A game-based ecological home decoration whole-process intelligent operation system

Abstract

The application discloses a home decoration full-process intelligent operation system based on a gamification ecology, and relates to the technical field of internet home decoration services. A home decoration multi-role exclusive module in the system provides different role permissions for different registered identities; a home decoration role level growth module automatically increases or decreases the level of a service party according to a gamification growth incentive mechanism; a home decoration regional pricing module determines the annual fee for entering a region according to the region and scale of a merchant; a supply-demand matching module matches service parties according to the decoration demand of a homeowner; a home decoration construction full-process management and control module automatically arranges a construction process, controls nodes and performs online acceptance; a copy generation module automatically generates publicity copies; and a completion data arrangement module supports uploading and automatically collecting full-project data after triggering of completion, generates completion data after classification, compilation and cataloging, and supports one-key downloading and delivery. The application can realize digital operation of the full process of home decoration.

Description

Technical Field

[0001] This application relates to the field of internet-based home decoration service technology, and in particular to a smart operation system for the entire home decoration process based on a gamified ecosystem. Background Technology

[0002] Internet-based home improvement services refer to a new model that utilizes internet technology to digitally transform the traditional home improvement industry. This involves facilitating transactions, ensuring information transparency, and standardizing services through online platforms, while ultimately relying on offline stores or construction sites for experience and delivery. However, existing internet-based home improvement services have the following drawbacks: 1. The home decoration industry platform only realizes basic information matching and has not created exclusive functions for each role in the home decoration industry chain, resulting in low efficiency of role collaboration; 2. There is a lack of growth incentive mechanisms for home decoration practitioners, resulting in weak sense of belonging among craftsmen, designers, and salespersons, and a high staff turnover rate; 3. Home renovation construction process control relies on manual labor, resulting in chaotic management of construction period, acceptance, and delivery, and low transparency; 4. The platform's fee structure is chaotic, with commission and order-taking fees increasing costs for merchants and practitioners, leading to excessive competition in the industry; 5. Renovation companies generally lack the ability to write promotional copy, making it difficult to efficiently convert actual construction site photos into marketing materials, resulting in high customer acquisition costs and low efficiency; 6. The compilation of as-built documents relies entirely on manual labor, resulting in chaotic classification, cumbersome compilation, non-standard formats, and long delivery cycles, which affects the settlement of final payments and the trust of the owners. 7. The home decoration industry has not formed a closed loop, and the customer acquisition, design, construction, delivery and after-sales service are disconnected.

[0003] Therefore, achieving intelligent operation across the entire process of home decoration industry, including multi-role collaboration, growth incentives, construction control, intelligent pricing, AI-powered intelligent marketing, and AI-automated processing of as-built data, can effectively promote the evolution of the home decoration industry towards "standardization, transparency, and digitalization". Summary of the Invention

[0004] The purpose of this application is to provide a smart operation system for the entire home decoration process based on a gamified ecosystem, which can realize the digital operation of the entire home decoration process.

[0005] To achieve the above objectives, this application provides the following solution: This application provides a home decoration full-process intelligent operation system based on a gamified ecosystem, including: a home decoration multi-role exclusive module, a home decoration role level growth module, a home decoration regional pricing module, a supply and demand matching module, a home decoration construction full-process control module, a copywriting generation module, and a completion data organization module; The home decoration multi-role exclusive module is used to provide users with account registration function, select registration identity, and provide role permissions according to the registration identity selected by the user during registration; The Home Decoration Character Ranking Module is used to develop a gamified growth incentive mechanism and automatically promote or demote the service provider's rank based on the gamified growth incentive mechanism. The home decoration regional pricing module is used to determine the annual fee for merchants to join based on their region and scale. The supply and demand matching module is used to match service providers in multiple dimensions based on the homeowner's renovation needs, and to assign orders to the successfully matched service providers. The home decoration construction process management module is used for automatic scheduling, node control, and online acceptance of home decoration construction procedures; The copywriting generation module is used to obtain construction site photos uploaded by the home decoration construction process control module at each node, extract decoration elements from the construction site photos, and match the process copywriting templates and styles to generate promotional copywriting. The as-built documentation organization module is used after the completion of the project. It supports uploading and automatically collecting all project data, which is then classified, compiled, and cataloged to generate as-built documentation. It also supports one-click download and delivery.

[0006] Optionally, it also includes: a visitor conversion display module; The visitor conversion display module is used to obtain completed construction project cases, node acceptance photos, and homeowner reviews from the home decoration construction process control module, and use them as case display content on the public page; it obtains basic information, level information, and service scope of service providers from the home decoration multi-role exclusive module, and uses them as display data for the artisan ranking and merchant rating; and it obtains promotional copy from the copy generation module and synchronizes it to the public page as case introduction content.

[0007] Optionally, it also includes: a home decoration data statistics module; The home decoration data statistics module is used for: Construction data is obtained from the home decoration construction process management module to generate construction reports and work order reports; the construction data includes construction progress, construction period milestones, acceptance results, number of work orders, and construction cycle; User management data is obtained from the home decoration multi-role exclusive module to generate management reports and renewal reports; the user management data includes user registration, activity and renewal data; The service provider's performance is obtained from the home decoration role ranking module, and a service provider performance report is generated; the service provider's performance includes service provider ranking, fulfillment rate and positive review rate data; The copywriting data is obtained from the copywriting generation module, and a usage report is generated; the copywriting data includes the number of times promotional copywriting is generated and the amount of copywriting used. The as-built data generation data is obtained from the as-built data organization module, and a data generation report is generated; the as-built data generation data includes the number of as-built data generation times and download volume data; The acquired construction data, user operation data, service provider performance, document data, and as-built data are statistically analyzed, and the statistical results are visualized in charts, exported, and anomaly alerts are provided.

[0008] Optionally, the registered identities include tourists, homeowners, construction workers, designers, project managers, salespersons, home improvement merchants, building material merchants, and platform operators; When providing role-based permissions based on the user's selected registration identity: a role-based access control permission model is adopted to control role permissions in three levels: role ID, permission code, and data scope; Permission codes include basic permission codes and extended permission codes; The data scope includes both tenant-level and role-level data.

[0009] Optionally, the gamified growth incentive mechanism includes: Gain experience points from the service provider; Obtain data on homeowner reviews, platform complaints, and violation records of service providers, and compile statistics on service provider approval rates, complaint rates, and number of violations; A weighted scoring model is used to determine the service provider's reputation score based on the service provider's positive review rate, complaint rate, and number of violations. Obtain the service provider's project schedule compliance rate, milestone acceptance pass rate, and change order fulfillment rate, and obtain the service provider's performance value by weighted summation; The total score of the service provider is determined by a three-dimensional weighted algorithm based on the service provider's experience score, reputation score, and performance score. The service provider's total score is compared with the preset upgrade threshold to determine whether the upgrade conditions are met. The service provider's total score is compared with the preset downgrade threshold to determine whether the downgrade conditions have been met.

[0010] Optionally, the home improvement regional pricing module is used to determine the annual merchant fee based on the merchant's location and size: Obtain merchant location information and merchant role ID from the home decoration multi-role exclusive module; Based on the merchant's location information, determine the region coefficient for merchant matching; Match the preset merchant type coefficient based on the merchant's role ID; Determine the matching scale coefficient for merchants based on their scale level; The base price is multiplied by the regional coefficient, merchant type coefficient, and scale coefficient, and the product is used to determine the annual fee for merchant entry.

[0011] Optionally, in terms of matching service providers across multiple dimensions based on the homeowner's renovation needs using a collaborative filtering algorithm, the supply and demand matching module is used for: Obtain visitor data for property owners; The system retrieves subsequent process requirements, replenishment requirements, and change requests for projects already under construction from the home decoration construction process management module, which can then be used as potential order dispatch requirements. Predict potential home improvement needs based on homeowners' historical construction data; Extract the feature data of visitor data, potential order placement needs, and potential home decoration needs respectively, and use them as the demand tags for homeowners; Get the service provider's rank, fulfillment rate, and positive review rate in the home decoration role ranking module, as well as the service provider's expertise, service scope, and online status in the home decoration multi-role exclusive module; The service provider's skill level, fulfillment rate, and positive review rate, as well as its expertise in craftsmanship, service scope, and online status, are integrated into a service provider capability tag. Based on the owner's needs tags, the matching dimensions of the service provider's capability tags are weighted and scored to obtain the service provider matching degree ranking results; Based on the service provider matching score ranking results, dispatch orders according to the dispatch strategy.

[0012] Optionally, when the home decoration construction process control module automatically schedules the home decoration construction procedures, it adopts the critical path method to clarify the construction period nodes, prerequisites, and critical paths of each home decoration construction procedure. Node management includes: uploading on-site photos for each home decoration construction process node, and unlocking the next home decoration construction process after online acceptance; Online acceptance includes support for electronic signatures, timestamps, tamper-proof features, and verification and evidence storage.

[0013] Optionally, in extracting decoration elements from construction site photos and matching process description templates and styles to generate promotional copy, the copy generation module is used for: Identify the construction stage, space, process details, and photo type in construction site photos, and extract decoration elements from the photos to obtain image recognition results; Based on the image recognition results, the process document template is automatically matched; From the merchant information configuration of the home decoration multi-role exclusive module, extract the merchant's own copywriting preset style based on the merchant ID; Based on the preset style of the copywriting, the tone and wording of the copywriting in the process copywriting template are automatically adjusted to generate promotional copywriting.

[0014] Optionally, it also includes: an underlying support layer and an application presentation layer; The business layer consists of modules for multiple roles in home decoration, a module for role progression in home decoration, a module for regional pricing in home decoration, a module for supply and demand matching, a module for full-process control of home decoration construction, a module for document generation, and a module for organizing as-built documents. Both the underlying support layer and the application presentation layer are used to support the implementation of business layer functions.

[0015] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a gamified ecosystem-based intelligent operation system for the entire home decoration process. The system includes a multi-role module that provides different permissions for each role, creating exclusive functions and improving role collaboration efficiency; a role ranking module that establishes a gamified growth incentive mechanism, automatically promoting or demoting service providers based on this mechanism, addressing issues of weak employee loyalty and high turnover among workers, designers, and sales staff; a regional pricing module that determines annual fees for merchants based on their location and scale, resolving the problem of inconsistent platform pricing models; a full-process construction management module that automatically schedules construction procedures, manages key milestones, and conducts online acceptance, eliminating reliance on manual labor; a copywriting generation module that efficiently transforms real-world construction site scenes into marketing materials, automatically generating promotional copy, resulting in low customer acquisition costs and high efficiency; and a completion data organization module that, upon completion, supports uploading and automatically compiling all project data, generating completion data through classification, compilation, and cataloging, while also supporting one-click download and delivery, overcoming the shortcomings of chaotic classification, cumbersome compilation, non-standard formats, and long delivery cycles. Therefore, this application targets the home decoration industry and realizes full-chain digital operation, including multi-role collaboration, growth incentives, construction control, intelligent pricing, AI intelligent marketing, and AI-automated processing of as-built data. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the structure of a home decoration full-process intelligent operation system based on a gamified ecosystem, provided as an embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] In one exemplary embodiment, such as Figure 1 As shown, a gamified ecosystem-based intelligent operation system for the entire home decoration process is provided, including: a multi-role exclusive module for home decoration, a home decoration role ranking module, a home decoration regional pricing module, a supply and demand matching module, a home decoration construction process control module, a document generation module, and a completion data organization module. The home decoration multi-role exclusive module is used to provide users with account registration function, select registration identity, and provide role permissions according to the registration identity selected by the user during registration; The Home Decoration Character Ranking Module is used to develop a gamified growth incentive mechanism and automatically promote or demote the service provider's rank based on the gamified growth incentive mechanism. The home decoration regional pricing module is used to determine the annual fee for merchants to join based on their region and scale. The supply and demand matching module is used to match service providers in multiple dimensions based on the homeowner's renovation needs, and to assign orders to the successfully matched service providers. The home decoration construction process management module is used for automatic scheduling, node control, and online acceptance of home decoration construction procedures; The copywriting generation module is used to obtain construction site photos uploaded by the home decoration construction process control module at each node, extract decoration elements from the construction site photos, and match the process copywriting templates and styles to generate promotional copywriting. The as-built documentation organization module is used after the completion of the project. It supports uploading and automatically collecting all project data, which is then classified, compiled, and cataloged to generate as-built documentation. It also supports one-click download and delivery.

[0021] All of the above modules constitute a full-chain digital operation system for the home decoration industry, encompassing multi-role collaboration, growth incentives, construction management, intelligent pricing, AI-powered intelligent marketing, and AI-automated processing of as-built data.

[0022] The following is a detailed introduction to each module in the system.

[0023] (1) Home decoration multi-role exclusive module The system provides an account registration function for users. When registering, users can choose their registration identity, which includes visitor, homeowner, construction worker, designer, project manager, salesperson, home improvement merchant, building material merchant, and platform operator. Based on the identity selected by the user during registration, the system provides a role ID, permission code, and data range, and also obtains the user's location information. Then, a role-based access control (RBAC) permission model is adopted to implement three-level control: role ID + permission code + data scope. The basic permission set is bound by the role ID, the permission code refines the function point permissions (such as view, add, modify, delete), and the data scope controls the data access boundary (such as only viewing one's own project / the project of this tenant).

[0024] Horizontal data isolation is achieved by using tenant_id, role_id, and project_id. Data from different roles and tenants is physically isolated and cannot be accessed without authorization.

[0025] Provide basic access control for all business modules: Role ID, permission code, and data scope are provided through a unified authentication interface. This enables identity verification and data isolation for modules such as the home decoration construction process management module, supply and demand matching module, home decoration data statistics module, document generation module, and completion data organization module, ensuring that data of different roles cannot be accessed without authorization.

[0026] Among them, role ID: When a user registers / joins, a fixed role ID is automatically assigned based on the user's identity (visitor / owner / worker / designer / project manager / salesperson / home improvement merchant / building material merchant / platform operator). The role ID is permanently bound to the user and will not change with changes in permissions.

[0027] Permission codes include basic permission codes and extended permission codes: Basic permission codes: The platform's preset set of function point permissions (such as project:view, project:create, process:audit, etc.), which are bound one-to-one with role IDs (such as "home decoration merchant" having project creation and process review permission codes by default).

[0028] Extended permission codes: Merchant administrators can assign permissions to sub-accounts in the backend, supporting granular operations down to the button level (e.g., "Sales staff can only view projects, not edit them").

[0029] The data scope includes both tenant-level and role-level data. Tenant level: Data from different merchants is automatically isolated by tenant_id, and merchants can only access all data under their own tenant.

[0030] Role-based: Automatically generated based on preset rules (e.g., the default data range for "Construction Technician" is "only projects they participated in", and for "Project Manager" it is "all projects under this merchant"), and supports custom configuration in the backend.

[0031] (2) Home Decoration Role Ranking Module First, establish independent ranking systems for craftsmen, designers, and merchants, including order taking, construction check-in, uploading of acceptance documents, completion of homeowner evaluations, participation in platform activities, homeowner evaluations, platform complaints, violation records, project schedule compliance rate, milestone acceptance pass rate, and change order fulfillment rate. Then, based on the acquired data, experience value, reputation value, and performance value are calculated respectively; Experience Points (EXP): These are earned by completing specified actions on the platform, including but not limited to the number of successful orders, the number of times construction process nodes are checked in, the number of times process acceptance documents are uploaded, the number of homeowner reviews completed (the number of times homeowners complete reviews and the star rating / content score of the reviews), and the number of times they participate in official platform activities. Different actions correspond to different experience points (the experience points corresponding to different actions are preset fixed values), and the accumulated experience points determine the level. Reputation Score (SR): Calculated based on a combination of data from homeowner reviews, platform complaints, and violation records. Positive behavior increases the reputation score, while negative behavior decreases it. Reputation Score (SR) is calculated using a weighted scoring model, as shown in the following formula: SR = Initial value + (Positive review rate × Positive review weight) - (Complaint rate × Complaint weight) - (Number of violations × Violation weight); where the initial value is 100 points, which is the default initial reputation value for all characters; Results range: 0-200 points, automatically mapped to reputation level (e.g., ≥180 points = S level, 150~179 points = A level, and so on). The complete SR reputation level classification criteria are shown in Table 1.

[0032] Table 1. Credit Rating (SR) Complete Classification Standards

[0033] Supplementary rules: 1. All newly registered characters start with 100 points (starting from Rank B); 2. A single serious violation can result in a deduction of 50 points and a downgrade in the penalty level; 3. An additional 10 points will be awarded if there are no complaints or violations for three consecutive months.

[0034] Performance Ratio (PR): refers to the ability of practitioners to fulfill the contractual obligations of completing construction milestones, schedules, and acceptances. It is calculated based on data such as the schedule compliance rate, milestone acceptance pass rate, and change fulfillment rate, and is one of the core evaluation indicators for professional development.

[0035] The project completion rate is calculated as follows: (Number of projects completed on time / Total number of completed projects) × 100%. Node acceptance pass rate = (Number of nodes that pass process acceptance on the first attempt / Total number of nodes accepted) × 100%; Change order fulfillment rate = (Number of projects completed on time according to the change order plan / Total number of change orders) × 100%; Performance Value (PR) = Schedule Compliance Rate × 0.4 + Milestone Acceptance Rate × 0.4 + Change Order Compliance Rate × 0.2; Rating mapping: The result is 0-100 points, corresponding to the performance level (e.g., ≥90 points = Excellent, 80-89 = Good, and so on). The complete performance value (PR) rating criteria are shown in Table 2.

[0036] Table 2 Performance Value (PR) Completeness Rating Standards

[0037] Finally, the total score of experience value, reputation value and performance value is calculated according to the points algorithm. The total score is then compared with the preset upgrade threshold to determine whether the upgrade conditions are met. This enables automatic promotion and demotion of mentors, designers and merchants, and automatically matches corresponding benefits, forming a gamified growth incentive mechanism to enhance practitioners' sense of belonging and platform stickiness.

[0038] Specifically, the total score for the experience value, reputation value, and performance value is calculated using a three-dimensional weighted algorithm: experience value (EXP) + reputation value (SR) + performance value (PR).

[0039] Meanwhile, it provides reputation and capability tags for the supply and demand matching module and the home decoration data statistics module: data such as performance value, reputation value, and completion rate, which directly affect the order assignment weight of the supply and demand matching module and are synchronized to the data statistics module to generate practitioner growth reports.

[0040] The gamified growth incentive mechanism can be summarized as follows: 1) Acquiring service providers' experience points; 2) Obtaining data on service providers' owner reviews, platform complaints, and violation records, and calculating their positive review rate, complaint rate, and number of violations; 3) Determining service providers' reputation score using a weighted scoring model based on their positive review rate, complaint rate, and number of violations; 4) Obtaining service providers' project completion rate, node acceptance pass rate, and change order fulfillment rate, and obtaining their performance score through weighted summation; 5) Determining service providers' total score using a three-dimensional weighted algorithm based on their experience points, reputation score, and performance score; 6) Comparing service providers' total score with a preset upgrade threshold to determine if they meet the upgrade conditions; 7) Comparing service providers' total score with a preset downgrade threshold to determine if they meet the downgrade conditions.

[0041] (3) Smart pricing module for home decoration areas The home decoration regional pricing module can be called the home decoration regional intelligent pricing module.

[0042] There are preset area levels (including S-level / A-level / B-level / C-level, with corresponding area coefficients of 1.2 / 1.0 / 0.9 / 0.8), merchant type coefficients, and merchant scale coefficients for different areas. Then, the merchant location information and merchant role ID are obtained from the home decoration multi-role exclusive module. Based on the merchant role ID, the preset merchant type coefficient is automatically matched, and based on the obtained merchant location information, the area coefficient to which it belongs is automatically matched. The merchant scale coefficient is obtained from the home decoration data statistics module. Specifically, the scale level (small / medium / large) is automatically calculated based on the number of projects and output value data of the merchant in the past 12 months, and the corresponding preset scale coefficient is obtained based on the calculated scale level.

[0043] Then, pricing is determined based on the merchant's regional level, merchant type coefficient, and scale coefficient.

[0044] Pricing formula: Final annual fee = base price × regional coefficient × scale coefficient × type coefficient.

[0045] The automatic calculation rules for scale levels are as follows: 1. Threshold preset (regional fine-tuning, universal standard) 1) Small businesses If the total number of projects is less than 20 and the annual total output value is less than 500,000 yuan, the corresponding scale coefficient is 0.85.

[0046] 2) Medium-sized businesses The total number of projects is 20 to 80, or the annual total output value is 500,000 to 2 million yuan (meeting either one is sufficient for the determination), corresponding to a scale coefficient of 1.0.

[0047] 3) Large merchants For projects with a total number of more than 80 projects or an annual total output value of more than 2 million yuan, the corresponding scale coefficient is 1.15.

[0048] 2. Calculation process The system retrieves data on all completed and ongoing projects from merchants over the past 12 months, and calculates the total number of projects and the cumulative total output value. Match two-dimensional thresholds to determine small / medium / large size, and bind a preset size coefficient.

[0049] (4) Supply and demand matching module The supply and demand matching module can be called the intelligent supply and demand matching module.

[0050] Based on the homeowner's renovation needs, budget, region, and style, and combined with the skill level, expertise, reputation, and service scope of the craftsmen / designers / vendors, a collaborative filtering algorithm is used for multi-dimensional matching to achieve accurate order dispatch and efficient order acceptance, thereby improving the efficiency of supply and demand matching.

[0051] Obtaining homeowner needs includes: Visitor data is obtained from the visitor conversion display module through the following methods: Public page browsing data: visitor browsing time, click behavior, and page stay on the merchant's public case pages and service introduction pages; Consultation records: questions and descriptions of needs submitted by visitors through the online consultation tool on the public page; Lead information: information such as the visitor's name, contact information, location, and intended renovation type; and then, NLP (Natural Language Processing) technology is used to extract tags such as apartment type, style, area, budget, process, and region to form a homeowner needs profile.

[0052] The system retrieves the subsequent process requirements, replenishment requirements, and change requirements of projects already under construction from the home decoration construction full-process management module. After being tagged by the system, these are used as potential order dispatch requirements for B-end practitioners. Among them, the requirements for subsequent processes are: after the current process is completed, the construction time, material requirements, and process requirements for the next process. Replenishment needs: Material replenishment and replacement needs arising during construction; Change requests: Change requests from the owner regarding construction plans, processes, and materials; The platform's historical construction data, including regional, apartment type, and style dimensions, is obtained from the home decoration data statistics module. Based on this data, potential home decoration demand is predicted, serving as a supplementary data source for supply and demand matching.

[0053] The detailed process for predicting potential home decoration demand based on historical construction data for a specific region, apartment type, and style is as follows: Step 1: Data Pool Extraction Three types of historical data were extracted from the home decoration data statistics module: Regional Dimension: Mainstream budget ranges, popular construction procedures, preferred apartment layouts, and frequency of renovation needs in each region; Apartment type dimension: average construction period, material consumption, and frequent additional item changes for two-bedroom / three-bedroom / large single-level / duplex apartments; Style dimension: Construction difficulties of styles such as modern minimalism, new Chinese style, and cream style, client budget distribution, and renovation needs.

[0054] Step 2: Label Clustering Modeling The data is grouped according to the three-dimensional combination of "region + apartment type + decoration style", and the historical order growth trend and quarterly demand peak are calculated for each group; By overlaying local real estate transaction data and publicly available second-hand property transfer data with weighted adjustments, areas with rising or falling demand can be identified.

[0055] Step 3: Generation of Potential Demands Short-term immediate demand: Based on the number of houses delivered in the area in the past 3 months, predict the order volume for complete / partial renovation of corresponding house types and styles; Process-related needs: Based on the historical construction sequence of the same type of house, predict the periodic labor and replenishment needs of processes such as water and electricity, masonry, and ceiling; Potential changes in requirements: Extract frequently added items (demolition and alteration, cabinet upgrades, moisture-proofing renovations) for similar apartment types and generate pre-tagged requirements; Step 4: Output to the supply and demand matching module Output structured demand tags (area + apartment type + budget range + required procedures) as a supplementary data source for work order reserves and matching practitioners' capabilities.

[0056] The multi-dimensional matching process of supply and demand is as follows: Step 1: Obtain the owner's needs (data source layer) Data source 1: Browsing / inquiry / leadership data from the visitor conversion module; Data source 2: Construction management module's requirements for subsequent construction processes / replenishment / changes; Data source 3: Historical construction data prediction from the data statistics module; Step 2: Requirement Tagging (Processing Layer) Input: All the required data obtained in the first step; Processing: Extract core tags (apartment type, style, budget, process, region, construction period, urgency) using NLP; Output: A standardized set of owner requirement tags.

[0057] Step 3: Service Provider Profile Construction (Processing Layer) Inputs: Rank, contract fulfillment rate, and positive review rate in the Home Improvement Role Ranking Module; Expertise, service scope, and online status in the Construction Management Module; Processing: Integrate into service provider capability tags (proficient in processes, service area, available budget, and project timeline). Output: A standardized set of service provider profiles.

[0058] Among them, 1. Acceptable budget consolidation rules Input data sources: rank, fulfillment rate, positive review rate, expertise in specific processes, and historical project output value; Extract the budget range of all historical completed projects of this practitioner and divide them into low-end / mid-end / high-end budget segments; Weighted scoring: High fulfillment rate + high positive feedback rate + high level → expand the upper limit of the budget that can be undertaken; multiple breaches of low-price orders will reduce the label of undertaking high-end budgets; Output labels are categorized into three ranges: "Budget for small apartments with basic needs", "Budget for mid-range complete renovation", and "Budget for high-end customized renovation".

[0059] 2. Rules for Integrating Project Schedule and Capacity Input data sources: Construction period compliance rate, historical average completion time for unit types, and change order fulfillment rate; Calculate the historical average completion time for the same apartment type, and adjust accordingly based on the completion rate: a completion rate ≥ 95% is marked as "fast delivery"; a completion rate < 70% is marked as "slow delivery". Combining expertise in various processes: those skilled in multi-process integrated construction can shorten the estimated construction period; those specializing in single-process construction have a narrower timeframe requirement. Output tags: Standardized construction period capability tags such as 7-day partial modification / 30-day complete installation / 60-day large-scale flat.

[0060] Step 4: Collaborative filtering + weighted scoring matching (matching layer) Input: Owner needs tags from step two, and service provider profiles from step three; Processing: Based on the homeowner's needs tags, the matching dimensions of the service provider profile are weighted and scored; Calculation process: Based on the homeowner's needs tags, each dimension of the service provider profile is compared; scores are calculated according to the corresponding weighted items, and the total matching score is obtained by summing them; all service providers are sorted from high to low according to the total score, and the matching results are output, with high scores being recommended first.

[0061] Output: Service provider matching score ranking results.

[0062] The correspondence between matching dimensions and weight scores is shown in Table 3, with a total weight score of 100 points.

[0063] Table 3. Correspondence between matching dimensions and weight scores

[0064] Step 5: Order Dispatch Execution (Application Layer) Input: The matching result from step four; Processing: Dispatch orders according to the dispatch strategy, and record logs throughout the process; Output: Order dispatch success / failure result.

[0065] The order dispatch strategy is explained as follows: The platform has four built-in switchable order dispatch strategies, which can be switched automatically or manually: High score priority strategy (default general): The top 3 practitioners are ranked according to their total score in the previous chapter, and their needs are pushed out simultaneously. Homeowners can choose independently, which is suitable for home improvement retail and partial renovation orders.

[0066] Regional proximity strategy: Prioritize matching with online professionals within 3 kilometers of the homeowner's community, and then add credit performance score to reduce commuting costs. Suitable for casual work and single-item construction of ceilings / waterproofing.

[0067] Balanced order dispatch strategy: Control the total number of orders received by practitioners at the same level each month to avoid monopolization by the top players; under the premise that the matching score meets the standard, prioritize recommending practitioners with fewer orders received in the current month to ensure the fairness of the ecosystem.

[0068] Merchant binding and return strategy (adapted to the open ecosystem of this project): When a request is attributed to a partner store, priority is given to pushing it to the registered designers / craftsmen under that store; if no one within the store accepts the request, it is then pushed to the entire external platform to resolve merchant resistance.

[0069] Supporting mechanisms: The entire order dispatch process is logged, recording the push time, order status, and final transaction entity, and updating the practitioner's performance and credit data in real time.

[0070] (5) Home decoration construction process control module It is used for automatic scheduling, node control and online acceptance of home decoration construction procedures, and provides core business data for supply and demand matching module, home decoration data statistics module, copywriting generation module and completion data organization module; The automatic scheduling of home renovation construction procedures includes: The automatic scheduling of project milestones is achieved based on the Critical Path Method (CPM). The specific process is as follows: Load the standard process library: It has built-in standard process dependencies for "start-up briefing → water and electricity → waterproofing → masonry → carpentry → ceiling → painting → main material installation → completion → cleaning", and clarifies the preceding processes and standard construction period for each process; Input the total project duration: After the user inputs the agreed total project duration, the start and end times of each process are calculated backwards from the total duration as the endpoint, according to the process dependencies. Generate Gantt charts and node plans: Generate visual Gantt charts based on the reverse engineering results, and clarify the schedule nodes, prerequisites, and critical paths of each process; Automatic conflict alerts: When there are conflicts in process dependencies (such as the inability to start subsequent processes due to incomplete preceding processes) or when the project schedule exceeds the total project duration, the system will automatically issue an alert and suggest adjustments. The node control includes: each process node must upload on-site photos and complete online acceptance (the uploaded on-site photos are associated with the corresponding project ID and process ID). Only after the acceptance is passed can the next process be unlocked, ensuring that the project schedule nodes are progressing as planned.

[0071] Online acceptance includes support for electronic signatures, timestamps, tamper-proof features, and verification and evidence storage.

[0072] This includes providing core business data for the supply and demand matching module, home decoration data statistics module, copywriting generation module, and as-built data organization module. Process progress, node photos, and acceptance results are synchronized to the supply and demand intelligent matching module as the basic data for order dispatching and credit assessment. Construction data and user behavior data are synchronized to the home decoration data statistics module to generate business reports; user behavior data includes: B-end practitioner behavior data, B-end merchant behavior data, C-end homeowner behavior data, and system interaction behavior; B2B practitioner behavior data includes: ①Construction site material upload behavior: number of photos / videos uploaded daily, shooting process, and upload time; ② AI tool behavior: Number of AI-generated product recommendation notes, publishing platforms (Douyin / Xiaohongshu), content exposure, and number of inquiries; ③ Work order operation behavior: node acceptance submission time, change order processing time, online confirmation and signature completion rate; ④ Member behavior: Membership renewal records, frequency of use of privilege functions, and participation records in platform training; B-end merchant behavior data includes: store backend login frequency, supply chain order frequency, employee account management operations, annual report fees, and event registration records.

[0073] C-end homeowner behavior data includes: frequency of site visits, online evaluation submissions, complaint initiation, plan change applications, electronic signature acceptance records, and click-through / inquiry behavior for recommended content.

[0074] System interaction behaviors include: message push open rate, alert notification processing time, account online time, and mini-program page dwell time.

[0075] Node photos are synchronized to the copywriting generation module to be used as materials for generating marketing content; process acceptance data are synchronized to the completion data module to be automatically collected and generated as-built archives.

[0076] (6) Visitor conversion display module The system also includes a visitor conversion display module, which has the following functions: Completed construction project cases, node acceptance photos, and homeowner evaluations are obtained from the home decoration construction process management module and used as case display content on the public page. Basic information, skill level, and service scope of merchants and craftsmen are obtained from the multi-role exclusive module of home decoration, and used as display data for the craftsman ranking and merchant rating; Marketing copy generated from construction photos can be retrieved from the copy generation module and synchronized to the public page as case study content.

[0077] (7) Home decoration data statistics module Data such as construction progress, project milestones, acceptance results, number of work orders, and construction cycle are obtained from the home decoration construction process management module and used to generate construction and work order reports. User registration, activity, and renewal data are obtained from the home decoration multi-role exclusive module to generate operation and renewal reports; Data on practitioners' ranks, contract fulfillment rates, and positive review rates are obtained from the home decoration role ranking module and used to generate practitioner performance reports. Data on the number of times AI copy was generated and its usage were obtained from the copy generation module to generate AI usage reports; The number of times as-built documents were generated and the number of downloads are obtained from the as-built document organization module, and are used to generate document generation reports.

[0078] The acquired data will be statistically analyzed, and the data can be visualized in charts, exported, and alerted for anomalies, providing data support for merchant operations and platform management.

[0079] The abnormal warning standards and processes are as follows: Early warning standards: Based on historical data and business rules, preset thresholds include: project delay warning (work process nodes exceed the planned project duration), work order abnormality warning (number of work orders is lower / higher than the same period in history), renewal warning (users have not renewed their subscriptions 7 days before the expiration date), construction abnormality warning (node ​​acceptance pass rate is lower than the preset value), and complaint warning (complaint rate is higher than the preset value). Early warning process: The system periodically scans the data statistics results. When the data exceeds the preset threshold, an early warning is automatically triggered. The system notifies the corresponding user role through in-system messages, SMS, push notifications, etc., and generates an anomaly report, supporting the tracing of the source of abnormal data.

[0080] (8) Copywriting generation module The copywriting generation module can be called the AI ​​Xiaohongshu Intelligent Copywriting Generation Module.

[0081] 1. Image recognition: Based on the project ID / process ID, corresponding construction site photos are obtained from the home decoration construction full-process management module. The obtained construction site photos are classified and identified, including construction stage (plumbing / masonry / carpentry, etc.), space (living room / bedroom / kitchen, etc.), craftsmanship details (tile laying / carpentry finishing, etc.), and photo type (panoramic / close-up / comparison of completed projects). Key elements in the photos (such as materials, colors, and craftsmanship details) are extracted as the basis for scene matching for copywriting generation.

[0082] The implementation scheme for construction site photo classification and recognition is as follows: 1. Model training base A lightweight CNN image classification model was trained based on a dataset of images specific to home renovation construction sites to distinguish and identify targets in 5 major categories: 1) Construction stage classification: plumbing / masonry / carpentry / painting / completion; 2) Spatial area classification: living room, bedroom, kitchen, bathroom, balcony, hallway; 3) Classification by process type: tile laying, ceiling finishing, waterproofing, pipe pre-embedding, etc.; 4) Photo material types: panoramic view, close-up details, before and after comparison photos, and actual photos of materials; 5) Scene attributes: Old house renovation / New house renovation / Partial renovation.

[0083] 2. Identify the execution process Retrieve site photos bound to the project ID and input them into the model; The model outputs multi-label classification results, along with confidence scores; The classification label is automatically determined when the confidence level is ≥85%; if it is below the threshold, it is pushed to manual review and correction, and the model is iterated in reverse.

[0084] 3. Output Results Structured tags: construction stage + space + process + material type, serving as the basis for subsequent key element extraction and copywriting template matching.

[0085] The solution for extracting key elements from a photo is as follows: 1. Layered extraction logic Entity detection (YOLO object detection model): Identifies entities within the image: materials such as tiles, plasterboard, waterproof membrane, solid wood trim, hardware, and kitchen and bathroom appliances; visual features such as wall color and board texture; Process feature extraction: Capture process details such as seam finishing, corner treatment, tile grouting, and pipe layout through edge detection and segmentation algorithms; Text OCR-assisted extraction: Recognize material labels, process markings, and water and electricity pipeline markings in photos to supplement product model and process standard information.

[0086] 2. Structured output The extracted results are assembled into key-value pairs: {material name, main color, core process, spatial location, construction stage}, and directly passed to the scene matching module to accurately retrieve the corresponding home decoration recommendation copy template.

[0087] 2. Scene matching: Based on the results of image recognition, the system automatically matches corresponding process text templates: water and electricity, waterproofing, masonry, carpentry, painting, completion, and finished comparison.

[0088] 3. Injection of merchant style Read the merchant's preset style: professional / friendly / high-end / down-to-earth, and automatically adjust the tone and word choice.

[0089] Merchants' preset style data is stored in the merchant information configuration of the home decoration multi-role exclusive module: When merchants join the system, they can configure their own preset copywriting style (professional / friendly / advanced / down-to-earth, etc.) in the backend. This data is bound to the merchant ID. The AI ​​copywriting generation module obtains the corresponding preset style through the merchant ID and automatically adjusts the tone and wording of the copywriting to achieve style matching.

[0090] 4. Content Generation Automatically outputs: title, body text, emojis, hashtags, and lead generation scripts.

[0091] 5. Output and Linkage One-click copy, one-click H5 generation, one-click synchronization to project album, and integration with as-built data.

[0092] 6. Billing and Quotas The billing and quota of this module are controlled based on the user's annual fee tier: Pay-per-use: Regular users have a fixed number of AI copywriting generation opportunities per month. Once the limit is exceeded, the service will be automatically blocked, or users can pay per use. Annual fee tier quota: Different annual fee tiers correspond to different AI copywriting generation quotas. The advanced tier supports unlimited generation. The quota data is bound to the user account and is controlled by the annual fee permissions of the home decoration multi-role exclusive module.

[0093] (9) As-built data organization module The as-built data organization module can be called the AI-powered intelligent as-built data organization and download module.

[0094] 1. Automatic data collection Supports uploading: contracts, quotations, drawings, changes, hidden photos, acceptance forms, material certificates of conformity, and test reports.

[0095] 2. AI intelligent processing OCR text recognition technology: recognizes key information such as forms, signatures, dates, acceptance conclusions, and project names in documents such as contracts, quotations, and acceptance forms, and extracts structured data; Image classification and archiving technology: Automatically identifies uploaded hidden photos, acceptance photos, and other data types, and automatically categorizes them according to work processes and data catalogs; Document structuring technology: Automatically generates a table of contents, page numbers, headers and footers according to home decoration archiving standards, completes chapter sorting, and realizes standardized compilation and cataloging of as-built documents.

[0096] 3. Automatic volume assembly and cataloging Automatically generated according to home decoration archiving standards: Cover → Title Page → Table of Contents → Page Numbers → Header and Footer → Chapter Sorting → Materials → Hidden Materials → Acceptance → Images → Completion Report.

[0097] 4. Document Generation The backend service automatically merges PDFs, adds watermarks and logos, compresses them, and generates ZIP files.

[0098] 5. Delivery capability One-click download, one-click forwarding to owners, one-click archiving, printable, and verifiable.

[0099] 6. Permissions and Quotas The number of generation attempts is determined by the annual fee tier, with the advanced tier supporting unlimited generation.

[0100] As an optional implementation, this system also includes: an underlying support layer and an application presentation layer; The business layer consists of modules for multiple roles in home decoration, a role progression module for home decoration, a regional pricing module for home decoration, a supply and demand matching module, a full-process management module for home decoration construction, a document generation module, and a completion data organization module; the underlying support layer and the application display layer are used to support the implementation of the functions of the business layer.

[0101] This system is based on a three-tier microservice architecture consisting of an underlying support layer, a core business layer, and an application presentation layer. It features front-end and back-end separation, supports distributed deployment, horizontal scaling, and high-concurrency access, and ensures that all modules have unified permissions, unified data, and unified scheduling.

[0102] (1) Bottom support layer 1. Service Architecture: The Spring Cloud / .NET microservice architecture is adopted, and the services are divided into: User Service, Permission Service, Construction Service, Order Service, AI Service, File Service, Message Service, Billing Service, and Statistics Service.

[0103] 2. Deployment method: Based on Docker+Kubernetes containerized orchestration, supporting elastic scaling; supports cross-platform deployment on Windows / Linux, and is compatible with cloud and local private deployment.

[0104] 3. Data Layer Relational database: MySQL 8.0, master-slave separation, database sharding and table partitioning, and transaction consistency guarantee.

[0105] Caching: Redis cluster, used for API rate limiting, tier calculation, and caching of hot data.

[0106] File storage: Object storage OSS / MinIO, storing images, PDFs, videos, and as-built documentation packages, with CDN acceleration supported.

[0107] 4. Security Mechanism The interface uses HTTPS encryption, JWT token authentication, and is protected against replay attacks and fraudulent activity.

[0108] Sensitive data anonymization, full-chain auditing of operation logs, and automatic data backup.

[0109] 5. AI Capability Foundation It provides unified access to image recognition, OCR, NLP, and large model generation capabilities, and offers standardized AI capability interfaces for upper-layer business modules to call.

[0110] (2) Application presentation layer PC management interface: Backend configuration, permissions, annual fee, work processes, templates, and data reports.

[0111] WeChat Mini Programs: Order taking, check-in, acceptance, AI copywriting, image editing, and data download.

[0112] Mobile H5 / APP: Full-featured, offline operation, automatic synchronization upon network recovery.

[0113] The core technical processes of this application system include: Step 1: Character Registration and Qualification Verification Corresponding module: Home decoration multi-role exclusive module; Function Description: After registering an account, users upload their qualifications. After OCR verification and automatic / manual review, the corresponding role permissions are activated and the rank initialization configuration is completed.

[0114] Step 2: Matching Owner Needs and Distributing Orders Corresponding modules: Visitor conversion display module, intelligent supply and demand matching module, and multi-role exclusive module for home decoration. Function Description: After a homeowner posts a request, the system uses NLP to tag the request and matches the homeowner with a suitable craftsman / designer based on a supply and demand matching algorithm. It supports order grabbing, order confirmation, and project creation.

[0115] Step 3: Full-process management of construction Corresponding module: Home decoration construction process management module; Function Description: After the project starts, the system reverse-engineers the process nodes based on the total construction period. Construction workers check in at each node, upload on-site photos, and unlock the next process after completing online acceptance. The progress of the owner, the merchant, and the workers is synchronized in real time.

[0116] Step 4: AI-powered Marketing and Data Processing Corresponding modules: Document generation module, As-built data organization module; Function Description: After construction node photos are uploaded, the system automatically generates marketing copy for Xiaohongshu (Little Red Book); after completion is triggered, AI automatically collects all project data, and generates PDF+ZIP format completion documents after classification, compilation, and cataloging, supporting one-click download and delivery.

[0117] Step 5: Behavioral Data Collection and Rights Settlement Corresponding modules: Home decoration role ranking module, Home decoration data statistics module; Function Description: The system automatically collects behavioral data such as practitioners' contract performance, reputation, performance, and completion rate, calculates their level and automatically updates their rights, completes the settlement of mentor / apprentice / guild rewards, and generates multi-dimensional business reports to provide data support for platform operation.

[0118] The key technical points of this application include: 1. Exclusive permissions and interface data isolation technology for nine key roles in the home decoration industry chain; 2. Customized ranking and incentive algorithms for home improvement professionals; 3. Digital management and online acceptance methods for the entire home decoration construction process; 4. A smart pricing system for annual fees that adapts to both regional and scale-based factors in the home decoration industry; 5. Home decoration scenario mentor-apprentice guild fission and intelligent supply and demand matching technology; 6. A method and process for automatically generating Xiaohongshu captions based on AI recognition of construction images; 7. AI-powered automatic classification, compilation, cataloging, and bookletization of home decoration completion documents, along with one-click download methods.

[0119] The core technical effects of the system proposed in this application are as follows: 1. The data and functions of the nine roles are completely isolated, greatly improving the experience and security.

[0120] 2. The entire construction process is digitalized, visualized, and traceable, reducing disputes and improving delivery efficiency.

[0121] 3. Intelligent annual fee pricing based on both regional and scale dimensions ensures fairness, transparency, no commission, and cost reduction.

[0122] 4. Gamified growth and mentor-apprentice interaction enable the platform to achieve self-growth and self-operation.

[0123] 5. AI-powered Xiaohongshu copywriting enables construction site photos to be transformed into marketing materials with a single click, solving customer acquisition pain points.

[0124] 6. AI-powered fully automated processing of as-built data reduces 3 days of work to 5 minutes, standardizes delivery, and facilitates final payment settlement.

[0125] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0126] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A smart operation system for the entire home decoration process based on a gamified ecosystem, characterized in that, include: The module includes modules for multiple roles in home decoration, a module for role progression in home decoration, a module for regional pricing in home decoration, a module for supply and demand matching, a module for full-process management of home decoration construction, a module for document generation, and a module for organizing as-built documents. The home decoration multi-role exclusive module is used to provide users with account registration function, select registration identity, and provide role permissions according to the registration identity selected by the user during registration; The home decoration role ranking module is used to develop a gamified growth incentive mechanism and automatically promote or demote the service provider's ranking based on the gamified growth incentive mechanism. The home decoration regional pricing module is used to determine the annual fee for merchants to join based on their region and scale. The supply and demand matching module is used to match service providers in multiple dimensions based on the homeowner's renovation needs, and to assign orders to the successfully matched service providers. The home decoration construction process management module is used for automatic scheduling, node control, and online acceptance of home decoration construction procedures; The copywriting generation module is used to obtain construction site photos uploaded by the home decoration construction process control module at each node, extract decoration elements from the construction site photos, and match the process copywriting templates and styles to generate promotional copywriting. The as-built documentation organization module is used after the completion of the project. It supports uploading and automatically collecting all project data, which is then classified, compiled, and cataloged to generate as-built documentation. It also supports one-click download and delivery.

2. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, Also includes: Visitor conversion display module; The visitor conversion display module is used to obtain completed construction project cases, node acceptance photos and homeowner reviews from the home decoration construction full process control module, and use them as case display content on the public page; it also obtains basic information, level information and service scope of service providers from the home decoration multi-role exclusive module, and uses them as display data for the artisan list and merchant rating. The promotional copy is obtained from the copy generation module and synchronized to the public page as case study content.

3. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, Also includes: Home decoration data statistics module; The home decoration data statistics module is used for: Construction data is obtained from the home decoration construction process management module to generate construction reports and work order reports; the construction data includes construction progress, construction period milestones, acceptance results, number of work orders and construction cycle; User management data is obtained from the home decoration multi-role exclusive module to generate management reports and renewal reports; the user management data includes user registration, activity and renewal data; The service provider's performance is obtained from the home decoration role ranking module, and a service provider performance report is generated; the service provider's performance includes service provider ranking, fulfillment rate and positive review rate data; The copywriting data is obtained from the copywriting generation module, and a usage report is generated; the copywriting data includes the number of times promotional copywriting is generated and the amount of copywriting used. The as-built data generation data is obtained from the as-built data organization module, and a data generation report is generated; the as-built data generation data includes the number of as-built data generation times and download volume data; The acquired construction data, user operation data, service provider performance, document data, and as-built data are statistically analyzed, and the statistical results are visualized in charts, exported, and anomaly alerts are provided.

4. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, The registered identities include tourists, homeowners, construction workers, designers, project managers, salespersons, home improvement merchants, building material merchants, and platform operators; When providing role-based permissions based on the user's selected registration identity: a role-based access control permission model is adopted to control role permissions in three levels: role ID, permission code, and data scope; Permission codes include basic permission codes and extended permission codes; The data scope includes both tenant-level and role-level data.

5. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, The gamified growth incentive mechanism includes: Gain experience points from the service provider; Obtain data on homeowner reviews, platform complaints, and violation records of service providers, and compile statistics on service provider approval rates, complaint rates, and number of violations; A weighted scoring model is used to determine the service provider's reputation score based on the service provider's positive review rate, complaint rate, and number of violations. Obtain the service provider's project schedule compliance rate, milestone acceptance pass rate, and change order fulfillment rate, and obtain the service provider's performance value by weighted summation; The total score of the service provider is determined by a three-dimensional weighted algorithm based on the service provider's experience score, reputation score, and performance score. The service provider's total score is compared with the preset upgrade threshold to determine whether the upgrade conditions are met. The service provider's total score is compared with the preset downgrade threshold to determine whether the downgrade conditions have been met.

6. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, Regarding determining the annual merchant onboarding fee based on the merchant's location and size, the home improvement regional pricing module is used for: Obtain merchant location information and merchant role ID from the home decoration multi-role exclusive module; Based on the merchant's location information, determine the region coefficient for merchant matching; Match the preset merchant type coefficient based on the merchant's role ID; Determine the matching scale coefficient for merchants based on their scale level; The base price is multiplied by the regional coefficient, merchant type coefficient, and scale coefficient, and the product is used to determine the annual fee for merchant entry.

7. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, In terms of multi-dimensional matching of service providers based on homeowners' renovation needs using collaborative filtering algorithms, the supply and demand matching module is used for: Obtain visitor data for property owners; The system retrieves subsequent process requirements, replenishment requirements, and change requests for projects already under construction from the home decoration construction process management module, which can then be used as potential order dispatch requirements. Predict potential home improvement needs based on homeowners' historical construction data; Extract the feature data of visitor data, potential order placement needs, and potential home decoration needs respectively, and use them as the demand tags for homeowners; Get the service provider's rank, fulfillment rate, and positive review rate in the home decoration role ranking module, as well as the service provider's expertise, service scope, and online status in the home decoration multi-role exclusive module; The service provider's skill level, fulfillment rate, and positive review rate, as well as its expertise in craftsmanship, service scope, and online status, are integrated into a service provider capability tag. Based on the owner's needs tags, the matching dimensions of the service provider's capability tags are weighted and scored to obtain the service provider matching degree ranking results; Based on the service provider matching score ranking results, dispatch orders according to the dispatch strategy.

8. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, When the home decoration construction process control module automatically schedules the home decoration construction procedures, it adopts the critical path method to clarify the construction period nodes, prerequisites and critical paths of each home decoration construction procedure. Node management includes: uploading on-site photos for each home decoration construction process node, and unlocking the next home decoration construction process after online acceptance; Online acceptance includes support for electronic signatures, timestamps, tamper-proof features, and verification and evidence storage.

9. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, In extracting decoration elements from construction site photos and matching them with process description templates and styles to generate promotional copy, the copy generation module is used for: Identify the construction stage, space, process details, and photo type in construction site photos, and extract decoration elements from the photos to obtain image recognition results; Based on the image recognition results, the process document template is automatically matched; From the merchant information configuration of the home decoration multi-role exclusive module, extract the merchant's own copywriting preset style based on the merchant ID; Based on the preset style of the copywriting, the tone and wording of the copywriting in the process copywriting template are automatically adjusted to generate promotional copywriting.

10. The intelligent operation system for the entire home decoration process based on a gamified ecosystem as described in claim 1, characterized in that, Also includes: The underlying support layer and the application presentation layer; The business layer consists of modules for multiple roles in home decoration, a module for role progression in home decoration, a module for regional pricing in home decoration, a module for supply and demand matching, a module for full-process control of home decoration construction, a module for document generation, and a module for organizing as-built documents. Both the underlying support layer and the application presentation layer are used to support the implementation of business layer functions.

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