A regional dynamic distribution method and system for a flower delivery franchise network

Abstract

The application relates to the field of franchise network management, and in particular to a regional dynamic distribution method and system for a flower delivery franchise network. The method comprises the following steps: obtaining a flower art order demand data set, based on which, a complex flower art order is task-decomposed to generate a flower art skill task chain information set; based on this, dynamic matching of an execution node and a skill label is performed, and based on this, targeted reconstruction and environment adaptation of a franchise store function are triggered to generate a dynamic node attribute mapping scheme set for driving node specialization and process standardization; based on this, semi-finished product life state tracking and final integrity encapsulation are performed to generate and output a flower art order full-link collaborative report. In the dynamic distribution process of the flower delivery franchise network, the application realizes standardized decomposition and specialized collaboration of complex orders, and guarantees the whole-process quality of flower art works as life art products.

Description

Technical Field

[0001] This application relates to the field of franchise network management, and in particular to a method and system for the regional dynamic deployment of a Huadi franchise network. Background Technology

[0002] In the field of high-end personalized floral art customization and delivery, floral works that carry specific emotional expressions and artistic value have their visual expressiveness, emotional communication effectiveness, and commercial value realization determined by the preservation of their entire life cycle from flower material processing and production to final delivery to the user. This is a core link in the supply of high-quality services in the context of experience economy and consumption upgrading.

[0003] However, when existing floral supply chain management methods are applied to flower delivery service franchise networks, they lack a mechanism for systematically and proactively modeling and dynamically safeguarding the life cycle of the artworks when faced with multiple constraints. This not only makes it difficult to achieve closed-loop quality control throughout the entire chain from production to delivery, but also often results in irreversible damage to the expressiveness of the artworks before delivery due to the lag in passive and reactive monitoring and intervention, which seriously affects user experience and brand reputation. Summary of the Invention

[0004] This application provides a method and system for dynamic regional deployment of a flower delivery franchise network to solve the above-mentioned technical problems.

[0005] Firstly, this application provides a method for the regional dynamic deployment of a flower delivery franchise network, the method comprising:

[0006] Obtain a floral order requirement dataset; based on the floral order requirement dataset, extract the physiological state requirements of floral materials, the sequence of craft techniques, the emotional expression scenarios, and the spatiotemporal delivery constraints, and according to the progressive construction logic defined by the spatial structure and functional hierarchy of floral works, decompose complex floral orders into tasks to generate a floral skill task chain information set;

[0007] Based on the floral art skill task chain information set, dynamic matching of execution nodes and skill tags is performed, and targeted reconstruction and environmental adaptation of franchise store functions are triggered accordingly, generating a set of dynamic node attribute mapping schemes to drive node specialization and process standardization.

[0008] Based on the dynamic node attribute mapping scheme set, the life status of semi-finished products is tracked and the final integrity is encapsulated, generating and outputting a full-chain collaborative report for floral orders.

[0009] Through the above technical solutions, the franchise network is upgraded into a flexible production organism that can be dynamically reorganized, realizing the standardized breakdown and professional collaboration of complex orders. It not only ensures the quality and emotional expression of floral works as works of art throughout the entire process, but also significantly improves the overall operational efficiency, resource utilization and customer trust of the network through a fully digital closed loop.

[0010] Optionally, the generation process of the floral art skill task chain information set includes: the floral art order requirement dataset includes physiological state requirements of floral materials, sequence of craft techniques, emotional expression scenarios, and spatiotemporal delivery constraints; based on the floral art order requirement dataset, according to the progressive construction logic defined by the spatial structure and functional hierarchy of floral art works, complex floral art orders are decomposed into a set of floral art sub-tasks with strict task distinction relationships; based on the set of floral art sub-tasks, a corresponding standardized task execution package is assigned to each floral art sub-task, thereby integrating all the standardized task execution packages to generate the floral art skill task chain information set.

[0011] Optionally, the process of constructing the floral art sub-task set includes: based on the sequence of techniques and the emotional expression scenario, parsing out multiple independent floral art work units contained in the order, and determining the type and style characteristics of each independent floral art work unit; for each independent floral art work unit, combining its physiological requirements for flower materials and its spatiotemporal delivery constraints, matching one or more core skill tags and corresponding standard working time expectations from a preset floral art work requirement mapping table; using each independent floral art work unit as a benchmark, and combining its matched core skill tags, decomposing it into independent allocation units that can be executed by franchise stores with different specialties; organizing all the independent allocation units into the floral art sub-task set with networked dependencies based on their logical relationships, material flow relationships, and standard working time expectations in the original order.

[0012] Optionally, the standardized task execution package includes: the standardized task execution package encapsulates the execution configuration data of each independent floral arrangement unit, including: a florist skill tag set, derived from the core skill tags matched by the corresponding independent allocation unit, used to identify the professional skill combination required to perform this task; a precise bill of materials, generated according to the type, style characteristics and physiological state requirements of the flowers of the independent allocation unit, and matched with preset material configuration rules; and quality node acceptance criteria, defined according to the position of the independent allocation unit in the networked dependency relationship and its process characteristics.

[0013] Optionally, the generation process of the dynamic node attribute mapping scheme set includes: based on the florist skill tag set and spatiotemporal requirements encapsulated in each of the independent allocation units, and according to the skill tag matching degree, the current workload of the node, and the physical microenvironment data of the node, selecting the optimal execution node from the franchise network; sending a reconstruction instruction to the optimal execution node to trigger its operation interface, material permissions, and work process to switch to a special execution mode that matches the assigned independent allocation unit; and encapsulating the matching relationship between each of the optimal execution nodes and the assigned independent allocation unit, the reconstruction instruction, and the switching result according to the special execution mode after the node completes the reconstruction, thereby generating the dynamic node attribute mapping scheme set.

[0014] Optionally, the step of selecting the optimal execution node from the franchise network includes: screening based on the skill tag matching degree: prioritizing franchise nodes whose registered skill tags are completely consistent with the florist skill tag set encapsulated by the independent allocation unit, and which have recently had successful execution records of the same independent allocation unit; screening based on the node's current workload: evaluating the workload saturation of candidate nodes within the execution period specified by the spatiotemporal requirements of the independent allocation unit, and selecting franchise nodes with sufficient capacity margin; verifying based on the node's physical microenvironment data: comparing the real-time physical environment parameters of the candidate franchise nodes with the preset physical microenvironment requirements of the independent allocation unit, and verifying whether their operating space size and environmental temperature and humidity control equipment are complete and up to standard; and comprehensively evaluating and ranking the candidate franchise nodes based on the screening and verification results, and selecting the node with the best overall performance as the optimal execution node.

[0015] Optionally, the process of generating the full-link collaborative report for the floral arrangement order includes: based on the dynamic node attribute mapping scheme set, performing relay tracking of the semi-finished product life status of the execution process of each independent allocation unit at its assigned optimal execution node; after all independent allocation units have completed execution and passed quality node acceptance, performing final summarization, inspection, and packaging of the semi-finished products of all units to complete the final integrity encapsulation; integrating the floral arrangement skill task chain information set, the dynamic node attribute mapping scheme set, and the tracking data and encapsulation results of each link to generate the full-link collaborative report for the floral arrangement order that includes task decomposition, node matching, process tracking, and quality confirmation.

[0016] Optionally, the semi-finished product life status tracking includes: dynamically synthesizing a virtual preservation corridor across nodes based on the physiological state requirements of the floral materials in each independent allocation unit and the physical microenvironment data of the nodes through which the corridor passes, and preset its floral life characteristic tolerance threshold; during the production and circulation process, real-time monitoring of the floral life characteristics is performed, and when the predicted data deviates from the floral life characteristic tolerance threshold, an optimization instruction including adjusting transportation parameters or changing transit nodes is actively triggered; before final delivery, the final scene adaptive encapsulation is triggered based on the actual life status of the floral work and the emotional expression scenario of the order.

[0017] Optionally, the method further includes: pre-setting a basic contribution value for each independent allocation unit in the floral skill task chain information set, wherein the basic contribution value is calculated based on the complexity of the core skill tag it matches and the expected standard working hours; weighting and correcting the basic contribution value according to the actual execution quality of each independent allocation unit under the quality node acceptance standard to generate the actual contribution value of the franchise node, wherein the quality basis comes from the end customer feedback; summarizing the corrected actual contribution values ​​of all independent allocation units in the order, and dynamically dividing the total revenue of the order according to the proportion of the actual contribution value of each unit in the total contribution value to generate a franchise node capability profile; the franchise node capability profile represents the quantitative indicators of the node's historical performance and reliability under the corresponding skill tag, and is used to provide historical performance basis for selecting the optimal execution node from the franchise network when generating a new floral skill task chain information set for subsequent orders.

[0018] Secondly, this application provides a regional dynamic deployment system for a flower delivery franchise network, the system comprising:

[0019] The task chain information module obtains the floral order demand dataset; based on the floral order demand dataset, it extracts the physiological state requirements of floral materials, the sequence of craft techniques, the emotional expression scenarios, and the spatiotemporal delivery constraints, and according to the progressive construction logic defined by the spatial structure and functional hierarchy of floral works, it decomposes complex floral orders into tasks and generates a floral skill task chain information set.

[0020] The node attribute mapping module is used to dynamically match execution nodes with skill tags based on the floral skill task chain information set, and trigger targeted reconstruction and environmental adaptation of franchise store functions accordingly, generating a set of dynamic node attribute mapping schemes to drive node specialization and process standardization.

[0021] The collaborative reporting module is used to perform relay tracking of the life status of semi-finished products and final integrity encapsulation based on the dynamic node attribute mapping scheme set, and generate and output a collaborative report of the entire floral order chain. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of an application scenario provided in an embodiment of this application;

[0024] Figure 2 A flowchart illustrating a method for dynamic regional deployment of a flower delivery franchise network, provided as an embodiment of this application;

[0025] Figure 3 This is a schematic diagram of the structure of a regional dynamic deployment system for a flower delivery franchise network, provided as an embodiment of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0027] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0028] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0029] Existing floral supply chain management methods, when faced with multiple constraints, lack a mechanism for systematic and forward-looking modeling and global dynamic protection of the life state of the works. This not only makes it difficult to achieve closed-loop quality control throughout the entire chain from production to delivery, but also often results in irreversible damage to the expressiveness of the works before delivery due to the lag in passive and reactive monitoring and intervention, which seriously affects user experience and brand reputation.

[0030] Based on this, this application provides a method and system for the regional dynamic deployment of a flower delivery franchise network. First, a dataset of floral order requirements is acquired, extracting the physiological state requirements of floral materials, the sequence of craft techniques, the emotional expression scenarios, and spatiotemporal delivery constraints. Then, based on the progressive construction logic defined by the spatial structure and functional hierarchy of the floral works, complex floral orders are decomposed into tasks, generating a floral skill task chain information set. Subsequently, the task scheduling center matches franchise nodes with corresponding skill tags in real time based on the floral skill task chain information set, and drives the nodes to perform targeted environment reconstruction, forming a dynamic production mapping. Finally, the system constructs a virtual preservation corridor for the orders, tracks the life state of semi-finished products throughout the process, and triggers adaptive encapsulation based on the final state and the original scenario, ultimately generating a full-link collaborative report and outputting it to the franchise store merchants. This solution upgrades the franchise network into a dynamically reconfigurable, elastic production organism, realizing standardized decomposition and professional collaboration of complex orders. It not only ensures the overall quality and emotional expression accuracy of floral works as living works of art throughout the process, but also significantly improves the overall operational efficiency, resource utilization, and customer trust of the network through a fully digital closed loop.

[0031] Figure 1 This is a schematic diagram illustrating an application scenario provided by this application. In the dynamic deployment of a flower delivery service franchise network, this application utilizes the method provided to achieve standardized breakdown and professional collaboration of complex orders, ensuring the overall quality of floral arrangements as works of art throughout their creation.

[0032] Specifically, the method of this application is applied to any server that communicates with the online flower ordering platform and obtains the floral order demand dataset provided by the online flower ordering platform through the server.

[0033] For specific implementation details, please refer to the following examples.

[0034] Figure 2 This is a flowchart illustrating a method for dynamic regional deployment of a delivery franchise network, provided as an embodiment of this application. The method of this embodiment can be applied to servers in the above-described scenario. For example... Figure 2 As shown, the method includes:

[0035] S201. Obtain the floral order demand dataset. Based on the floral order demand dataset, extract the physiological state requirements of floral materials, the sequence of craft techniques, the emotional expression scenarios, and the spatiotemporal delivery constraints. According to the progressive construction logic defined by the spatial structure and functional hierarchy of the floral works, decompose the complex floral orders into tasks and generate a floral skill task chain information set.

[0036] The “flower delivery franchise network” referred to in this application is a flower delivery service network.

[0037] A floral order demand dataset refers to a collection of structured and unstructured data received by a flower delivery franchise network, containing basic order information (such as recipient address and time) and deeper demand information (such as usage scenarios, emotional expression, style preferences, budget range, and special requirements for floral materials). The data originates from a flower delivery network order platform. Based on this floral order demand dataset, physiological requirements for floral materials, sequences of craft techniques, emotional expression scenarios, and spatiotemporal delivery constraints can be extracted. Following a progressive construction logic defined by the spatial structure and functional hierarchy of floral works, complex floral orders are decomposed into a set of floral sub-tasks with strict task distinctions. Then, based on this set of floral sub-tasks, a corresponding standardized task execution package is assigned to each floral sub-task, thereby generating a floral skill task chain information set. Task decomposition can be a process of transforming complex floral orders into a series of standardized, executable, and transferable atomic skill tasks based on a demand profile generated by biological analysis. Floristry skill task chain information set can refer to an information set consisting of a series of ordered and logically related atomic skill tasks generated through parsing and decomposition.

[0038] Specifically, modern floral consumption has transcended basic material needs, increasingly focusing on emotional expression, scene adaptation, and artistic experience. Order demands exhibit highly personalized, emotional, and professional complex characteristics. However, traditional flower delivery franchise networks mostly remain at the level of information transmission and simple order dispatch in order processing, lacking the ability to deeply analyze and structure the multi-dimensional needs of orders. This results in the network's inability to accurately understand subjective requirements such as "creating a sense of surprise" and "reflecting high-level aesthetics," and even more so, difficulty in breaking them down into specific, assignable, executable, and measurable tasks. Consequently, the quality of order execution heavily relies on the individual experience and on-the-spot performance of the florist receiving the order, resulting in low standardization, difficulty in improving network collaboration efficiency, and uncertainty in the delivery of complex, high-end orders. This solution addresses this core bottleneck by introducing biological analysis and task decomposition, transforming vague emotional needs into task chains with clear skill requirements and environmental parameters. This process essentially translates artistic language into engineering language, laying an indispensable and structured data foundation for subsequent scientific, capability-based dynamic resource scheduling.

[0039] S202. Based on the floral art skill task chain information set, perform dynamic matching of execution nodes and skill tags, and trigger targeted reconstruction and environmental adaptation of franchise store functions accordingly, generating a set of dynamic node attribute mapping schemes to drive node specialization and process standardization.

[0040] Execution nodes can refer to physical franchise stores or sites with specific processing capabilities within the Flower Delivery franchise network. Each node is digitally modeled in the system and possesses a set of attributes including geographical location, spatial layout, equipment list, on-duty florist skill profiles, historical work data, and real-time environmental sensor data. Skill tags can be standardized codes and classifications of basic floral art skills, such as "Ecuadorian rose water retention treatment," "structural framework construction," "natural color scheme," and "luxury-grade gift box packaging." Dynamic matching can be the process of finding the execution node with the highest attribute-to-task fit across the entire network based on the requirements of each task in the "floral art skill task chain," in real-time (or near real-time). Targeted reconstruction and environmental adaptation can be the specific set of instructions issued by the system to the target node after matching, aiming to temporarily adapt its physical environment or workflow to the needs of a specific task. The dynamic node attribute mapping scheme set can be the complete set of "task-node-adaptation requirements" correspondence schemes formed after the skill task chain matching for the entire order is completed.

[0041] Specifically, after obtaining a standardized task chain, the key to determining overall network efficiency and order quality lies in how to efficiently and accurately allocate it to the most suitable production nodes in the network. Traditional franchise networks often adopt a static order dispatch model based on geographical location or fixed rotation, which cannot perceive and utilize the heterogeneity and dynamic changes in professional skills, equipment configuration, real-time capacity, and environmental conditions among different franchise stores. This rigid allocation method is prone to capability mismatch: simple tasks occupy professional node resources, while complex tasks are assigned to nodes with insufficient capabilities, resulting in low resource utilization, failure to maximize professional value, and difficulty in coping with structural fluctuations in order demand. This step addresses this problem by dynamically matching execution nodes with skill tags and driving targeted reconstruction and environmental adaptation of nodes, aiming to shape the entire network into a dynamically reconfigurable elastic production system. It enables each order to find the optimal execution path globally and allows nodes to be temporarily configured with the best working state for specific tasks, thereby realizing the transformation from fixed-function stores to flexible production units.

[0042] S203. Based on the dynamic node attribute mapping scheme set, perform semi-finished product life status tracking and final integrity encapsulation, and generate and output a full-link collaborative report for floral orders.

[0043] Semi-finished product lifecycle tracking involves continuous and seamless monitoring and data recording of the core vital signs (such as moisture content, cell activity, and morphological retention) of floral materials or semi-finished floral arrangements as they move between different stages during order execution. Complete packaging involves selecting and executing the most suitable packaging, tagging, presentation, and other final delivery steps based on the original emotional expression of the order and the real-time status of the final artwork after all production stages are completed. A comprehensive floral order end-to-end collaborative report is a document summarizing data from the entire order process.

[0044] Specifically, the core value of floral products lies in their freshness and emotional resonance as "living works of art." From flower processing and arrangement to final delivery to the customer, multiple stages and waiting periods are involved, during which the flowers' physiological state continuously changes. In the traditional model, this process is almost a black box, lacking continuous monitoring and assurance measures for the life state of semi-finished products. Quality risks accumulate during the process, and accountability is difficult to trace after problems arise. Furthermore, final delivery is often merely a simple logistical action, disconnected from the emotional context of the order, potentially leading to a flawed experience. The shortcomings of existing processes in ensuring the life state and providing a closed loop for emotional delivery are significant factors hindering service quality improvement and customer trust building. This step addresses this shortcoming by implementing relay tracking of the life state of semi-finished products and final integrity packaging, constructing a quality protection and experience delivery closed loop throughout the entire order chain. It ensures proactive management of the flower lifecycle and allows for the design of the most appropriate delivery ceremony based on the final state of the arrangement and the original scene, thereby transforming the reliability of the production process into perceptible value and trust for the customer. The final generated end-to-end collaborative report provides data assets for process optimization, responsibility definition, and value verification.

[0045] The method provided in this embodiment first acquires a floral order demand dataset, extracts the physiological state requirements of floral materials, the sequence of craft techniques, the emotional expression scenarios, and the spatiotemporal delivery constraints. Based on the progressive construction logic defined by the spatial structure and functional hierarchy of the floral artwork, complex floral orders are decomposed into tasks, generating a floral skill task chain information set. Subsequently, the task scheduling center matches franchise nodes with corresponding skill tags in real time based on the floral skill task chain information set, and drives the nodes to perform targeted environment reconstruction, forming a dynamic production mapping. Finally, the system constructs a virtual preservation corridor for the order, tracks the life state of the semi-finished products throughout the process, and triggers adaptive encapsulation based on the final state and the original scenario, ultimately generating a full-link collaborative report and outputting it to the franchise store merchants. This solution upgrades the franchise network into a dynamically reconfigurable, elastic production organism, realizing standardized decomposition and professional collaboration of complex orders. It not only ensures the overall quality and emotional expression accuracy of floral artworks as living works of art, but also significantly improves the overall operational efficiency, resource utilization, and customer trust of the network through a fully digital closed loop.

[0046] In some embodiments, the floral order requirement dataset includes requirements for the physiological state of floral materials, a sequence of craft techniques, emotional expression scenarios, and spatiotemporal delivery constraints. Based on the floral order requirement dataset, and according to the progressive construction logic defined by the spatial structure and functional hierarchy of floral works, complex floral orders are decomposed into a set of floral sub-tasks with strict task distinctions. Based on the set of floral sub-tasks, a corresponding standardized task execution package is assigned to each floral sub-task, thereby integrating all standardized task execution packages to generate a floral skill task chain information set.

[0047] The physiological requirements for floral materials can be specific quantitative requirements in the order regarding the freshness, openness, and color saturation of the flowers used. The sequence of techniques can be a list of the execution order of the floral techniques required to complete the order, such as "water retention treatment -> spiral structure construction -> color gradient filling -> heterogeneous material decoration". The emotional expression scenario can be the specific context served by the order and the emotion expected to be conveyed, such as "birthday surprise", "business thanks", or "solemn memorial". The spatiotemporal delivery constraints can be the final time node that the order must be completed and the geographical location of delivery. The progressive construction logic can be the progressive assembly rules of the floral arrangement, from the core structure to the surface decoration, in both physical space and visual hierarchy. The set of floral subtasks can be a group of independent task units with clear dependencies and input / output definitions, obtained by breaking down a complex order according to the progressive construction logic. For example, a large flower basket can be broken down into five subtasks: "base construction", "main flower positioning", "filling with complementary flowers", "foliage trimming", and "finished product packaging". A standardized task execution package can be a digital instruction package encapsulated for each floral subtask, containing all the information required for its execution. It serves as a "work order" driving franchise stores to carry out specialized production. The floral skill task chain information set can be an ordered set composed of all standardized task execution packages organized according to their dependencies, representing a complete, network-executable production plan for completing the order.

[0048] The spatial structure and functional hierarchy of a floral arrangement can be seen as a hierarchical division of the arrangement in terms of physical space and visual / functional presentation. This division is used to determine the progressive assembly sequence of the arrangement from the "core structure" to the "surface decoration / encapsulation". For example, a flower basket / bouquet arrangement can be divided into layers such as "base / skeleton layer, main flower positioning layer, filler flower layer, foliage trimming layer, and finished product packaging / encapsulation layer", and a progressive construction logic of "skeleton first, then filler; main flower first, then filler" can be formed accordingly.

[0049] Logical relationships can be the process sequence dependencies / input-output relationships between floral subtasks or independently assigned units to complete the same order, used to characterize the constraints on the execution order of different tasks.

[0050] Specifically, traditional franchise networks often treat floral orders as an indivisible whole, directly assigning them to a florist or store. This approach heavily relies on the comprehensive capabilities of the receiving node, failing to handle the complex demands of orders (such as wedding arrangements involving multiple large-scale structural works) that require a combination of highly complex skills. Furthermore, if a node reaches capacity saturation or lacks a key skill, order delays or quality degradation can occur. The fundamental flaw lies in the lack of an engineering-based analysis of the order's internal structure, failing to break down complex skill requirements into atomic tasks that can be completed in parallel by multiple specialized nodes within the network. This step addresses this core issue by first deconstructing complex orders—which integrate floral physiology, technological sequences, emotional context, and spatiotemporal constraints—into a set of distinct and interdependent floral subtasks based on the progressive construction logic defined by the spatial and functional hierarchy of the floral arrangement (e.g., skeleton before filling, main flowers before accessories). For example, a "surprise proposal bouquet" order can be broken down into five subtasks: "Ecuadorian rose water retention pretreatment," "heart-shaped structural skeleton construction," "integrated decoration with string lights and ribbons," and "luxury-grade gift box packaging." Then, the system matches and encapsulates a standardized task execution package for each subtask. This package precisely specifies the skill tags, material lists, and acceptance criteria required for execution. Finally, all task packages are chained together according to their process logic to generate a structured floral art skill task chain information set.

[0051] The approach provided in this embodiment achieves a fundamental shift from "overall outsourcing" to "process decoupling," enabling complex orders to be broken down into standardized tasks that can be collaboratively completed by nodes with different expertise within the network. This breaks through the bottleneck of the capabilities and capacity of individual nodes, providing a unique and necessary structured input for subsequent dynamic deployment and efficient collaboration based on precise skill matching.

[0052] In some embodiments, based on the sequence of craft techniques and the emotional expression scenario, multiple independent floral art units contained in the order are parsed out, and the type and style characteristics of each independent floral art unit are determined. For each independent floral art unit, combined with its physiological requirements for the flowers and spatiotemporal delivery constraints, one or more core skill tags and corresponding standard working time expectations are matched from a preset floral art demand mapping table to complete the work. Based on each independent floral art unit, combined with its matched core skill tags, it is decomposed into independent allocation units that can be executed by franchise stores with different specialties. All independent allocation units are organized into a set of floral art sub-tasks with networked dependencies according to their logical relationships, material flow relationships and standard working time expectations in the original order.

[0053] An independent floral arrangement unit can be a single floral entity that can be independently designed, produced, and delivered within a composite order (such as a wedding package), such as a "bridal bouquet," "centerpiece for the main table," or "reception arch." Core skill tags can be identifiers of the professional skills required to complete a specific type and style of floral arrangement, such as "spiral technique (advanced)," "structural wire shaping," or "fusion of heterogeneous materials." The standard expected time can be the average estimated time (e.g., 1.5 hours) required for a skilled florist with the corresponding core skills to complete this independent arrangement unit under ideal conditions. An independently allocated unit can be the smallest task unit that can be directly assigned to a single franchise node, formed by further considering networked production constraints (such as franchise store expertise and physical flow) based on the "independent floral arrangement unit." Networked dependencies can be the logical sequence, material transfer, or spatiotemporal coordination relationships between different independently allocated units. For example, the "structural framework" unit must be created first before the "floral filling" unit can be built upon it.

[0054] Specifically, when traditional franchise networks receive complex orders containing multiple works, they often treat them as a whole or roughly divide them into several large parts for allocation. This coarse-grained approach has serious drawbacks: First, it cannot identify the differentiated skill requirements of different works within the order (e.g., bouquets require meticulous binding, while backdrops require large-scale structures), potentially leading to tasks that the organization is not skilled at being assigned to a particular node. Second, it ignores the production order and material flow relationships between works, easily causing production process chaos and wasted time. Third, it lacks accurate estimation of the working hours for each work, making it difficult to balance production capacity across nodes and reverse-engineer delivery times. This step aims to achieve a refined deconstruction from "overall allocation" to "atomic task network." Its core implementation process is as follows: The system first analyzes the sequence of craft techniques and emotional expression scenarios of the order, identifies and separates multiple independent work units, and determines their type and style. For example, a "high-end business launch event" order may contain two independent units: "podium table flowers" (modern style) and "corporate logo floral wall" (structural style). Subsequently, for each unit, based on its physiological requirements for floral materials (e.g., the logo wall requires durable flowers) and final delivery deadline, the system matches the set of core skill tags necessary to complete it from a pre-defined mapping table (e.g., "logo wall" requires tags such as "large-scale structural welding" and "floral foam fixing") and the corresponding expected standard working hours (e.g., "table centerpieces" are estimated to require 2 hours). Next, using each independent work unit as a benchmark, and combining its matched skill tags, it is directly or further broken down (e.g., a large flower wall is broken down into three sections—upper, middle, and lower—that can be made by different people in parallel) into independent allocation units that can be executed by franchise stores with different specialties. Finally, the system analyzes the logical order of all independent allocation units in the original order (e.g., table centerpieces are made before flower walls), material flow relationships (e.g., specific flowers procured in a unified manner need to be delivered to a certain node first), and their respective work periods, organizing them into a task graph with clear networked dependencies, i.e., a set of floral art sub-tasks.

[0055] The method provided in this embodiment enables in-depth structured analysis of composite orders, generating a refined task network that includes skill requirements, project time estimates, and task dependencies. This lays an indispensable planning blueprint with complete constraint information for subsequent dynamic node scheduling and collaborative production process optimization based on precise matching.

[0056] In some embodiments, the standardized task execution package encapsulates the execution configuration data for each independent floral arrangement unit, including: a florist skill tag set, derived from the core skill tags matched by the corresponding independent allocation unit, used to identify the combination of professional skills required to perform this task; a precise bill of materials, generated by matching preset material configuration rules based on the type, style characteristics, and physiological state requirements of the flowers in the independent allocation unit; and quality node acceptance criteria, defined according to the position of the independent allocation unit in the networked dependency relationship and its process characteristics.

[0057] A florist's skill tag set can be a collection of tags encapsulated within a standardized task execution package, used to uniquely identify the combination of professional skills required to perform the independent assignment unit. An accurate bill of materials can be a detailed list of consumables, derived through systematic calculations to complete a specific independent assignment unit, including the type, grade, quantity, reserve wastage rate, and specifications of auxiliary materials. Quality checkpoint acceptance criteria can be a set of quantifiable or objectively verifiable pass / fail criteria defined for the output of the independent assignment unit. Preset material configuration rules can be a knowledge base or algorithmic rules stored in the system that associate and match floral arrangement types and styles with specific material types, quantities, and specifications.

[0058] Technological characteristics can be the production processes corresponding to independently allocated units, which can be characterized by a sequence of technological techniques and task types.

[0059] Specifically, in a distributed collaborative production network, if tasks are merely broken down without unified and precise execution instructions, each participating node will still rely on the florist's personal experience and subjective judgment for production, leading to three core problems: First, skill requirements are vaguely communicated, easily resulting in a quality decline where "orders can be accepted but not executed well"; second, material estimation is crude, either causing production interruptions due to insufficient material reserves or cost waste and spoilage due to over-purchasing; finally, the lack of objective acceptance standards for intermediate outputs results in inconsistent quality of semi-finished products as they circulate between nodes, leading to frequent conflicts in the final assembly stage. This step aims to transform abstract task requirements into "digital work orders" that can be executed unambiguously by any node. Its core implementation process is: the system takes an independently allocated unit as input and automatically encapsulates and generates a corresponding standardized task execution package. This package first inherits the core skill tags matched by the unit, forming a florist skill tag set (e.g., encapsulating the tags "metal wire shaping (advanced)" and "preserved flower processing" for the "heterogeneous material fusion decoration" unit). Secondly, based on the unit's type (e.g., "hanging floral arrangement"), style characteristics (e.g., "forest style"), and physiological requirements of the floral materials (e.g., "requires dehydration-resistant foliage"), the system queries preset material configuration rules to generate a precise material list (example: the list precisely specifies "3 staghorn ferns, 2 air plants, 20 imported eucalyptus leaves, 5 meters of 2mm copper-coated iron wire," and indicates a 10% waste reserve ratio). Finally, based on the unit's position in the network (e.g., as the last process before final packaging) and its technological characteristics, quality node acceptance standards are defined (e.g., for the "gift box packaging" unit, the standards are defined as "bouquet fixed displacement less than 2mm," "moisturizing layer completely covers floral foam and is not exposed," and "ribbon knot symmetry deviation less than 3 degrees"). Through this three-element packaging, each task package becomes a complete instruction entity driving production.

[0060] The method provided in this embodiment integrates and digitally encapsulates the requirements, resources, and quality standards of each atomic task, fundamentally eliminating misunderstandings and arbitrary execution in collaborative production. It provides precise production guidelines for participating nodes, ensuring the consistency of input and output across nodes, and is a key foundation for achieving process standardization and controllable final product quality.

[0061] In some embodiments, based on the florist skill tag set and spatiotemporal requirements encapsulated in each independent allocation unit, the optimal execution node is selected from the franchise network according to the skill tag matching degree, the node's current workload, and the node's physical microenvironment data; a reconstruction instruction is sent to the optimal execution node, triggering its operation interface, material permissions, and work process to switch to a special execution mode that matches the assigned independent allocation unit; according to the special execution mode after the node completes reconstruction, the matching relationship between each optimal execution node and the assigned independent allocation unit, the reconstruction instruction, and the switching result are encapsulated to generate a dynamic node attribute mapping scheme set.

[0062] Skill tag matching can be a numerical indicator used to quantitatively evaluate the degree of agreement between the set of registered skill tags of a franchise node and the set of florist skill tags encapsulated in the independent allocation unit. Node current workload can be quantitative data representing the proportion or saturation state of a franchise node's committed task volume relative to its theoretical maximum capacity at a specific evaluation time or in a future period. Node physical microenvironment data can be a set of parameters reflecting the physical conditions and environmental status of the franchise node's actual operating location, including but not limited to workbench dimensions, storage space volume, real-time temperature and humidity readings, and the availability and status of specific processing equipment (such as temperature-controlled cabinets and cold storage for flowers). The optimal execution node can be the franchise store most suitable for executing a specific independent allocation unit, determined from the franchise network after multi-dimensional comprehensive evaluation and screening. Reconfiguration commands can be digital control commands sent by the central scheduling system to the selected optimal execution node to trigger an instantaneous switch in its internal operating environment. The special execution mode can refer to the dynamic adjustment of the operation interface, material access permission library, standard operating procedure display and equipment parameter preset of the franchise node after receiving the reconstruction instruction, so as to serve only the current specific task package.

[0063] Spatiotemporal requirements may include spatiotemporal delivery constraints for orders and task execution time constraints. Task execution time constraints are used to limit the executable time interval of independent allocation units within the network, so as to conduct node workload assessment and scheduling.

[0064] Specifically, in a distributed floral production network, statically assigning task packages to fixed nodes has serious drawbacks: Node functions are fixed, making it impossible to dynamically adjust resource allocation based on task characteristics, leading to inefficiency when handling specialized tasks; uneven node loads result in busy nodes becoming bottlenecks, while idle nodes fail to fully utilize their capabilities; and mismatched environmental conditions, such as assigning orchid processing tasks requiring constant temperature to small shops without temperature control equipment, directly leading to quality risks. The traditional "order dispatch-order acceptance" model cannot solve these dynamic adaptation problems. This step aims to achieve real-time, accurate, and adaptive matching and switching between tasks and nodes. The core implementation process is as follows: First, for each packaged, independently allocated unit, the system uses its contained florist skill tag set and time and space requirements as the screening criteria. It calculates in real time the compliance of all candidate nodes in the franchise network across three dimensions: skill matching (e.g., requiring a perfect match between the "architectural welding" and "heterogeneous materials" tags), current workload (assessing whether its existing tasks account for 70% or 30% of its capacity in the next 4 hours), and physical microenvironment (e.g., verifying whether the workbench length is greater than 2 meters and whether the ambient humidity can be stable between 60% and 70%). A weighted scoring algorithm (e.g., assigning weights of 0.5, 0.3, and 0.2 to the three dimensions respectively) is used to select the node with the highest comprehensive score as the optimal execution node. Subsequently, the system sends a reconstruction command containing specific configuration parameters to this node, triggering its internal system: the operation interface only displays the precise bill of materials and quality node acceptance standards for the current task; material permissions only unlock warehouse access for the specific floral materials required for the task; and the workflow guidance switches to a standard step-by-step video or graphic guide for this task type. After the node completes the switch and provides confirmation, the system records and encapsulates the complete mapping relationship of "task-node-instruction-result" to generate a dynamic node attribute mapping scheme set.

[0065] The method provided in this embodiment realizes a leap from static assignment to dynamic targeted reconstruction, enabling each node in the network to instantly transform into a dedicated "workshop" for a specific task. This greatly improves the accuracy of resource utilization and the environmental adaptability of task execution, providing key scheduling and execution basis for the reliable and efficient collaborative production of complex orders.

[0066] In some embodiments, screening is performed based on skill tag matching: priority is given to matching franchise nodes whose registered skill tags are completely consistent with the florist skill tag set encapsulated by the independent allocation unit, and which have recently had successful execution records of similar independent allocation units; screening is also performed based on the node's current workload: the workload saturation of candidate nodes within the execution period specified by the spatiotemporal requirements of the independent allocation unit is evaluated, and franchise nodes with sufficient capacity margin are selected; verification is performed based on the node's physical microenvironment data: the real-time physical environment parameters of candidate franchise nodes are compared with the preset physical microenvironment requirements of the independent allocation unit to verify whether their operating space size and environmental temperature and humidity control equipment are complete and up to standard; based on the comprehensive screening and verification results, the candidate franchise nodes are scored and ranked, and the node with the best overall performance is selected as the optimal execution node.

[0067] Workload saturation can be the proportion (e.g., 80%) of the total estimated working hours of the candidate franchise node's existing scheduled tasks to the node's maximum available working hours during the specified execution period of the independent allocation unit. Real-time physical environment parameters can be a set of data reflecting the physical state of the operating space, collected and reported in real time by the candidate franchise node through IoT sensors, including but not limited to the size of the workbench, ambient temperature, ambient humidity, and light intensity. Preset physical microenvironment requirements can be specific parameter specifications set for the execution environment of a particular independent allocation unit to ensure the production quality and physiological state of the flowers (e.g., requiring a constant ambient temperature of 18-22℃ and humidity of 65%-75%). Scoring and ranking can be the process by which the system comprehensively and quantitatively scores the candidate franchise nodes that have passed the initial screening based on a preset weight model across multiple dimensions such as skill matching, workload saturation, and environmental compliance, and forms a priority list according to the scores.

[0068] Specifically, traditional task allocation relying solely on a single dimension (such as simple geographical proximity or the presence or absence of skill tags) will lead to deep-seated imbalances in network collaboration. For example, matching only by skill might assign an urgently needed architectural task to a node that possesses the skill but is already at full capacity, resulting in delivery delays; or neglecting environmental verification might send orchid processing tasks requiring constant humidity to a small shop lacking humidification equipment, directly causing flower material waste. This "seeing the trees but not the forest" screening mechanism cannot achieve an optimal solution among skill adaptation, capacity balancing, and physical environment assurance, leading to overall network inefficiency and uncontrollable quality risks. This step addresses this problem by constructing a multi-level, progressive, and comprehensively verified dynamic screening funnel. The core implementation process is as follows: First, the system performs screening based on skill tag matching. Using the skill tag set encapsulated by the independently allocated unit (such as {Spiral Technique (Advanced) , Heterogeneous Material Fusion}) as a benchmark, it retrieves a pool of registered tags that are completely matched (i.e., contain and are not less than the required tags) from the network. It further prioritizes nodes with recent (e.g., within the past week) successful execution records of similar units to ensure the reliability of experience. Next, it performs screening based on the current workload of the nodes. The system obtains the existing task schedules of each node in the candidate pool within the future task execution window (e.g., 14:00-18:00 today), calculates its workload saturation (e.g., if existing tasks occupy 3.5 hours, and the maximum working time within the node window is 5 hours, then the saturation is 70%), and selects nodes with saturation below a preset threshold (e.g., 80%) and sufficient capacity margin (e.g., 1.5 hours in the example above). Next, a verification based on the physical microenvironment data of the nodes is performed. The system retrieves the real-time physical environment parameters of the candidate nodes (e.g., the operating table length is 2.2 meters and the current humidity is 63% as determined by sensors) and compares them item by item with the preset physical microenvironment requirements of the task unit (e.g., the operating table length must be ≥2 meters and the humidity must be maintained at 60%-70%). Nodes that fail to meet any key indicators (e.g., space size, temperature and humidity control capabilities) are eliminated. Finally, for the nodes that pass the above three-level screening, the system performs a weighted comprehensive score based on indicators such as the completeness of skill matching, the reciprocal of load saturation (the more margin, the higher the score), and the compliance of environmental parameters (e.g., assigning weights of 0.4, 0.3, and 0.3 to the three dimensions), and sorts them according to the total score. The node ranked first is selected as the optimal execution node for final dispatch.

[0069] The method provided in this embodiment establishes a quantifiable node selection mechanism that encompasses all dimensions, from skills and production capacity to the hard environment. This ensures that the selected nodes not only "can do it," but also "have the space to do it" and "do it in a suitable environment," fundamentally achieving a precise triple match between task requirements and node resources in terms of capability, time, and space.

[0070] In some embodiments, based on a dynamic node attribute mapping scheme set, the execution process of each independent allocation unit at its assigned optimal execution node is tracked in a relay manner to determine the semi-finished product life status. After all independent allocation units have completed execution and passed quality node acceptance, the semi-finished products of all units are finally summarized, inspected, and packaged to complete the final integrity encapsulation. The floral art skill task chain information set, the dynamic node attribute mapping scheme set, and the tracking data and encapsulation results of each link are integrated to generate a full-link collaborative report for floral art orders that includes task decomposition, node matching, process tracking, and quality confirmation.

[0071] Semi-finished product lifecycle tracking can be a process of continuous and uninterrupted status monitoring and data recording of the entire process of production, temporary storage, and transfer to downstream nodes for each independent allocation unit at its corresponding optimal execution node, based on a dynamically mapped node attribute scheme and a centralized recording of allocation relationships. Integrity encapsulation can be the process of physically assembling and performing final quality inspection of all semi-finished products at the final assembly node (or central collection center) after all independent allocation units have completed their execution and passed their respective quality node acceptance standards, and then uniformly packaging them according to order delivery requirements.

[0072] Specifically, in a distributed collaborative production network, without the collection of status data throughout the entire task execution process and the integration of data from a global perspective, order management will fall into "information silos" and "process black boxes": each participating node only knows the completion status of its own task, the central dispatcher cannot grasp the life status of semi-finished products in real time during circulation (such as whether the temperature and humidity exceed the standard during transportation from node A to node B), and the end customer cannot know the complex collaborative process behind the product. Once the delivered finished product has quality defects, it is difficult to trace the root cause of the problem (whether it is a process error at a specific node or caused by the circulation environment), leading to unclear responsibilities and disputes. Therefore, it is necessary to establish a traceable digital mirror system that covers the entire chain from task issuance to finished product packaging. Its core implementation process is: first, based on a dynamic node attribute mapping scheme set, the system automatically triggers relay tracking of the life status of semi-finished products at the optimal execution node assigned to each independent allocation unit. For example, when a node begins processing a "skeleton" unit, the system records its start time and the batch of materials used. It also records timestamps and brief images of key production milestones (such as welding completion) via sensors configured at the node or manual clocking. After completion, an RFID tag is affixed to the unit, and its temperature and humidity data during transport to the next node are transmitted in real-time via an onboard IoT device. When all units are completed and arrive at the final assembly point, the system verifies the electronic acceptance form for each unit, triggering a complete packaging process. At the assembly point, based on pre-set assembly drawings, the units (such as the skeleton, floral fillers, and decorative accessories) are physically assembled, and overall quality is inspected (e.g., checking stability and color matching). Finally, based on the emotional context of the order (e.g., "wedding centerpiece"), final packaging is performed (e.g., using semi-transparent frosted paper and champagne-colored ribbon). Images of the finished packaged product and the tracking number are recorded. Finally, the system automatically integrates the initial floral skill task chain information set, the dynamic node attribute mapping scheme set during the execution process, the detailed tracking logs of each unit, all quality acceptance certificates, and the final packaging record and finished product image according to timeline and logical relationship, to generate a structured, queryable and auditable full-chain collaborative report of floral orders.

[0073] The method provided in this embodiment constructs a digitally transparent link throughout the order lifecycle, enabling full visibility of the production process, status tracking, and quality traceability, which greatly improves the reliability of the collaborative network, customer trust, and problem diagnosis efficiency.

[0074] In some embodiments, based on the physiological state requirements of the floral materials in each independent allocation unit and the physical microenvironment data of the nodes along the route, a virtual preservation corridor across nodes is dynamically synthesized, and its floral vitality tolerance threshold is preset; during the production and circulation process, the floral vitality is monitored in real time, and when the predicted data deviates from the floral vitality tolerance threshold, an optimization instruction including adjusting transportation parameters or changing transit nodes is actively triggered; before final delivery, the final scene adaptive encapsulation is triggered based on the actual vitality of the floral work and the emotional expression scenario of the order.

[0075] A virtual preservation corridor can be a continuous data curve dynamically constructed in digital space, representing the theoretical environmental experience of flowers, based on the physiological state requirements of each independent allocation unit in the current order (e.g., a unit requires humidity >65%) and the node physical microenvironment data of each optimal execution node it plans to pass through (e.g., node A humidity 70%, node B humidity 60%, transport vehicle humidity 55%). The floral vitality tolerance threshold can be a safe floating boundary for key physiological parameters (e.g., tissue water content, cell damage rate) set based on the virtual preservation corridor to ensure the survival and appearance of flowers. Floral vitality characteristics can be key indicators used to quantify the physiological state of semi-finished or finished floral products, such as petal cell turgor pressure (indirectly reflecting water content), stem incision microbial activity, ethylene release rate, etc. Optimization commands can be digital commands proactively issued to relevant links (e.g., transport vehicle control system, transfer nodes) to adjust environmental parameters or change the execution plan when the system determines through a predictive model that the floral vitality characteristics will deviate from their tolerance threshold in subsequent nodes or transportation stages. Scene-adaptive packaging can be achieved before final delivery by dynamically adjusting the final packaging materials, auxiliary decorations (such as cards, string lights), and even the content of the blessing message based on the actual life state of the floral artwork (such as the degree of flower opening) and the emotional expression scene of the order (such as "romantic proposal"). This ensures that the final delivery is not only physically complete but also highly consistent with the scene requirements in terms of emotional presentation.

[0076] Specifically, traditional floral arrangement management often limits itself to logistics tracking (such as location and temperature), lacking the ability to accurately predict and proactively intervene in the evolution of the flowers' life state. This leads to two core risks: First, it cannot predict the cumulative stress damage caused to flowers by environmental differences across stages (such as moving from a high-humidity workshop to a dry transport vehicle). Often, flowers are only discovered to be implicitly dehydrated or rotten when they arrive at the final stage, which is too late. Second, the final packaging is rigid and uniform, unable to adapt to the actual state of the flowers (such as roses blooming unexpectedly early) and the emotional core of the order (such as flowers for a solemn funeral versus flowers for a joyful celebration), which may lead to a misalignment of emotional expression or a reduction in perceived value. This step aims to upgrade state tracking from "passive recording" to "proactive prediction and closed-loop control." The core implementation process is as follows: The system first synthesizes a virtual preservation corridor based on the physiological state requirements of the flowers in each independent allocation unit and the physical microenvironment data of the nodes along the route. For example, for a unit requiring "fresh bouquets," the humidity curve is required to smoothly transition from 70% at node A to 65% at node B, and key floral vital sign tolerance thresholds are set for this corridor (such as the relative water content of petals not being lower than 58%). During real-time monitoring of production and circulation, the system continuously acquires floral vital sign data and runs a predictive model. When the model predicts that the moisture content of the bouquet will drop below the 58% tolerance threshold after one hour in the next stage of transportation (because the vehicle humidity is only 50%), the system immediately and proactively triggers optimization instructions. For example, it instructs the transport vehicle to start the humidification module to increase the humidity to 60%, or it instructs the route to be changed to prioritize a transfer node that can provide "hydration and rest." All optimization instructions and their execution effects are recorded. Finally, during the delivery and packaging stage, the system initiates scenario-adaptive packaging: for example, if it detects that the actual flower opening rate is 90% (more open than the expected 80%), and the order scenario is "anniversary", it will automatically recommend and prompt the packaging staff to use more gorgeous glossy wrapping paper and attach a customized card with the message "Deepest Love", instead of using standard simple packaging.

[0077] The method provided in this embodiment constructs a prediction-based, cross-node proactive protection system for the life status of floral materials and a scene intelligent adaptation mechanism, realizing a leap from "environmental adaptation" to "state protection" and from "physical delivery" to "emotional delivery". It systematically reduces circulation losses and significantly improves the scene fit of the final delivery and customer experience.

[0078] In some embodiments, a basic contribution value is pre-set for each independent allocation unit in the floral skill task chain information set. The basic contribution value is calculated based on the complexity of its matched core skill tag and the expected standard working hours. The basic contribution value is weighted and corrected according to the actual execution quality of each independent allocation unit under the quality node acceptance standard to generate the actual contribution value of the franchise node. The quality basis comes from the end customer feedback. The corrected actual contribution values ​​of all independent allocation units in the order are summarized, and the total revenue of the order is dynamically divided according to the proportion of the actual contribution value of each unit in the total contribution value to generate the franchise node capability profile. The franchise node capability profile represents the quantitative indicators of the node's historical performance and reliability under the corresponding skill tag. It is used to provide historical performance basis for selecting the optimal execution node from the franchise network when generating a new floral skill task chain information set for subsequent orders.

[0079] The basic contribution value can be a pre-set quantitative score representing the theoretical contribution of each independent allocation unit in the floral skill task chain information set before task execution. The actual contribution value of a franchise node can be the final contribution score generated after weighting and correcting the basic contribution value based on the actual execution quality of the independent allocation unit under the quality node acceptance standard. Dynamic segmentation can be the process by which the system summarizes the actual contribution values ​​of all independent allocation units in an order after quality correction, and calculates and allocates the total revenue (such as total turnover) of the order based on the proportion of each unit's actual contribution value in the total actual contribution value of the order. The franchise node capability profile can be a dynamically updated digital profile used to represent the quantitative indicators of the historical performance and reliability of a franchise node under a specific core skill tag. The basis for historical performance can be the quantitative historical performance data from the franchise node capability profile that the system additionally calls when selecting the optimal execution node for a unit in a subsequent new order floral skill task chain information set, in addition to considering immediate factors such as skill matching, real-time load, and environment.

[0080] Specifically, traditional franchise network revenue distribution models often employ simple proportional sharing (such as fixed commission) or average distribution based on the number of participating nodes. This static model has serious flaws: it completely ignores the significant differences in skill complexity and working hours among different task units (for example, a 6-hour architecture project is equivalent to a 1-hour simple bouquet wrapping project), and it fails to effectively reflect the actual performance quality of nodes (for example, a node that consistently receives positive customer feedback receives the same reward as a node that frequently generates complaints), leading to a "free-rider" phenomenon. This severely dampens the enthusiasm of high-performing nodes and indirectly encourages the inertia of low-performing nodes, causing a vicious cycle in the overall network quality. To establish a positive incentive loop of "distribution according to work, and rewarding excellence," this step introduces a dynamic quantitative distribution system deeply linked to task value and performance quality. The core implementation process is as follows: First, when the order is broken down to generate a floral skill task chain information set, the system calculates a basic contribution value for each independently assigned unit. For example, a unit requiring the tags "Spiral Technique (Advanced)" and "Color Gradient Design" has complexity coefficients of 0.7 and 0.5 respectively. After weighting, the overall complexity coefficient is 0.6, which is then multiplied by the expected standard working time of 3 hours to obtain a basic contribution value of 1.8. After the order is completed, the system calculates a quality correction coefficient (e.g., a coefficient of 1.2 for excellent performance) based on the achievement of each unit's quality node acceptance standards (such as completion rate and process precision) and the final customer feedback (e.g., the customer specifically praised the color scheme of the unit in the evaluation). The basic contribution value of 1.8 is multiplied by this coefficient to obtain the actual contribution value of the node to this unit, which is 2.16. The system summarizes the actual contribution values ​​of all units in the order (assuming a total of 10.8). If the 2.16 of a certain unit accounts for 20%, it is dynamically divided, and the execution node corresponding to that unit receives 20% of the total order revenue. Meanwhile, the node's performance in this task under the tags "Spiral Technique (Advanced)" and "Color Gradient Design" (quality coefficient 1.2, revenue share 20%) was recorded and updated in its affiliated node capability profile. When new tasks requiring similar skill tags arise in the future, the high-performance data accumulated in this profile will serve as strong historical performance evidence, significantly increasing the node's priority in the selection process.

[0081] The method provided in this embodiment constructs a precise incentive and capability evaluation system that quantifies value, links quality, and dynamically allocates resources. This fundamentally aligns node revenue with their actual contribution and capability level, driving the franchise network to spontaneously evolve towards high quality and professionalism, and continuously optimizing resource matching efficiency.

[0082] Figure 3 This application provides a schematic diagram of the structure of a regional dynamic deployment system for a flower delivery franchise network, as shown in one embodiment. Figure 3As shown, the regional dynamic deployment system 300 of the flower delivery franchise network in this embodiment includes: a task chain information module 301, a node attribute mapping module 302, a collaborative reporting module 303, and a re-evaluation information module 304.

[0083] The task chain information module 301 is used to obtain a floral order demand dataset, and based on the floral order demand dataset, to perform biological analysis and task decomposition of multi-dimensional demand features of floral tasks, and generate a floral skill task chain information set.

[0084] The node attribute mapping module 302 is used to dynamically match the execution node with the skill tag based on the floral skill task chain information set, and trigger the targeted reconstruction and environmental adaptation of the franchise store function accordingly, and generate a set of dynamic node attribute mapping schemes to drive node specialization and process standardization.

[0085] The collaborative reporting module 303 is used to perform relay tracking of the life status of semi-finished products and final integrity encapsulation based on the dynamic node attribute mapping scheme set, and generate and output a collaborative report of the entire floral order chain.

[0086] Optionally, the task chain information module 301, during the generation process based on the floral art skill task chain information set, is specifically used for: the floral art order demand dataset including the physiological state requirements of floral materials, the sequence of craft techniques, the emotional expression scenarios, and the spatiotemporal delivery constraints; based on the floral art order demand dataset, according to the progressive construction logic defined by the spatial structure and functional hierarchy of the floral art works, decomposing complex floral art orders into a set of floral art sub-tasks with strict task distinction relationships; based on the set of floral art sub-tasks, assigning a corresponding standardized task execution package to each floral art sub-task, thereby integrating all the standardized task execution packages to generate the floral art skill task chain information set.

[0087] Optionally, the task chain information module 301, during the construction process based on the floral art sub-task set, is specifically used for: parsing out multiple independent floral art work units contained in the order based on the sequence of craft techniques and the emotional expression scenario, and determining the type and style characteristics of each independent floral art work unit; for each independent floral art work unit, combining its physiological requirements for flower materials and its spatiotemporal delivery constraints, matching one or more core skill tags and corresponding standard working time expectations from a preset floral art work requirement mapping table; using each independent floral art work unit as a benchmark, and combining its matched core skill tags, decomposing it into independent allocation units that can be executed by franchise stores with different specialties; and organizing all the independent allocation units into the floral art sub-task set with networked dependencies based on their logical relationships, material flow relationships, and standard working time expectations in the original order.

[0088] Optionally, when the task chain information module 301 is based on the standardized task execution package, it is specifically used for: the standardized task execution package encapsulates the execution configuration data of each independent floral arrangement unit, including: a florist skill tag set, derived from the core skill tags matched by the corresponding independent allocation unit, used to identify the professional skill combination required to perform this task; a precise material list, generated by matching preset material configuration rules according to the type, style characteristics and physiological state requirements of the independent allocation unit; and quality node acceptance criteria, defined according to the position and process characteristics of the independent allocation unit in the networked dependency relationship.

[0089] Optionally, the node attribute mapping module 302, during the generation process based on the dynamic node attribute mapping scheme set, is specifically used for: based on the florist skill tag set and spatiotemporal requirements encapsulated in each of the independent allocation units, and according to the skill tag matching degree, the node's current workload, and the node's physical micro-environment data, selecting the optimal execution node from the franchise network; sending a reconstruction instruction to the optimal execution node, triggering its operation interface, material permissions, and work process to switch to a special execution mode matching the assigned independent allocation unit; and encapsulating the matching relationship, reconstruction instruction, and switching result between each optimal execution node and the assigned independent allocation unit according to the special execution mode after the node completes reconstruction, thereby generating the dynamic node attribute mapping scheme set.

[0090] Optionally, when the node attribute mapping module 302 selects the optimal execution node from the franchise network, it is specifically used for: screening based on the skill tag matching degree: prioritizing matching franchise nodes whose registered skill tags are completely consistent with the florist skill tag set encapsulated by the independent allocation unit, and which have recently had successful execution records of the same independent allocation unit; screening based on the node's current workload: evaluating the workload saturation of candidate nodes within the execution period specified by the spatiotemporal requirements of the independent allocation unit, and selecting franchise nodes with sufficient capacity margin; verifying based on the node's physical microenvironment data: comparing the real-time physical environment parameters of the candidate franchise nodes with the preset physical microenvironment requirements of the independent allocation unit, and verifying whether their operating space size and environmental temperature and humidity control equipment are complete and up to standard; and comprehensively evaluating and ranking the candidate franchise nodes based on the screening and verification results, and selecting the node with the best overall performance as the optimal execution node.

[0091] Optionally, the collaborative reporting module 303, in the process of generating the full-link collaborative report for the floral order, is specifically used for: based on the dynamic node attribute mapping scheme set, performing relay tracking of the semi-finished product life status of the execution process of each independent allocation unit at its assigned optimal execution node; after all independent allocation units have completed execution and passed quality node acceptance, performing final summarization, inspection, and packaging of the semi-finished products of all units to complete the final integrity encapsulation; integrating the floral skill task chain information set, the dynamic node attribute mapping scheme set, and the tracking data and encapsulation results of each link to generate the full-link collaborative report for the floral order that includes task decomposition, node matching, process tracking, and quality confirmation.

[0092] Optionally, when the collaborative reporting module 303 tracks the life status of semi-finished products, it is specifically used to: dynamically synthesize a virtual preservation corridor across nodes based on the physiological state requirements of the floral materials in each independent allocation unit and the physical microenvironment data of the nodes through which the corridor passes, and preset its floral life characteristic tolerance threshold; during the production and circulation process, monitor the floral life characteristics in real time, and when the predicted data deviates from the floral life characteristic tolerance threshold, actively trigger an optimization instruction including adjusting transportation parameters or changing transit nodes; before final delivery, trigger the final scene adaptive encapsulation based on the actual life status of the floral work and the emotional expression scenario of the order.

[0093] Optionally, the system further includes the re-evaluation information module 304, specifically used for: presetting a basic contribution value for each independent allocation unit in the floral skill task chain information set, the basic contribution value being calculated based on the complexity of its matched core skill tag and the expected standard working hours; weighting and correcting the basic contribution value according to the actual execution quality of each independent allocation unit under the quality node acceptance standard, generating the actual contribution value of the franchise node, the quality basis being derived from end-customer feedback; summarizing the corrected actual contribution values ​​of all independent allocation units in the order, and dynamically dividing the total order revenue according to the proportion of each unit's actual contribution value in the total contribution value, generating a franchise node capability profile; the franchise node capability profile characterizes the quantitative indicators of the node's historical performance and reliability under the corresponding skill tag, used to provide historical performance basis for selecting the optimal execution node from the franchise network when generating a new floral skill task chain information set for subsequent orders.

[0094] The system in this embodiment can be used to execute the methods of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

Claims

1. A method for dynamic regional deployment of a flower delivery franchise network, characterized in that, include: Obtain a dataset of floral order requirements, extract the physiological state requirements of floral materials, the sequence of craft techniques, the emotional expression scenarios, and the spatiotemporal delivery constraints, and decompose complex floral orders into tasks based on the progressive construction logic defined by the spatial structure and functional hierarchy of floral works, generating a set of floral skill task chain information. The process of breaking down complex floral orders into tasks and generating a floral skill task chain information set includes: The floral order demand dataset includes requirements for the physiological state of floral materials, sequences of craft techniques, emotional expression scenarios, and spatiotemporal delivery constraints. After extracting the physiological requirements of the floral materials, the sequence of techniques, the emotional expression scenarios, and the spatiotemporal delivery constraints, the complex floral order is decomposed into a set of floral sub-tasks with strict task distinctions based on the progressive construction logic defined by the spatial structure and functional hierarchy of the floral artwork. Each floral sub-task is assigned a corresponding standardized task execution package, and all standardized task execution packages are integrated to generate a floral skill task chain information set. The standardized task execution package encapsulates the execution configuration data of the corresponding floral art sub-task. The execution configuration data includes at least a set of skill tags for identifying the combination of professional skills required to execute the floral art sub-task. Based on the aforementioned floral art skill task chain information set, dynamic matching of execution nodes and skill tags is performed, thereby triggering targeted reconstruction and environmental adaptation of franchise store functions. This generates a set of dynamic node attribute mapping schemes to drive node specialization and process standardization, including: Based on the skill tag set and spatiotemporal requirements encapsulated in each standardized task execution package in the floral skills task chain information set, the optimal execution node is selected from the franchise network according to the skill tag matching degree, the current workload of the node, and the physical microenvironment data of the node. And send a refactoring instruction to the optimal execution node to trigger its operation interface, material permissions and work process to switch to a special execution mode that matches the assigned floral sub-task; Then, based on the specific execution mode after the node is reconstructed, the matching relationship between the optimal execution node and the assigned floral sub-task, the reconstruction instructions and the switching results are encapsulated to generate a dynamic node attribute mapping scheme set; The targeted reconstruction and environment adaptation are specific instruction sets issued by the system to the target node after matching, aiming to temporarily adapt its physical environment or workflow to the needs of a specific task. The dynamic node attribute mapping scheme set is a complete set of "task-node-adaptation requirements" correspondence schemes formed after the skill task chain of the entire order is matched; Based on the dynamic node attribute mapping scheme set, the life status of semi-finished products is tracked and the final integrity is encapsulated, generating and outputting a full-chain collaborative report for floral orders; Semi-finished product life status tracking involves continuous and seamless monitoring and data recording of the core vital signs of semi-finished floral materials or floral arrangements flowing between different nodes during the order execution process. The core vital signs include water content, cell activity, and morphological retention. Complete packaging is the final delivery step after all production stages of an order are completed, based on the original emotional expression scenario of the order and the real-time status of the final work, selecting and executing the most matching packaging, supplementary cards, and presentation methods.

2. The method according to claim 1, characterized in that, The process of constructing the set of floral design subtasks includes: Based on the sequence of techniques and the emotional expression scenario, the multiple independent floral art pieces contained in the order are analyzed, and the type and style characteristics of each independent floral art piece are determined. For each independent floral arrangement unit, based on the physiological requirements of the floral materials and the spatiotemporal delivery constraints, one or more core skill tags and corresponding standard working hours expected values ​​are matched from the preset floral arrangement requirement mapping table to complete the work. Based on each individual floral arrangement unit, and combined with its corresponding core skill tag, it is broken down into independent allocation units that can be executed by franchise stores with different specialties. All the independent allocation units are organized into a set of floral subtasks with networked dependencies, based on their logical relationships in the original order, material flow relationships, and the expected standard working hours.

3. The method according to claim 2, characterized in that, The standardized task execution package includes: The standardized task execution package encapsulates the execution configuration data for each of the independent floral arrangement units, including: The florist skill tag set is derived from the core skill tags matched by the corresponding independent allocation unit, and is used to identify the combination of professional skills required to perform this task; An accurate bill of materials is generated by matching preset material configuration rules based on the type and style characteristics of the independent allocation unit and the physiological state requirements of the flowers. The quality node acceptance criteria are defined based on the position of the independent allocation unit in the networked dependency relationship and its process characteristics.

4. The method according to claim 3, characterized in that, The process of generating the dynamic node attribute mapping scheme set includes: Based on the florist skill tag set and spatiotemporal requirements encapsulated in each of the independent allocation units, the optimal execution node is selected from the franchise network according to the skill tag matching degree, the current workload of the node, and the physical microenvironment data of the node. Send a reconfiguration command to the optimal execution node to trigger its operation interface, material permissions and work process to switch to a special execution mode that matches the allocated independent allocation unit; Based on the special execution mode after the node has been reconstructed, the matching relationship, reconstruction instructions and switching results between each optimal execution node and the allocated independent allocation unit are encapsulated to generate the dynamic node attribute mapping scheme set.

5. The method according to claim 4, characterized in that, The step of selecting the optimal execution node from the franchise network includes: The selection is based on the skill tag matching degree: priority is given to matching franchise nodes whose registered skill tags are completely consistent with the florist skill tag set encapsulated by the independent allocation unit, and which have recently had successful execution records of the same independent allocation unit. Screening is performed based on the current workload of the nodes: the workload saturation of candidate nodes during the execution period specified by the time and space requirements of the independent allocation unit is evaluated, and the affiliated nodes with sufficient capacity margin are screened out. Verification is performed based on the physical microenvironment data of the nodes: the real-time physical environment parameters of the candidate franchise nodes are compared with the preset physical microenvironment requirements of the independent allocation unit to verify whether their operating space size and environmental temperature and humidity control equipment are complete and meet the standards. Based on the comprehensive screening and verification results, the candidate franchise nodes are scored and ranked, and the node with the best overall score is selected as the optimal execution node.

6. The method according to claim 5, characterized in that, The process of generating the end-to-end collaborative report for floral orders includes: Based on the dynamic node attribute mapping scheme set, the semi-finished life state relay tracking is performed on the execution process of each independent allocation unit at its allocated optimal execution node. After all independent allocation units have been completed and quality checkpoints have been accepted, the semi-finished products of all units are finally summarized, inspected and packaged to complete the final integrity packaging. By integrating the floral art skill task chain information set, the dynamic node attribute mapping scheme set, and the tracking data and encapsulation results of each stage, a full-chain collaborative report of the floral art order is generated, which includes task decomposition, node matching, process tracking, and quality confirmation.

7. The method according to claim 6, characterized in that, The process of tracking the life cycle status of semi-finished products includes: Based on the physiological state requirements of the flowers in each independent allocation unit and the physical microenvironment data of the nodes through which they pass, a virtual preservation corridor across nodes is dynamically synthesized, and its floral vitality tolerance threshold is preset. During the production and distribution process, the vital signs of the floral art are monitored in real time, and when the predicted data deviates from the tolerance threshold of the vital signs of the floral art, an optimization command including adjusting transportation parameters or changing transit nodes is actively triggered. Before final delivery, based on the actual life state of the floral arrangement and the emotional expression of the order, the final scene adaptive encapsulation is triggered. Scene-adaptive packaging is a process where, before final delivery, the system dynamically adjusts the final packaging materials, auxiliary decorations, and even the content of the blessing message based on the actual life state of the floral arrangement and the emotional expression of the order.

8. The method according to claim 7, characterized in that, The method further includes: A basic contribution value is preset for each independent allocation unit in the floral skill task chain information set. The basic contribution value is calculated based on the complexity of the core skill tag it matches and the expected standard working hours. Based on the actual performance quality of each independent allocation unit under the quality node acceptance criteria, the basic contribution value is weighted and corrected to generate the actual contribution value of the franchise node. The quality basis comes from the end customer feedback. The actual contribution values ​​of all the independent allocation units in the order are summarized after correction, and the total revenue of the order is dynamically divided according to the proportion of the actual contribution value of each unit in the total contribution value, generating a franchise node capability profile; The capability profile of the franchise node represents a quantitative indicator of the node's historical performance and reliability under the corresponding skill tag. It is used to provide a basis for selecting the optimal execution node from the franchise network when generating a new set of floral skill task chain information for subsequent orders.

9. A regional dynamic deployment system for a flower delivery franchise network, characterized in that, The method applied to any one of claims 1-8 includes: The task chain information module is used to obtain the floral order demand dataset, extract the physiological state requirements of flowers, the sequence of craft techniques, the emotional expression scenarios, and the spatiotemporal delivery constraints, and decompose complex floral orders into tasks based on the progressive construction logic defined by the spatial structure and functional hierarchy of the floral works, generating a floral skill task chain information set. The node attribute mapping module is used to dynamically match execution nodes with skill tags based on the floral skill task chain information set, and trigger targeted reconstruction and environmental adaptation of franchise store functions accordingly, generating a set of dynamic node attribute mapping schemes to drive node specialization and process standardization. The collaborative reporting module is used to perform relay tracking of the life status of semi-finished products and final integrity encapsulation based on the dynamic node attribute mapping scheme set, and generate and output a collaborative report of the entire floral order chain.

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