Plant management method and device, electronic equipment and storage medium
By acquiring plant images and environmental data, identifying plant species and seasonal data, and combining this with knowledge data for management, the problem of poor plant growth was solved, and precise management under environmental differences was achieved.
Patent Information
- Application Number
- CN202510898384.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-30
- Publication Date
- 2025-11-18
AI Technical Summary
In existing technologies, it is difficult to manage plants accurately according to their different environments, resulting in poor plant growth.
By acquiring image data of plants and home environment data, plant species are identified and seasonal data is obtained, which is then combined with knowledge data for management.
This enables accurate management based on differences in the plant environment, thereby improving the quality of plant growth.
Smart Images
Figure CN120975952A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of data management, and particularly relates to a plant management method and device, electronic equipment and a storage medium. BACKGROUND
[0002] The growth environment is a basic factor affecting the growth quality of plants, and the growth environment is, for example, temperature, light, moisture and terrain soil and the like. During the growth of plants, reasonable management of plants is the key to ensuring the healthy growth of plants. At present, the existing management method cannot accurately manage plants according to different environments of plants, resulting in poor growth of plants. Therefore, there is an urgent need for a plant management method that can accurately manage plants according to different environments of plants to solve the problem that the existing management method cannot accurately manage plants according to different environments of plants, resulting in poor growth of plants. SUMMARY
[0003] The present application provides a plant management method, which aims to solve the problem that the existing management method cannot accurately manage plants according to different environments of plants, resulting in poor growth of plants. The present application obtains image data of a target plant and home environment data of the target plant, determines target knowledge data corresponding to the target plant species according to the image data, obtains seasonal data of the current time, and manages the target plant according to the seasonal data, the home environment data and the target knowledge data, thereby solving the problem that the existing management method cannot accurately manage plants according to different environments of plants, resulting in poor growth of plants.
[0004] In a first aspect, the present application provides a plant management method, which comprises the following steps:
[0005] Obtaining image data of a target plant and home environment data of the target plant;
[0006] Determining target knowledge data corresponding to the target plant species based on the image data;
[0007] Obtaining seasonal data of the current time, and managing the target plant based on the seasonal data, the home environment data and the target knowledge data.
[0008] Optionally, the home environment data of the target plant is obtained by:
[0009] Obtaining climate data of a location where the target plant is located and competition data between plants;
[0010] Determining the home environment data of the target plant based on the climate data and the competition data between plants.
[0011] Optionally, obtaining climate data of the target plant's location includes:
[0012] Obtain the first location of the target plant at the regional level and the second location at the home level;
[0013] Based on the first location and the second location, the location of the target plant is determined;
[0014] Based on the location of the target plant, the climate data of the target plant's location is determined.
[0015] Optionally, obtaining the competition and cooperation data between plants includes:
[0016] Obtain other plants located in the same location as the target plant;
[0017] Based on the other plants, competition and cooperation data between the target plant and the other plants are determined.
[0018] Optionally, determining the target knowledge data corresponding to the target plant species based on the image data includes:
[0019] Based on the image data, the plant species of the target plant are determined;
[0020] Based on the correspondence between plant species and knowledge data, the target knowledge data corresponding to the plant species is determined, with different plant species corresponding to different knowledge data.
[0021] Optionally, determining the plant species of the target plant based on the image data includes:
[0022] Plant image recognition is performed on the image data to identify the target plant;
[0023] Plant species identification is performed on the target plant to determine the plant species of the target plant.
[0024] Optionally, the management of the target plant based on the seasonal data, the home environment data, and the target knowledge data includes:
[0025] Based on the seasonal data, the home environment data, and the target knowledge data, the current growth data of the target plant is determined;
[0026] The target plant is managed based on the current growth data.
[0027] Secondly, embodiments of the present invention provide a plant management device, the plant management device comprising:
[0028] an acquisition module, configured to acquire image data of a target plant and home environment data of the target plant;
[0029] a determination module, configured to determine target knowledge data corresponding to a category of the target plant based on the image data;
[0030] a management module, configured to acquire seasonal data of a current time, and manage the target plant based on the seasonal data, the home environment data and the target knowledge data.
[0031] In a third aspect, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor implements the steps of the plant management method provided in the embodiments of the present application when executing the computer program.
[0032] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program, and the computer program implements the steps of the plant management method provided in the embodiments of the present application when executed by a processor.
[0033] In the embodiments of the present application, the image data of a target plant and the home environment data of the target plant are acquired, the target knowledge data corresponding to the category of the target plant is determined based on the image data, the seasonal data of a current time is acquired, and the target plant is managed based on the seasonal data, the home environment data and the target knowledge data. The present application acquires the image data of a target plant and the home environment data of the target plant, determines the target knowledge data corresponding to the category of the target plant according to the image data, acquires the seasonal data of a current time, and manages the target plant according to the seasonal data, the home environment data and the target knowledge data, thereby solving the problem that the existing management method cannot accurately manage plants according to different environments of the plants, resulting in poor growth of the plants. BRIEF DESCRIPTION OF DRAWINGS
[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.
[0035] Figure 1 is a flowchart of a plant management method provided in the embodiments of the present application;
[0036] Figure 2is a structural schematic diagram of a plant management device provided by an embodiment of the present application.
[0037] Figure 3 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION
[0038] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the protection scope of the present application.
[0039] As shown in Figure 1 , Figure 1 is a flowchart of a plant management method provided by an embodiment of the present application. The plant management method comprises the following steps:
[0040] 101, obtaining image data of a target plant and home environment data of the target plant.
[0041] In the embodiments of the present application, the plant management method can be applied to a plant management platform. The plant management platform can be constructed based on a centralized server or a distributed server. The plant management platform comprises a data interface (for uploading by a sensor or a user), a knowledge database, and a knowledge database construction program. The data interface can be used for the image data of the target plant and the home environment data of the target plant. The knowledge database construction program can be used to implement construction of the knowledge database. The knowledge database is dedicated to providing additional associated information for the identified data entities, so as to improve the understanding depth of the content by the data recognition system.
[0042] The target plant can be a potted plant, such as a green lily, a evergreen, a jade plant, etc.
[0043] The image data can be a photo of the target plant taken by a camera or a mobile phone.
[0044] The home environment data can be understood as the position of the room, the window, the balcony, etc. where the target plant is located, and the surrounding light, temperature, humidity, etc.
[0045] It should be noted that by obtaining the image data of the target plant and the home environment data of the target plant, the growth condition of the target plant can be analyzed.
[0046] 102, determining target knowledge data corresponding to the target plant species based on the image data.
[0047] In the embodiments of the present application, the plant species can be understood as plant species in biological taxonomy, such as green wisteria, evergreen, clivia, rose, sunflower, etc.
[0048] The target knowledge data can be knowledge data corresponding to the plant species. The knowledge data includes knowledge data of various potted plants, including plant species, growth environment, maintenance method, etc., such as green wisteria knowledge data, evergreen knowledge data, clivia knowledge data, etc.
[0049] It can be understood that different plant species correspond to different knowledge data.
[0050] It should be noted that the plant recognition model can be used to recognize the plant species of the target plant, and the corresponding knowledge data can be determined in the corresponding relationship between the plant species and the knowledge data, and the corresponding knowledge data can be determined as the target knowledge data.
[0051] The plant recognition model can be obtained by training an untrained image recognition model based on sample image data and plant species annotation data in the corresponding sample image. The untrained plant recognition model can be a plant recognition model based on deep learning or machine learning, such as ResNet, AlexNet, etc. Specifically, the untrained plant recognition model is trained based on sample image data and plant species annotation data of the corresponding sample image data. During the training process, the parameters of the plant recognition model are adjusted by the minimum loss function to obtain the trained plant recognition model. The plant species annotation data can be information for classifying and describing target objects, such as green wisteria, evergreen, clivia, rose, sunflower, etc. The training can be supervised training, which is a method of training a model using a set of data with known labels, and optimizing model parameters to enable the model to predict new data labels or make decisions based on existing data characteristics. The loss function is used to evaluate and optimize the performance of the model. The loss function can be mean square error loss function, cross-entropy loss function, etc.
[0052] The corresponding relationship between the plant species and the knowledge data is a corresponding relationship set by the system in advance, such as green wisteria corresponding to green wisteria knowledge data, evergreen corresponding to evergreen knowledge data, clivia corresponding to clivia knowledge data, etc.
[0053] 103, obtain the season data of the current time, and manage the target plant based on the season data, the home environment data, and the target knowledge data.
[0054] In the embodiments of the present application, the seasonal data of the current time can be understood as the current season, such as spring, summer, autumn and winter.
[0055] The management can be understood as management operations of regulating and maintaining the target plant, such as adjusting the watering frequency, the fertilization amount, whether to need shading, etc.
[0056] Specifically, the current growth data of the target plant can be determined by the seasonal data of the current time, in combination with the target knowledge data of the target plant and the home environment data, and the target plant is managed according to the current growth data.
[0057] In the embodiments of the present application, the image data of the target plant and the home environment data of the target plant are acquired, the target knowledge data corresponding to the target plant species is determined based on the image data, the seasonal data of the current time is acquired, and the target plant is managed based on the seasonal data, the home environment data and the target knowledge data. Through acquiring the image data of the target plant and the home environment data of the target plant, determining the target knowledge data corresponding to the target plant species according to the image data, acquiring the seasonal data of the current time, and managing the target plant according to the seasonal data, the home environment data and the target knowledge data, the present application solves the problem that the existing management method cannot accurately manage the plant according to the different environment of the plant, resulting in poor growth of the plant.
[0058] It can be understood that in the specific embodiments of the present application, plant data, image data, knowledge data, seasonal data, environment data and other related data are involved. When the embodiments of the present application are applied to specific products or technologies, the permission or consent of the user needs to be obtained, and the collection, use and processing of related data, as well as the training, deployment and calling of algorithm models, need to comply with relevant laws, regulations and standards of the country and region.
[0059] Optionally, in the step of acquiring the home environment data of the target plant, the climate data of the location where the target plant is located and the competition data between plants can be acquired; and the home environment data of the target plant is determined based on the climate data and the competition data between plants.
[0060] In the embodiments of the present application, the location where the target plant is located can be understood as the place or environment where the target plant grows, including geographical location, indoor, outdoor, balcony, garden, etc.
[0061] The climate data can be understood as weather conditions, and the climate data includes the average value and variation range of temperature, precipitation, humidity and other elements. The climate data reflects the basic characteristics of cold, warm, dry and wet in the region, and the climate data is collected by meteorological stations, satellites, etc.
[0062] The competition data between the plants can be understood as the interaction between the plants for the resources such as sunlight, moisture, nutrients, etc., and the competition includes the competition relationship and the cooperation relationship. The competition data between the plants can be used to analyze the ecological habits and the life forms of the plants, so as to determine the competition relationship or the cooperation relationship between the plants in the same environment.
[0063] The home environment data is obtained according to the climate data of the location where the target plant is located and the competition data between the plants, and includes the environment data such as the location where the target plant is located, the location near the window, the location on the balcony, and the competition data between the plants.
[0064] Optionally, in the step of obtaining the climate data of the location where the target plant is located, a first location at a region level and a second location at a home level of the target plant can be obtained; the location where the target plant is located is determined based on the first location and the second location; and the climate data of the location where the target plant is located is determined based on the location where the target plant is located.
[0065] In the embodiment of the present application, the region level can be understood as the information of the region, such as a city, a province, a country, etc.
[0066] The first location can be the location of the target plant at the region level.
[0067] The home level can be understood as the information of the home, such as the type of the house, the orientation, the floor, the ventilation state, etc.
[0068] The second location can be the location of the target plant at the home level.
[0069] The location where the target plant is located includes the place or the environment where the target plant grows, including the geographical location, the indoor, the outdoor, the balcony, the garden, etc. The location where the target plant is located can be determined by the geographic information system (GIS) technology. The geographic information system (GIS) technology is a technology combining geography, cartography, remote sensing and computer science, and is used to collect, manage, analyze and display geographical data.
[0070] The climate data includes the average value and the variation range of the elements such as temperature, precipitation, humidity, etc. The climate data reflects the basic characteristics of the cold, warm, dry, wet, etc. of the region, and the climate data is collected by the weather station, satellite, etc.
[0071] In a possible embodiment, the first location at the region level and the second location at the home level of the target plant can be determined by the geographic information system (GIS), the location where the target plant is located is determined, and the climate data such as temperature, humidity, rainfall, etc. of the location where the target plant is located is obtained by using the weather station.
[0072] Optionally, in the step of acquiring competition data between plants, other plants in the same location as the target plant can be acquired; and based on the other plants, competition data between the target plant and the other plants is determined.
[0073] In the embodiments of the present application, other plants in the same location as the target plant can be acquired, and based on the other plants, competition data between the target plant and the other plants is determined.
[0074] The competition data between plants can be understood as the interaction between plants for resources such as sunlight, water, and nutrients, and the competition includes competition and cooperation. The competition data between plants can be analyzed for ecological habits and life forms to determine the competition or cooperation between plants in the same environment.
[0075] Specifically, the competition data between plants can be collected by observing and measuring the target plant and surrounding other plants. The position, quantity, and growth state of the target plant and surrounding other plants can be recorded using a camera or a sensor. Then, the competition relationship between the target plant and surrounding other plants can be determined by analyzing the position, quantity, and growth state of the target plant and surrounding other plants. For example, if there are too many other plants around the target plant, or the growth state of the other plants is better than that of the target plant, it can be determined that there is a competition relationship between the target plant and the other plants; if the growth state of the target plant and surrounding other plants is the same, it can be determined that there is a cooperation relationship between the target plant and the other plants.
[0076] Optionally, in the step of determining the target knowledge data corresponding to the plant species of the target plant based on the image data, the plant species of the target plant can be determined based on the image data; and based on the correspondence between the plant species and the knowledge data, the target knowledge data corresponding to the plant species is determined, and different plant species correspond to different knowledge data.
[0077] In the embodiments of the present application, the plant species of the target plant can be identified by a plant recognition model based on the image data, and the corresponding knowledge data can be determined in the correspondence between the plant species and the knowledge data, and the corresponding knowledge data is determined as the target knowledge data.
[0078] The plant recognition model can recognize the plant species in the image data. The plant recognition model can be obtained by training an untrained image recognition model based on sample image data and plant species annotation data corresponding to the sample image data. The untrained plant recognition model can be a plant recognition model based on deep learning or machine learning, such as ResNet, AlexNet, etc. Specifically, the untrained plant recognition model is trained based on sample image data and plant species annotation data corresponding to the sample image data. During the training process, the parameters of the plant recognition model are adjusted by a minimum loss function to obtain a trained plant recognition model. The plant species annotation data can be information for classifying and describing target objects, such as green lily, evergreen, dracaena, rose, sunflower, etc. The training can be supervised training, which is a method of training a model using a set of data with known labels. The model can predict the labels of new data or make decisions based on the characteristics of existing data by optimizing the model parameters. The loss function is used to evaluate and optimize the performance of the model. The loss function can be a mean square error loss function, a cross-entropy loss function, etc.
[0079] The plant species can be understood as plant species in biological taxonomy, such as green lily, evergreen, dracaena, rose, sunflower, etc.
[0080] The target knowledge data can be knowledge data corresponding to the plant species of the target plant. The knowledge data includes knowledge data of various potted plants, including plant species, growth environment, maintenance method, etc. For example, green lily knowledge data, evergreen knowledge data, dracaena knowledge data, etc.
[0081] The corresponding relationship between the plant species and the knowledge data is a pre-set corresponding relationship by the system, such as green lily corresponding to green lily knowledge data, evergreen corresponding to evergreen knowledge data, dracaena corresponding to dracaena knowledge data, etc. Different plant species correspond to different knowledge data.
[0082] In one possible embodiment, the image recognition model is used to recognize the plant in the image data, and the target plant is identified as green lily. The corresponding knowledge data of the green lily in the corresponding relationship between the plant species and the knowledge data is determined as the green lily knowledge data, and the green lily knowledge data is determined as the target knowledge data.
[0083] Optionally, in the step of determining the plant species of the target plant based on the image data, the plant image recognition can be performed on the image data to recognize the target plant, and the plant species recognition can be performed on the target plant to determine the plant species of the target plant.
[0084] In the embodiments of the present application, the plant image recognition can be understood as a process of plant recognition on the image data to identify the processing of the plant.
[0085] The target plant can be a potted plant, such as green wisteria, evergreen, and so on.
[0086] The plant species recognition can be understood as a process of plant species recognition on the target plant to identify the processing of the plant species.
[0087] The plant species can be a plant species in biological taxonomy, such as green wisteria, evergreen, and so on.
[0088] It should be noted that the plant image recognition on the image data can be performed by a plant recognition model to identify the target plant, and the plant species recognition on the target plant can be performed to determine the plant species of the target plant. The plant recognition model can recognize the plant in the image data and identify the specific plant species of the plant. The plant recognition model can be a plant recognition model based on deep learning or machine learning, such as ResNet, AlexNet, and so on.
[0089] Optionally, the step of managing the target plant based on the seasonal data, the home environment data, and the target knowledge data can determine the current growth data of the target plant based on the seasonal data, the home environment data, and the target knowledge data; and manage the target plant based on the current growth data.
[0090] In the embodiments of the present application, the seasonal data can be understood as the current season, such as spring, summer, autumn, and winter.
[0091] The home environment data is obtained according to the climate data of the location where the target plant is located and the competition data between plants, and includes the environmental data such as the location of the target plant in the room, near the window, balcony, and the competition data between plants.
[0092] The target knowledge data is the knowledge data corresponding to the plant species of the target plant. The knowledge data includes the knowledge data of each potted plant, including the species, growth environment, and maintenance method of the plant, such as green wisteria knowledge data, evergreen knowledge data, and so on.
[0093] The current growth data is obtained according to the seasonal data, the home environment data, and the target knowledge data, and the current growth data can reflect the growth condition of the target plant.
[0094] The management can be a management operation of regulating and maintaining the target plant, such as adjusting the watering frequency, the amount of fertilizer, and whether to need shading, and so on.
[0095] In one possible embodiment, if the current growth data shows that the temperature and humidity are both suitable, but the light is insufficient, the target value plant position can be adjusted to increase the light time to promote the healthy growth of the target plant.
[0096] As shown in Figure 2 The plant management device provided by the embodiment of the present application comprises:
[0097] The acquisition module 201 is configured to acquire image data of a target plant and home environment data of the target plant.
[0098] The determination module 202 is configured to determine target knowledge data corresponding to the target plant species based on the image data.
[0099] The management module 203 is configured to acquire seasonal data of a current time, and manage the target plant based on the seasonal data, the home environment data and the target knowledge data.
[0100] Optionally, the acquisition module 201 is further configured to acquire climate data of a position where the target plant is located and competition and cooperation data between plants; and determine the home environment data of the target plant based on the climate data and the competition and cooperation data between plants.
[0101] Optionally, the acquisition module 201 is further configured to acquire a first position at a region level and a second position at a home level where the target plant is located; determine the position where the target plant is located based on the first position and the second position; and determine the climate data of the position where the target plant is located based on the position where the target plant is located.
[0102] Optionally, the acquisition module 201 is further configured to acquire other plants located at the same position as the target plant; and determine the competition and cooperation data between the target plant and the other plants based on the other plants.
[0103] Optionally, the determination module 202 is further configured to determine the plant species of the target plant based on the image data; and determine the target knowledge data corresponding to the plant species based on a corresponding relationship between plant species and knowledge data, wherein different plant species correspond to different knowledge data.
[0104] Optionally, the determination module 202 is further configured to perform plant image recognition on the image data to recognize the target plant; and perform plant species recognition on the target plant to determine the plant species of the target plant.
[0105] Optionally, the management module 203 is further configured to determine current growth data of the target plant based on the seasonal data, the home environment data and the target knowledge data, and manage the target plant based on the current growth data.
[0106] As shown in Figure 3 the embodiments of the present application also provide an electronic device, which comprises a processor, and the processor can execute any one of the plant management methods.
[0107] Specifically, the electronic device comprises a processor 301 and a memory 302, and a computer program for executing the plant management method stored in the memory 302 and executable on the processor 301, wherein:
[0108] The processor 301 executes the computer program for the plant management method stored in the memory 302, and performs the following steps:
[0109] obtain image data of a target plant and home environment data of the target plant;
[0110] determine target knowledge data corresponding to the target plant species based on the image data;
[0111] obtain seasonal data of the current time, and manage the target plant based on the seasonal data, the home environment data and the target knowledge data.
[0112] Optionally, the processor 301 performs the obtaining of the home environment data of the target plant, comprising:
[0113] obtain climate data of a location where the target plant is located and competition data between plants;
[0114] determine the home environment data of the target plant based on the climate data and the competition data between plants.
[0115] Optionally, the processor 301 performs the obtaining of the climate data of the location where the target plant is located, comprising:
[0116] obtain a first location at a regional level and a second location at a home level where the target plant is located;
[0117] determine the location where the target plant is located based on the first location and the second location;
[0118] determine the climate data of the location where the target plant is located based on the location where the target plant is located.
[0119] Optionally, the processor 301 performs the obtaining of the competition data between plants, comprising:
[0120] acquire other plants in the same location as the target plant;
[0121] determine competition data between the target plant and the other plants based on the other plants.
[0122] Optionally, the determining the target knowledge data corresponding to the plant species of the target plant based on the image data comprises:
[0123] determining the plant species of the target plant based on the image data.
[0124] determining the target knowledge data corresponding to the plant species based on a corresponding relationship between the plant species and the knowledge data, wherein different plant species correspond to different knowledge data.
[0125] Optionally, the determining the plant species of the target plant based on the image data comprises:
[0126] performing plant image recognition on the image data to recognize the target plant.
[0127] performing plant species recognition on the target plant to determine the plant species of the target plant.
[0128] Optionally, the managing the target plant based on the seasonal data, the home environment data and the target knowledge data comprises:
[0129] determining current growth data of the target plant based on the seasonal data, the home environment data and the target knowledge data.
[0130] managing the target plant based on the current growth data.
[0131] The embodiment of the present application further provides a computer readable storage medium, and the computer readable storage medium stores a computer program.
[0132] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing relevant hardware, and the program can be stored in a computer readable storage medium. When the program is executed, the program can include the processes of the above-mentioned embodiment methods. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM) or a random access memory (RAM).
[0133] The above only describes the preferred embodiments of the present application, and cannot limit the scope of the present application. Any equivalent changes made according to the claims of the present application are still within the scope of the present application.
Claims
1. A method for managing a plant, characterized by, The method comprises the following steps: obtaining image data of a target plant and home environment data of the target plant; based on the image data, determining target knowledge data corresponding to the target plant species; obtaining seasonal data of the current time, and based on the seasonal data, the home environment data and the target knowledge data, managing the target plant.
2. The method for managing plants according to claim 1, wherein The home environment data of the target plant comprises: obtaining climate data of the location of the target plant and competition data between plants; based on the climate data and the competition data between plants, determining the home environment data of the target plant.
3. The method for managing plants according to claim 2, wherein The climate data of the location of the target plant comprises: obtaining a first location at the regional level and a second location at the home level of the target plant; based on the first location and the second location, determining the location of the target plant; based on the location of the target plant, determining the climate data of the location of the target plant.
4. The method for managing plants according to claim 2, wherein The competition data between plants comprises: obtaining other plants in the same location as the target plant; based on the other plants, determining the competition data between the target plant and the other plants.
5. The method for managing plants according to claim 1, wherein Based on the image data, the target knowledge data corresponding to the target plant species comprises: based on the image data, determining the plant species of the target plant; based on the corresponding relationship between plant species and knowledge data, determining the target knowledge data corresponding to the plant species, different plant species corresponding to different knowledge data.
6. The method for managing plants according to claim 5, wherein Based on the image data, the plant species of the target plant comprises: performing plant image recognition on the image data to identify the target plant; performing plant species identification on the target plant to determine the plant species of the target plant.
7. The method for managing plants according to claim 1, wherein Based on the seasonal data, the home environment data and the target knowledge data, the management of the target plant comprises: based on the seasonal data, the home environment data and the target knowledge data, determining the current growth data of the target plant; based on the current growth data, managing the target plant.
8. A plant management device, characterized by comprising: The plant management device comprises: an acquisition module for obtaining image data of a target plant and home environment data of the target plant; a determination module for determining target knowledge data corresponding to the target plant species based on the image data; a management module for obtaining seasonal data of the current time, and based on the seasonal data, the home environment data and the target knowledge data, managing the target plant.
9. An electronic device, comprising: comprise: a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the plant management method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, The computer program is stored on the computer readable storage medium, and when executed by the processor, the steps of the plant management method according to any one of claims 1 to 7 are implemented.