Intelligent presentation method for plant care solutions, intelligent plant care method

Abstract

This invention discloses a method for intelligently presenting plant care plans and a method for intelligent plant care. The method for intelligently presenting plant care plans includes, in response to input of a plant name, presenting the care plan corresponding to the plant name in a visual interface; and / or, making adaptation adjustments to the matched care plan; and outputting the adjusted care plan to the user in a visual interface format. This method, which allows for intelligent generation of care plans by simply inputting the plant name, improves the efficiency of care plan generation.

Description

Technical Field

[0001] This invention relates to the field of information processing technology, specifically to a method for intelligently presenting plant maintenance solutions and a method for intelligent plant maintenance. Background Technology

[0002] Currently, plant care relies on personal experience or consulting books and online information. However, there are many types of plants, and personal experience only plays a limited role, which is inefficient and labor-intensive. Summary of the Invention

[0003] The main objective of this invention is to provide a smart method for presenting plant care solutions and a smart plant care method, in order to address the shortcomings of related technologies.

[0004] To achieve the above objectives, according to a first aspect of the present invention, a method for intelligently presenting plant care plans is provided, comprising, in response to an input operation of a plant name, presenting the care plan corresponding to the plant name in a visual interface; and / or, performing adaptation adjustments on the matched care plan; and outputting the adjusted care plan to the user terminal in the form of a visual interface.

[0005] To achieve the above objectives, according to a second aspect of the present invention, a plant intelligent maintenance method is provided, comprising: responding to a maintenance check-in trigger operation corresponding to any plant name in a plant maintenance interface, presenting a maintenance record interface for that plant name, wherein maintenance records associated with that plant name are presented in chronological order in the maintenance record interface; if a maintenance check-in trigger operation for any maintenance record is detected, displaying a plurality of preset maintenance tags in the maintenance check-in interface, wherein each maintenance tag corresponds to a maintenance type; responding to a selection operation of one or more maintenance tags (default or reselected), displaying maintenance check-in records indicating one or more maintenance types successfully checked in by one or more maintenance tags, wherein no triggerable maintenance check-in control is associated with each maintenance check-in record.

[0006] This embodiment presents a method for intelligently presenting plant care plans and a method for intelligent plant care. The intelligent plant care plan presentation method includes, in response to the input of a plant name, presenting the corresponding care plan on a visual interface; and / or, making adaptation adjustments to the matched care plan; and outputting the adjusted care plan to the user in a visual interface format. This method, which allows for intelligent generation of care plans by simply inputting the plant name, improves the efficiency of care plan generation. Attached Figure Description

[0007] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0008] Figure 1 This is a flowchart of the intelligent presentation method for plant maintenance solutions according to an embodiment of the present invention; Figures 2-9 This is an application diagram of an embodiment of the present invention; Figure 10 This is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0009] To enable those skilled in the art to better understand the present invention, 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0010] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of the invention described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0011] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0012] According to an embodiment of the present invention, an intelligent maintenance method is provided, with reference to... Figure 1 This includes step 101: in response to the input of a plant name, presenting the maintenance plan corresponding to the plant name in a visual interface; and / or, step 102: making adaptation adjustments to the matched maintenance plan; and outputting the adjusted maintenance plan to the user in the form of a visual interface.

[0013] In this embodiment, when a user enters "pomegranate flower" in the input field of the mini-program, the maintenance plan for "pomegranate flower" is directly retrieved from the database and displayed on the interface. However, since the maintenance plan varies slightly depending on the environment, the user's authorized location information (e.g., the user's location is "Haidian District, Beijing") is automatically obtained, and "Plant Name: Pomegranate Flower" + "Region: Haidian District, Beijing" is encapsulated into a request packet and sent to the backend server through the interface.

[0014] By searching using "plant name keywords + family and genus tags", we can identify that "pomegranate flower" corresponds to "Punica genus of Punicaceae". The database already contains standardized care plans for this plant, so we can directly select the plan content (including: "prefers warm and sunny conditions, dislikes dark and damp conditions; prefers well-drained sandy soil; has strong self-seeding ability" etc.).

[0015] During adaptation adjustments, environmental data of the user's location, such as climate data, is incorporated. Climate data for "Haidian District, Beijing" (temperate monsoon climate: hot and rainy summers, cold and dry winters, average annual sunshine duration of 2600 hours) is obtained, and the locked maintenance plan is adjusted accordingly. For example, the original standardized plan's "watering: water when dry" is adjusted to: "water once every 2-3 days in summer (June-August), avoid waterlogging; move indoors to a sunny location in winter (November-February), water once every 10-15 days"; and a region-specific reminder is added: "When the winter temperature in Beijing is below 5℃, fertilization should be suspended to avoid root damage from freezing."

[0016] Finally, the adjusted maintenance plan is returned to the mini-program frontend from the output backend of the visualization interface. The frontend displays the adjusted content in a visual form: "It prefers a warm, sunny environment and does not grow well in dark and damp places. It is extremely tolerant of poor soil and can adapt to most soils, but it particularly loves well-drained sandy soil. It grows vigorously and requires little management. Although it is an annual, it has a strong self-seeding ability and can achieve the effect of being ornamental for many years. [Suitable for Beijing area] Water once every 2-3 days in summer and move it indoors to a sunny place in winter and water once every 10-15 days."

[0017] As an optional implementation of this embodiment, in response to the input operation of the plant name, the maintenance plan corresponding to the plant name is presented to the visual interface; and / or, the matching maintenance plan is adapted; and the adjusted maintenance plan is output to the user terminal in the form of a visual interface.

[0018] In this optional implementation, after responding to the input operation of the plant name, the plant name is sent to the server for the server to match the plant name with the plant maintenance plan database. During the matching, if the plant is already included in the database, the maintenance plan corresponding to the included plant is used as the maintenance plan to be presented; if the plant is not included, a customized maintenance plan is directly generated based on predetermined rules.

[0019] In this optional implementation, as described in detail above, if the database contains the corresponding plant, and if the database does not include the plant input by the user, the database will automatically trigger the family and genus association for the unlisted plant, retrieve the general benchmark scheme of the corresponding category, and supplement the details by combining the plant's public basic characteristics (such as growth area and morphological characteristics) to form a usable customized scheme, thus avoiding the situation of "no scheme to match".

[0020] For example, taking "Emei Rose" as an example, the system identifies that "Emei Rose" belongs to "Rosaceae family, Rosa genus". It then retrieves the "General Maintenance Standard Scheme for Rosaceae family, Rosa genus" from the family and genus maintenance standard database (content: "Prefers full sunlight, tolerates partial shade; requires loose, fertile, and well-drained soil; applies diluted liquid fertilizer every 15 days during the growing season"). Combining this with publicly available scientific information that "Emei Rose is a high-altitude wild species", the system adds the exclusive characteristic "tolerant to low temperatures (can overwinter at -10℃), dislikes continuous high temperatures in summer (shading is required above 35℃)", generating a customized maintenance standard scheme. Furthermore, based on environmental data, such as the climate of different regions, the system is adjusted to suit Chengdu's "subtropical monsoon climate (hot and rainy summers, mild and dry winters)". The adjusted scheme includes: watering: "Water once every 1-2 days in summer, drain water promptly after rain; water once every 5-7 days in winter"; and sunlight: "Requires 3 hours of shade at midday in summer, and full sun exposure during other times." Finally, the visual interface displays a customized care plan for Rosa 'Emei' (Rosaceae family, Rosa genus). For plants not included in the list, relevant families and genera can be recommended directly. No restrictions are imposed here.

[0021] In the two-tiered standardized maintenance system, the single-plant-specific solution can be expanded through regular data iteration (adding new scientific research results and user feedback every quarter); similar general benchmark solutions can quickly cover rare / niche plants that are not included in the classification system based on the plant taxonomy system, expanding the number of matching plant species from the traditional hundreds to tens of thousands, thus improving the coverage rate.

[0022] Furthermore, for cases where the database cannot match plant conditions, plant care solutions can be determined through a process that combines publicly available online information with AI integration.

[0023] For example, generate a unique capture and integration task ID and configure the core parameters: After capturing and standardizing the data, the preprocessed structured data is organized into a Prompt input template by dimension, credibility score, and original text excerpt, for example: Based on the following web scraping information on the care of [XX plant], integrate and generate a structured and actionable care plan. Requirements: 1. The content is organized into four modules: "Basic Attributes, Environmental Requirements, Maintenance Operations, and Emergency Handling"; 2. Prioritize information with high credibility (the higher the rating, the higher the priority). In case of information conflict, the authoritative source data shall prevail. 3. Supplement the missing dimensions with general care recommendations for the plant's family and genus; 4. Use simple language, avoid technical jargon, and be suitable for ordinary family users; 5. Added region adaptation prompt (user region: Beijing).

[0024] [Screenshot Information] 1. Authoritative source (score 9): XX plant belongs to XX family and XX genus, prefers warmth, with a suitable growth temperature of 18-28℃, and dislikes waterlogging; 2. Professional Source (Score 8): Fertilize XX plant once a month during its growing season. The soil should be well-drained sandy soil. 3. Practical example (score 6): In the Beijing area, XX plant needs to be moved indoors during winter and watering should be reduced.

[0025] Then, the locally deployed large language model is invoked, and the above Prompt template is input. The output is a structured maintenance plan text, including module title, core parameters, and practical instructions, such as

Specific Maintenance Plan for XX Plant

[0026] As an optional implementation of this embodiment, when generating a maintenance plan, maintenance-related data for plants with different names are collected; the collected maintenance information for plants with different names is structurally classified according to specified dimensions to form an initial plant maintenance information pool; duplicate information in the initial plant maintenance information pool is deduplicated to obtain an initial maintenance information set; the trained verification model is used to identify errors in the initial maintenance information set and automatically correct the maintenance information; after automatic correction of the maintenance information, a standardized plant maintenance plan is formed through manual verification; and the standardized plant maintenance plan is stored in a plant maintenance plan database.

[0027] In this optional implementation method, plant-related data can be collected from compliant data sources. For example, structured scientific research data such as plant physiological characteristics, growth environment parameters, and pest and disease control can be collected from authoritative scientific research data sources; semi-structured data such as maintenance experience, practical skills, and regional adaptation suggestions can be collected from publicly available online data sources such as professional horticulture websites (e.g., the official website of the Chinese Society for Horticultural Science) and experienced horticulture communities (e.g., "Ta Hua Xing"); and user-uploaded plant maintenance feedback data can be obtained from plant identification APP open platforms (e.g., "Xing Se" and "Hua Ban Lv"), collecting UGC data such as common problems encountered by users in practice and maintenance adjustment suggestions.

[0028] Furthermore, based on the core dimensions of plant care, a structured tagging system is designed. Using Named Entity Recognition (NER) technology, it automatically identifies entities such as plant names, care parameters, and environmental conditions in the original data. A rule engine then maps the identified entities to a pre-defined structured tagging system, generating structured data. For example, "Pomegranate flowers prefer warm sunlight" is mapped to {Environmental requirements: {Light requirements: {Light intensity: Prefers sunlight}, Temperature requirements: {Suitable temperature: 15-25℃}}}.

[0029] For example, the structured tagging system is referenced in Table 1: Table 1 The deduplication and integration logic includes duplicate information identification, which identifies homologous or heterologous duplicate data based on the combination key of "plant name + core maintenance parameters"; for information with different expressions but consistent core (such as "water 1-2 times a week" and "water once every 3-5 days"), it is unified into standardized expressions (such as "watering frequency: 3-7 days / time, adjusted according to the season") through expert preset rules. After deduplication, the output forms an initial plant care information pool, with each data point accompanied by a source credibility score (scientific research data > professional websites > UGC data).

[0030] Furthermore, the verification model can be built based on a multi-dimensional contradiction identification model of the BERT pre-trained model. During training, the training data consists of maintenance data labeled with "correct samples - incorrect samples" (sample size ≥ 100,000). The incorrect samples include "logical contradictions (such as the same plant being labeled as 'likes sun' and 'avoids direct sunlight') and parameter conflicts (such as the same plant being labeled as 'once a day' and 'once a month' for watering frequency). The accuracy of the model training objective in identifying contradictory information points is ≥ 95%, and the accuracy of labeling missing information items is ≥ 90%.

[0031] Regarding full verification and automatic correction, the verification model performs a full scan of the initial information pool, identifying and automatically marking logical contradictions and parameter conflicts. The model verification process automatically identifies and corrects information inconsistencies, ensuring the logical consistency and parameter accuracy of the maintenance plan. During automatic correction, automatic correction rules are used, along with missing item labeling. Data lacking key maintenance parameters (such as unlabeled light requirements) is marked as "to be manually supplemented." For example, the automatic correction rules include credibility priority, which prioritizes data sources with high credibility scores (such as research data covering network data); and range merging, which merges conflicting parameter ranges (such as "watering 1-2 times / week" and "watering 2-3 times / week") into a broader, more reasonable range (such as "watering 1-3 times / week").

[0032] For example, taking pomegranate flowers as an example, there was a conflict in the initial data: "prefers strong direct sunlight" (scientific research data) and "avoids summer sun exposure" (online data); after model identification, it was automatically corrected to: "prefers a sunny environment, and needs appropriate shading at noon in summer" (merging the core conclusion of scientific research data and the regional adaptation suggestions of online data); the missing item was marked: "pest and disease control methods" were not included and need to be manually added.

[0033] Furthermore, the manual verification process includes expert verification and standardized supplementation. Verification experts must possess intermediate or higher professional titles in horticulture / plant protection, or have over 5 years of professional cultivation experience. The verification platform is a web-based expert collaboration system supporting parallel verification by multiple experts. Expert verification content prioritizes "awaiting manual supplementation" for missing items. High-risk data after model correction (e.g., rare plant care information) and regional adaptability parameters (e.g., differences in plant care between North and South China) are also included. Further, the data verified by experts is standardized and formatted, unifying parameter units (e.g., "light duration: 6-8 hours / day") and expression methods (e.g., "watering: when dry, 3-5 days / time in summer"). Regional adaptability tags are added, such as "indoor care required in winter in northern regions" and "drainage required during the rainy season in southern regions." Finally, a standardized plant care plan is formed, with each plan accompanied by an "expert verification signature" and "verification time."

[0034] For example, taking pomegranate flowers as an example, the standardized maintenance plan is as follows: {Plant name: Pomegranate flower, Family and genus: Punicaceae, Environmental requirements: {Light: 6-8 hours / day, Temperature: 15-25℃}, Maintenance operation: {Watering: Water when dry (3-5 days / time in summer, 10-15 days / time in winter)}, Emergency treatment: {Aphid control: 10% imidacloprid 1500 times dilution}, Regional suitability: {North China: Indoor maintenance in winter}}.

[0035] As an optional implementation of this embodiment, after responding to the input operation of the plant name, maintenance information is retrieved from a specified data source based on the plant name; and a maintenance plan is generated based on the maintenance information.

[0036] In this optional implementation, besides generating maintenance plans based on databases, it can also be directly generated. For example, the backend generates a keyword group for crawling based on the plant name submitted by the user: core keyword (plant name) + extended keywords ("maintenance method", "growing environment", "watering frequency", "light requirements", etc.); the targeted crawler traverses the specified public information sources according to the keyword group, and sets crawling rules and filtering rules: automatically remove advertising, marketing content, and non-professional subjective information (such as "I personally think XX flower does not need watering"); format rules: prioritize crawling structured text content (such as tables, segmented popular science articles), and split unstructured content (such as long text) into paragraphs; frequency rules: the crawling request frequency for a single plant is ≤ n times / second to avoid triggering the target website's anti-crawling mechanism; the crawling results are labeled with "information source type + publication time" and temporarily stored in a temporary data pool (Redis), and the crawling timeout threshold is set to 10 seconds (if the timeout occurs, only the authoritative source data that has been crawled will be used).

[0037] Information deduplication and redundant information removal are performed based on a two-dimensional approach: "content similarity + core parameters." Text similarity is calculated using the SimHash algorithm; content with a similarity ≥ 85% is considered duplicated, and only the most recent version or the version with higher authority from the source is retained. Core parameter deduplication removes obvious outliers (e.g., "watering frequency" or "light duration") from numerical parameters such as "watering frequency" and "light duration," retaining data within reasonable ranges. Redundant content removal removes information irrelevant to plant care (e.g., ornamental value or market price), retaining only core care-related content.

[0038] Structured Classification and Dimension Mapping: A pre-defined structured dimension system for maintenance information is used to automatically map captured unstructured / semi-structured information to fixed dimensions such as basic attributes, environmental requirements, maintenance operations, and emergency treatment. NLP Named Entity Recognition (NER) technology is employed to automatically extract core parameters from the text (e.g., extracting "watering frequency: 2-3 times / week" from "watering pothos 2-3 times per week"), generating a structured maintenance information table. Further, the maintenance information is verified and corrected: The initial verification of the intelligent model includes calling the pre-trained "Plant Maintenance Information Conflict Identification Model" (based on the BERT framework) to perform a full verification of the structured information table: Logical contradiction verification: Identifying conflicting information (such as "prefers strong light" and "avoids direct sunlight"), prioritizing the retention of authoritative information source data; Parameter rationality verification: Based on the commonalities of plant families and genera (such as "succulents are generally drought-tolerant"), verifying whether parameters conform to the growth patterns of this type of plant, and marking abnormal parameters (such as "succulents are watered once a day"); Abnormal / contradictory information identified during verification is marked "to be corrected," and a verification report is generated. Manual correction (optional, for high-priority / rare plants): If common plants (such as pothos, roses) are captured, the system automatically corrects them based on the verification report (such as using authoritative source parameters to cover conflicting content); if rare / niche plants are captured, the system pushes the verification report to the horticultural expert verification end, where experts supplement / correct missing / erroneous information (such as "watering frequency of a rare orchid"), forming a corrected structured maintenance information set.

[0039] Finally, personalized maintenance plans are generated based on the corrected maintenance information set, and a basic maintenance plan is generated according to rules that users can understand and execute: unifying data units (such as "light: 6 hours / day" and "watering: 3-5 days / time"), converting professional terms into common expressions (such as "soil pH value 6.0-7.0" into "slightly acidic to neutral soil"), organizing content into modules, and adapting to the front-end display logic. Based on the supplementary information submitted by users, the basic plan is personalized and adjusted as follows: For example, regional adaptation: based on the user-authorized regional information (e.g., "Beijing"), supplementary suggestions for regional differences are provided (e.g., "In Beijing, potted plants need to be moved indoors to a sunny spot during winter"); scenario adaptation: based on the user-filled "potted / ground-planted" and "location space" parameters are adjusted (e.g., "The balcony has sufficient sunlight, so supplemental lighting can be reduced; the living room has insufficient sunlight, so it is recommended to supplemental lighting for 4 hours daily"); and operation adaptation: professional operations are simplified for ordinary users (e.g., "fertilizer ratio 1:1000" is changed to "dilute 1 scoop of fertilizer with 1000ml of water").

[0040] The above implementation is merely exemplary and can be redesigned as needed. This embodiment enables one-click generation of maintenance plans, improving the efficiency of maintenance plan generation.

[0041] According to embodiments of the present invention, the present invention also provides a method for intelligently presenting plant care solutions, such as... Figure 1 As shown, this includes responding to a maintenance check-in trigger operation corresponding to any plant name in the plant maintenance interface, providing a check-in interface to execute the maintenance check-in process and obtain a maintenance record indicating completion; wherein, the maintenance check-in process includes: Step 201: Present the maintenance record interface for any plant with that name, wherein the maintenance record interface presents the maintenance records associated with any plant with that name in chronological order.

[0042] In this step, the maintenance check-in can be triggered in any way, such as by clicking a control in the interface settings. The control can also be of various types. Triggering can also be done via voice or other methods; there are no restrictions here.

[0043] Taking control triggering as an example, refer to Figure 2 The diagram illustrates the plant maintenance interface. This interface displays the plants added by the currently logged-in account that require maintenance. For plants with maintenance records but no check-ins, a corresponding maintenance check-in control can be triggered. When the control is triggered, the plant's maintenance record will be displayed. (See reference...) Figure 3 .

[0044] Step 202: If a maintenance check-in trigger operation is detected for any maintenance record, multiple preset maintenance tags will be displayed on the maintenance check-in interface, where each maintenance tag corresponds to a maintenance type. If there are any maintenance records that have not been checked in, the user can trigger the maintenance check-in control, after which a maintenance label will be displayed, for reference. Figure 4 The maintenance tags are selected by default when setting up the maintenance record. For example, the maintenance tags for the "prevent water accumulation and prevent sun exposure" maintenance record of sunflowers are selected by default.

[0045] Furthermore, no maintenance records are configured for newly added plants. Therefore, a new maintenance record is automatically generated by default after a new plant is added. This intelligent maintenance record is generated based on a pre-associated maintenance plan. This intelligently generated maintenance record can be deleted or added to.

[0046] For example, when intelligently generating maintenance records, for the plant name added by the user, the server is requested to call the maintenance plan association engine to execute the following logic: match the standardized maintenance plan corresponding to the plant name; extract the core content of the standardized maintenance plan; combine the user's location (e.g., the user authorizes to obtain "Beijing"), adjust the maintenance plan for Shanghai's current season (winter), and adjust the watering frequency to "7-10 days / time"; add a regional prompt: "Indoor air is dry in Beijing in winter, so the leaves need to be sprayed with water once a week".

[0047] Step 203: In response to the selection of one or more maintenance tags, either by default or by reselection, display maintenance check-in records for one or more maintenance types indicated by one or more maintenance tags that have been successfully checked in. No maintenance check-in control that can be triggered is associated with the maintenance check-in record.

[0048] In this step, if the user selects the final maintenance tag and successfully checks in, that record will no longer have a corresponding maintenance check-in control. If all check-in records are successfully checked in, the plants in the maintenance interface will not have a corresponding triggerable maintenance check-in control.

[0049] This embodiment achieves a fully automated closed loop of "task generation - execution check-in - status synchronization - subsequent plan creation," eliminating the need for manual user intervention in subsequent plan settings. This makes the maintenance process more efficient and significantly improves the continuity and intelligence of the interaction. Maintenance check-in records are stored in a structured format in the system database (including check-in time, maintenance type, plant growth status feedback, etc.), forming a user-specific plant maintenance behavior dataset. Based on this data (e.g., a user consistently completes watering check-ins on weekends, or a certain type of plant has a higher check-in frequency in summer), the backend can optimize the user's maintenance plan (e.g., prioritizing watering plans for weekend periods). Simultaneously, it provides real user behavior data support for the regional and seasonal adaptation iteration of standardized maintenance plans, improving the personalization and accuracy of maintenance plans and achieving a positive data cycle of "plan guidance - behavior feedback - plan optimization."

[0050] As an optional implementation of this embodiment, the method further includes: responding to the triggering operation of the maintenance plan viewing control in the presented maintenance record interface, requesting to call the maintenance plan corresponding to any plant with that name; and displaying the maintenance plan in the plant maintenance plan display interface after the maintenance plan is called.

[0051] In this optional implementation, since users may lack sufficient experience in caring for various plants, they can refer to the care plan and follow steps 101-103 for care. Therefore, the reliability of the care plan is very important. In this embodiment, the care plan is pre-generated and can be viewed.

[0052] You can select the "View" component in the plant care record interface to view the care plan. The format of the "View" component is not limited here; for example, clicking on the plant's image can trigger the viewing action. (See reference...) Figure 5 The diagram illustrates the sunflower care plan.

[0053] The interface for presenting maintenance plans can simultaneously display the plant's price, detailed information, and images; there are no restrictions on this.

[0054] As an optional implementation of this embodiment, when the control for setting maintenance reminder information for any plant name is triggered in the maintenance record interface, a maintenance reminder setting page is presented. This page displays a maintenance tag and a reminder configuration information component. If the triggering of the maintenance tag and reminder configuration information component is detected, a target maintenance record is generated based on the maintenance type indicated by the maintenance tag and the reminder configuration information, and displayed on the maintenance check-in page. When the generated target maintenance record is displayed on the maintenance check-in page, the target maintenance record is associated with the maintenance check-in control.

[0055] In this optional implementation, refer to Figure 6 Users can trigger reminder configuration controls such as Figure 6 The clock icon in the middle then displays the reminder settings page, such as... Figure 7 The maintenance reminder settings interface displays maintenance tags. When a tag is selected, it reminds the user of the type of maintenance to be performed. The reminder configuration information component can include a reminder time setting component, a reminder cycle, and a reminder content component. Once triggered, the reminder content component allows the user to input text information.

[0056] Furthermore, if the addition is successful, the settings information can be displayed in the maintenance record interface for reference. Figure 3 For newly generated records that have not yet been checked in, there is a corresponding maintenance check-in control. This means that a check-in operation can be performed on maintenance records that have not yet been checked in, but there is no corresponding maintenance check-in control for records that have already been checked in, and it is not possible to continue checking in.

[0057] Furthermore, in the maintenance record interface, each maintenance record is displayed in the order of the reminder time set.

[0058] The above method allows users to personalize their maintenance plans based on provided maintenance solutions. These plans consist of multiple user-configured reminders. This referable and configurable approach helps users plan their maintenance more clearly, thereby improving maintenance efficiency.

[0059] As an optional implementation method in this embodiment, when the growth record control under any maintenance record in the maintenance record interface of any plant is triggered, the growth record configuration interface is displayed; the input growth record configuration information is obtained, and the growth record configuration information is displayed under the maintenance record.

[0060] In this optional implementation, refer to Figure 3 For each maintenance record, a corresponding growth record control is set up. When this growth record control is triggered, the growth record configuration interface can be displayed. (See reference...) Figure 8 Users can upload images and add text.

[0061] As an optional implementation method in this embodiment, after a successful check-in, when the modification control of the maintenance label under any maintenance record is triggered, a preset display interface of multiple maintenance labels is presented for reselecting the maintenance label.

[0062] In this optional implementation, refer to Figure 9 The diagram shows a corresponding edit control after a successful maintenance check-in record. This control can be triggered to adjust maintenance tags such as... Figure 4 The selection will then be re-selected. This will allow you to modify the maintenance type in the maintenance record.

[0063] As an optional implementation of this embodiment, the method further includes: responding to the trigger operation of the plant name addition control in the plant maintenance interface, sending the target plant name indicated by the trigger operation of the plant name addition control to the server, so that the server can determine the relevant plant name from the database based on the target plant name; obtaining the relevant plant name sent by the server, and displaying the relevant plant name addition interface, wherein the relevant plant name addition interface includes the plant name addition control; when the plant name addition control is triggered, adding the plant name indicated by the trigger operation to the plant maintenance interface.

[0064] In this optional implementation, the plants displayed in the plant maintenance interface are pre-added by the user by triggering the add control. If a new plant needs to be added, the add control can be triggered to provide a plant name input interface. Based on the plant name entered by the user, the server can retrieve the relevant plant from the database. If a complete match exists, the name of the plant is retrieved from the database and provided to the interface. Subsequently, the maintenance plan can be viewed and the maintenance record can be generated.

[0065] The above method can be implemented using a mini-program. A mini-program is a cloud-based app developed using a specific programming language that can be used without downloading or installing. One of the characteristics of mini-programs is their ease of use, as they do not require manual installation on the terminal's operating system.

[0066] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0067] According to embodiments of the present invention, the present invention also provides an electronic device, the electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to implement the methods described in any of the above embodiments.

[0068] According to embodiments of the present invention, the present invention also provides a readable storage medium storing computer instructions that enable a computer to perform the methods described in any of the above embodiments when executed.

[0069] According to embodiments of the present invention, the present invention also provides a computer program product that, when executed by a processor, can implement the methods described in any of the above embodiments.

[0070] Figure 10 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices.

[0071] like Figure 10 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0072] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0073] The computing unit 301 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the object matching method. For example, in some embodiments, the object matching method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the methods described above may be performed.

[0074] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0075] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0076] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

Claims

1. A method for intelligently presenting plant care solutions, characterized in that, include: In response to the input of plant name, the corresponding maintenance plan for the plant name is presented on the visual interface; And / or, make adaptation adjustments to the matched maintenance plan; The revised maintenance plan will be presented to users in a visual interface.

2. The intelligent presentation method for plant maintenance solutions according to claim 1, characterized in that, After responding to the input of a plant name, the plant name is sent to the server so that the server can match the plant name with the plant care solution database; When performing the matching, if the plant is already included in the database, the corresponding care plan for that plant will be presented as the care plan to be displayed. If the plant is not included in the list, a customized maintenance plan will be generated directly based on the predefined rules.

3. The intelligent presentation method for plant maintenance solutions according to claim 1, characterized in that, After responding to the input of a plant name, maintenance information is retrieved from a specified data source based on the plant name; and a maintenance plan is generated based on the maintenance information.

4. The intelligent presentation method for plant maintenance solutions according to claim 3, characterized in that, When generating a maintenance plan, maintenance-related data for plants with different names are collected; the collected maintenance information for plants with different names is structurally classified according to specified dimensions to form an initial plant maintenance information pool; duplicate information in the initial plant maintenance information pool is deduplicated to obtain an initial maintenance information set. The trained verification model is used to identify errors in the initial maintenance information set and automatically correct the maintenance information. After the maintenance information is automatically corrected, a standardized plant maintenance plan is formed by manual verification. Standardized plant maintenance plans are stored in the plant maintenance plan database.

5. A smart plant care method, characterized in that, include: In response to the maintenance check-in trigger operation corresponding to any plant name in the plant maintenance interface, the check-in interface is provided to execute the maintenance check-in process and obtain the maintenance record of the check-in completion; During the maintenance check-in process, the maintenance record interface for any plant with that name is displayed. The maintenance record interface displays the maintenance records associated with any plant with that name in chronological order. If a maintenance check-in trigger operation is detected for any maintenance record, multiple preset maintenance tags will be displayed in the maintenance check-in interface, where each maintenance tag corresponds to a maintenance type. In response to the selection of one or more maintenance tags, either by default or by reselection, display the maintenance check-in records of one or more maintenance types indicated by one or more maintenance tags that have been successfully checked in.

6. The intelligent plant care method according to claim 5, characterized in that, The method also includes: In response to the triggering operation of the maintenance plan viewing control in the presented maintenance record interface, a request is made to call the maintenance plan corresponding to any plant with that name; Once the maintenance plan is invoked, it will be displayed in the plant maintenance plan display interface.

7. The intelligent plant care method according to claim 5, characterized in that, The method also includes: When the control for setting maintenance reminder information for any plant with that name is triggered in the maintenance record interface, the maintenance reminder settings interface is displayed. In the maintenance reminder settings page, maintenance tags and reminder configuration information components are displayed. If a trigger operation is detected for the maintenance label and reminder configuration information component, a target maintenance record is generated based on the maintenance type indicated by the maintenance label and the reminder configuration information and displayed in the maintenance record interface. When the generated target maintenance record is displayed in the maintenance record interface, the target maintenance record is associated with the maintenance check-in control.

8. The intelligent plant care method according to claim 5, characterized in that, The method also includes: When the growth record control under any maintenance record in the maintenance record interface of any plant is triggered, the growth record configuration interface is displayed. Retrieve the input growth record configuration information and display it under any maintenance record.

9. The intelligent plant care method according to claim 5, characterized in that, After a successful check-in, when the modification control for the maintenance label under any maintenance record is triggered, a preset interface of multiple maintenance labels will be displayed for reselecting the maintenance label.

10. The intelligent plant care method according to claim 5, characterized in that, The method also includes: In response to the triggering operation of the plant name addition control in the plant maintenance interface, the target plant name indicated by the triggering operation of the plant name addition control is sent to the server, so that the server can determine the relevant plant name from the database based on the target plant name; Get the relevant plant names sent by the server and display the relevant plant name addition interface, wherein the relevant plant name addition interface includes plant name addition controls; When the plant name addition control is triggered, the plant name indicated by the triggering operation will be added to the plant maintenance interface.

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