Garden material supply chain collaborative management system based on cloud computing

Abstract

The invention relates to the technical field of supply chain management, and discloses a cloud computing-based garden material supply chain collaborative management system, which is characterized in that a dynamic life cycle material ownership unit is created for each garden material, and intelligent matching of a long-term contract is realized by utilizing a dynamic health index and growth trend prediction of the dynamic life cycle material ownership unit; the risk monitoring engine actively monitors the health condition of the signed material, and once the health condition is lower than a preset risk threshold value, a risk event is triggered; a global substitute search module automatically searches qualified substitutes in a supplier inventory and project excess material circulation pool; and after confirmation of the purchaser, the contract recombination module completes subject matter change through an atomicity transaction. Through full-life-cycle dynamic tracking and active risk hedging of living materials, the performance guarantee rate of a long-term contract is remarkably improved, value reutilization of project excess materials is realized, and the stability and efficiency of a supply chain are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to a garden material supply chain collaborative management system based on cloud computing. Background Art

[0002] In landscaping projects, forward contracts are a common business model for ensuring the availability of landscaping materials of specific specifications at a specific time in the future. However, existing supply chain management methods, especially when dealing with living assets such as trees and seedlings, have inherent limitations.

[0003] Current management systems often treat garden materials as ordinary commodities, managing them with static information, recording only the product name, source, and initial specifications upon entry. This approach completely ignores the most critical characteristic of living assets: their dynamic lifespan. In the months or even longer between contract signing and future delivery, the health of the materials may deteriorate, and their growth rate may fall short of expectations. However, these critical dynamic changes are not effectively tracked or reflected in existing systems. This results in significant information asymmetry and contract performance uncertainty for purchasers throughout the contract lifecycle.

[0004] When performance risks actually occur, such as when materials are discovered to be dead or substandard just before delivery, existing response measures are often passive and inefficient. The process of finding alternatives usually relies on manual communication, which is time-consuming and labor-intensive, and is limited to the scattered inventory of individual suppliers, which can easily lead to project delays and economic losses. In addition, the existing system generally lacks an effective integration mechanism for potential resources such as project surplus materials. These valuable materials are often idle or wasted due to information silos, and fail to enter the supply chain to realize the value cycle, further exacerbating the inefficiency of resource allocation. Therefore, existing technologies have obvious deficiencies in dynamic monitoring of living assets, proactive risk management, and global resource integration, making it difficult to guarantee the reliability of forward contracts, which restricts the efficiency and resilience of the entire supply chain. Summary of the Invention

[0005] The existing supply chain management of garden materials, especially the management of living plant materials, has the following technical problems: First, material information is usually static data and cannot reflect the dynamic changes of living materials such as growth and health during the inventory cycle, resulting in information distortion; second, there is a time mismatch between project demand and material supply, and forward procurement lacks a reliable performance guarantee mechanism, resulting in high contract performance risks; finally, the remaining materials generated after project completion are difficult to be effectively managed and reused, resulting in waste of resources.

[0006] In order to solve the above technical problems, the present invention provides a garden material supply chain collaborative management system based on cloud computing.

[0007] The system includes: A dynamic lifecycle material ownership unit generation module is used to create a corresponding dynamic lifecycle material ownership unit for one or a batch of garden materials. The dynamic lifecycle material ownership unit includes a static attribute set, a dynamic attribute set, and an ownership and contract attribute set; A forward contract management module, configured to match the forecast specifications of the dynamic lifecycle material ownership unit with the forward demand of the purchaser to generate a forward contract, set a contract risk threshold in the contract, and lock the status of the dynamic lifecycle material ownership unit; a risk monitoring engine, configured to continuously monitor the dynamic health index in the dynamic attribute set of the dynamic lifecycle material ownership unit in a locked state, and trigger a risk event when the dynamic health index is lower than the contract risk threshold; The global alternative search module is used to automatically search for one or more qualified alternative dynamic life cycle material ownership units when the risk event is triggered.

[0008] Preferably, the dynamic attribute set of the dynamic lifecycle material ownership unit includes: The dynamic health index is used to quantify the current health status of the garden material; and The growth trend prediction data is used to predict the physical specifications of the garden material at a future time point based on a preset growth model function.

[0009] In a specific embodiment, the system further includes a dynamic health index evaluation module. The dynamic health index evaluation module is configured to: collecting raw measurement values ​​of a plurality of vital sign parameters associated with the garden material; processing the raw measurement values ​​through a normalization function; The normalized multiple parameter values ​​are weighted and summed to calculate the dynamic health index, which is calculated as follows: ; in, For time point The health index score, is the total number of parameters involved in the evaluation, For the The preset weight coefficients of the parameters, is the normalization function, For the time point The collected The raw measured values ​​of the parameters.

[0010] In a specific embodiment, the forward contract management module uses the growth trend forecast data to calculate the forecast specifications of the dynamic lifecycle material ownership unit at the delivery time of the forward demand, and matches the forward demand based on the forecast specifications.

[0011] Preferably, the search scope of the global alternative search module is configured to include: Dynamic lifecycle material ownership units in a usable state held by one or more suppliers; and A dynamic lifecycle material ownership unit stored in the project residual material recycling pool.

[0012] In a specific embodiment, the dynamic lifecycle material ownership unit generation module is further configured to: Receive the remaining material information of the completed project, create a new dynamic life cycle material ownership unit for the remaining material, initialize its ownership and status information and store it in the project remaining material circulation pool.

[0013] In a specific embodiment, the system further includes a utility evaluation module. The utility evaluation module is configured to calculate a utility score for each of the alternative dynamic lifecycle material ownership units when the global alternative search module searches for multiple qualified alternative dynamic lifecycle material ownership units, and provide a decision ranking for the purchaser based on the utility score.

[0014] Furthermore, the parameters used by the utility evaluation module to calculate the utility score include: The similarity in specifications between the replacement dynamic lifecycle material ownership unit and the original dynamic lifecycle material ownership unit; The current dynamic health index of the alternative dynamic life cycle material ownership unit; and The estimated transportation cost of delivering the alternative dynamic lifecycle material title unit to the delivery location.

[0015] In a specific embodiment, the system further includes a contract restructuring module. The contract restructuring module is configured to automatically send a new transaction offer to the current owner of the alternative dynamic lifecycle material ownership unit after the purchaser confirms the selection from the alternatives provided by the global alternative search module, and guide the completion of the subject matter change of the forward contract.

[0016] Preferably, the ownership and contract attribute set of the dynamic lifecycle material ownership unit includes: Current owner ID; The current status identifier of the dynamic lifecycle material ownership unit, where the current status identifier is used to indicate whether it is available, locked, or in transit; and If the current status is identified as locked, the associated forward contract identifier is also included.

[0017] The present invention provides a cloud computing-based collaborative management system for the supply chain of garden materials. It has the following beneficial effects: 1. This invention provides a dynamic digital representation of garden materials by constructing a dynamic lifecycle material ownership unit containing a dynamic attribute set. The dynamic health index and growth trend prediction data in this dynamic attribute set can reflect the life state and specification trends of materials (especially living plants) over time. This enables the system to manage and make decisions based on real-time data, overcoming the information distortion caused by traditional static data management methods.

[0018] 2. This invention establishes a mechanism for automatically identifying and addressing contract risks by implementing a risk monitoring engine and a global alternative search module. The risk monitoring engine continuously monitors the status of locked materials based on preset contract risk thresholds. Once a risk event is identified, the global alternative search module automatically initiates the search for alternatives. This mechanism transforms manual passive response into proactive system processing, reducing the uncertainty of forward contract performance caused by material status changes.

[0019] 3. This invention achieves resource recycling at the end of the supply chain by establishing a project surplus material recycling pool and incorporating it into the search scope of the global alternative search module. This design eliminates the need for isolated, sunk assets from surplus materials generated by projects and instead integrates them back into the overall supply chain system as effective inventory resources. When new procurement needs or contract risk events arise, these surplus materials can be accessed by the system, reducing resource waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of the functional module structure of a garden material supply chain collaborative management system according to one embodiment of the present invention; Figure 2 This is a schematic diagram of the data structure of a dynamic lifecycle material ownership unit according to an embodiment of the present invention; Figure 3 A schematic diagram of a dynamic data processing flow according to an embodiment of the present invention; Figure 4 A schematic diagram of the forward contract management process according to an embodiment of the present invention; Figure 5 A schematic diagram of the risk monitoring engine workflow according to an embodiment of the present invention; Figure 6 A schematic diagram of a global alternative search process according to an embodiment of the present invention; Figure 7A schematic diagram of a contract restructuring process according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the process of recycling project waste materials according to an embodiment of the present invention.

[0021] Among them, 10. Dynamic life cycle material ownership unit generation module; 20. Forward contract management module; 30. Risk monitoring engine; 40. Global alternative search module; 50. Data processing and evaluation unit; 60. Data storage unit; 70. Utility evaluation module; 80. Contract reorganization module; 210. Static attribute set; 220. Dynamic attribute set; 230. Ownership and contract attribute set. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] Refer to the attached Figure 1 , Figure 1 This figure illustrates the functional module architecture of a collaborative management system for a gardening material supply chain according to one embodiment of the present invention. The system can be deployed on one or more cloud servers. Its physical deployment architecture includes application servers and a data storage unit. The application servers host the system's various functional modules, while the data storage unit persistently stores the data required for system operation.

[0024] The system provided by the embodiment of the present invention includes multiple functional modules, and these modules perform data exchange and communication through preset interfaces.

[0025] In one embodiment, the system includes a dynamic lifecycle material ownership unit generation module 10, a forward contract management module 20, a risk monitoring engine 30, a global alternative search module 40, a data processing and evaluation module 50, and a data storage unit 60. In a preferred embodiment, the system also includes a utility evaluation module 70 and a contract restructuring module 80 to provide more intelligent decision support and automated contract modification capabilities.

[0026] The dynamic lifecycle material ownership unit generation module 10 creates a corresponding dynamic lifecycle material ownership unit (DLMEU) for an item or batch of garden materials. A user terminal (such as a supplier's computer or mobile device) submits the material's initial static data to the application server via a network interface. The application server invokes the dynamic lifecycle material ownership unit generation module 10, generates a DLMEU data object containing a unique identifier, and writes the object to the data storage unit 60.

[0027] The forward contract management module 20 is connected to the data storage unit 60 and is used to read DLMEU data. Upon receiving a forward demand request from a purchaser's user terminal, the forward contract management module 20 executes a matching algorithm to select DLMEUs that meet the request. Upon user confirmation, the forward contract management module 20 generates an electronic forward contract, writes the contract details to the data storage unit 60, updates the status of the selected DLMEU to locked, and sets a contract risk threshold for the contract.

[0028] The risk monitoring engine 30 is configured as a backend service. It queries the data storage unit 60 at preset intervals (e.g., once an hour) to obtain the dynamic attribute set 220 of all locked DLMEUs. The risk monitoring engine 30 compares the obtained real-time dynamic health index with the contract risk threshold set in the corresponding contract. When the dynamic health index of a DLMEU is detected to be lower than its contract risk threshold, the risk monitoring engine 30 triggers a risk event and sends a control signal containing the original contract requirements to the global alternative search module 40.

[0029] The global alternative search module 40 is activated upon receiving a control signal from the risk monitoring engine 30. Based on the original contract requirements contained in the signal, it initiates a search query to the data storage unit 60. This query targets all available DLMEUs in the data storage unit 60, including supplier inventory and the project surplus recycling pool. The global alternative search module 40 returns a list of one or more qualified alternative DLMEUs found to the original contract's purchaser's user terminal via the application server.

[0030] The data processing and evaluation unit 50 integrates a dynamic health index assessment module and a growth trend prediction module. It receives raw data from IoT devices or human input, calculates a dynamic health index, predicts growth trends, and then updates the calculated results to the dynamic attribute set of the corresponding DLMEU in the data storage unit 60. The forward contract management module 20 invokes the growth trend prediction function of the data processing and evaluation unit 50 during matching.

[0031] The data storage unit 60 can be composed of one or more relational databases, non-relational databases, or file storage systems. It is configured to store all DLMEU data objects, user information, forward contract details, and system operation logs. All functional modules read and write to the data storage unit 60 using standard database connection protocols.

[0032] In a preferred embodiment, the utility evaluation module 70 receives the list of qualified alternatives provided by the global alternative search module 40 and calculates a quantitative comprehensive utility score for each alternative. This score can be weighted based on multiple dimensions, such as specification similarity, health status, and transportation cost. Its function is to provide purchasers with a data-driven, organized decision-making reference to assist them in selecting the optimal option from multiple potential alternatives.

[0033] In a preferred embodiment, once the purchaser selects and confirms an item from the list of alternatives, the contract restructuring module 80 is activated, executing an atomic database transaction to securely and consistently modify the contract subject matter. This includes releasing the lock between the original item and the contract, binding the newly selected item to the contract, and updating the contract details. This module ensures automation and data consistency during the contract modification process.

[0034] Refer to the attached Figure 2 , Figure 2 This is a schematic diagram of the data structure of a Dynamic Lifecycle Material Ownership Unit (DLMEU) according to one embodiment of the present invention. A DLMEU is a standardized data object used in the system to uniquely map and manage an item or batch of garden materials. The following details the composition of the DLMEU and its processing within the system.

[0035] The creation and initialization of DLMEU is performed by the dynamic lifecycle material ownership unit generation module 10. When an authorized user (for example, a seedling supplier) accesses the system through his or her user terminal, a material registration process can be initiated. The user submits the initial information of the new material through the graphical user interface. After receiving this information, the dynamic lifecycle material ownership unit generation module 10 first generates a globally unique identifier (UID) for the material. The UID can be generated by combining the server timestamp, supplier code, and serial number to ensure its uniqueness. Subsequently, the dynamic lifecycle material ownership unit generation module 10 assembles this UID and the initial information submitted by the user into a structured DLMEU data object and stores it in the data storage unit 60.

[0036] Refer to the attached Figure 2A DLMEU data object logically includes three attribute sets. The first is the static attribute set 210, which contains inherent information about the material that does not change over time. Specifically, the static attribute set 210 includes: uid, the aforementioned globally unique identifier; Category represents a material category, and its value is selected from a standardized material classification table preset in the data storage unit 60, such as "tree" or "ground cover"; Species represents a specific species or product name, such as "Ginkgo"; origin, which records the source or manufacturer information of the material; initialSpec, which records the initial physical specifications of the material when it is registered. This field is stored in a structured data format (such as JSON) and contains multiple measurement key-value pairs, such as {"height_cm": 300, "trunk_diameter_mm": 50}; creationTime, records the exact timestamp when the DLMEU object was created.

[0037] The second is the dynamic attribute set 220, which contains the state information of the material that changes dynamically over time and is periodically calculated and updated by the data processing and evaluation unit 50 in the system. Specifically, the dynamic attribute set 220 includes: healthIndex is a floating point value used to quantify the current overall health status of the living plant; growthPrediction stores future specification data generated by the growth trend prediction model. This field can be stored as a set of time series data, where each data point contains a future timestamp and the corresponding predicted specification vector; mediaLog stores one or more uniform resource locators (URLs) pointing to multimedia files. These files (such as images and videos) record the form of the material at different points in time. The files themselves can be stored in an independent distributed file system; lastUpdateTime records the timestamp of the last update of the dynamic attribute set 220.

[0038] The third is the ownership and contract attribute set 230, which records the ownership, flow status and transaction information of the material. Specifically, the ownership and contract attribute set 230 includes: currentOwner, which records the identifier of the entity that currently holds ownership of the material; Status is an enumeration type status field used to manage the life cycle of DLMEU; contractID: When the status field value is LOCKED, this field is used to store the unique identifier of the associated forward contract; location, records the current geographical location coordinates of the material, which can be obtained and updated by GPS equipment or other positioning methods.

[0039] The state transitions in the status field follow a pre-defined state machine model to ensure the rigor of business logic. When a DLMEU is created, if the material is new, its initial state is set to AVAILABLE. If the material is a project remnant, its initial state is set to RECYCLED. Once the forward contract management module 20 successfully generates a forward contract for the DLMEU, its state changes from AVAILABLE or RECYCLED to LOCKED. If the contract is subsequently canceled or replaced due to the triggering of a risk hedging mechanism, its state reverts from LOCKED to AVAILABLE. During the contract fulfillment phase, when the material begins transportation, its state changes to IN_TRANSIT. Once the purchaser confirms receipt, the final state changes to DELIVERED. Once the state changes to DELIVERED, the DLMEU's data record is archived, and the system ceases subsequent monitoring and updates of its dynamic attribute set 220.

[0040] Refer to the attached Figure 3 , Figure 3 FIG2 is a schematic diagram of a dynamic data processing flow according to an embodiment of the present invention. The flow is executed by the data processing and evaluation unit 50 to collect, process and evaluate the dynamic data of garden materials associated with the DLMEU to generate and update the dynamic attribute set 220 of the DLMEU.

[0041] The data collection phase of this process supports multi-source heterogeneous data input. One input source is IoT sensor devices deployed in the garden material growth environment, such as soil moisture sensors, ambient light intensity sensors, and temperature sensors. These sensor devices periodically send the collected physical quantity data to a designated IoT gateway via wireless communication modules (such as NB-IoT or LoRa). The gateway then reports the data to the system's API interface via a standard data transmission protocol (such as MQTT). Another input source is manual entry by authorized users through user terminals. Users can submit observation data on material morphology (for example, leaf color rating, pest and disease level) and records of maintenance operations performed in mobile applications or web forms.

[0042] After receiving these raw data from different sources and formats, the system first performs standardization processing. For sensor data, the system parses its raw electrical signals or protocol data packets into standard physical units (for example, soil moisture is parsed into percentages, light intensity is parsed into μmol / m 2 / s). For manually entered qualitative descriptions, the system converts them into numerical values ​​using a pre-set mapping table (for example, "normal" leaf color is mapped to 1, and "slightly yellowed" is mapped to 0.5). All standardized data is timestamped and associated with the corresponding DLMEU unique identifier, forming a structured data record that is stored in the data storage unit 60.

[0043] The dynamic health index evaluation module within the data processing and evaluation unit 50 is used to perform the calculation of the health index. This module reads a set of the latest standardized data records associated with a DLMEU and applies the following evaluation model: ; In this model, Is the DLMEU at the time point Dynamic health index. is the total number of parameters involved in the evaluation. It's at the time The collected Standardized measurement of a parameter. It is The weight coefficients of the parameters are pre-configured in a weight configuration table of the data storage unit 60 according to the physiological characteristics of the species, and the sum of all the weight coefficients is 1.

[0044] Is a normalization function used to convert measurements in different physical units into Mapped to a uniform [0,1] interval. In a specific implementation, the maximum and minimum normalization method is used: ; in, and Respectively represent the lower and upper limits of the appropriate physiological range of the corresponding parameters of the species. These thresholds are also stored in the data storage unit 60 according to the species information. For some parameters whose higher values ​​represent worse conditions (such as pest and disease levels), reverse normalization is used. The value is eventually written to the healthIndex field in the dynamic attribute set 220 of the DLMEU.

[0045] The growth trend prediction module within the data processing and evaluation unit 50 is used to predict the physical specifications of the DLMEU at future points in time. This module, executed when called by the forward contract management module 20, uses a mathematical model consistent with the growth patterns of the species, such as the logistic growth function for single-dimensional specifications such as height and diameter at breast height: ; In this function, Is delivered in the future The forecast specification for a physical dimension (dim). is the maximum growth limit of the species in this dimension, which is obtained from the species database as a static parameter. It is a dynamically calculated growth rate coefficient, and its value is positively correlated with the recent average health index of the DLMEU. The module first obtains the historical health index data of the DLMEU from the data storage unit 60 to calculate the average value, and then calculates the current dynamic growth rate in combination with the basic growth rate parameter. Finally, the prediction specifications are substituted into the function to obtain the prediction specifications. The prediction specifications of all key dimensions are combined into a prediction specification vector and updated to the growthPrediction field.

[0046] Refer to the attached Figure 4 , Figure 4 FIG2 is a schematic diagram of a forward contract management process according to an embodiment of the present invention. The process is executed by the forward contract management module 20, which is used to respond to the forward demand of the purchaser and complete the matching and generation of forward contracts by working in conjunction with other modules in the system.

[0047] The process begins with the purchaser submitting a structured forward demand to the system through their user terminal. This demand is not free text, but a data object containing multiple predefined fields. Specifically, the data object includes: A future delivery time ; A target specification range , the range is a set of key-value pairs used to define the upper and lower limits of multiple physical measurements, for example {"height_cm_min": 450, "height_cm_max": 500, "trunk_diameter_mm_min": 80}; A minimum acceptable health index at the time of delivery ; One delivery location .

[0048] The demand data object is sent to the application server and received by the forward contract management module 20 .

[0049] After receiving the forward demand, the forward contract management module 20 performs the intelligent matching process. First, the forward contract management module 20 initiates a preliminary screening query to the data storage unit 60 to obtain all DLMEUs with the status of AVAILABLE or RECYCLED as candidate sets.

[0050] Then, for each DLMEU in the candidate set, the forward contract management module 20 calls the growth trend prediction function in the data processing and evaluation unit 50. This function predicts the growth trend of the DLMEU based on its current specifications, historical health data, and the time from the current time to the delivery time. The time span of , calculates its forecast specification vector at the delivery time The forward contract management module 20 verifies the specification matching of each DLMEU using the following conditions: ; in, represents a specific physical measurement (such as height), is the set of all physical measurements included in the requirements specification range, and are the acceptable lower and upper limits for the measure, is the predicted value of DLMEU on this measure. Only DLMEU that meets the above conditions are retained.

[0051] After the specifications are matched, the forward contract management module 20 will also perform a health status prediction. The passing conditions for the prediction are: ; in, is the current real-time health index of the DLMEU. This is the minimum acceptable health index specified by the purchaser. A DLMEU must meet both the specification matching criteria and the health status prediction criteria to be considered a qualified match by the system. All qualified matches are compiled into a list and presented to the purchaser's user terminal via the application server.

[0052] After the purchaser selects one or more satisfactory DLMEUs from the list and confirms the transaction intent, the forward contract management module 20 enters the contract generation and locking phase. First, a new electronic contract data object is created in the data storage unit 60. This object contains a newly generated unique contract ID. The contract content includes the identifiers of the purchaser and supplier (i.e., the current owner of the selected DLMEU), the user ID of the selected DLMEU, the agreed price, and the delivery terms.

[0053] A key technical step is that the forward contract management module 20 sets the contract risk threshold in the contract data object The threshold is calculated using the following formula: ; in, Is the minimum health index required by the purchaser, is the risk buffer margin preset by the system, and its value is a constant greater than zero. In a specific implementation, Can be set to 0.1. Serves as the basis for subsequent risk monitoring engine 30 to make judgments.

[0054] After the contract data object is created and stored, the forward contract management module 20 immediately sends an update command to the data storage unit 60. This command modifies the ownership and contract attribute set 230 of the selected DLMEU: it updates the value of its status field from AVAILABLE or RECYCLED to LOCKED, and updates the value of its contractID field to the newly generated contract ID. This operation completes the system-level lock on the physical material, ensuring that it cannot participate in other transaction matching until the current contract is fulfilled or its status changes.

[0055] Refer to the attached Figure 5 , Figure 5 Figure 3 is a schematic diagram of the risk monitoring engine workflow according to one embodiment of the present invention. This process is executed by the risk monitoring engine 30, which runs as a background service deployed on an application server. It continuously monitors the status of materials under forward contracts and initiates subsequent processing mechanisms when potential performance risks are detected.

[0056] The risk monitoring engine 30 operates using a time-triggered polling mechanism. System administrators can configure a global or contract-specific monitoring cycle based on business needs (e.g., high-value contracts or high-risk species). The engine is run by a system-level task scheduler (e.g., a Cron-based scheduling service) according to this cycle. Automatically wakes up and performs a full surveillance scan.

[0057] At the beginning of a monitoring cycle, the risk monitoring engine 30 first initiates a query request to the data storage unit 60. This query condition filters out all DLMEU data objects whose status field value in the ownership and contract attribute set 230 is LOCKED. The goal of this operation is to obtain a list of all DLMEUs currently in the contract-locked state.

[0058] For each locked DLMEU returned by the query, the engine performs the following actions: First, the risk monitoring engine 30 reads the latest dynamic health index from the dynamic attribute set 220 of the DLMEU. At the same time, the associated contract unique identifier contractID is read from the ownership and contract attribute set 230 of the DLMEU.

[0059] Subsequently, the risk monitoring engine 30 uses the obtained contractID to send another query to the data storage unit 60 to locate and read the forward contract data object associated with the DLMEU. From the contract data object, the engine extracts the pre-set contract risk threshold. .

[0060] Get and After the two values ​​are compared, the engine performs a comparison. The triggering conditions of risk events are defined as: ; The core logic of this judgment is that the current health of the materials has fallen below the safety buffer line set for the contract, posing a potential delivery risk.

[0061] If the above conditions are not met, the engine does not perform any operation on the DLMEU and continues to process the next item in the list. If the conditions are met, the risk monitoring engine 30 formally triggers the risk event. The triggering actions include: First, extract the original purchaser's requirements from the read contract data object, including the target specification range , delivery time and delivery location .

[0062] The engine then encapsulates these raw demand information together with the UID of the default DLMEU into a control signal.

[0063] Finally, the control signal is sent to the global alternative search module 40 to activate the alternative search process. After completing the scan of all locked DLMEUs, the monitoring cycle ends and the engine returns to the dormant state to wait for the next scheduling.

[0064] Refer to the attached Figure 6 , Figure 6 Figure 2 is a schematic diagram of the global alternative search process according to one embodiment of the present invention. This process is executed by the global alternative search module 40. This module is activated upon receiving a control signal from the risk monitoring engine 30 and functions to search for one or more qualified alternative materials for a forward contract in which a risk event has occurred.

[0065] When the global substitute search module 40 is activated, it will receive a control signal containing the original contract requirements, which at least includes: the category and name of the original material, the target specification range , original delivery time , the minimum acceptable health index and delivery location .

[0066] The core functionality of the global alternative search module 40 lies in its search scope. It operates on the data storage unit 60 through a unified data query interface. This query is designed to simultaneously cover two logical inventory pools: regular supplier inventory and a project surplus inventory pool. This is achieved by setting filter conditions in the database query statement. The logical conditions are: status='AVAILABLE' ∨ status='RECYCLED'; This query condition ensures that all DLMEUs in the available state or the residual material circulation state are included in the preliminary selection range, forming the basis of the global search.

[0067] In order to improve the pertinence and execution efficiency of the query, the global alternative search module 40 adopts a multi-level filtering search strategy.

[0068] The first level is basic attribute filtering. The global substitute search module 40 first filters based on the basic category and name of the material to ensure that the species of the substitute is consistent with the original contract subject matter. At the same time, it can filter based on the delivery location. Perform a rough geographical screening, for example, filter out all DLMEUs that are located within a certain radius (e.g., 500 km) of the delivery location to pre-emptively exclude options that are not feasible in terms of transportation costs.

[0069] The second level is the fine matching of specifications and health. For the DLMEU candidate set that has passed the first level of filtering, the global alternative search module 40 performs the same matching algorithm as described above for each entry. It calls the growth trend prediction function of the data processing and evaluation unit 50 to calculate the delivery time of each candidate DLMEU. Forecast specifications Then, verify it with the following conditions: ; Only candidate DLMEUs whose predicted specifications fully meet the original contract requirements will be retained. After this, the global alternative search module 40 will also perform a health check, the conditions of which are: ; in, The current real-time health index of the DLMEU.

[0070] After the aforementioned multi-level filtering, all DLMEUs remaining in the list are considered qualified alternatives. The global alternative search module 40 compiles the unique identifiers (UIDs) of these qualified alternatives and their key attributes (such as current specifications, health index, owner, and geographic location) into a result set. This result set is then passed to the utility evaluation module 70 for further decision support and ranking. Alternatively, in embodiments without the utility evaluation module 70, the result set is directly pushed via the application server to the user terminal of the original contract purchaser for selection.

[0071] In a preferred embodiment, referring to the attached Figure 1 The system also includes a utility evaluation module 70. This module is invoked after the global alternative search module 40 completes its search and returns a set of qualified alternatives. Its function is to calculate a quantitative utility score for each qualified alternative DLMEU and, based on this score, provide a decision-making ranking reference for the purchaser.

[0072] The utility evaluation module 70 Calculate the utility score of qualified alternatives The model is as follows: ; In this model, , , are preset non-negative weight coefficients used to adjust the relative importance of different evaluation dimensions. These coefficients are stored in the system configuration parameters. For example, in one embodiment, .

[0073] The three sub-items on the right side of the equation represent the specification similarity score, health status score, and transportation cost score, respectively.

[0074] Specification similarity score A score that quantifies how closely a substitute product matches the specifications of the original contracted item at the time of delivery. This score is calculated using the following steps: First, calculate the specification deviation between the substitute and the original target in each physical dimension and perform normalized Euclidean distance calculation: ; in, It is The specification deviation distance of the alternatives. It is Alternatives in dimension Above the forecast specifications for delivery time. The original contract object is in dimension Above the forecast specifications for delivery time.

[0075] and These are the upper and lower limits of the dimension specification requirements in the original contract.

[0076] The distance value is then converted into a similarity score using an exponential function: ; This formula ensures that the closer the specifications are, the higher the score is, and the score range is between (0,1].

[0077] Health status score It is directly derived from the current health index of the alternative, as the index itself has been normalized. Its calculation formula is: ; in, It is The real-time dynamic health index of each substitute at the evaluation moment, whose value range is between [0,1].

[0078] Shipping cost score Used to quantify the cost of transporting the replacement to the delivery location. First, the system estimates the transportation cost In one implementation, the cost can be estimated as the product of the transportation distance and the cost factor related to the material category. Then, in order to incorporate it into the unified utility evaluation model, the transportation costs of all candidate alternatives need to be normalized: ; in, It is Estimated shipping costs for the alternatives. and are the maximum and minimum estimated transportation costs among all candidate alternatives in the current batch, respectively. This formula maps transportation costs to the interval [0, 1], with higher costs giving higher scores. Because cost is a negative indicator in the total utility model, a minus sign is used in the overall formula.

[0079] After calculating the utility scores for all eligible alternatives After that, the utility evaluation module 70 lists the alternatives according to Finally, the application server presents an ordered list containing the scores of each item and the total utility score of the alternatives to the user terminal of the purchaser.

[0080] Refer to the attached Figure 7 , Figure 7Figure 8 is a schematic diagram of a contract restructuring process according to one embodiment of the present invention. In a preferred embodiment, this process is executed by contract restructuring module 80. This module is activated after the purchaser's user terminal selects a replacement DLMEU from a list of alternatives and issues a confirmation instruction. Its function is to automatically complete the change of the contract subject matter to ensure contract continuity.

[0081] The starting signal of this process is a data packet sent by the purchaser's user terminal to the application server. The data packet contains two key pieces of information: the unique identifier contractID of the original contract where the risk event occurred, and the unique identifier uid_new of the replacement DLMEU selected by the user.

[0082] After receiving the signal, the contract reorganization module 80 executes an atomic data update operation comprising multiple steps to ensure the consistency of the data state in the data storage unit 60. The atomic operation specifically includes the following consecutive database transactions: First, the module queries and locks the original contract data object based on contractID, and reads the unique identifier uid_orig of the original contract subject from it.

[0083] Second, the module sends an update command to the data storage unit 60 for the original DLMEU (the DLMEU pointed to by uid_orig). This command changes the status field in its ownership and contract attribute set 230 from LOCKED back to AVAILABLE and clears or sets its contractID field to an invalid value. This action releases the binding between the original material and the contract.

[0084] Third, the module issues an update command to the data storage unit 60 for the contract data object itself. This command changes the value of the contract field that records the unique identifier of the subject matter from uid_orig to uid_new. If there are differences in price or other terms between the old and new materials, the corresponding fields in the contract may also be updated during this step.

[0085] Fourth, the module issues an update command to the data storage unit 60 for the newly selected replacement DLMEU (the one pointed to by uid_new). This command modifies the status field in its ownership and contract attribute set 230 from AVAILABLE or RECYCLED to LOCKED and sets the value of its contractID field to the ID of the contract currently being processed. This operation formally binds the new material to the contract.

[0086] All of the above database update instructions are encapsulated and executed within a single transaction. Only when all instructions complete successfully is the transaction committed, and the data state changes are solidified. If any step fails, the entire transaction is rolled back, and all data is restored to its state before the process started, avoiding inconsistent intermediate states.

[0087] After the transaction is successfully submitted, the contract restructuring module 80 also performs a notification distribution operation. It sends a structured notification message to the user terminals of the purchaser, the supplier of the original material, and the supplier of the new material, clearly informing them that the contract subject matter has changed, providing the identifiers of the old and new materials, and the current status of the contract.

[0088] Refer to the attached Figure 8 , Figure 8 The system provided by the embodiment of the present invention also includes a mechanism for managing and reusing the value of the remaining garden materials generated during the project execution.

[0089] When a landscaping project generates surplus materials, an authorized user (e.g., a project manager or on-site personnel) can initiate the process of pooling the surplus materials through their user terminal. The user first accurately measures the current physical specifications of the surplus materials and assesses their health. The user then submits this real-time data, along with information such as the material type and name, to the system.

[0090] After receiving the request to put the surplus material into the pool, the system calls the dynamic lifecycle material ownership unit generation module 10 to create a new DLMEU data object for this surplus material. The newly generated DLMEU has the following specific configurations: First, the system assigns it a new unique identifier uid; Second, in the static attribute set 210, the initialSpec field is directly populated with the current measurement specification submitted by the user; The most critical thing is that in its ownership and contract attribute set 230, the currentOwner field is set to the identifier of the project entity, and the initial value of the status field is directly set to RECYCLED.

[0091] The project surplus recycling pool is not a separate physical storage unit, but rather a logical data collection within data storage unit 60 that is managed using specific status identifiers. Specifically, the recycling pool logically consists of all DLMEUs whose status field value is "RECYCLED." The system manages, retrieves, and accesses resources within this pool by querying and filtering on the status field.

[0092] The DLMEU surplus in the recycling pool is designed to seamlessly re-enter the supply chain. Specifically, the database query logic within the forward contract management module 20, when initially matching new forward demand, and the global alternative search module 40, when searching for alternatives to at-risk contracts, are configured to include both the AVAILABLE and RECYCLED states.

[0093] In this way, project surplus materials and regular supplier stocks together constitute the complete set of materials that can be supplied by the system, thus realizing the reuse of surplus material value.

[0094] When a DLMEU with a status of RECYCLED is selected by a purchaser and a new forward contract is signed, the forward contract management module 20 or contract restructuring module 80 changes its status field from RECYCLED to LOCKED and associates the new contract ID. This status change indicates that the surplus material has been successfully retrieved from the circulation pool and has re-entered the active contract fulfillment cycle, completing its value cycle.

[0095] In order to better understand the technical solution of the present invention, the workflow of the system and method provided by the present invention will be described in detail below through a specific application scenario.

[0096] The scene is set up as follows: Purchaser A: An entity planning to build a large park project requires a batch of ginkgo trees of specific specifications and requires delivery in 18 months.

[0097] Supplier A: A seedling supplier.

[0098] Supplier B: The project department of another completed project holds surplus garden materials that can be recycled.

[0099] The process steps are as follows: 1. Material registration and DLMEU generation: Supplier A owns a batch of healthy ginkgo saplings. Its staff enters the initial data of these saplings into the system using a user terminal, including the species "Ginkgo," the current average height of 2.5 meters, and the diameter at breast height of 4 centimeters. The system invokes the dynamic lifecycle material ownership unit generation module 10, creates a DLMEU for these saplings, assigns it a unique identifier, UID-A, and sets its status to AVAILABLE.

[0100] 2. Forward contract demand and matching: 18 months later, Purchaser A published a forward purchase demand for its park project through the system: 10 ginkgo trees are needed, with delivery specifications of height between [4.8, 5.2] meters, diameter at breast height between [7.5, 8.5] centimeters, and an acceptable minimum health index of is 0.8.

[0101] After receiving this request, the forward contract management module 20 begins matching. It selects UID-A as a candidate. The forward contract management module 20 calls the growth trend prediction function of the data processing and evaluation unit 50. Based on UID-A's historical health data and growth model, the system predicts its delivery time in 18 months. Its specifications will reach 5.0 meters in height and 8.0 centimeters in diameter at breast height, which fully meets the required specification range. .

[0102] 3. Contract generation and locking: Purchaser A confirms to select Supplier A's UID-A. The forward contract management module 20 generates an electronic forward contract with the contract ID CID-123. In this contract, the system Calculate and set contract risk thresholds Subsequently, the forward contract management module 20 updates the status of UID-A from AVAILABLE to LOCKED and associates its contractID field with CID-123.

[0103] 4. Risk monitoring and event triggering: Over the next 12 months, Supplier A continued to care for the ginkgo trees and submitted dynamic data to the system through IoT devices and manual input. Data processing and evaluation unit 50 continuously calculated their health index, which remained above 0.9.

[0104] However, in the 13th month, due to an unexpected pest and disease, the dynamic health index of UID-A It dropped to 0.88. The risk monitoring engine 30 deployed on the server detected that this situation met the risk condition during its routine polling scan: ; The engine immediately triggers the risk event and packages the demand information of the original contract CID-123 into a control signal and sends it to the global alternative search module 40.

[0105] 4. Global alternative search and surplus material discovery: The global alternative search module 40 is activated. It searches the entire data storage unit 60 according to the original requirement, and the search scope covers all DLMEUs whose status is AVAILABLE or RECYCLED.

[0106] The search module discovered that Supplier B had entered a batch of remaining ginkgo trees from its project into the system a month prior, generating UID-B with a status of RECYCLED. The trees' current specifications (5.1 meters in height and 8.2 centimeters in diameter at breast height) met delivery requirements, and their health index was 0.92. UID-B was therefore identified as a suitable replacement.

[0107] 5. Utility evaluation and decision support: Utility evaluation module 70 evaluates all eligible alternatives, including UID-B. Because UID-B (from project surplus) is geographically closer, its transportation cost score is lower; its current specifications closely match the demand, resulting in a higher specification similarity score. After comprehensive calculations, UID-B receives the highest total utility score, U. The system pushes this ranking result to Purchaser A's user terminal.

[0108] 6. Contract Restructuring: Purchaser A adopts the system's suggestion and selects UID-B as a replacement. Contract Restructuring Module 80 executes an atomic transaction: Unlock the status of UID-A from LOCKED to AVAILABLE.

[0109] Update the material identifier associated with contract CID-123 from UID-A to UID-B.

[0110] Update the status of UID-B from RECYCLED to LOCKED.

[0111] Through the above process, the system proactively identified and resolved potential delivery risks in the supply chain without interrupting the contract. At the same time, by calling on resources in the project surplus material recycling pool, it successfully completed the seamless replacement of the contract subject matter, ensuring that the final project requirements of Purchaser A were met.

[0112] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. The garden material supply chain collaborative management system based on cloud computing is characterized by: include: A dynamic lifecycle material ownership unit generation module is used to create a corresponding dynamic lifecycle material ownership unit for one or a batch of garden materials. The dynamic lifecycle material ownership unit includes a static attribute set, a dynamic attribute set, and an ownership and contract attribute set; A forward contract management module, configured to match the forecast specifications of the dynamic lifecycle material ownership unit with the forward demand of the purchaser to generate a forward contract, set a contract risk threshold in the contract, and lock the status of the dynamic lifecycle material ownership unit; a risk monitoring engine, configured to continuously monitor the dynamic health index in the dynamic attribute set of the dynamic lifecycle material ownership unit in a locked state, and trigger a risk event when the dynamic health index is lower than the contract risk threshold; The global alternative search module is used to automatically search for one or more qualified alternative dynamic life cycle material ownership units when the risk event is triggered.

2. The cloud computing-based garden material supply chain collaborative management system according to claim 1 is characterized in that: The dynamic attribute set of the dynamic lifecycle material ownership unit includes: A dynamic health index, used to quantify the current health of the garden material; and The growth trend prediction data is used to predict the physical specifications of the garden material at a future time point based on a preset growth model function.

3. The cloud computing-based garden material supply chain collaborative management system according to claim 2, characterized in that: The system further includes a dynamic health index evaluation module, wherein the dynamic health index evaluation module is configured to: collecting raw measurement values ​​of a plurality of vital sign parameters associated with the garden material; processing the raw measurement values ​​through a normalization function; The normalized multiple parameter values ​​are weighted and summed to calculate the dynamic health index.

4. The cloud computing-based garden material supply chain collaborative management system according to claim 2, characterized in that: The forward contract management module is further configured to: The growth trend forecast data is used to calculate the forecast specifications of the dynamic life cycle material ownership unit at the delivery time of the long-term demand, and the long-term demand is matched based on the forecast specifications.

5. The garden material supply chain collaborative management system based on cloud computing according to claim 1 is characterized in that: The search scope of the global alternative search module is configured to include: Dynamic lifecycle material ownership units in a usable state held by one or more suppliers; and A dynamic lifecycle material ownership unit stored in the project residual material recycling pool.

6. The garden material supply chain collaborative management system based on cloud computing according to claim 5 is characterized in that: The system further includes a utility evaluation module configured to: When the global alternative search module searches for multiple qualified alternative dynamic lifecycle material ownership units, a utility score is calculated for each alternative dynamic lifecycle material ownership unit, and a decision ranking is provided to the purchaser based on the utility score.

7. The cloud computing-based garden material supply chain collaborative management system according to claim 6, characterized in that: The parameters used by the utility evaluation module to calculate the utility score include: The similarity in specifications between the replacement dynamic lifecycle material ownership unit and the original dynamic lifecycle material ownership unit; The current dynamic health index of the alternative dynamic life cycle material ownership unit; and The estimated transportation cost of delivering the alternative dynamic lifecycle material title unit to the delivery location.

8. The garden material supply chain collaborative management system based on cloud computing according to claim 5 is characterized in that: The dynamic lifecycle material ownership unit generation module is further configured to: Receive the remaining material information of the completed project, create a new dynamic life cycle material ownership unit for the remaining material, initialize its ownership and status information and store it in the project remaining material circulation pool.

9. The garden material supply chain collaborative management system based on cloud computing according to claim 1, characterized in that: The ownership and contract attribute set of the dynamic lifecycle material ownership unit includes: Current owner ID; The current status identifier of the dynamic lifecycle material ownership unit, where the current status identifier is used to indicate whether it is available, locked, or in transit; and If the current status is identified as locked, the associated forward contract identifier is also included.

10. The garden material supply chain collaborative management system based on cloud computing according to claim 1, characterized in that: The system further includes a contract restructuring module, wherein the contract restructuring module is configured to: After the purchaser confirms the selection from the alternatives provided by the global alternative search module, a new transaction offer is automatically sent to the current owner of the alternative dynamic lifecycle material ownership unit, and the subject matter change of the forward contract is guided to be completed.

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