growth status type that the user needs to monitor. This allows each user to monitor various growth statuses of the farmland they need to monitor based on different growth status types.

[0036] Figure 1 This is an application scenario diagram of a crop monitoring method provided in one embodiment of this application, such as... Figure 1As shown, the system corresponding to the crop monitoring method in this embodiment includes: a user terminal 1, an electronic device 2, and a server 3 storing remote sensing images of farmland. The user terminal 1 has a client corresponding to the crop monitoring system, and the electronic device 2 has a server corresponding to the crop monitoring system. The user terminal 1 and the server 3 storing the remote sensing images of farmland are communicatively connected to the electronic device 2. The server 3 storing the remote sensing images of farmland includes original remote sensing images of farmland. First, at least one user triggers a crop monitoring request through the corresponding operation interface of the user terminal 1. The electronic device 2 receives the crop monitoring request triggered by at least one user and obtains the basic monitoring requirement information included in the request. The basic monitoring requirement information includes: a monitoring task identifier, the location information of at least one farmland, the type of crop to be monitored, and the type of growth condition to be monitored. The type of growth condition to be monitored is any one or more of drought, flood, pests, and yield. After obtaining basic monitoring requirements information from at least one user, the location information of farmland in each user's monitoring task is determined based on the monitoring task identifier and the location information of at least one farmland in each basic monitoring requirement information. Then, based on the farmland location information and the preset image download size, the farmland information to be merged and downloaded is determined, and the corresponding farmland remote sensing images are downloaded from server 3, which stores farmland remote sensing images, based on the farmland information to be merged and downloaded. The farmland remote sensing images are then cropped according to the monitored crop type and corresponding farmland location information in each basic monitoring requirement information to obtain the target farmland remote sensing images corresponding to each user's monitoring task. Finally, based on the target farmland remote sensing images, farmland location information, monitored crop type, and monitored growth status type, the crops in at least one user's monitoring task are monitored to obtain monitoring results, and a monitoring report corresponding to the monitoring task identifier is generated based on the monitoring results.

[0037] The data transmission method provided in this application is intended to solve the above-mentioned technical problems of the prior art.

[0038] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0039] Figure 2 A flowchart of a crop monitoring method provided in an embodiment of this application is shown below. Figure 2 As shown, the executing entity in this embodiment is a crop monitoring device. Since this crop monitoring device is located within an electronic device, the crop monitoring method provided in this embodiment includes the following steps:

[0040] Step 201: In response to receiving a crop monitoring request triggered by at least one user through the operation interface, obtain the basic monitoring requirement information included in the crop monitoring request. The basic monitoring requirement information includes: monitoring task identifier, location information of at least one farmland, type of crop to be monitored, and type of growth status to be monitored. The type of growth status to be monitored is any one or more of drought, flood, pests, and yield.

[0041] Among them, the crop monitoring request is a request that instructs the server corresponding to the crop monitoring device to monitor the crops.

[0042] The basic monitoring requirements information is the information stored here when a user triggers a crop monitoring request, which is required to monitor the crops. Specifically, the basic monitoring requirements information includes: a monitoring task identifier, the location information of at least one farmland, the type of crop to be monitored, and the type of growth status to be monitored.

[0043] Among them, the monitoring task identifier is an identifier that represents the identity of a certain monitoring task.

[0044] Among them, the location information of at least one farmland is the location of at least one farmland that needs to be monitored in the monitoring task.

[0045] Among them, the monitored crop type refers to the type of crop to be monitored in the monitoring task.

[0046] For example, the monitoring task identifier can be a task number, task name, or other identifier. The location information of at least one farmland can be the latitude and longitude coordinates of at least one farmland. The monitored crop type can be a grain crop, a vegetable crop, a legume crop, or other crop type. The above example can also be other examples, and this embodiment is not limited in its comparison.

[0047] The monitoring growth condition type refers to the type of crop growth condition to be monitored in the monitoring task. Specifically, the monitoring growth condition types include any one or more of the following: drought, flood, pests, and yield.

[0048] It should be noted that before receiving a crop monitoring request triggered by at least one user through the user interface, at least one user must create a new monitoring task based on their own needs through the user terminal's user interface. This new task involves selecting the location information of at least one field of farmland to be monitored, the type of crop to be monitored, and the type of growth status to be monitored through the corresponding window. After making the selection, a confirmation component is triggered. Then, in response to the user's confirmation component, the corresponding device of at least one user terminal obtains the new monitoring task and, based on the user's selections, generates basic monitoring requirement information for the task. Finally, this basic monitoring requirement information is stored in the crop monitoring request, and the request is sent to the server corresponding to the crop monitoring device.

[0049] In this embodiment, the server corresponding to the crop monitoring device responds to receiving a crop monitoring request sent by at least one user terminal device and obtains the basic monitoring requirements information stored in the crop monitoring request.

[0050] It is understandable that for at least one farmland location in the basic monitoring requirements, there is a corresponding monitored crop type. Therefore, when forming the basic monitoring requirements based on the user's selections in the newly created monitoring task, if it is determined that the user has selected multiple farmland locations, then the various monitored crop types from these multiple farmland locations are retrieved, along with the monitored crop type selected by the user. It is then determined whether there is a monitored crop type among these multiple monitored crop types that the user has not selected. If so, the location information of the farmland corresponding to the monitored crop type not selected by the user is retrieved, and this location information is deleted.

[0051] Step 202: Determine the farmland information to be merged and downloaded based on the location information of farmland in the monitoring task corresponding to at least one user and the preset image download size, and download the corresponding farmland remote sensing image based on the farmland information to be merged and downloaded.

[0052] The preset image download size is the pre-defined size of the image to be downloaded. This size can be smaller than or equal to the area of ​​the farmland remote sensing image acquired by the satellite.

[0053] Among them, the farmland information to be merged and downloaded is the farmland information required when obtaining the farmland remote sensing image corresponding to the farmland to be merged and downloaded.

[0054] Among them, farmland remote sensing images are farmland distribution images obtained by satellites based on the received energy reflection from ground objects.

[0055] In this embodiment, in response to obtaining at least one basic monitoring requirement information, the monitoring task identifier and the location information of at least one farmland are obtained. The location information of all farmlands is compared to determine if there are any identical location information. If so, it is determined that all farmlands will be integrated, and the location information of all integrated farmlands is obtained after integration. Based on the location information of all integrated farmlands and a preset image download size, the farmland information to be merged and downloaded is obtained, and the corresponding farmland remote sensing image is downloaded from the server storing farmland remote sensing images according to the farmland information to be merged and downloaded.

[0056] Specifically, when integrating the location information of all farmland, the same location information among all farmland locations can be integrated into one.

[0057] Specifically, when obtaining the farmland information to be merged and downloaded based on the location information of all integrated farmland and the preset image download size, the specific steps can be as follows: obtain the preset image download size, determine that the location information of all integrated farmland is within the preset image download size, and determine that the location information of all integrated farmland within the preset image download size is the farmland information to be merged and downloaded.

[0058] Understandably, if it is determined that there are locations of all farmland that are not within the preset image download size, then the location information of all farmland that are integrated will be adjusted according to the preset image download size, and the adjusted location information of all farmland will be the farmland information to be merged and downloaded.

[0059] Step 203: Crop the farmland remote sensing image according to the location information of the farmland and the type of monitored crop to obtain at least one target farmland remote sensing image corresponding to the monitoring task of a user.

[0060] Among them, the target farmland remote sensing images are the farmland remote sensing images corresponding to each monitoring task.

[0061] It should be noted that when downloading the corresponding remote sensing images of farmland based on the farmland information to be merged, since the farmland information to be merged includes integrated information on all farmland, the downloaded farmland remote sensing images include those corresponding to the monitoring tasks of all users. Therefore, the downloaded farmland remote sensing images need to be cropped to obtain the target farmland remote sensing images corresponding to the monitoring tasks of each user.

[0062] Understandably, since each farmland has a corresponding type of monitored crop, it is necessary to predetermine the types of monitored crops for all farmland and associate and store the types of monitored crops for all farmland with the location information of all farmland to form a pre-defined farmland type mapping table.

[0063] The preset farmland type mapping table is a data table that stores the location information of all farmland and the mapping relationship between the corresponding monitored crop types.

[0064] Specifically, after acquiring the downloaded farmland remote sensing images, the system obtains the location information of at least one monitored crop type and at least one corresponding farmland for each monitoring task, and acquires a preset farmland type mapping table. The system then searches the preset farmland type mapping table for the location information of farmland that has a mapping relationship with the monitored crop type, identifying the location information of the farmland corresponding to that monitored crop type. After obtaining the location information of the farmland corresponding to the monitored crop type, the downloaded farmland remote sensing images can be cropped according to this information. Thus, based on the location information of at least one farmland corresponding to each monitoring task, the target farmland remote sensing images for each monitoring task are obtained.

[0065] Step 204: Based on the remote sensing image of the target farmland, the location information of the farmland, the type of monitored crop, and the type of monitored growth, monitor the crops in at least one user monitoring task to obtain monitoring results.

[0066] The monitoring results are the results generated when monitoring the growth of the monitored crop types during the monitoring task.

[0067] Specifically, after acquiring remote sensing images of target farmland corresponding to at least one user's monitoring task, the system obtains basic monitoring requirements information, including the type of crop growth to be monitored, and locates the farmland corresponding to the monitored crop type based on the target farmland remote sensing images. The system then monitors the crop growth at the location corresponding to the monitored crop type, thereby generating corresponding monitoring results.

[0068] For example, after acquiring remote sensing images of target farmland corresponding to at least one user's monitoring task, if the monitored crop type is legumes and the monitored growth condition type is drought, the location of the legume-corresponding farmland can be located using the target farmland remote sensing image, and the growth condition of the legumes at that location can be monitored. The generated monitoring result can then represent the drought level of the legume-corresponding farmland. Furthermore, if the monitored crop type is legumes and the monitored growth condition type is drought and yield, the generated monitoring result can represent the drought level and yield level of the legume-corresponding farmland.

[0069] Step 205: Generate a monitoring report for the monitoring task corresponding to the monitoring task identifier based on the monitoring results.

[0070] The monitoring report is a file that stores details of the monitoring task.

[0071] The monitoring report may include monitoring results, types of monitored crops, location information of farmland, and types of crop growth. It may also include monitoring time, time of report generation, or other information. This embodiment does not limit this.

[0072] Specifically, after obtaining the monitoring results corresponding to at least one monitoring task, the monitoring results corresponding to each monitoring task, along with the monitored crop type, farmland location information, and monitored growth status type, are stored in a specified format to form a monitoring report. Furthermore, the monitoring task identifier corresponding to each monitoring task is obtained, and the monitoring task identifier is associated with the monitoring report to generate a monitoring report corresponding to each monitoring task identifier.

[0073] The crop monitoring method provided in this embodiment, in response to receiving a crop monitoring request triggered by at least one user through an operation interface, obtains the basic monitoring requirement information included in the crop monitoring request; the basic monitoring requirement information includes: monitoring task identifier, location information of at least one farmland, type of monitored crop, and type of monitored growth condition; the type of monitored growth condition is any one or more of drought, flood, pests, and yield; the farmland information to be merged and downloaded is determined according to the location information of the farmland in the monitoring task corresponding to at least one user and the preset image download size, and the corresponding farmland remote sensing image is downloaded based on the farmland information to be merged and downloaded; the farmland remote sensing image is cropped according to the location information of the farmland and the type of monitored crop to obtain the target farmland remote sensing image corresponding to the monitoring task corresponding to at least one user; the crops in the monitoring task of at least one user are monitored based on the target farmland remote sensing image, the location information of the farmland, the type of monitored crop, and the type of monitored growth condition to obtain monitoring results; and a monitoring report corresponding to the monitoring task identifier is generated based on the monitoring results. Because the monitoring task identifier, the location information of at least one farmland, the type of crop to be monitored, and the type of growth condition to be monitored are pre-stored in the user-triggered crop monitoring request, and the growth condition type is further subdivided into any one or more of drought, flood, pest, and yield, when a user triggers a crop monitoring request, by obtaining the location information of at least one farmland in the request and the pre-set image download size, the farmland information to be merged and downloaded can be determined, and the farmland remote sensing images can be downloaded accordingly. Furthermore, by obtaining the location information of each farmland and the type of crop to be monitored, the downloaded farmland remote sensing images can be cropped to obtain the target farmland remote sensing images corresponding to at least one crop that the user needs to monitor, without having to frequently download the original farmland remote sensing images based on each user's needs, thus improving the efficiency of farmland remote sensing image download. Furthermore, after acquiring remote sensing images of the target farmland, by obtaining the location information of the farmland corresponding to each user, the type of crop to be monitored, and the type of growth status to be monitored, the crops in the corresponding monitoring tasks of each user can be monitored based on the remote sensing images of the target farmland. This allows for the acquisition of monitoring results for each monitoring task, and the generation of monitoring reports for each monitoring task. This makes the monitoring results more comprehensive, enabling users to promptly learn about the growth status of crops and meeting the needs of each user for monitoring crops.

[0074] Figure 3 A flowchart of a crop monitoring method provided in another embodiment of this application is shown below. Figure 3As shown, the content of the farmland information to be merged and downloaded is further refined, and the farmland remote sensing image corresponding to the farmland information to be merged and downloaded is further refined. In this embodiment, the farmland information to be merged and downloaded includes the farmland location information to be merged and downloaded; the specific steps for downloading the farmland remote sensing image corresponding to the farmland information to be merged and downloaded are as follows:

[0075] Step 301: Send an image download request to the image storage server. The image download request includes the location information of the farmland to be merged and downloaded. The location information of the farmland to be merged and downloaded is used to instruct the image storage server to obtain remote sensing images of farmland corresponding to all the farmland to be merged and downloaded.

[0076] Among them, the farmland location information to be merged and downloaded is the location information corresponding to the farmland to be merged and downloaded, which is specifically used to instruct the image storage server to obtain farmland remote sensing images including all farmland to be merged and downloaded.

[0077] Among them, the image storage server is a server that stores remote sensing images of farmland.

[0078] Among them, the image download request is a request to the image storage server to download remote sensing images of farmland.

[0079] In this embodiment, based on the farmland information to be merged and downloaded, the location information of the farmland to be merged and downloaded, which is included in the farmland information to be merged and downloaded, is obtained. The location information of the farmland to be merged and downloaded is stored in the image download request, and the image download request storing the location information of the farmland to be merged and downloaded is sent to the image storage server.

[0080] Step 302: Receive remote sensing images of farmland sent by the image storage server.

[0081] Specifically, upon receiving an image download request, the image storage server retrieves the farmland location information to be merged and downloaded, as included in the download request, and obtains the latest farmland remote sensing image within a preset image download size range. Based on the farmland location information, it locates the corresponding area of ​​the farmland to be merged and downloaded within the latest farmland remote sensing image. After successful location locating, it acquires this area, determines the farmland remote sensing image corresponding to this area as the farmland remote sensing image to be merged and downloaded, and sends this farmland remote sensing image to the corresponding server of the crop monitoring device. The corresponding server of the crop monitoring device then receives the farmland remote sensing image sent by the image storage server and acquires that farmland remote sensing image.

[0082] The latest farmland remote sensing images are those generated from the latest satellite data collection.

[0083] Specifically, when locating the corresponding area of ​​the farmland to be merged and downloaded in the latest farmland remote sensing image based on the farmland location information to be merged and downloaded, the following steps can be taken: calculate the outermost latitude and longitude coordinates of the area where the farmland to be merged and downloaded is located based on the location information of the farmland to be merged and downloaded, select the area where the farmland to be merged and downloaded is located based on the outermost latitude and longitude coordinates, and determine the selected area as the corresponding area of ​​the farmland to be merged and downloaded.

[0084] Among them, the latitude and longitude coordinates of the outermost edge are the latitude and longitude coordinates of the edge of the farmland.

[0085] The crop monitoring method provided in this embodiment includes farmland location information to be merged and downloaded. When downloading corresponding remote sensing images of farmland based on this farmland information, the method includes: sending an image download request to an image storage server, the image download request including the farmland location information to be merged and downloaded, which instructs the image storage server to acquire remote sensing images of all farmland to be merged and downloaded; and receiving the farmland remote sensing images sent by the image storage server. Since the farmland remote sensing images are stored in the image storage server, by pre-storing the farmland location information to be merged and downloaded in the image download request, and by sending the image download request to the image storage server, the image storage server can be instructed to acquire remote sensing images of all farmland to be merged and downloaded based on the farmland location information. Furthermore, by receiving the farmland remote sensing images sent by the image storage server, all farmland remote sensing images corresponding to the farmland to be merged and downloaded can be acquired quickly and smoothly, further improving the efficiency of downloading farmland remote sensing images.

[0086] Figure 4 A flowchart of a crop monitoring method provided in another embodiment of this application is shown below. Figure 4 As shown, the basic monitoring requirements information further refines the content, and further refines the monitoring of crops in at least one user monitoring task based on remote sensing images of the target farmland, farmland location information, monitored crop type, and monitored growth status type to obtain monitoring results. Therefore, in this embodiment, the basic monitoring requirements information also includes: monitoring period; monitoring crops in at least one user monitoring task based on remote sensing images of the target farmland, farmland location information, monitored crop type, and monitored growth status type to obtain monitoring results, specifically including the following steps:

[0087] Step 401: Obtain the location information of the farmland and the monitoring duration that matches the type of crop being monitored. The monitoring duration is related to the area, type, and growth period of the crop.

[0088] Among them, the monitoring duration is the time required to monitor the growth of crops.

[0089] The region where the crop is located refers to the actual area where the crop is situated.

[0090] The growth period refers to the time that crops go through during their growth, which may include the seedling stage, the growth stage, and the maturity stage.

[0091] For example, if the monitored crop type is a grain crop, the region is the Northwest, and the growing season is the growing season, then the monitoring period can be from May to July.

[0092] Understandably, before obtaining the location information of farmland and the monitoring duration matching the crop type, it is necessary to first determine the monitoring duration corresponding to each crop type in at least one region and at least one growth period based on the region, type, and growth period of each crop, and then associate and store each crop type with the corresponding at least one monitoring duration to form a preset monitoring duration mapping table.

[0093] Specifically, when acquiring the location information of farmland and the monitoring duration matching the type of crop being monitored, a preset monitoring duration mapping table is obtained, and a remote sensing image of the target farmland is acquired. The location information of the farmland corresponding to the type of crop being monitored is located in the remote sensing image of the target farmland, and the type of crop being monitored, its current growth stage, and its current location are determined. Based on this determination, the preset monitoring duration mapping table is used to find the location information of the farmland and the monitoring duration matching the type of crop being monitored.

[0094] Step 402: Determine the corresponding monitoring results for each monitoring cycle within the monitoring period based on the remote sensing image of the target farmland.

[0095] The monitoring cycle refers to the frequency of monitoring crop growth within the monitoring period, such as weekly, monthly, or quarterly.

[0096] It is understandable that the monitoring period is the monitoring period set by the user through the operation interface.

[0097] Specifically, after obtaining the location information of the farmland and the monitoring duration matching the type of crop to be monitored, remote sensing images of the target farmland and monitoring cycles, including basic monitoring requirements, are acquired. In response to the current date falling within the monitoring duration corresponding to the type of crop to be monitored, the type of crop is monitored periodically according to the remote sensing images of the target farmland, and monitoring results for each monitoring cycle are generated.

[0098] The crop monitoring method provided in this embodiment further includes monitoring requirements such as: monitoring period; when monitoring crops in at least one user monitoring task based on remote sensing images of the target farmland, farmland location information, monitored crop type, and monitored growth status to obtain monitoring results, the method includes: obtaining a monitoring duration matching the farmland location information and monitored crop type, the monitoring duration being related to the crop's location, type, and growth period; and determining the corresponding monitoring result for each monitoring cycle within the monitoring duration based on the target farmland remote sensing image. Since different crop types are located in different areas and have different growth periods, by pre-determining the monitoring duration for each crop type in different areas and during different growth periods, a monitoring duration matching the farmland location information and monitored crop type can be further determined based on the above determination results. By obtaining the user-set monitoring period, crops can be monitored within the monitoring period, and the corresponding monitoring result can be determined based on the target farmland remote sensing image. This allows for accurate monitoring of the key growth periods of crops, avoiding unnecessary monitoring and saving monitoring resources.

[0099] As an optional embodiment, this embodiment is in Figure 3 Based on the corresponding embodiment, the monitoring generation type is any one or more of drought, flood, pests, and yield. Step 402 specifically includes the following steps:

[0100] Step 4021: Obtain a prediction model that matches the type of crop being monitored and the type of growth status being monitored.

[0101] Among them, the prediction model is a model for predicting crop growth.

[0102] Understandably, when determining the corresponding monitoring results based on remote sensing images of target farmland, a predictive model is used to assess the growth status of the crop types included in the image. Therefore, it is necessary to pre-determine the corresponding predictive models based on different types of monitored crops and different monitoring growth statuses.

[0103] For example, if the monitored crop type is legumes and the monitored growth condition type is drought, then the prediction model can be a model for assessing the drought condition of legumes.

[0104] Specifically, in response to at least one monitoring task, the monitoring of the crop type is carried out according to the monitoring cycle based on the corresponding target farmland remote sensing image within the monitoring period. The monitoring crop type and the monitoring growth status type corresponding to at least one monitoring task are obtained, and multiple predetermined prediction models are obtained. Among the multiple prediction models, the prediction model that matches the monitoring crop type and the monitoring growth status type is selected.

[0105] Step 4022: In each monitoring cycle within the monitoring period, the remote sensing image of the target farmland is input into the corresponding prediction model, and the prediction model is used to predict the degree of the monitored growth condition type to obtain the monitoring results corresponding to each monitoring cycle, with the degree being any one of severe, moderate, or mild.

[0106] Specifically, after obtaining the prediction model, in response to a monitoring period within the monitoring duration corresponding to at least one monitoring task on the current date, the target agricultural remote sensing image corresponding to at least one monitoring task is input into the corresponding prediction model. The prediction model is used to predict the degree of the monitored growth condition type in order to obtain the monitoring results corresponding to that monitoring period.

[0107] Understandably, for each monitoring cycle within the monitoring period, the target agricultural remote sensing image will be input into the corresponding prediction model to obtain the monitoring results for each monitoring cycle. Furthermore, the predicted growth level corresponding to the growth condition type can be any one of severe, moderate, or mild.

[0108] Understandably, the prediction model can be a machine learning model that has been trained to convergence. Specifically, when using the prediction model to predict the degree of monitoring growth type, the specific steps can be as follows: after inputting farmland remote sensing images corresponding to at least one monitoring task into the prediction model, the prediction model determines the monitoring results corresponding to each farmland remote sensing image and outputs the degree of monitoring growth type reflected by the monitoring results.

[0109] The training process for the prediction model involves first acquiring a training sample set, then inputting the training samples into the prediction model. The model is trained based on these training samples, and the training parameters are adjusted. The model is then assessed to determine if it meets pre-defined convergence criteria. If it does, the prediction model that meets the convergence criteria is identified as a converged prediction model. The training samples in the training sample set are remote sensing images of farmland labeled with the corresponding monitoring growth type and degree.

[0110] The crop monitoring method provided in this embodiment monitors one or more of the following conditions: drought, flood, pests, and yield. When determining the corresponding monitoring result based on the remote sensing image of the target farmland in each monitoring cycle within the monitoring period, the method includes: acquiring a prediction model matching the monitored crop type and the monitored growth condition type; inputting the remote sensing image of the target farmland into the corresponding prediction model in each monitoring cycle within the monitoring period, and using the prediction model to predict the severity of the monitored growth condition type to obtain the monitoring result for each monitoring cycle, with the severity being any one of severe, moderate, or mild. Since it is necessary to evaluate the growth status of the crop types included in the remote sensing image of the target farmland based on the prediction model, by pre-determining the prediction models corresponding to various monitored growth condition types for each type of crop, a prediction model matching the monitored crop type and monitored growth condition type can be obtained based on the monitored crop type and monitored growth condition type corresponding to the monitoring task. Furthermore, by inputting the remote sensing image of the target farmland into the corresponding prediction model in each monitoring cycle within the monitoring period, the monitoring results corresponding to each monitoring task can be predicted based on the prediction model. This allows users to accurately and promptly obtain information on the specific growth status of the monitored crop type based on the severity (severe, moderate, or mild) of the monitoring results.

[0111] As an optional embodiment, this embodiment, based on the above embodiments, generates a monitoring report corresponding to the monitoring task identifier based on the monitoring results, specifically including the following steps:

[0112] For each monitoring task, a monitoring report is generated based on the type of crop being monitored, the type of growth being monitored, and the monitoring results.

[0113] In this embodiment, in response to obtaining the monitoring results corresponding to at least one monitoring task, a monitoring report corresponding to the monitoring task identifier is generated based on the monitoring results.

[0114] Specifically, the monitoring task identifier corresponding to each monitoring task is obtained, along with the monitored crop type, monitored growth condition type, and monitoring results for each monitoring task. Based on these results, the monitored crop type, monitored growth condition type, and monitoring results for each monitoring task are stored, and a monitoring report for each monitoring task is generated. The monitoring report for each monitoring task is then associated with the monitoring task identifier for that monitoring task, thereby generating a monitoring report for each monitoring task corresponding to each monitoring task identifier.

[0115] The crop monitoring method provided in this embodiment, when generating monitoring reports for monitoring tasks corresponding to monitoring task identifiers based on monitoring results, includes: generating a monitoring report for each monitoring task corresponding to a monitoring task identifier, based on the monitored crop type, monitored growth condition type, and monitoring results. Since the obtained monitoring results are the monitoring results for each monitoring task identifier corresponding to a monitoring task, a monitoring report can be generated by storing the monitored crop type, monitored growth condition type, and monitoring results. Furthermore, by associating each monitoring task's corresponding monitoring task identifier with the monitoring report, a monitoring report corresponding to each monitoring task identifier can be generated, allowing each user to easily obtain the corresponding monitoring report.

[0116] As an optional embodiment, this embodiment, based on the above embodiments, uses a predictive model to predict the degree of monitoring growth type, and after obtaining the monitoring results corresponding to each monitoring cycle, further includes:

[0117] The monitoring results are marked in the remote sensing image of the target farmland to obtain the marked remote sensing image of the target farmland.

[0118] Understandably, in order to more intuitively display the crop growth status in each field in the remote sensing image of the target farmland corresponding to at least one monitoring task, the monitoring results output in each monitoring cycle are marked in the remote sensing image of the target farmland to form a marked remote sensing image of the target farmland.

[0119] Specifically, after obtaining the monitoring results for each monitoring cycle, the field containing the monitoring results is read, and the field containing the monitoring results is marked in the target remote sensing image according to the location information of the farmland corresponding to the monitored crop type to which the monitoring results belong, thereby obtaining the target farmland remote sensing image marked with the monitoring results.

[0120] For each monitoring task identified, a monitoring report is generated based on the type of crop being monitored, the type of growth condition being monitored, and the monitoring results. This report includes:

[0121] For each monitoring task, a monitoring report in a preset image and text format is generated based on the type of monitored crop, the type of monitored growth, the monitoring results, and the remote sensing image of the marked target farmland.

[0122] The preset graphic and text format is a graphic and text format that is set in advance according to the specified format of the monitoring report.

[0123] In this embodiment, in response to obtaining the monitoring results corresponding to at least one monitoring task, a monitoring report is generated for each monitoring task corresponding to the monitoring task identifier, based on the type of monitored crop, the type of monitored growth, and the monitoring results.

[0124] Specifically, the monitoring task identifiers corresponding to each monitoring task are obtained, along with the monitored crop type, monitored growth status type, monitoring results, and the marked target farmland remote sensing image for each monitoring task. Based on these results, the monitored crop type, monitored growth status type, monitoring results, and the marked target farmland remote sensing image for each monitoring task are stored in a preset image-text format. A monitoring report in a preset image-text format for each monitoring task is generated. The monitoring report for each monitoring task is then associated with the monitoring task identifier for that task, thereby generating a monitoring report for each monitoring task in a preset image-text format corresponding to each monitoring task identifier.

[0125] The crop monitoring method provided in this embodiment, after predicting the degree of monitoring growth type using a predictive model to obtain the monitoring results corresponding to each monitoring cycle, further includes: marking the monitoring results in the remote sensing image of the target farmland to obtain the marked remote sensing image of the target farmland; and generating a monitoring report for each monitoring task corresponding to each monitoring task identifier, based on the monitored crop type, monitored growth type, and monitoring results. This includes: generating a monitoring report in a preset image and text format for each monitoring task corresponding to each monitoring task identifier, based on the monitored crop type, monitored growth type, monitoring results, and the marked remote sensing image of the target farmland. Since the remote sensing image of the target farmland can more intuitively display the monitoring results corresponding to the monitoring task, marking the monitoring results corresponding to each monitoring cycle in the remote sensing image of the target farmland can obtain the marked remote sensing image of the target farmland. By obtaining the monitored crop type, monitored growth type, monitoring results, and marked remote sensing image of the target farmland corresponding to each monitoring task identifier, the monitoring-related information corresponding to each monitoring task can be stored in the monitoring report according to the preset image and text storage format. This allows each user to intuitively and in detail understand the crop growth status through the content of the monitoring report.

[0126] As an optional embodiment, this embodiment further includes, in addition to any of the above embodiments, the following:

[0127] Step 501: In response to detecting that the user has enabled the early warning task service, periodically determine the monitoring results of the user's corresponding farmland in each monitoring growth type.

[0128] Among them, the early warning task service is a service that reminds users when the early warning conditions are met.

[0129] Among them, the early warning conditions are the conditions that must be met to execute the early warning.

[0130] For example, if the monitored crop type is legumes and the monitored growth condition type is drought, then the warning condition can be to issue a warning when the drought condition of the legumes reaches a severe level.

[0131] It is understandable that before the monitoring results are generated within the monitoring period, farmland may be at risk of being severely affected by certain monitored growth conditions due to natural disasters or other factors. Therefore, by enabling the early warning task service, the monitoring results of the user's corresponding farmland for each monitored growth condition type can be determined periodically, and the user can be reminded to pay special attention to a certain monitored growth condition type when the monitoring results meet the early warning conditions.

[0132] Specifically, this embodiment determines that the user has enabled the early warning task service based on the user's activation of the early warning task service. It periodically determines the monitoring results of each type of monitoring growth status of the user's corresponding farmland within the monitoring market. After determining the monitoring results, it judges whether there are at least one type of monitoring growth status whose monitoring results meet the early warning conditions.

[0133] Step 502: If the monitoring results of at least one type of growth monitoring meet the early warning conditions, an early warning message is sent to the user terminal.

[0134] Among them, the early warning information prompts users to pay special attention to a certain type of growth status being monitored.

[0135] Specifically, based on whether there is a monitoring result for at least one type of growth condition that meets the early warning conditions, if it is determined that there is a monitoring result for at least one type of growth condition that meets the early warning conditions, it means that there is at least one type of growth condition that may be severely affected by natural disasters or other factors. Then, the location information of the farmland corresponding to the user's monitoring task, the type of crop being monitored, the type of growth condition that meets the early warning conditions, and the corresponding monitoring results are obtained, and the above-mentioned content is stored to form an early warning message, which is then sent to the user terminal.

[0136] Understandably, after the early warning information is sent to the user's terminal, the user can take corresponding measures to protect the farmland under the warning.

[0137] The crop monitoring method provided in this embodiment further includes: responding to the detection that a user has activated the early warning task service, periodically determining the monitoring results of the user's corresponding farmland for each monitored growth condition type; if the monitoring results of at least one monitored growth condition type meet the early warning conditions, then sending an early warning notification to the user terminal. Since farmland is at risk of being severely affected by occasional natural disasters or other factors for a certain monitored growth condition type, after determining that a user has activated the early warning task service, periodically determining the monitoring results of the user's corresponding farmland for each monitored growth condition type allows for a determination of whether the early warning conditions are met. Therefore, when the early warning conditions are met, an early warning notification is generated based on the monitored crop type, the monitored growth condition type that meets the early warning conditions, and the corresponding monitoring results, and this notification is sent to the user terminal. This enables users to promptly learn about the impact on their farmland when it is severely affected, allowing them to take appropriate measures to mitigate the risks.

[0138] Figure 5 This is a schematic diagram of the structure of a crop monitoring device provided in one embodiment of this application, as shown below. Figure 5 As shown, the crop monitoring device provided in this embodiment is located in an electronic device. The crop monitoring device 60 provided in this embodiment includes: an acquisition module 61, a determination module 62, a download module 63, a cropping module 64, a monitoring module 65, and a generation module 66.

[0139] The system includes the following modules: Acquisition module 61, which, in response to receiving a crop monitoring request triggered by at least one user through an interface, acquires the basic monitoring requirements information included in the request. These requirements include: a monitoring task identifier, location information of at least one farmland, type of monitored crop, and type of monitored growth. The monitored growth type is any one or more of drought, flood, pests, and yield. Determination module 62, which determines the farmland information to be merged and downloaded based on the location information of the farmland in the monitoring task corresponding to at least one user and a preset image download size. Download module 63, which downloads the corresponding farmland remote sensing image based on the farmland information to be merged and downloaded. Cropping module 64, which crops the farmland remote sensing image based on the farmland location information and type of monitored crop to obtain the target farmland remote sensing image corresponding to the monitoring task of at least one user. Monitoring module 65, which monitors the crops in the monitoring task of at least one user based on the target farmland remote sensing image, farmland location information, type of monitored crop, and type of monitored growth to obtain monitoring results. Generation module 66, which generates a monitoring report corresponding to the monitoring task identifier based on the monitoring results.

[0140] The crop monitoring device provided in this embodiment can perform... Figure 2The implementation principles and technical effects of the methods shown are similar, and will not be repeated here.

[0141] Optionally, the farmland information to be merged and downloaded includes the farmland location information to be merged and downloaded.

[0142] Accordingly, when downloading the corresponding farmland remote sensing image based on the farmland information to be merged and downloaded, the download module 63 is specifically used for:

[0143] Send an image download request to the image storage server. The image download request includes the location information of the farmland to be merged and downloaded. The location information of the farmland to be merged and downloaded is used to instruct the image storage server to obtain remote sensing images of farmland corresponding to all farmland to be merged and downloaded; receive the remote sensing images of farmland sent by the image storage server.

[0144] Optionally, the basic monitoring requirements information may also include: the monitoring period.

[0145] Accordingly, when monitoring crops in at least one user monitoring task based on remote sensing images of the target farmland, farmland location information, monitored crop type, and monitored growth status type to obtain monitoring results, the monitoring module 65 is specifically used for:

[0146] The system acquires location information of farmland and monitoring durations that match the type of crop being monitored. The monitoring duration is related to the region, type, and growth period of the crop. Within each monitoring period, the corresponding monitoring results are determined based on remote sensing images of the target farmland.

[0147] Optionally, the monitoring generation type can be any one or more of the following: drought, flood, pests, and yield.

[0148] Accordingly, module 62 determines the corresponding monitoring results for each monitoring cycle within the monitoring duration based on the remote sensing image of the target farmland, specifically for:

[0149] Obtain a prediction model that matches the type of crop being monitored and the type of growth condition being monitored; input the remote sensing image of the target farmland into the corresponding prediction model for each monitoring cycle within the monitoring period, and use the prediction model to predict the degree of the type of growth condition being monitored, so as to obtain the monitoring results corresponding to each monitoring cycle, with the degree being any one of severe, moderate and mild.

[0150] Optionally, when generating a monitoring report for a monitoring task corresponding to the monitoring task identifier based on the monitoring results, the monitoring module 65 is specifically used for:

[0151] For each monitoring task, a monitoring report is generated based on the type of crop being monitored, the type of growth being monitored, and the monitoring results.

[0152] The crop monitoring device provided in this embodiment also includes a tagging module.

[0153] The labeling module is used to label the monitoring results in the remote sensing image of the target farmland after the determination module 62 uses a prediction model to predict the degree of monitoring growth type and obtain the monitoring results corresponding to each monitoring cycle, so as to obtain the labeled remote sensing image of the target farmland.

[0154] Accordingly, the monitoring module 65, when generating a monitoring report for each monitoring task identifier based on the type of monitored crop, the type of monitored growth, and the monitoring results, is specifically used for:

[0155] For each monitoring task, a monitoring report in a preset image and text format is generated based on the type of monitored crop, the type of monitored growth, the monitoring results, and the remote sensing image of the marked target farmland.

[0156] The crop monitoring device provided in this embodiment also includes a transmission module.

[0157] The determining module 62 is also used to periodically determine the monitoring results of the user's corresponding farmland for each monitoring growth condition type in response to the detection that the user has started the early warning task service; the sending module is used to send early warning prompt information to the user terminal if the monitoring results of at least one monitoring growth condition type meet the early warning conditions.

[0158] The crop monitoring device provided in this embodiment can perform... Figures 3-4 The specific implementation principles and technical effects of any of the method embodiments shown are similar, and will not be repeated here.

[0159] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, as shown below. Figure 6 As shown, the electronic device 70 provided in this embodiment includes a processor 71 and a memory 72 that is communicatively connected to the processor.

[0160] The memory 72 stores computer-executable instructions; the processor 71 executes the computer-executable instructions stored in the memory to implement the crop monitoring method provided in any of the above embodiments. Related explanations can be understood by referring to the descriptions and effects corresponding to the steps in the accompanying drawings, and will not be elaborated upon here.

[0161] The program may include program code, which includes computer-executable instructions. Memory 72 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.

[0162] In this embodiment, the memory 72 and the processor 71 are connected via a bus. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0163] This application also provides a computer-readable storage medium storing computer-executable instructions. When executed by a processor, these instructions are used to implement the crop monitoring method provided in any of the above embodiments. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0164] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the crop monitoring method provided in any of the above embodiments.

[0165] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0166] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0167] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0168] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0169] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0170] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0171] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0172] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0173] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for monitoring crops, characterized in that, The method includes: In response to receiving a crop monitoring request triggered by at least one user through an operation interface, the system obtains the monitoring requirement information included in the crop monitoring request; the monitoring requirement information includes: a monitoring task identifier, location information of at least one farmland, type of crop to be monitored, and type of growth status to be monitored; the type of growth status to be monitored is any one or more of drought, flood, pests, and yield. The farmland information to be merged and downloaded is determined based on the location information of farmland in the monitoring task corresponding to at least one user and the preset image download size, and the corresponding farmland remote sensing image is downloaded based on the farmland information to be merged and downloaded. Obtain a preset farmland type mapping table; wherein, the preset farmland type mapping table is a data table that stores the mapping relationship between the location information of all farmland and the corresponding monitored crop type; The location information of the farmland that has a mapping relationship with the monitored crop type is found in the preset farmland type mapping table, and the location information of the farmland that has a mapping relationship with the monitored crop type is determined as the location information of the farmland corresponding to the monitored crop type; The remote sensing image of the farmland is cropped according to the location information of the farmland and the type of monitored crop to obtain a remote sensing image of the target farmland corresponding to at least one user's monitoring task. Based on the remote sensing image of the target farmland, the location information of the farmland, the type of monitored crop, and the type of monitored growth, at least one crop in a user monitoring task is monitored to obtain monitoring results. Based on the monitoring results, a monitoring report is generated corresponding to the monitoring task identified by the monitoring task identifier; The method further includes: in response to detecting that a user has enabled the early warning task service, periodically determining the monitoring results of the user's corresponding farmland for each monitoring growth condition type; if the monitoring results of at least one monitoring growth condition type meet the early warning conditions, then sending an early warning prompt message to the user terminal.

2. The method according to claim 1, characterized in that, The farmland information to be merged and downloaded includes the location information of the farmland to be merged and downloaded; The farmland remote sensing image downloaded based on the farmland information to be merged and downloaded includes: An image download request is sent to the image storage server. The image download request includes the location information of the farmland to be merged and downloaded. The location information of the farmland to be merged and downloaded is used to instruct the image storage server to obtain remote sensing images of farmland corresponding to all the farmland to be merged and downloaded. Receive remote sensing images of farmland sent by the image storage server.

3. The method according to claim 1, characterized in that, The monitoring requirements information also includes: the monitoring period; Based on the remote sensing image of the target farmland, the location information of the farmland, the type of crop to be monitored, and the type of growth status to be monitored, at least one crop in a user monitoring task is monitored to obtain monitoring results, including: The location information of the farmland and the monitoring duration matched with the type of crop are obtained, and the monitoring duration is related to the area, type and growth period of the crop; The monitoring results for each monitoring cycle within the monitoring period are determined based on remote sensing images of the target farmland.

4. The method according to claim 3, characterized in that, The determination of corresponding monitoring results for each monitoring cycle within the monitoring duration based on remote sensing images of the target farmland includes: Obtain a prediction model that matches the monitored crop type and the monitored growth condition type; In each monitoring cycle within the monitoring period, the remote sensing image of the target farmland is input into the corresponding prediction model, and the prediction model is used to predict the degree of the monitored growth condition type to obtain the monitoring result corresponding to each monitoring cycle. The degree is any one of severe, moderate and mild.

5. The method according to claim 4, characterized in that, The process of generating a monitoring report based on the monitoring results, corresponding to the monitoring task identifier, includes: For each monitoring task identified, a monitoring report is generated based on the type of monitored crop, the type of monitored growth, and the monitoring results.

6. The method according to claim 5, characterized in that, After using the prediction model to predict the degree of monitoring growth type to obtain the monitoring results for each monitoring cycle, the method further includes: The monitoring results are marked in the remote sensing image of the target farmland to obtain the marked remote sensing image of the target farmland; The process of generating a monitoring report for each monitoring task corresponding to a monitoring task identifier, based on the monitored crop type, the monitored growth condition type, and the monitoring results, includes: For each monitoring task identified, a monitoring report in a preset image and text format is generated based on the monitored crop type, the monitored growth condition type, the monitoring results, and the marked remote sensing image of the target farmland.

7. A crop monitoring device, characterized in that, The device includes: The acquisition module is used to respond to receiving a crop monitoring request triggered by at least one user through an operation interface, and to acquire the monitoring requirement information included in the crop monitoring request; the monitoring requirement information includes: monitoring task identifier, location information of at least one farmland, type of crop to be monitored, and type of growth status to be monitored; the type of growth status to be monitored is any one or more of drought, flood, pests, and yield; The determination module is used to determine the farmland information to be merged and downloaded based on the location information of farmland in the monitoring task corresponding to at least one user and the preset image download size; The download module is used to download the corresponding farmland remote sensing image based on the farmland information to be merged and downloaded; The acquisition module is further configured to acquire a preset farmland type mapping table; wherein, the preset farmland type mapping table is a data table that stores the mapping relationship between the location information of all farmland and the corresponding monitored crop type; The determining module is further configured to search the preset farmland type mapping table for the location information of the farmland that has a mapping relationship with the monitored crop type, and determine the location information of the farmland that has a mapping relationship with the monitored crop type as the location information of the farmland corresponding to the monitored crop type; The cropping module is used to crop the remote sensing image of the farmland according to the location information of the farmland and the type of monitored crop, so as to obtain the remote sensing image of the target farmland corresponding to at least one user's monitoring task. The monitoring module is used to monitor crops in at least one user monitoring task based on the remote sensing image of the target farmland, the location information of the farmland, the type of monitored crops, and the type of monitored growth, so as to obtain monitoring results; The generation module is used to generate a monitoring report for the monitoring task corresponding to the monitoring task identifier based on the monitoring results; The crop monitoring device also includes: a transmission module; The determining module is also used to periodically determine the monitoring results of the user's corresponding farmland for each monitoring growth condition type in response to the detection that the user has enabled the early warning task service; The sending module is used to send a warning message to the user terminal if the monitoring results of at least one type of growth monitoring meet the warning conditions.

8. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 6.

Images