A data detection and analysis system for a garden plant growth environment

Abstract

The application discloses a kind of data detection analysis systems for garden plant growth environment, belong to the technical field of landscaping, including input module, cloud search module, database, GPS module, camera module, data processing module, detection module, judging module, date measurement module, alarm module, analysis module, storage module and display module, wherein, the cloud search module is connected with cloud platform by WiFi;The camera module includes camera device;The detection module includes detection device, the health status of garden plant can be judged in real time by the application, so that the sick garden plant can be treated in time, and the analysis of growth environment can change according to the change of planting species, so that the data detection and analysis of garden plant growth environment can be adapted, and then the growth environment of garden plant can be changed accordingly, to ensure the growth quality of garden plant.

Description

Technical Field

[0001] This invention relates to the field of landscaping technology, and in particular to a data detection and analysis system for the growth environment of garden plants. Background Technology

[0002] Garden plants are plant materials suitable for landscaping, including woody and herbaceous flowering, foliage, or fruiting plants, as well as protective and economic plants suitable for gardens, green spaces, and scenic spots. Plants used for indoor floral decoration also belong to garden plants. Garden plants are divided into two main categories: woody garden plants and herbaceous garden plants. In addition, they also include ferns, aquatic plants, succulent cacti, and carnivorous plants. As people's living standards continue to improve, people's pursuit of the quality of garden plants is gradually increasing. The factors that affect the quality of garden plants mainly include the content of various elements in the soil, temperature, humidity, and light intensity.

[0003] A search revealed that Chinese patent number CN202010579258.7 discloses a monitoring system for the safety of agricultural product planting environment. Although it can monitor the planting environment in real time and ensure product quality, it is limited to a single planting type and cannot analyze whether the growth environment is qualified based on the planting type. Therefore, it is not suitable for data detection and analysis of the growth environment of garden plants. At the same time, it cannot make targeted changes to the growth environment of garden plants, which reduces the growth quality of garden plants. Furthermore, general detection and analysis systems cannot judge the health status of garden plants in real time, and thus cannot provide timely treatment for diseased garden plants, resulting in system defects. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a data detection and analysis system for the growth environment of garden plants.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A data detection and analysis system for the growth environment of garden plants includes an input module, a cloud search module, a database, a GPS module, a camera module, a data processing module, a detection module, a judgment module, a date measurement module, an alarm module, an analysis module, a storage module, and a display module.

[0007] The cloud search module is connected to the cloud platform via WiFi; the camera module includes a camera device; and the detection module includes a detection device.

[0008] Furthermore, the input module is used to input the names of the planted garden plants and send them to the cloud search module; the cloud search module retrieves leaf feature information, planting information, and seasonal change information corresponding to the garden plant names based on the cloud platform; the database is used to store the leaf feature information, planting information, and seasonal change information corresponding to the garden plant names and establish a mapping relationship; the GPS module is used to generate camera coordinate information and detection coordinate information for the camera device and detection device; the camera module is used to take photos of the garden plants, generate image data, and send it to the data processing module; the data processing module is used to process the image data, generate plant geographical location information and leaf appearance information; the date measurement module is used to measure the date, generate date information, and send it to the judgment module.

[0009] Furthermore, the specific steps for generating plant geographic location information are as follows:

[0010] S1. Geographic coordinates centered on camera coordinate information;

[0011] S2. Based on the camera range of the camera device, establish a spatial coordinate system with the central geographic coordinates as the center;

[0012] S3. Select a geographic coordinate point in the spatial coordinate system as a control point, and assign the control point to the pixel point in the imaging matrix of the camera device. Using the control point and the pixel point as known quantities, obtain the geographic coordinates of other pixel points in the imaging matrix based on projection transformation and coordinate transformation.

[0013] S4. Derive the geographic coordinates of the garden plants based on the pixels where they are located, thus obtaining the geographical location information of the plants, and send it to the storage module.

[0014] The storage module is used to store plant geographic location information.

[0015] Furthermore, the judgment module is used to determine whether the garden plants are normal, and the specific steps of the judgment are as follows:

[0016] SS1 receives blade appearance information generated by the data processing module;

[0017] SS2. Extract the leaf feature information stored in the database, calculate the similarity value between the leaf appearance information and the leaf feature information mentioned in step SS1, extract the leaf feature information corresponding to the maximum similarity value, and extract the corresponding seasonal change information according to the mapping relationship.

[0018] SS3. Determine the season of the garden plants based on the date information, and then use crawling technology to crawl the leaf information corresponding to the season in the seasonal change information, and calculate the similarity value between the leaf appearance information and the leaf information again.

[0019] SS4. Determine whether garden plants are normal based on similarity values:

[0020] A. If the similarity value is <90%, the garden plants are abnormal, an alarm command is generated and sent to the alarm module;

[0021] B. If the similarity value is ≥90%, the garden plants are normal, and the operation is repeated in the camera module.

[0022] The alarm module is used to generate voice alarms.

[0023] Furthermore, the detection module is used to detect the growth environment of garden plants, generate environmental information, and send it to the analysis module; the analysis module is used to analyze whether the environmental information is normal, and its analysis process is as follows:

[0024] SSS1: Determine the names of garden plants around the detection device based on the detection coordinate information and the plant geographical location information in the storage module;

[0025] SSS2. Extract the planting information corresponding to the names of garden plants in step SSS1 based on the mapping relationship. The planting information includes soil threshold information, temperature threshold information, humidity threshold information and light intensity threshold information.

[0026] SSS3: Determine whether each data point in the environmental information falls within the threshold range in step SSS2;

[0027] SSS3. If all items are present, the environmental information is normal. If any item is not present, the environmental information is abnormal. An alarm command is generated and sent to the alarm module. At the same time, an analysis report is generated and the names of the garden plants, detection coordinates, and analysis report are sent to the display module.

[0028] The display module is used to display the names of garden plants, detection coordinate information, and analysis reports.

[0029] Furthermore, the environmental information includes soil information, temperature information, humidity information, and light intensity information.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0031] 1. This invention generates image data through a camera module and sends it to a data processing module to obtain leaf appearance information of garden plants. A judgment module then receives the leaf appearance information, extracts leaf feature information stored in a database, calculates the similarity value between the two, extracts the leaf feature information corresponding to the maximum similarity value, and extracts the corresponding seasonal change information based on the mapping relationship. The judgment module then determines the season of the garden plant based on the date information and uses web crawling technology to retrieve leaf information corresponding to the seasonal change information. The similarity value between the leaf appearance information and the leaf information is calculated again. If the similarity value is <90%, the garden plant is abnormal, an alarm command is generated, and an alarm module issues a voice alarm. If the similarity value is ≥90%, the garden plant is normal, achieving the goal of real-time judgment of the health status of garden plants, thus enabling timely treatment of diseased garden plants.

[0032] 2. This invention obtains plant geographic location information through a data processing module, then the analysis module determines the names of garden plants around the detection device based on the detection coordinate information and plant geographic location information, and obtains the corresponding planting information according to the mapping relationship. Then, the detection module detects the growth environment of the garden plants to form environmental information. By comparing the environmental information with the planting information, if the environmental information is not within the range of the planting information, the growth environment of the garden plants is unqualified, otherwise it is qualified. This allows the analysis of the growth environment to change according to the changes in planting species, thereby adapting to the data detection and analysis of the garden plant growth environment. In this way, the growth environment of the garden plants can be modified in a targeted manner to ensure the growth quality of the garden plants. Attached Figure Description

[0033] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0034] Figure 1 This is a flowchart illustrating a data detection and analysis system for the growth environment of garden plants proposed in this invention. Detailed Implementation

[0035] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0036] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0037] Example 1:

[0038] Please see Figure 1 The present invention provides a technical solution: a data detection and analysis system for the growth environment of garden plants, comprising an input module, a cloud search module, a database, a GPS module, a camera module, a data processing module, a detection module, a judgment module, a date measurement module, an alarm module, an analysis module, a storage module, and a display module;

[0039] The cloud search module connects to the cloud platform via WiFi; the camera module includes a camera device; the detection module includes a detection device; the input module is used to input the names of planted garden plants and send them to the cloud search module; the cloud search module retrieves leaf characteristic information, planting information, and seasonal change information corresponding to the names of garden plants based on the cloud platform; the database is used to store leaf characteristic information, planting information, and seasonal change information corresponding to the names of garden plants and establish a mapping relationship; the GPS module is used to generate camera coordinate information and detection coordinate information for the camera device and the detection device; the camera module is used to take photos of garden plants, generate image data, and send it to the data processing module; the data processing module is used to process the image data, generate plant geographical location information and leaf appearance information; the date measurement module is used to measure the date, generate date information, and send it to the judgment module; the judgment module is used to determine whether the garden plants are normal, and the specific steps of the judgment are as follows:

[0040] SS1 receives blade appearance information generated by the data processing module;

[0041] SS2. Extract the leaf feature information stored in the database, calculate the similarity value between the leaf appearance information and the leaf feature information mentioned in step SS1, extract the leaf feature information corresponding to the maximum similarity value, and extract the corresponding seasonal change information according to the mapping relationship.

[0042] SS3. Determine the season of the garden plants based on the date information, and then use crawling technology to crawl the leaf information corresponding to the season in the seasonal change information, and calculate the similarity value between the leaf appearance information and the leaf information again.

[0043] SS4. Determine whether garden plants are normal based on similarity values:

[0044] A. If the similarity value is <90%, the garden plants are abnormal, an alarm command is generated and sent to the alarm module;

[0045] B. If the similarity value is ≥90%, the garden plants are normal, and the operation is repeated in the camera module.

[0046] The alarm module is used to generate voice alarms.

[0047] Specifically, in the process of judging the condition of garden plants, the camera module captures images of the surrounding area to form image data. The data processing module then processes the image data to obtain the leaf appearance information of the garden plants. The judgment module receives the leaf appearance information, extracts the leaf feature information stored in the database, calculates the similarity value between the two, extracts the leaf feature information corresponding to the maximum similarity value, and extracts the corresponding seasonal change information according to the mapping relationship. At this time, the judgment module determines the season of the garden plants based on the date information, and then uses web crawling technology to crawl the leaf information corresponding to the season in the seasonal change information. The similarity value between the leaf appearance information and the leaf information is calculated again. If the similarity value is <90%, the garden plants are abnormal, an alarm command is generated, and the alarm module issues a voice alarm. If the similarity value is ≥90%, the garden plants are normal, achieving the purpose of judging the health status of garden plants in real time, so that diseased garden plants can be treated in a timely manner.

[0048] Example 2:

[0049] Please see Figure 1 This invention provides a technical solution: a data detection and analysis system for the growth environment of garden plants, wherein the specific steps for generating plant geographic location information are as follows:

[0050] S1. Geographic coordinates centered on camera coordinate information;

[0051] S2. Based on the camera range of the camera device, establish a spatial coordinate system with the central geographic coordinates as the center;

[0052] S3. Select a geographic coordinate point in the spatial coordinate system as a control point, and assign the control point to the pixel point in the imaging matrix of the camera device. Using the control point and the pixel point as known quantities, obtain the geographic coordinates of other pixel points in the imaging matrix based on projection transformation and coordinate transformation.

[0053] S4. Derive the geographic coordinates of the garden plants based on the pixels where they are located, thus obtaining the geographical location information of the plants, and send it to the storage module.

[0054] The storage module stores plant geographic location information, the detection module detects the growth environment of garden plants, generates environmental information, and sends it to the analysis module; the analysis module analyzes whether the environmental information is normal, and its analysis process is as follows:

[0055] SSS1: Determine the names of garden plants around the detection device based on the detection coordinate information and the plant geographical location information in the storage module;

[0056] SSS2. Extract the planting information corresponding to the names of garden plants in step SSS1 based on the mapping relationship. The planting information includes soil threshold information, temperature threshold information, humidity threshold information and light intensity threshold information.

[0057] SSS3: Determine whether each data point in the environmental information falls within the threshold range in step SSS2;

[0058] SSS3. If all items are present, the environmental information is normal. If any item is not present, the environmental information is abnormal. An alarm command is generated and sent to the alarm module. At the same time, an analysis report is generated and the names of the garden plants, detection coordinates, and analysis report are sent to the display module.

[0059] The display module is used to display the names of garden plants, detection coordinates, and analysis reports. The environmental information includes soil information, temperature information, humidity information, and light intensity information.

[0060] Specifically, in the process of analyzing the growth environment of garden plants, the data processing module uses the camera coordinate information as the central geographic coordinate and establishes a spatial coordinate system based on the camera range. Then, a geographic coordinate point is selected as a control point within this system, and the control point is mapped to a pixel in the imaging matrix of the camera device. Using the control point and the pixel as known quantities, the geographic coordinates of other pixels in the imaging matrix are obtained through projection transformation and coordinate transformation. Finally, the geographic coordinates of the garden plants are derived from the pixels where they are located, thus obtaining the plant's geographic location information. The analysis module then determines the names of the garden plants surrounding the detection device based on the detection coordinate information and the plant's geographic location information, and obtains the corresponding planting information based on the mapping relationship. The detection module then detects the growth environment of the garden plants, forming environmental information. This environmental information is compared with the planting information. If the environmental information is not within the range of the planting information, the garden plant's growth environment is considered unqualified; otherwise, it is considered qualified. This allows the analysis of the growth environment to change according to variations in planting species, thus adapting to the data detection and analysis of the garden plant's growth environment. This enables targeted modifications to the garden plant's growth environment, ensuring the quality of its growth.

[0061] The working principle and usage process of this invention are as follows: When it is necessary to determine the condition of garden plants, the camera module captures images of their surroundings, forming image data. The data processing module then processes this image data to obtain leaf appearance information. The judgment module receives this leaf appearance information, extracts leaf feature information stored in the database, calculates the similarity value between the two, extracts the leaf feature information corresponding to the maximum similarity value, and extracts the corresponding seasonal change information based on the mapping relationship. The judgment module then determines the season of the garden plant based on the date information and uses web crawling technology to retrieve leaf information corresponding to the season from the seasonal change information. The similarity value between the leaf appearance information and the leaf information is calculated again. If the similarity value is <90%, the garden plant is abnormal, an alarm command is generated, and the alarm module issues a voice alarm. If the similarity value is ≥90%, the garden plant is normal, achieving the purpose of real-time assessment of the health status of garden plants. This allows for timely treatment of sick garden plants. When it is necessary to analyze the growth environment of garden plants, the data processing module uses camera coordinate information... Using the central geographic coordinates as the basis, a spatial coordinate system is established based on the camera's range. A geographic coordinate point is then selected within this system as a control point, and this control point is mapped to a pixel in the imaging matrix of the camera device. Using the control point and the pixel as known quantities, the geographic coordinates of other pixels in the imaging matrix are obtained through projection transformation and coordinate transformation. Finally, the geographic coordinates of the garden plants are derived from the pixels where they are located, thus obtaining the plant's geographic location information. The analysis module then determines the names of the garden plants surrounding the detection device based on the detection coordinates and the plant's geographic location information, and obtains the corresponding planting information based on the mapping relationship. The detection module then detects the growth environment of the garden plants, generating environmental information. This environmental information is compared with the planting information. If the environmental information is not within the range of the planting information, the garden plant's growth environment is considered unqualified; otherwise, it is considered qualified. This allows the analysis of the growth environment to change according to variations in planting species, thus adapting to the data detection and analysis of the garden plant's growth environment. This enables targeted changes to the garden plant's growth environment, ensuring the quality of its growth and completing the operation.

[0062] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A data detection analysis system for a horticultural plant growing environment, characterized by, The application comprises an input module, a cloud search module, a database, a GPS module, a camera module, a data processing module, a detection module, a judgment module, a date measurement module, an alarm module, an analysis module, a storage module and a display module. The cloud search module is connected with a cloud platform through WiFi, and the camera module comprises a camera device. The input module is used for inputting the names of the planted garden plants and sending them to the cloud search module. The cloud search module retrieves the leaf feature information, planting information and seasonal change information corresponding to the names of the garden plants according to the cloud platform. The database is used for storing the leaf feature information, planting information and seasonal change information corresponding to the names of the garden plants and establishing a mapping relationship. The GPS module is used for generating the camera coordinate information and detection coordinate information of the camera device and the detection device. The camera module is used for taking photos of the garden plants, generating image data and sending them to the data processing module. The data processing module is used for processing the image data, generating the plant geographical position information and leaf appearance information. The specific operation steps for generating the plant geographical position information are as follows: S1, taking the camera coordinate information as the center geographical coordinate; S2, establishing a space coordinate system with the center geographical coordinate as the center according to the camera range of the camera device; S3, selecting a geographical coordinate point as a control point in the space coordinate system, taking the control point and the pixel point in the imaging matrix corresponding to the control point as known quantities, and then obtaining the geographical coordinates of other pixel points in the imaging matrix according to the projection transformation and coordinate conversion; S4, deriving the geographical coordinates of the garden plants according to the pixel point where the garden plants are located, obtaining the plant geographical position information, and sending it to the storage module; The storage module is used for storing the plant geographical position information. The judgment module is used for judging whether the garden plants are normal or not, and the specific steps are as follows: SS1, receiving the leaf appearance information generated by the data processing module; SS2, extracting the leaf feature information stored in the database, calculating the similarity value between the leaf appearance information and the leaf feature information, extracting the leaf feature information corresponding to the maximum similarity value, and extracting the corresponding seasonal change information according to the mapping relationship; SS3, judging the season where the garden plants are located according to the date information, using the crawler technology to crawl the leaf information of the corresponding season in the seasonal change information, and calculating the similarity value between the leaf appearance information and the leaf information again; SS4, determining whether the garden plants are normal or not according to the similarity value: If the similarity value is less than 90%, the garden plants are not normal, an alarm instruction is generated, and it is sent to the alarm module; If the similarity value is greater than or equal to 90%, the garden plants are normal, and the operation is repeated in the camera module; The alarm module is used for generating a voice alarm. The detection module is used for detecting the growth environment of the garden plants, generating environment information and sending it to the analysis module. The analysis module is used for analyzing whether the environment information is normal or not, and the analysis process is as follows: SSS1, determining the name of the garden plant around the detection device according to the detection coordinate information and the geographical position information of the plant in the storage module; SSS2, extracting the planting information corresponding to the name of the garden plant in step SSS1 according to the mapping relationship, wherein the planting information includes soil threshold information, temperature threshold information, humidity threshold information and light intensity threshold information; SSS3, judging whether each data in the environmental information belongs to the threshold interval in step SSS2; SSS4, if all belong, the environmental information is normal, if any one does not belong, the environmental information is not normal, an alarm instruction is generated and sent to the alarm module, an analysis report is generated at the same time, and the name of the garden plant, the detection coordinate information and the analysis report are sent to the display module; The display module is used for displaying the name of the garden plant, the detection coordinate information and the analysis report.

2. The data detection and analysis system for garden plant growth environment according to claim 1, characterized in that, The environmental information includes soil information, temperature information, humidity information and light intensity information.

Images