Cloud-computing-based garden material supply chain collaborative management system

Abstract

The application relates to the technical field of supply chain management, and discloses a garden material supply chain collaborative management system based on cloud computing, which creates a dynamic life cycle material ownership unit for each garden material, and realizes intelligent matching of a long-term contract by using a dynamic health index and a growth trend prediction of the dynamic life cycle material ownership unit; a risk monitoring engine actively monitors the health condition of the signed material, and once the health condition is lower than a preset risk threshold, a risk event is triggered; a global substitute search module automatically searches for qualified substitutes in the supplier inventory and a project surplus material recycling pool; after confirmation of a purchaser, a contract reorganization module completes target object change in an atomic transaction. Through dynamic tracking of a whole life cycle of a living material and active risk hedging, the application significantly improves a performance guarantee rate of a long-term contract, realizes value reuse of project surplus materials, and improves stability and efficiency of a supply chain.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of supply chain management, in particular to a cloud computing-based garden material supply chain collaborative management system. BACKGROUND

[0002] In garden greening projects, long-term contracts are a common business model to ensure that specific specifications of garden materials can be obtained 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 mostly manage garden materials as ordinary goods, only recording their names, sources, and initial specifications when they are put into storage. This approach completely ignores the most critical characteristic of living assets, which is that their life status changes dynamically over time. From the signing of the contract to the delivery in the future, the health of the materials may deteriorate, and the growth rate may not meet expectations, but these critical dynamic changes cannot be effectively tracked and reflected in existing systems. This leads to significant information asymmetry and contract uncertainty for the purchaser during the entire contract period.

[0004] When the contract risk actually occurs, for example, the materials are found to be dead or not up to specifications near the delivery date, the existing response measures are usually passive and inefficient. The process of finding alternatives usually relies on manual communication, which is time-consuming and labor-intensive, and the range is limited to the scattered inventory of individual suppliers, which easily leads to project delays and economic losses. In addition, the existing system generally lacks an effective integration mechanism for potential resources such as project leftovers, and these valuable materials are often idle or wasted due to information silos, failing to enter the supply chain to realize value recycling, further exacerbating the inefficiency of resource allocation. Therefore, the existing technology has obvious shortcomings in dynamic monitoring, active risk management, and global resource integration of living assets, making it difficult to ensure the reliability of long-term contracts and restricting the efficiency and resilience of the entire supply chain. SUMMARY

[0005] The existing garden material supply chain management, especially the management of living plant materials, has the following technical problems: First, the material information is usually static data, which cannot reflect the dynamic changes such as growth and health of living materials during the inventory period, leading to distorted information; second, there is a time mismatch between project demand and material supply, and long-term procurement lacks a reliable contract performance guarantee mechanism, with high contract performance risk; finally, the surplus materials generated after the completion of the project are difficult to manage and reuse effectively, causing resource waste.

[0006] To solve the above technical problems, the present application provides a cloud computing-based garden material supply chain collaborative management system.

[0007] The system comprises:

[0008] The 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.

[0009] The forward contract management module is used to match the predicted 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.

[0010] The risk monitoring engine is used to continuously monitor the dynamic health index of the dynamic attribute set of the dynamic lifecycle material ownership unit that is in a locked state, and to trigger a risk event when the dynamic health index is lower than the contract risk threshold.

[0011] The global alternative search module is used to automatically search for one or more qualified alternative dynamic lifecycle material ownership units when the risk event is triggered.

[0012] Preferably, the dynamic attribute set of the dynamic lifecycle material ownership unit includes:

[0013] The dynamic health index is used to quantify the current health status of the garden materials; and

[0014] Growth trend prediction data is used to predict the physical specifications of the garden materials at future points in time based on a preset growth model function.

[0015] In one specific embodiment, the system further includes a dynamic health index assessment module. The dynamic health index assessment module is configured to:

[0016] Raw measurements of multiple vital sign parameters related to the garden materials were collected;

[0017] The original measurement values ​​are processed using a normalization function;

[0018] The dynamic health index is calculated by weighted summation of multiple normalized parameter values, and the calculation formula is as follows:

[0019] ;

[0020] in, For time points Health index score, The total number of parameters participating in the evaluation. For the first Preset weighting coefficients for each parameter. is a normalization function, is a time point the first raw measurement of the parameter.

[0021] In one embodiment, the forward contract management module utilizes the growth trend prediction data to calculate a predicted specification of the dynamic lifecycle material ownership unit at the delivery time of the forward demand, and matches the predicted specification with the forward demand.

[0022] Preferably, the search range of the global substitute search module is configured to include simultaneously:

[0023] dynamic lifecycle material ownership units held by one or more suppliers in an available state; and

[0024] dynamic lifecycle material ownership units stored in a project surplus recycling pool.

[0025] In one embodiment, the dynamic lifecycle material ownership unit generation module is further configured to:

[0026] receive remaining material information of a completed project, and create a new dynamic lifecycle material ownership unit for the remaining material, and store the new dynamic lifecycle material ownership unit in the project surplus recycling pool after initializing the ownership and state information thereof.

[0027] In one embodiment, the system further comprises a utility evaluation module. The utility evaluation module is configured to calculate a utility score for each of the qualified substitute dynamic lifecycle material ownership units when the global substitute search module searches for multiple qualified substitute dynamic lifecycle material ownership units, and provide a decision ranking for the purchaser based on the utility scores.

[0028] Further, the parameters relied on by the utility evaluation module when calculating the utility score include:

[0029] a specification similarity between the substitute dynamic lifecycle material ownership unit and the original dynamic lifecycle material ownership unit;

[0030] a current dynamic health index of the substitute dynamic lifecycle material ownership unit; and

[0031] an estimated transportation cost of transporting the substitute dynamic lifecycle material ownership unit to the delivery location.

[0032] In one embodiment, the system further comprises a contract reorganization module. The contract reorganization module is configured to automatically send a new transaction offer to the current owner of the alternative dynamic life cycle material ownership unit and guide the completion of the subject change of the forward contract after the procurement party confirms the selection from the alternative provided by the global substitute search module.

[0033] Preferably, the ownership and contract attribute set of the dynamic life cycle material ownership unit comprises:

[0034] Current owner identification;

[0035] Current state identification of the dynamic life cycle material ownership unit, the current state identification indicating that it is available, locked or in transit; and

[0036] If the current state identification is locked, it further comprises an associated forward contract identification.

[0037] The present application provides a cloud computing-based garden material supply chain collaborative management system. It has the following beneficial effects:

[0038] 1. The present application provides a dynamic digital expression method for garden materials by constructing a dynamic life cycle material ownership unit containing a dynamic attribute set. The dynamic health index and growth trend prediction data in the dynamic attribute set can reflect the life state and specification trend of materials (especially living plants) over time, so that the system can manage and make decisions based on near real-time data, overcoming the information distortion problem caused by traditional static data management methods.

[0039] 2. The present application establishes an automatic identification and processing mechanism for contract risks by setting up a risk monitoring engine and a global substitute search module. The risk monitoring engine continuously monitors the state of the locked material based on the preset contract risk threshold. Once a risk event is identified, the global substitute search module automatically starts the search process for alternative solutions. This mechanism changes passive human response to active system processing, reducing the uncertainty of contract performance due to changes in material state.

[0040] 3. The present application realizes the recycling of resources at the end of the supply chain by setting up a project surplus material recycling pool and including it in the search range of the global substitute search module. This design makes the surplus material generated by the project no longer a isolated sunken asset, but an effective inventory resource that is re-integrated into the entire supply chain system. When new procurement demands or contract risk events occur, these surplus materials can be called by the system, thereby reducing resource waste. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1A function module structure schematic diagram of the garden material supply chain collaborative management system of one embodiment of the present application;

[0042] Figure 2 A data structure schematic diagram of the dynamic lifecycle material ownership unit of one embodiment of the present application;

[0043] Figure 3 A dynamic data processing flow schematic diagram of one embodiment of the present application;

[0044] Figure 4 A forward contract management flow schematic diagram of one embodiment of the present application;

[0045] Figure 5 A risk monitoring engine work flow schematic diagram of one embodiment of the present application;

[0046] Figure 6 A global substitute search flow schematic diagram of one embodiment of the present application;

[0047] Figure 7 A contract reorganization flow schematic diagram of one embodiment of the present application;

[0048] Figure 8 A project surplus recycling flow schematic diagram of one embodiment of the present application.

[0049] Wherein, 10, dynamic lifecycle material ownership unit generation module; 20, forward contract management module; 30, risk monitoring engine; 40, global substitute 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

[0050] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0051] Referring to the drawings Figure 1 , Figure 1 is a function module structure schematic diagram of the garden material supply chain collaborative management system of one embodiment of the present application. The system can be deployed on one or more cloud servers, and its physical deployment architecture includes an application server and a data storage unit. The application server is used to carry various function modules of the system, and the data storage unit is used to persistently store the data required for the system to run.

[0052] The system provided by the embodiments of the present application comprises a plurality of functional modules which exchange data and communicate through preset interfaces.

[0053] In one embodiment, the system comprises a dynamic lifecycle material entitlement unit generation module 10, a forward contract management module 20, a risk monitoring engine 30, a global substitute search module 40, a data processing and evaluation unit 50, and a data storage unit 60. In a preferred embodiment, the system can further comprise a utility evaluation module 70 and a contract reorganization module 80 to provide more intelligent decision support and automated contract change functions.

[0054] The function of the dynamic lifecycle material entitlement unit generation module 10 is to create a corresponding dynamic lifecycle material entitlement unit (DLMEU) for one or a batch of landscaping materials. The user terminal (such as the computer or mobile device of the supplier user) submits the initial static data of the material to the application server through the network interface, and the application server calls the dynamic lifecycle material entitlement unit generation module 10 to generate a DLMEU data object containing a unique identifier, and writes the object into the data storage unit 60.

[0055] The forward contract management module 20 is connected with the data storage unit 60 and is used to read the DLMEU data. When receiving a forward demand request from the purchaser user terminal, the forward contract management module 20 performs a matching algorithm to screen out the DLMEU that meets the demand. After the user confirms, the forward contract management module 20 generates an electronic forward contract, writes the contract content into the data storage unit 60, and updates the state of the selected DLMEU to be locked, while setting a contract risk threshold in the contract.

[0056] The risk monitoring engine 30 is configured as a background service which queries the data storage unit 60 at preset time intervals (for example, once an hour) to obtain the dynamic attribute set 220 of all DLMEUs in the locked state. The risk monitoring engine 30 compares the real-time dynamic health index obtained with the contract risk threshold set in the corresponding contract. When detecting that the dynamic health index of a DLMEU is lower than its contract risk threshold, the risk monitoring engine 30 triggers a risk event and sends a control signal containing the original contract demand to the global substitute search module 40.

[0057] The global substitute search module 40 is activated upon receiving the control signal from the risk monitoring engine 30. It initiates a search query to the data storage unit 60 according to the original contract requirements contained in the signal. The target scope of the query covers all the DLMEUs in the data storage unit 60 with a status of available, including both the supplier inventory and the project surplus recycling pool. The global substitute search module 40 returns the list of one or more qualified substitute DLMEUs found to the original contract's purchaser user terminal through the application server.

[0058] The data processing and evaluation unit 50 is internally integrated with a dynamic health index evaluation module and a growth trend prediction module. It receives the raw data input by the Internet of Things devices or manually, calculates the dynamic health index, and predicts the growth trend, and then updates the calculation results to the dynamic attribute set of the corresponding DLMEU in the data storage unit 60. The long-term contract management module 20 calls the growth trend prediction function of the data processing and evaluation unit 50 when matching.

[0059] 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 the data objects of all DLMEUs, user information, long-term contract content, and system operation logs. All functional modules perform read and write operations on the data storage unit 60 through standard database connection protocols.

[0060] In a preferred embodiment, the utility evaluation module 70 receives the list of qualified substitutes provided by the global substitute search module 40 and calculates a quantitative comprehensive utility score for each substitute. The score can be calculated based on multiple dimensions such as specification similarity, health status, transportation cost, etc. The function is to provide a data-driven, ordered decision reference for the purchaser to help them choose the optimal solution from multiple potential substitutes.

[0061] In a preferred embodiment, when the purchaser selects one from the substitute list and confirms it, the contract reorganization module 80 is activated to perform an atomic database transaction operation to safely and consistently complete the change of the contract subject. The specific operation includes: releasing the lock relationship between the original material and the contract, binding the newly selected material with the contract, and updating the contract content. The module ensures the automation and data consistency of the contract change process.

[0062] Referring to the accompanying drawings Figure 2 , Figure 2 is a data structure diagram of a dynamic life cycle material ownership unit (DLMEU) according to an embodiment of the present application. The DLMEU is a standardized data object in the system for uniquely mapping and managing one or a batch of garden materials. The following will describe the composition of the DLMEU and its processing flow in the system in detail.

[0063] The creation and initialization of a DLMEU is performed by the dynamic lifecycle material ownership unit generation module 10. When an authorized user (e.g. a nursery supplier) accesses the system through his user terminal, a material registration process can be initiated. The user submits initial information of a new material through the graphical user interface. Upon receiving these information, the dynamic lifecycle material ownership unit generation module 10 first generates a globally unique identifier (UID) for the material, which can be generated by combining a server timestamp, a supplier code and a serial number to ensure its uniqueness. Subsequently, the dynamic lifecycle material ownership unit generation module 10 assembles the UID with the initial information submitted by the user into a structured DLMEU data object, and stores it in the data storage unit 60.

[0064] Referring to the accompanying drawings Figure 2 , a DLMEU data object logically comprises three attribute sets. The first is the static attribute set 210, which contains inherent information of the material that does not change over time. Specifically, the static attribute set 210 includes:

[0065] uid, the aforementioned globally unique identifier;

[0066] category, representing the material category, whose value is selected from a standardized material classification table pre-stored in the data storage unit 60, such as “tree” or “ground cover”; species, representing the specific species or variety, such as “ginkgo”;

[0067] origin, recording the origin or producer information of the material;

[0068] initialSpec, recording the initial physical specification of the material at the time of registration, which is stored in a structured data format (e.g. JSON) containing multiple dimension key-value pairs, such as {"height_cm": 300, "trunk_diameter_mm": 50};

[0069] creationTime, recording the precise timestamp when the DLMEU object was created.

[0070] The second is the dynamic attribute set 220, which contains state information of the material that changes dynamically over time, calculated and updated periodically by the data processing and evaluation unit 50 in the system. Specifically, the dynamic attribute set 220 includes:

[0071] healthIndex, a floating point value quantifying the current comprehensive health condition of the living plant;

[0072] growthPrediction, stores future specification data generated by the growth trend prediction model, which can be stored as a set of time series data, each data point contains a future timestamp and a corresponding predicted specification vector;

[0073] mediaLog, stores one or more uniform resource locators (URLs) pointing to multimedia files (such as images, videos) that record the appearance of the material at different time points, the files themselves can be stored in a separate distributed file system;

[0074] lastUpdateTime, records the timestamp of the last time the dynamic attribute set 220 was updated.

[0075] 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:

[0076] currentOwner, records the identifier of the entity that currently holds the ownership of the material;

[0077] status, a status field of an enumeration type, used to manage the life cycle of the DLMEU;

[0078] contractID, when the value of the status field is LOCKED, this field is used to store the unique identifier of the associated forward contract;

[0079] location, records the current geographic coordinates of the material, which can be obtained and updated by GPS devices or other positioning methods.

[0080] The status flow of the status field follows a preset state machine model to ensure the rigor of the business logic. When the DLMEU is created, if the material is new, its initial state is set to AVAILABLE. If the material is a project surplus, its initial state is set to RECYCLED. When 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 the risk hedging mechanism, its state will return to AVAILABLE from LOCKED. During the contract performance phase, when the material starts to be transported, the state can be changed to IN_TRANSIT. When the purchaser confirms receipt, the final state changes to DELIVERED. After the state changes to DELIVERED, the data record of the DLMEU is archived by the system, and the system will stop monitoring and updating the dynamic attribute set 220 of the DLMEU.

[0081] Referring to the drawings Figure 3 , Figure 3 is a dynamic data processing flowchart according to an embodiment of the present application. The flow is executed by the data processing and evaluation unit 50 for collecting, processing and evaluating the dynamic data of the garden materials associated with the DLMEU, to generate and update the dynamic attribute set 220 of the DLMEU.

[0082] The data collection phase of the flow supports multi-source heterogeneous data input. One input source is the Internet of Things sensing devices deployed in the growing environment of the garden materials, such as soil moisture sensors, ambient light intensity sensors and temperature sensors. These sensing devices periodically send the collected physical quantity data to a designated Internet of Things gateway through a wireless communication module (e.g. NB-IoT or LoRa), and the gateway reports the data to the API interface of the system through a standard data transmission protocol (e.g. MQTT). Another input source is the manual input by authorized users through user terminals. Users can submit observation data on the material morphology (e.g. leaf color score, pest and disease level) and records of the maintenance operations performed in the mobile application or web form.

[0083] After the system receives these raw data from different sources and in different formats, it first performs standardization processing. For sensor data, the system parses the original electrical signal or protocol data packet into standard physical quantity units (e.g. soil moisture is parsed into percentage, light intensity is parsed into pmol / m 2 / s). For qualitative descriptions of manual input, the system converts them into numerical values through a pre-set mapping table (e.g. leaf color "normal" is mapped to 1, "slightly yellow" is mapped to 0.5). All standardized data are attached with a timestamp and associated with the unique identifier of the corresponding DLMEU, forming structured data records stored in the data storage unit 60.

[0084] The dynamic health index evaluation module in the data processing and evaluation unit 50 is used to perform the calculation of the health index. The module reads a set of the latest standardized data records associated with a DLMEU, and applies the following evaluation model:

[0085] ;

[0086] In this model, is the dynamic health index of the DLMEU at time point . is the total number of parameters participating in the evaluation. is the standardized measurement value of the th parameter collected at time point . is the standardized measurement value of the weight coefficients of the parameters, whose values are pre-configured in a weight configuration table in the data storage unit 60 according to the physiological characteristics of the species, and the sum of all the weight coefficients is 1.

[0087] is a normalization function for mapping the measurement values in different physical units to a uniform [0, 1] interval. In one specific implementation, the max-min normalization method is adopted:

[0088] ;

[0089] wherein and represent the lower and upper limits of the suitable physiological range of the corresponding parameter of the species, respectively. These threshold values are also stored in the data storage unit 60 according to the species information. For some parameters whose values represent the worse state with higher values (e.g. the grade of disease and pest), the reverse normalization processing is adopted. The calculated value is finally written into the healthIndex field in the dynamic attribute set 220 of the DLMEU.

[0090] The growth trend prediction module in the data processing and evaluation unit 50 is used to predict the physical specifications of the DLMEU at future time points. The module is executed when called by the forward contract management module 20, and selects a mathematical model consistent with the growth law of the species, such as the Logistic growth function for single-dimensional specifications such as height and diameter at breast height:

[0091] ;

[0092] In this function, is the predicted specification of a certain physical dimension (dim) at the future delivery time . is the maximum growth limit value of the species in this dimension, which is obtained as a static parameter from the species database. is a dynamically calculated growth rate coefficient, whose value is positively correlated with the recent average health index of the DLMEU. is the current time. 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, and finally substitutes it into the function to obtain the predicted specification. The predicted specifications of all key dimensions are combined into a predicted specification vector and updated into the growthPrediction field.

[0093] Referring to the accompanying drawings, Figure 4 , Figure 4 ​is a flowchart of a forward contract management process according to an embodiment of the present application. The process is performed by the forward contract management module 20 in response to a forward requirement submitted by a buyer, and through the cooperation with other modules in the system, the matching and generation of a forward contract is accomplished.

[0094] The process starts with a buyer submitting a structured forward requirement to the system through his user terminal. The requirement is not a free text, but a data object containing a number of pre-defined fields. Specifically, the data object includes:

[0095] a future delivery time ;

[0096] a target specification range , which is a set of key-value pairs defining the upper and lower bounds of a number of physical dimensions, e.g. {"height_cm_min": 450, "height_cm_max": 500, "trunk_diameter_mm_min": 80};

[0097] a minimum health index acceptable at delivery ;

[0098] a delivery location .

[0099] The requirement data object is sent to the application server and received by the forward contract management module 20.

[0100] Upon receiving the forward requirement, the forward contract management module 20 performs an intelligent matching process. First, the forward contract management module 20 initiates a preliminary filtering query to the data storage unit 60 to obtain all DLMEUs with status AVAILABLE or RECYCLED as a candidate set.

[0101] Subsequently, for each DLMEU in the candidate set, the forward contract management module 20 invokes the growth trend prediction function in the data processing and evaluation unit 50. The function computes the predicted specification vector of the DLMEU at the delivery time based on its current specification, historical health data, and the time span from the current time to the delivery time . The forward contract management module 20 checks the specification matching degree of each DLMEU by the following condition:

[0102] ;

[0103] wherein, represents a specific physical dimension (e.g. height), is the set of all physical dimensions included in the requirement specification range, and are the acceptable lower and upper limits of the metric, is the predicted value of the DLMEU on the metric. Only the DLMEU that satisfies the above condition is retained.

[0104] After the specification matching, the forward contract management module 20 also makes a pre-judgment of the health status. The passing condition of the pre-judgment is:

[0105] ;

[0106] wherein, is the current real-time health index of the DLMEU, is the acceptable minimum health index set in the procurement party’s requirement. A DLMEU must satisfy both the specification matching condition and the health status pre-judgment condition to be confirmed by the system as a qualified matching item. All qualified matching items are compiled into a list and presented to the procurement party user terminal through the application server.

[0107] When the procurement party selects one or more satisfactory DLMEUs from the list and confirms the transaction intention, 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, which contains a newly generated unique contract ID. The contract content includes the identifiers of the procurement party and the supplier (i.e. the current owner of the selected DLMEU), the uid of the selected DLMEU, the agreed price, and the delivery terms.

[0108] A key technical step is that the forward contract management module 20 sets a contract risk threshold in the contract data object. The threshold is calculated by the following formula:

[0109] ;

[0110] wherein, is the minimum health index required by the procurement party, is the system preset risk buffer margin, which is a constant greater than zero. In a specific implementation, may be set to 0.1. The threshold serves as the basis for the subsequent risk monitoring engine 30 to make judgments.

[0111] After the contract data object is created and stored, the forward contract management module 20 immediately sends an update instruction to the data storage unit 60. The instruction is used to modify the ownership and contract attribute set 230 of the selected DLMEU: update the value of its status field from AVAILABLE or RECYCLED to LOCKED, and update the value of its contractID field to the newly generated contract ID. This operation completes the system-level locking of the physical material, ensuring that it will not participate in other transaction matches until the current contract is fulfilled or a state change occurs.

[0112] Referring to the drawings Figure 5 , Figure 5 is a risk monitoring engine workflow diagram according to an embodiment of the present application. The flow is executed by the risk monitoring engine 30, which runs as a background service deployed on the application server, for continuous state monitoring of the materials that have signed forward contracts, and initiates subsequent processing mechanisms when potential fulfillment risks are detected.

[0113] The risk monitoring engine 30 works in a time-triggered polling mechanism. The system administrator can configure a monitoring period globally or for specific contracts according to business needs (e.g., high-value contracts or high-risk species) . The engine is automatically awakened and performs a complete monitoring scan according to this period by the system-level task scheduler (e.g., Cron-based scheduling service).

[0114] At the beginning of a monitoring period, the risk monitoring engine 30 first initiates a query request to the data storage unit 60. The condition of the query is to filter out all entries in the DLMEU data object 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.

[0115] For each locked DLMEU returned by the query, the engine performs the following operations:

[0116] First, the risk monitoring engine 30 reads the latest dynamic health index of the DLMEU from its dynamic attribute set 220. At the same time, it reads the associated contract unique identifier contractID from the ownership and contract attribute set 230 of the DLMEU.

[0117] Subsequently, the risk monitoring engine 30 uses the obtained contractID to initiate 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 .

[0118] Upon acquiring and two numerical values, the engine performs a comparison judgment. The triggering condition of a risk event is defined as:

[0119] ;

[0120] The core logic of this judgment is that the current health condition of the material has fallen below the safety buffer line set for the contract, constituting a potential delivery risk.

[0121] If the above condition does not hold, the engine does not perform any operation on this DLMEU and continues to process the next entry in the list. If the condition holds, the risk monitoring engine 30 formally triggers a risk event. The triggering actions include:

[0122] First, from the read contract data object, the original buyer's requirements are extracted, including the target specification range , delivery time and delivery location .

[0123] Then, the engine encapsulates these original requirement information together with the UID of the defaulting DLMEU into a control signal.

[0124] Finally, the control signal is sent to the global substitute search module 40 to activate the substitute search process. After completing the scanning of all locked DLMEUs, the current monitoring period ends, and the engine returns to the dormant state to wait for the next scheduling.

[0125] Referring to the accompanying Figure 6 , Figure 6 is a schematic diagram of the global substitute search process according to an embodiment of the present application. The process is executed by the global substitute search module 40. The module is activated after receiving the control signal from the risk monitoring engine 30, and its function is to find one or more qualified substitute materials for the long-term contract that has occurred a risk event.

[0126] 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 , the original delivery time , the acceptable minimum health index and the delivery location .

[0127] The core function of the universe alternative search module 40 is embodied in the setting of its search range. It operates on the data storage unit 60 through a unified data query interface. The query is designed to cover two logical inventory pools simultaneously: one is the regular supplier inventory, and the other is the project surplus recycling pool. This is achieved by setting a filter condition in the database query statement, whose logical condition is:

[0128] status = 'AVAILABLE' V status = 'RECYCLED';

[0129] This query condition ensures that all DLMEUs in the available state or surplus recycling state are included in the initial selection range, forming the basis of the universe search.

[0130] In order to improve the pertinence and execution efficiency of the query, the universe alternative search module 40 adopts a multi-level filtering search strategy.

[0131] The first level is basic attribute filtering. The universe alternative search module 40 first filters based on the basic category and name of the material, ensuring that the species of the alternative is consistent with the original contract target. At the same time, it can perform a rough geographical location screening according to the delivery location For example, it filters out all DLMEUs whose geographical location is within a certain radius (such as 500 kilometers) of the delivery location, to preclude options that do not have feasible transportation costs.

[0132] The second level is specification and health degree fine matching. For the candidate set of DLMEUs that pass the first level of filtering, the universe 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 predicted specification of each candidate DLMEU at the delivery time . Then, it is verified by the following conditions:

[0133] ;

[0134] Only the candidate DLMEU whose predicted specification completely meets the original contract requirements will be retained. After that, the universe alternative search module 40 will also perform a health degree check, with the condition being:

[0135] ;

[0136] Where, is the current real-time health index of the DLMEU.

[0137] After the above multi-level filtering, all DLMEUs that remain 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 ranking, or, in embodiments where the utility evaluation module 70 is not configured, it is directly pushed to the user terminal of the original contract purchaser via the application server for selection.

[0138] In a preferred embodiment, refer to the appendix Figure 1 The system also includes a utility evaluation module 70. The utility evaluation module 70 is invoked after the global alternative search module 40 completes its search and returns a set containing multiple qualified alternatives. Its function is to calculate a quantified utility score for each qualified alternative (DLMEU) and provide the purchaser with a decision-making ranking reference based on this score.

[0139] Utility assessment module 70 pairs Calculate the utility score of each qualified substitute. The model is as follows:

[0140] ;

[0141] In this model, , , These are preset non-negative weighting coefficients used to adjust the relative importance of different evaluation dimensions; these coefficients are stored in the system's configuration parameters. For example, in one embodiment, they can be set... .

[0142] The three sub-items on the right side of the equation represent the specification similarity score, health status score, and transportation cost score, respectively.

[0143] Specification similarity score This score is used to quantify how closely a substitute approximates the original contractually awarded object in terms of specifications at the time of delivery. The score is calculated through the following steps:

[0144] First, calculate the specification deviations of the substitute from the original target in each physical dimension, and then perform normalized Euclidean distance calculation:

[0145] ;

[0146] in, It is the first The specification deviation distance of the alternative. It is the first One alternative in dimension Specifications based on delivery time forecasts. is the original contract subject matter in dimension on delivery time.

[0147] and are the upper and lower bounds of the dimension specification requirement in the original contract.

[0148] Subsequently, the distance value is converted to a similarity score by an exponential function:

[0149] ;

[0150] This formula ensures that the closer the specifications, the higher the score, and the score range is between (0, 1].

[0151] Health condition score is directly taken from the current health index of the substitute, as the index itself has been normalized. Its calculation formula is:

[0152] ;

[0153] where, is the real-time dynamic health index of the th substitute at the evaluation moment, whose value range is between [0, 1].

[0154] Transportation cost score is used to quantify the cost of transporting the substitute to the delivery location. First, the system estimates the transportation cost . In one specific implementation, the cost can be estimated as the product of the transportation distance and the cost factor related to the material category. Subsequently, in order to incorporate it into the unified utility assessment model, it is necessary to normalize the transportation cost of all candidate substitutes:

[0155] ;

[0156] where, is the estimated transportation cost of the th substitute. and are the maximum and minimum values of the estimated transportation cost among all candidate substitutes in the current batch, respectively. This formula maps the transportation cost to the interval [0, 1], and the higher the cost, the higher the score. Since the cost is a negative indicator in the total utility model, a minus sign is used in the total formula.

[0157] After calculating the utility scores for all qualified substitutes, the utility assessment module 70 sorts the substitute list according to The values of the various items are sorted in descending order. Finally, the ordered list containing the individual item scores and the total utility score of the alternative is presented to the user terminal of the purchaser by the application server.

[0158] Referring to the drawings Figure 7 , Figure 7 is a schematic diagram of the contract reconfiguration process according to an embodiment of the present application. The process is executed by the contract reconfiguration module 80 in a preferred embodiment. The module is activated after the purchaser's user terminal selects a certain alternative DLMEU from the list of alternatives and issues a confirmation instruction, and its function is to automate the change of the contract subject matter to ensure the continuity of the contract.

[0159] The starting signal of the process is a data packet sent by the purchaser's user terminal to the application server, which contains two key pieces of information: the unique identifier of the original contract in which the risk event occurred, contractID, and the unique identifier of the alternative DLMEU selected by the user, uid_new.

[0160] Upon receiving the signal, the contract reconfiguration module 80 performs an atomic data update operation comprising a plurality of steps to ensure the consistency of the data state in the data storage unit 60. The atomic operation specifically comprises the following consecutive database transactions:

[0161] First, the module queries and locks the original contract data object according to the contractID and reads the unique identifier of the original contract subject matter, uid_orig, from it.

[0162] Second, the module issues an update instruction to the data storage unit 60 for the original DLMEU (i.e. the DLMEU pointed to by uid_orig). The instruction modifies the status field in the contract attribute set 230 from LOCKED back to AVAILABLE and clears or invalidates the contractID field. This operation releases the original material from the binding relationship with the contract.

[0163] Third, the module issues an update instruction to the data storage unit 60 for the contract data object itself. The instruction modifies the field value recording the unique identifier of the contract subject matter from uid_orig to uid_new. If there are differences in the prices or other terms of the new and old materials, the corresponding fields in the contract can also be updated at this step.

[0164] Fourth, the module issues an update instruction to the data storage unit 60 for the newly selected replacement DLMEU (i.e. the DLMEU pointed by uid_new). The instruction modifies the ownership and contract attribute set 230 from AVAILABLE or RECYCLED to LOCKED in the status field, and sets the value of the contractID field to the contractID currently being processed. This operation establishes the formal binding relationship between the new material and the contract.

[0165] All the above database update instructions are encapsulated in a transaction. Only when all the instructions are successfully completed, the transaction is committed, and the data state changes are solidified. If any step fails, the entire transaction will be rolled back, and all data will be restored to the state before the flow is started, to avoid the appearance of inconsistent intermediate states.

[0166] After the transaction is successfully committed, the contract reorganization module 80 also performs a notification distribution operation. It sends structured notification messages to the user terminals of the purchaser, the supplier of the original material, and the supplier of the new material, respectively, to explicitly inform that the contract subject has changed, and to provide the identifiers of the new and old materials and the current state of the contract.

[0167] Referring to the accompanying drawings Figure 8 , Figure 8 is a schematic diagram of a project surplus material recycling process according to an embodiment of the present application. The system provided by the embodiment of the present application also includes a mechanism for managing and recycling the value of the surplus garden materials generated during the execution of a project.

[0168] When a garden greening project generates surplus materials, the project authorized user (for example, a project manager or a site user) can start the surplus material entry process through the user terminal. The user first accurately measures the current physical specifications of the surplus materials and evaluates their health status. Then, the user submits these real-time data, together with the category, name, and other information of the materials, to the system.

[0169] After receiving the surplus material entry request, the system calls the dynamic lifecycle material ownership unit generation module 10 to create a brand new DLMEU data object for this item of surplus material. The newly generated DLMEU has the following specific configurations:

[0170] First, the system assigns it a brand new unique identifier uid;

[0171] Second, in the static attribute set 210, the initialSpec field is directly filled with the current measured specifications submitted by the user;

[0172] Most importantly, 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 set directly to RECYCLED.

[0173] The project surplus recycling pool is not a separate physical storage unit, but a logical data set managed by a specific state identifier in the data storage unit 60. Specifically, the recycling pool is logically composed of all DLMEUs whose status field value is RECYCLED. The system manages, retrieves, and calls resources in this pool through querying and filtering the status field.

[0174] The surplus DLMEUs in this recycling pool are designed to seamlessly re-enter the supply chain. In specific implementations, the forward contract management module 20 when initially matching new forward demand, and the global substitute search module 40 when looking for substitutes for contracts at risk, both of their internal database query logic are configured to include both AVAILABLE and RECYCLED states.

[0175] In this way, project surplus and regular supplier inventory together constitute the complete set of materials available to the system, thereby realizing the reuse of surplus value.

[0176] When a DLMEU with a status of RECYCLED is selected by a buyer and a new forward contract is signed, the forward contract management module 20 or the contract restructuring module 80 will change its status field from RECYCLED to LOCKED and associate a new contract ID. This change of state indicates that the surplus item has been successfully called from the recycling pool and has re-entered the active contract fulfillment cycle, completing its value cycle.

[0177] In order to better understand the technical solutions of the present application, the workflow of the system and method provided by the present application will be described in detail below through a specific application scenario.

[0178] The scenario is set as follows:

[0179] Buyer A: an entity planning to build a large park project, which needs a batch of specific spec silver ginkgo trees and requires delivery in 18 months.

[0180] Supplier A: a nursery supplier.

[0181] Supplier B: the project department of another completed project, holding surplus landscaping materials that can be recycled.

[0182] The process steps are as follows:

[0183] 1. Material registration and DLMEU generation:

[0184] Supplier A has a batch of healthy ginkgo saplings. Its staff, through a user terminal, enters the initial data of this batch into the system, including species "ginkgo", current average height 2.5 meters, and breast diameter 4 centimeters. The system calls the dynamic life cycle material ownership unit generation module 10 to create a DLMEU for this batch of saplings, assigns it a unique identifier UID-A, and sets its status status to AVAILABLE.

[0185] 2. Future contract demand and matching:

[0186] 18 months later, purchaser A, for its park project, issues a future procurement demand through the system: 10 ginkgo trees are needed, with the size requirement of height between [4.8, 5.2] meters and breast diameter between [7.5, 8.5] centimeters, and the acceptable minimum health index 0.8.

[0187] After receiving this demand, the future contract management module 20 starts matching. It filters out UID-A as a candidate. The future contract management module 20 calls the growth trend prediction function of the data processing and evaluation unit 50. According to the historical health data of UID-A and the growth model, the system predicts that its size will reach 5.0 meters in height and 8.0 centimeters in breast diameter at the delivery time 18 months later, fully meeting the demand size range .

[0188] 3. Contract generation and locking:

[0189] Purchaser A confirms the selection of supplier A's UID-A. The future contract management module 20 generates an electronic future contract with contract ID CID-123. In this contract, the system calculates and sets the contract risk threshold according to the size range and health index of UID-A . Then, the future contract management module 20 updates the status of UID-A from AVAILABLE to LOCKED, and associates its contractID field to CID-123.

[0190] 4. Risk monitoring and event triggering:

[0191] In the next 12 months, supplier A continues to maintain this batch of ginkgo trees and submits dynamic data to the system through Internet of Things devices and manual input. The data processing and evaluation unit 50 continuously calculates its health index, which has been maintained above 0.9.

[0192] However, in the 13th month, due to an unexpected pest and disease, the dynamic health index of UID-A The risk monitoring engine 30 deployed on the server detects this situation satisfies the risk condition in its routine polling scan:

[0193] ;

[0194] The engine immediately triggers a risk event and packs the requirement information of the original contract CID-123 into a control signal and sends it to the global substitute search module 40.

[0195] 4. Global Substitute Search and Surplus Discovery:

[0196] The global substitute search module 40 is activated. It searches the entire data storage unit 60 according to the original requirement, the search range covers all DLMEUs with status AVAILABLE or RECYCLED.

[0197] The search module discovers that supplier B entered a batch of ginkgo trees from the surplus of a project into the system a month ago, generating UID-B, whose status is RECYCLED. The current specifications of this batch of trees (height 5.1 meters, diameter at breast height 8.2 centimeters) have met the delivery requirements, and its current health index is 0.92. UID-B is therefore identified as a qualified substitute.

[0198] 5. Utility Evaluation and Decision Support:

[0199] The utility evaluation module 70 evaluates all qualified substitutes including UID-B. Since UID-B (from project surplus) is geographically closer, its transportation cost score is lower; its current specifications are highly consistent with the requirements, and the specification similarity score is higher. After comprehensive calculation, UID-B obtains the highest total utility score U. The system pushes this ranking result to the user terminal of the buyer A.

[0200] 6. Contract Reorganization:

[0201] The buyer A adopts the system's suggestion and chooses UID-B as a substitute. The contract reorganization module 80 performs atomic transactions:

[0202] Unlock UID-A from LOCKED to AVAILABLE.

[0203] Update the material identifier associated in the contract CID-123 from UID-A to UID-B.

[0204] Update the status of UID-B from RECYCLED to LOCKED.

[0205] Through the above process, the system actively identifies and solves the potential delivery risk in the supply chain without interrupting the contract, and successfully completes the seamless replacement of the contract subject matter by calling the resources in the project surplus recycling pool, ensuring that the final project demand of the purchaser A is met.

[0206] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications, changes, omissions, substitutions and adaptations can be made by those skilled in the art without departing from the application, which is defined by the following claims and their equivalents.

Claims

1. A cloud-based collaborative management system for the garden materials supply chain, characterized in that: include: The dynamic lifecycle material ownership unit generation module is used to create corresponding dynamic lifecycle material ownership units 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. The dynamic attribute set includes: A dynamic health index is used to quantify the current health status of the garden materials; and Growth trend prediction data is used to predict the physical specifications of the garden materials at future points in time based on a preset growth model function. The forward contract management module is used to calculate the predicted delivery time of the dynamic life cycle material ownership unit in the long term using the growth trend prediction data, and to match the predicted specifications of the dynamic life cycle material ownership unit with the long term demand of the purchaser to generate a forward contract, set a contract risk threshold in the contract, and lock the status of the dynamic life cycle material ownership unit. The risk monitoring engine is used to continuously monitor the dynamic health index of the dynamic attribute set of the dynamic lifecycle material ownership unit that is in a locked state, and to 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 lifecycle material ownership units when the risk event is triggered.

2. The cloud-based collaborative management system for garden materials supply chain according to claim 1, characterized in that, The system also includes a dynamic health index assessment module, which is configured as follows: Raw measurements of multiple vital sign parameters related to the garden materials were collected; The original measurement values ​​are processed using a normalization function; The dynamic health index is calculated by weighting and summing the normalized parameter values.

3. The cloud-based collaborative management system for garden materials supply chain according to claim 1, characterized in that, The search scope of the global alternative search module is configured to include: Dynamic lifecycle material ownership units held by one or more suppliers and in an available state; and Dynamic lifecycle material ownership units stored in the project surplus material recycling pool.

4. The cloud-based collaborative management system for garden materials supply chain according to claim 3, characterized in that, The system also includes a utility evaluation module, which is configured to: When the global alternative search module finds 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.

5. The cloud-based collaborative management system for garden materials supply chain according to claim 4, 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 lifecycle material ownership unit; and Estimated transportation costs for transporting the alternative dynamic lifecycle material ownership units to the delivery location.

6. The cloud-based collaborative management system for garden materials supply chain according to claim 3, characterized in that, The dynamic lifecycle material ownership unit generation module is further configured as follows: Receive the remaining material information of completed projects, create new dynamic lifecycle material ownership units for the remaining materials, initialize their ownership and status information, and store them in the project's remaining material recycling pool.

7. The cloud-based collaborative management system for garden materials supply chain according to claim 1, characterized in that, The ownership and contract attribute set of the dynamic lifecycle material ownership unit includes: Current owner identifier; The current status identifier of the dynamic lifecycle material ownership unit, which indicates whether it is available, locked, or in transit; and If the current status is identified as locked, it also includes the associated forward contract identifier.

8. The cloud-based collaborative management system for garden materials supply chain according to claim 1, characterized in that, The system also includes a contract restructuring module, which 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 change of the subject matter of the forward contract is guided to be completed.

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