A blockchain-based inventory management system for bamboo cellulose raw materials

Abstract

This invention discloses a blockchain-based inventory management system for bamboo cellulose raw materials, specifically in the field of on-chain inventory management. It addresses the problems of quality degradation, cross-warehouse transfers, and low intelligence in transaction triggering of traditional bamboo cellulose raw materials during the storage cycle. This invention constructs a digital fingerprint of the raw materials by collecting their core physical characteristics and batch information; it predicts quality changes in the next transaction window based on a dynamic quality degradation model combined with storage environment parameters, thus exposing risks in advance; when the degradation exceeds a threshold, it automatically enters on-chain auction, selecting trading partners based on anonymous bidding and reputation weight; for continuously unsold inventory, it calculates a transfer priority index through a global inventory map and automatically executes cross-warehouse transfers. This mechanism achieves reliable recording, dynamic early warning, and automatic decision-making throughout the entire inventory management process, improving the efficiency of raw material circulation and quality management capabilities under multi-warehouse collaboration.

Description

Technical Field

[0001] This invention relates to the field of on-chain inventory management technology, and more specifically, to an inventory management system for bamboo cellulose preparation raw materials based on blockchain. Background Technology

[0002] In the bamboo cellulose preparation industry, the quality of raw materials generally deteriorates over time during harvesting, storage, transportation, and pre-processing. This is especially true in areas with high humidity, high temperature, or fluctuating storage environments, where core physical indicators such as fiber length distribution and cellulose content typically show a downward trend. This results in significant differences in the quality retention capacity of raw materials across different warehouses. Traditional inventory management methods primarily rely on manual inspections or batch management based on static records from the warehousing system. These methods struggle to quantitatively assess the dynamic changes in raw material quality and cannot achieve advance scheduling based on deterioration trends.

[0003] Furthermore, traditional raw material trading models generally rely on offline negotiations or simple online publishing mechanisms, resulting in low transparency regarding raw material quality and information asymmetry between suppliers and consumers, leading to low transaction efficiency. When raw material quality approaches its processing limits, suppliers cannot trigger disposal procedures in a timely manner, resulting in raw material depreciation or waste. Against this backdrop, there is a lack of a method that can incorporate the dynamic changes in bamboo cellulose raw material quality into the entire inventory management process, and automate the processing of key behaviors such as storage environment, quality degradation trends, competitive bidding, and cross-warehouse transfers within a reliable on-chain data system.

[0004] Therefore, a management system is needed that leverages the immutability of blockchain and the automatic execution characteristics of smart contracts to construct digital fingerprints for raw materials, drive transaction and allocation decisions based on quality prediction, and achieve end-to-end traceability, in order to solve problems such as lagging quality assessment, crude allocation decisions, and delayed transaction triggering in existing inventory management methods. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a blockchain-based inventory management system for bamboo cellulose preparation raw materials to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A blockchain-based inventory management system for bamboo cellulose preparation raw materials includes:

[0008] The inventory creation module is used to obtain the quality indicators, origin, and harvest batch information of bamboo cellulose raw materials, and encrypt them together as a digital fingerprint of the raw materials, anchoring it to the blockchain network to create the corresponding inventory unit.

[0009] The quality prediction module is used to establish a dynamic quality decay model for each inventory unit. Based on the storage environment parameters, it predicts the estimated value of the quality indicators for the next automatic transaction time window. When the decay of the raw material quality indicators of the inventory unit exceeds the set decay threshold, it is automatically marked as an on-chain auction state.

[0010] The auction monitoring module is used to continuously monitor all inventory units on the blockchain, dynamically reverse auction the inventory units marked as being in an on-chain auction state, and broadcast the raw material data information of the inventory to all certified consumer nodes.

[0011] The auction election module is used to dynamically set the starting price based on the decay rate of raw material quality indicators of inventory units. It conducts a comprehensive evaluation based on the anonymous bids and historical performance reputation of consumer nodes, elects the winning consumer node, locks the corresponding inventory assets, and generates an on-chain electronic transaction contract.

[0012] The cross-warehouse transfer module is used to trigger cross-warehouse transfers when an inventory unit in the on-chain auction status enters the unsold state. It uses a global inventory map to locate the optimal target warehouse and automatically completes the on-chain transfer of asset ownership.

[0013] As a further aspect of the present invention, the inventory establishment module acquires the quality indicators, origin, and harvest batch information of bamboo cellulose raw materials, and encrypts them together into a raw material digital fingerprint, anchoring it to the blockchain network to create a corresponding inventory unit. Specifically, this includes:

[0014] The fiber length distribution and cellulose content of bamboo cellulose raw materials were collected as the core physical property dataset.

[0015] The dispersion of fiber length distribution is fused with cellulose content to calculate and convert it into quantifiable raw material quality indicators. These quality indicators are then combined with the month code and geographical coordinates of the harvest batch.

[0016] An asymmetric encryption algorithm is used to perform encryption operations on the spliced ​​complete dataset to generate a raw material digital fingerprint. The raw material digital fingerprint and the current blockchain timestamp are submitted to the network node. After consensus verification, a uniquely identified inventory unit is created.

[0017] As a further aspect of the present invention, the quality prediction module specifically includes establishing a dynamic quality decay model for each inventory unit, which specifically includes:

[0018] Collect the ambient temperature sequence, ambient humidity sequence, and corresponding raw material quality index sequence for each inventory unit during the historical storage period, and divide the storage period into storage time units of fixed length.

[0019] Calculate the arithmetic mean of temperature and humidity within each storage time unit, correlate the average value with the change in quality indicators of the corresponding time unit, and establish a correlation dataset.

[0020] The least squares method is used to fit a multivariate linear equation for the change in quality indicators with respect to the average values ​​of temperature and humidity on the associated dataset, and the multivariate linear equation is used as a dynamic quality degradation model.

[0021] As a further aspect of the present invention, the quality prediction module predicts the estimated value of the quality index for the next automatic transaction time window based on warehousing environment parameters. Specifically, when the degradation of the raw material quality index of the inventory unit exceeds a set degradation threshold, it is automatically marked as an on-chain auction state.

[0022] Obtain the preset storage environment temperature and humidity parameters for the inventory unit before the next automatic transaction time window arrives;

[0023] The preset storage environment temperature and humidity parameters are input into the quality dynamic decay model. Based on the initial raw material quality index, the model calculates and outputs the estimated value of the quality index when the next automatic transaction time window arrives.

[0024] When the decline of the estimated quality index relative to the initial raw material quality index exceeds the preset decline threshold, the status field of the corresponding inventory unit will be automatically updated to the on-chain auction status.

[0025] As a further aspect of the present invention, the auction monitoring module continuously monitors all inventory units on the blockchain, dynamically reverse-bids inventory units marked as being in an on-chain auction state, and broadcasts the raw material data information of the inventory to all certified consumer nodes, specifically including:

[0026] The smart contract continuously scans for changes in the state field of all inventory units in the blockchain. When it detects an inventory unit whose state field changes to the on-chain auction state, it immediately creates the corresponding on-chain auction instance.

[0027] The auction instance calls the raw material data information of the inventory unit to assemble and generate an auction announcement that includes inventory quantity, location information and quality indicator decay rate;

[0028] The auction instance broadcasts the auction announcement to all consumer node addresses that have completed identity verification through event push on the blockchain network, and then enters the waiting bidding state.

[0029] As a further aspect of the present invention, in the auction selection module, the starting price is dynamically determined based on the decay rate of raw material quality indicators of the inventory unit, and a comprehensive score is performed based on the anonymous bids and historical performance reputation of the consumption node, specifically including:

[0030] Obtain the initial quality index data and decay rate of raw materials in the inventory unit that has entered the on-chain auction state, and multiply the base price corresponding to the initial quality index by the decay rate to obtain the adjusted starting price.

[0031] Extract historical performance records of each bidding consumer node from the blockchain storage, and calculate the reputation weight coefficient based on the proportion of on-time delivery in past transactions.

[0032] After the auction closes, encrypted bidding is initiated at each node, and the bid price is weighted by the reputation weight coefficient of the corresponding node to calculate the comprehensive score.

[0033] As a further aspect of the present invention, the auction election module, which elects the winning consumer node, locks the corresponding inventory asset, and generates an on-chain electronic transaction contract, specifically includes:

[0034] The bidding nodes are sorted in descending order of their overall scores, and the top-ranked consumer node is selected as the winning consumer node.

[0035] The smart contract binds the blockchain address of the auction winner to the owner's address field of the inventory unit, and changes the status field of the inventory unit from the on-chain auction status to the locked status, so that the transaction can be carried out when the automatic transaction time window arrives.

[0036] Based on the transaction price and raw material data of the inventory unit, a detailed transaction terms are generated, and an on-chain electronic transaction contract is created and stored.

[0037] As a further aspect of the present invention, in the cross-warehouse transfer module, when the on-chain auction status of an inventory unit enters a failed auction state, cross-warehouse transfer is triggered. The optimal target warehouse is located based on a global inventory map, and the on-chain transfer of asset ownership is automatically completed. Specifically, this includes:

[0038] The smart contract continuously monitors the inventory units in the on-chain auction state. When no valid bids are generated within a set number of consecutive storage cycles, the status of the corresponding inventory unit is changed to "unsold".

[0039] Based on the geographical location information of the unsold inventory units, scan the target warehouses with the same category of inventory and their corresponding capacity lists in the global inventory map;

[0040] The average quality index decay rate of each target warehouse during its historical storage cycle is retrieved. The average quality index decay rate is then weighted and integrated with the transportation distance from the unsold inventory unit to the target warehouse. The allocation priority index for each target warehouse is generated with capacity as a constraint.

[0041] The target warehouse with the highest allocation priority index is selected for raw material inventory allocation. The ownership address of the unsold inventory unit is updated to the address of the target warehouse through a smart contract, and an asset transfer record is generated on the blockchain.

[0042] The technical effects and advantages of this invention, a blockchain-based inventory management system for bamboo cellulose preparation raw materials:

[0043] By digitizing the quality indicators of bamboo cellulose raw materials and anchoring them to the blockchain, unique identification and tamper-proof end-to-end traceability of inventory units are achieved. This ensures that key data remains consistent and reliable throughout the entire process of harvesting, warehousing, trading, and allocation, solving the problem of easily tampered or missing traditional inventory information. Simultaneously, by constructing a dynamic quality decay model based on fiber length distribution and cellulose content, quality changes are transformed from passive recording to predictable trend analysis. This allows for the early identification of potential quality risks before the automatic trading window arrives, and automatic entry into the on-chain auction process when the quality decay exceeds a threshold, improving the timeliness and accuracy of inventory disposal. Relying on a dynamic reverse auction mechanism driven by decay magnitude, raw materials can be circulated more efficiently when quality risks increase, and fair and reliable election transactions are achieved by combining the historical performance reputation of consumer nodes.

[0044] For inventory that fails to sell at auction repeatedly, this invention utilizes a cross-warehouse transfer mechanism to generate a transfer priority index based on warehouse depreciation rate, transportation distance, and capacity limitations, thereby achieving intelligent allocation of warehousing resources and optimized management of the raw material lifecycle. Through smart contracts, the invention automatically executes inventory status updates, transaction contract generation, and asset ownership transfers, reducing manual intervention, increasing transparency and responsiveness throughout the inventory management process, and significantly improving traditional problems such as lagging quality management, low transfer efficiency, and information asymmetry in transactions. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the structure of an inventory management system for bamboo cellulose preparation raw materials based on blockchain according to the present invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0047] Example 1

[0048] Figure 1 This invention provides an inventory management system for bamboo cellulose preparation raw materials based on blockchain, comprising:

[0049] The inventory creation module is used to obtain the quality indicators, origin, and harvest batch information of bamboo cellulose raw materials, and encrypt them together as a digital fingerprint of the raw materials, anchoring it to the blockchain network to create the corresponding inventory unit.

[0050] The quality prediction module is used to establish a dynamic quality decay model for each inventory unit. Based on the storage environment parameters, it predicts the estimated value of the quality indicators for the next automatic transaction time window. When the decay of the raw material quality indicators of the inventory unit exceeds the set decay threshold, it is automatically marked as an on-chain auction state.

[0051] The auction monitoring module is used to continuously monitor all inventory units on the blockchain, dynamically reverse auction the inventory units marked as being in an on-chain auction state, and broadcast the raw material data information of the inventory to all certified consumer nodes.

[0052] The auction election module is used to dynamically set the starting price based on the decay rate of raw material quality indicators of inventory units. It conducts a comprehensive evaluation based on the anonymous bids and historical performance reputation of consumer nodes, elects the winning consumer node, locks the corresponding inventory assets, and generates an on-chain electronic transaction contract.

[0053] The cross-warehouse transfer module is used to trigger cross-warehouse transfers when an inventory unit in the on-chain auction status enters the unsold state. It uses a global inventory map to locate the optimal target warehouse and automatically completes the on-chain transfer of asset ownership.

[0054] In the inventory establishment module, the quality indicators, origin, and harvest batch information of bamboo cellulose raw materials are obtained and encrypted together into a digital fingerprint of the raw materials, which is then anchored to the blockchain network to create the corresponding inventory unit.

[0055] To address the core physical properties of bamboo cellulose raw materials, a standardized testing method based on industry-proven sample subdivision was employed for each batch of bamboo cellulose. Testing personnel selected multiple representative samples from the same harvest batch, pulverized and separated them at a constant cutting scale, and then used optical imaging combined with automated analysis equipment to measure the fiber length distribution. During the measurement process, each fiber was independently imaged and its contour identified, ensuring that both the shortest and longest fibers within the sampling range were counted. The equipment automatically identified the number of fibers in each length interval, thus obtaining a complete fiber length distribution sequence. Simultaneously, chemical titration and spectral analysis were used to detect the cellulose content in the samples, ensuring the stability and reliability of the obtained content data. Subsequently, the dispersion of the fiber length distribution was calculated. Dispersion reflects the uniformity and compactness of the fiber structure; excessive dispersion usually indicates high fiber fragmentation, thus affecting the cellulose preparation process. The dispersion here is quantitatively characterized by statistical methods to assess the shift in the distribution range. This dispersion is then integrated with the cellulose content, and a weighted approach is used to ensure that both physical characteristics jointly influence the final quality index. The weighting is determined based on long-term experimental experience from bamboo cellulose raw material processing enterprises to ensure that the quality index reflects chemical properties and structural uniformity. After calculating the quality index, it is concatenated with the month code corresponding to the harvest batch and the geographical coordinates of the collection location to form a complete, well-structured, and batch-unique raw material attribute record.

[0056] The assembled raw material dataset undergoes asymmetric encryption using a widely adopted and security-evaluated asymmetric encryption algorithm. The dataset is encrypted with a public key to ensure that any node can only verify the data and cannot reverse-engineer it. This dataset includes information such as fiber length distribution dispersion, quality indicators generated from cellulose content, harvest batch month codes, and origin coordinates. The data structure is formatted to ensure a clear and stable structure of the encrypted input, preventing inconsistencies in encryption results due to data format differences. During encryption, the module executes data segmentation, padding, and ciphertext generation according to algorithm requirements, ultimately outputting a ciphertext digital fingerprint of the raw material. This digital fingerprint is highly unique; any slight change will produce a completely different ciphertext, thus achieving precise identification of raw material batches. After the digital fingerprint is generated, it is paired and encapsulated with the current blockchain timestamp to form a transaction structure submitted for on-chain verification. The system broadcasts this structure to multiple consensus nodes through a node network. Each node receives the structure and performs consistency verification according to the established on-chain consensus mechanism, such as checking whether the submission format conforms to the on-chain data template, verifying whether the encrypted structure in the digital fingerprint meets algorithm specifications, and determining the validity of the timestamp. After successful verification, the consensus node writes the submission into a new block within the block generation cycle. Once the block is confirmed by a majority of nodes on the chain, the raw material's digital fingerprint is officially recorded on the chain, and the data is assigned an irreversible unique number on the chain. The system then creates a corresponding inventory unit based on the digital fingerprint, generates a unique identifier for the inventory unit, and records its creation time, on-chain address, and association information with the raw material batch. This allows the inventory unit to be accurately identified and tracked in subsequent processes such as quality prediction, auction, and allocation.

[0057] In the quality prediction module, a dynamic quality decay model is established for each inventory unit. Based on the storage environment parameters, the estimated value of the quality index for the next automatic transaction time window is predicted. When the decay of the raw material quality index of the inventory unit exceeds the set decay threshold, it is automatically marked as an on-chain auction state.

[0058] To construct a mathematical model that accurately reflects the dynamic degradation of bamboo cellulose raw material quality due to changes in the storage environment, the system extracts and structures continuous monitoring data generated during the past storage cycle of the target storage unit. Specifically, for each storage unit, monitoring devices within the storage facility record environmental temperature and humidity sequences at a fixed frequency. This monitoring data covers the entire storage period and reflects the intensity of environmental impact on the raw material at different times. Simultaneously, quality testing equipment periodically tests the fiber quality of the same batch of raw material, generating a quality index sequence. After collecting these three types of sequences, the system divides the complete storage cycle into continuous storage time units, each corresponding to a fixed time length, such as 24 hours or 48 hours. The time length is pre-set based on the physical characteristics of the bamboo cellulose raw material to ensure that environmental fluctuations within each time unit are statistically significant. After division, the system performs an arithmetic average of the temperature records at all monitoring moments within each storage time unit to obtain the average temperature value for that unit; the same processing is applied to all humidity records to obtain the average humidity value. Subsequently, the changes in quality indicators between two adjacent storage time units are calculated. These changes characterize the degree of decline in raw material quality during that time period. The changes in quality indicators are linked to the average temperature and average humidity of the time units using a synchronous or staggered time-point correspondence method, and then merged into a correlated dataset through a data structure. This correlated dataset contains multiple time units, each consisting of average temperature, average humidity, and the change in quality. Through this construction method, a correlated dataset with a completely clear correspondence between environmental influencing factors and quality changes is established.

[0059] The obtained associated data set is analyzed, and the least squares method is used to perform regression fitting on the correspondence between quality changes and average temperature and average humidity. The regression fitting process does not involve manually setting variables; it directly uses the actual temperature and humidity records and corresponding quality changes of each storage time unit as input. The fitting result forms a linear equation structure including temperature and humidity coefficients, which is used to characterize the linear relationship between environmental factors and quality decay. After fitting, this equation is stored as the dynamic quality decay model for this inventory unit in the off-chain execution area. Temperature and humidity parameters within the prediction period are extracted from the environmental control records of the storage facility. The prediction period length is set as the future interval from the current moment to the start of the next automatic transaction time window. The temperature and humidity parameters in this future interval are determined by the storage facility control strategy. To maintain prediction stability, the future temperature and humidity are smoothed to prevent jumps in the input data. The processed temperature and humidity parameters are input into the decay model according to the model requirements, participating in the calculation together with the initial quality indicators of the raw materials. Finally, the estimated quality indicator value of the inventory unit at the time the transaction window arrives is output. The estimated quality indicator is compared with the initial quality indicator. If the decline exceeds a pre-set decline threshold, the status field of the inventory unit is automatically updated to on-chain auction status. The decline threshold is determined based on historical processing loss data to ensure that the disposal process is triggered in a timely manner before a significant decline in quality.

[0060] The auction monitoring module continuously monitors all inventory units on the blockchain, dynamically reverse-bids inventory units marked as being in an on-chain auction state, and broadcasts the raw material data information of the inventory to all certified consumer nodes.

[0061] The smart contracts deployed in the blockchain network nodes scan the state fields of all inventory units in real time through an event listening mechanism. Each inventory unit has an independent data structure stored on the chain, including a unique identifier, raw material quality information, inventory quantity, and state fields. During its cyclical execution, the smart contract parses all state updates submitted to the chain. When the state field of an inventory unit changes from a normal storage state to an on-chain auction state, the listening module immediately captures the corresponding event. This event is generated by the blockchain's underlying event log, which records the values ​​before and after the state change and the trigger time. After confirming the state field change, the smart contract automatically creates an on-chain auction instance based on the inventory unit's unique identifier. The auction instance exists as an internal data structure of the smart contract, containing the number of auction cycles, auction status, bid record block address, and basic fields required for the auction announcement, and establishes a correlation between the instance's creation time and the triggering inventory unit.

[0062] The smart contract is executable code deployed on blockchain nodes, used to automatically parse and respond to on-chain data changes during inventory management. The smart contract predefines the data structure of inventory units and the value range of their state fields, and automatically executes state parsing logic upon receiving on-chain transactions related to inventory units. Whenever a state field of an inventory unit is updated via an on-chain transaction, the smart contract reads the new value of that field and compares it one by one with the preset on-chain auction states. When a change in state field to an on-chain auction state is detected, the smart contract immediately generates a corresponding auction instance record on the chain, including the instance number, the associated inventory unit identifier, and the internal control parameters required for the auction process, and stores the auction instance in the on-chain state storage area. The smart contract executes without manual triggering; all nodes execute consistently under the blockchain consensus mechanism, ensuring that the creation of auction instances after inventory state changes is real-time, automatic, and tamper-proof.

[0063] After the auction instance is created, the smart contract reads all raw material data corresponding to the inventory unit from on-chain storage based on the unique identifier of the inventory unit. This information includes inventory quantity, storage location information, initial quality indicators, and the previously calculated quality decay rate. After reading the data, the auction instance performs structured processing on the fields, assembling the raw material data according to the auction announcement template. The template is predefined during smart contract deployment and includes the announcement title, inventory quantity field, storage location field, quality decay rate field, and announcement generation time. During actual generation, the system fills in the fields according to the actual situation of the inventory unit. For example, the inventory quantity field is filled with the physical quantity of the current inventory batch, the location information field is filled with the geocode and warehouse number of the storage warehouse, and the quality decay rate field is displayed according to the data output by the quality prediction model. All announcement content is real on-chain data, obtained directly through contract API calls. After assembly, the auction instance stores the announcement in a designated on-chain storage area.

[0064] After the auction announcement is generated, the smart contract invokes the blockchain network's event push mechanism to broadcast the announcement content to all authenticated consumer nodes. The authentication status of consumer nodes is managed on-chain by a separate permission management contract; authenticated nodes are marked as legitimate addresses eligible to participate in bidding. When the auction instance broadcasts, it generates an event push record containing a summary of the announcement, the auction instance number, the corresponding inventory unit number, and the event trigger time, which is received by all nodes in the network. After the push is complete, the auction instance automatically updates its status to the waiting-to-bid state and internally records the bidding deadline block height. Upon receiving the announcement, if a consumer node needs to participate in the auction, it submits an encrypted bid transaction to the auction contract address before the bidding deadline. During the waiting phase, the auction instance continuously receives all bid records and sorts them by timestamp. The entire bidding process requires no additional manual coordination; it is driven by the smart contract, ensuring that the auction instance immediately enters an efficient and verifiable bidding waiting state after the announcement is broadcast.

[0065] In the bidding election module, the starting price is dynamically set based on the decay rate of the raw material quality index of the inventory unit. The consumer node is comprehensively scored based on its anonymous bid and historical performance reputation. The winning consumer node is elected, the corresponding inventory asset is locked, and an on-chain electronic transaction contract is generated.

[0066] Once a storage unit is marked as being auctioned on-chain by the smart contract, its basic data record is retrieved from the on-chain storage area based on its unique identifier. This record includes the raw material's initial quality index, current quality degradation rate, and a base price field related to that batch of raw material. The initial quality index is a quantified value calculated through physical characteristic testing during the warehousing stage, and the degradation rate is the percentage change calculated by the quality prediction module based on historical environment and future storage conditions. The base price is multiplied by the degradation rate to obtain the adjusted starting price. This calculation process is not used to predict revenue, but rather to ensure that the degree of raw material quality degradation is reflected in the auction price, enabling the auction process to accurately reflect the current value of the inventory.

[0067] Before the auction officially begins, historical transaction information of all consumer nodes is extracted from the blockchain's permission and performance record contract. Consumer nodes are entity nodes with on-chain bidding permissions, typically composed of identifiable processing enterprises or raw material purchasers. Each consumer node has an independent authorization record stored in the blockchain permission management contract, generated from the node's real-name authentication results, indicating that the node meets the eligibility requirements for participating in the auction. Each consumer node has a corresponding performance record in its historical transactions, including whether the node completed delivery on time as agreed in the contract, whether there were any delays, and the duration of those delays. When reading this information, the performance of the same node in multiple past transactions is statistically analyzed, and the node's on-time delivery ratio is calculated. To avoid a single abnormal behavior affecting the overall evaluation, the statistical process uses a fixed period window, such as the performance of the most recent ten transactions or a recent certain time range, as the evaluation basis. A higher on-time delivery ratio indicates that the node has a more stable performance capability. A reputation weight coefficient is assigned to each consumer node based on this ratio. This coefficient is a fixed value between zero and one and is used to weight the bid price when calculating the overall score.

[0068] Upon entering the bidding phase, the block height at which the bidding deadline is reached is recorded. Once the block height is reached, the smart contract automatically stops accepting new bidding transactions. Bidding transactions are submitted in encrypted form. Consumer nodes use the publicly available auction instance number on the chain as their bidding target, construct bidding information including an encrypted price field, and submit it to the auction execution contract address. After the deadline, the contract decrypts each encrypted bid price according to the decryption authorization submitted by the bidding nodes, writing the plaintext bid price into the bidding list of the auction instance. Subsequently, it reads each bid price from the bidding list and performs a direct numerical calculation with the recorded reputation weight coefficient, multiplying the bid price by the node's reputation weight coefficient. The resulting value is the node's comprehensive score. The comprehensive score is a single and explicit numerical field, stored internally in the smart contract using a list structure. After calculating the comprehensive scores for all bidding records, all nodes are sorted in descending order of their comprehensive scores. The sorting algorithm is executed directly on the chain, using the smart contract's built-in comparison logic to compare the comprehensive scores of each bidding node, ultimately forming a ranking list. The top-ranked bidding node is automatically identified as the winning consumer node, and its address is written into the winner field of the auction instance. The smart contract reads the winner's blockchain address from the auction instance's data structure and writes it into the owner address field of the inventory unit. The inventory unit's data structure is a fixed on-chain format, including owner address, status, quality, and quantity fields. When writing the new owner address, the smart contract calls a status update instruction to replace the original owner address with the winner's address in an overwrite manner. After the address binding is completed, the smart contract calls the inventory unit's status update process, updating the inventory unit's status field from "on-chain auction status" to "locked status." The "locked status" indicates that the inventory unit has completed the auction election and is awaiting the arrival of the on-chain automatic transaction time window.

[0069] Once the automatic transaction window arrives, the smart contract enters its automatic triggering phase. During this period, the contract automatically executes the transfer of inventory ownership to the winning address. The transfer operation involves writing instructions on-chain to update the final ownership information of the inventory unit and record the block height at which the transaction was completed, the winning address, and the inventory number. This transfer operation requires no external intervention and is executed by on-chain consensus nodes according to unified logic, ensuring the formal on-chain delivery of ownership of the inventory unit is completed when the transaction window arrives. After determining the winning node and binding ownership, the smart contract reads the final transaction price from the auction instance record and retrieves the raw material-related fields from the inventory unit, including inventory quantity, raw material quality indicators, origin information, batch number, and storage location information. The contract combines these fields into a transaction terms detail according to a preset format. This detail is structured data, containing price terms, quantity terms, quality terms, delivery terms, and on-chain address records for both parties. After generating the terms detail, the smart contract creates an on-chain electronic transaction contract. This contract binds the winning consumer node and the current owner address of the inventory unit, and the details are stored as static fields within the contract.

[0070] In the cross-warehouse transfer module, when the on-chain auction status of an inventory unit enters the auction failure state, cross-warehouse transfer is triggered. The optimal target warehouse is located based on the global inventory map, and the on-chain transfer of asset ownership is automatically completed.

[0071] The smart contract executes automatically as each block height advances. After a storage unit enters the on-chain auction state, the smart contract records its starting block height and marks the auction window it's in in the contract state. Subsequently, with each new block, the smart contract reads the bidding record table associated with the auction instance, which stores the bid transaction numbers submitted by all consumer nodes. If the smart contract doesn't detect a valid bid for the storage unit within several consecutive storage cycles, it determines that the auction has not attracted any participants within the specified period based on a preset cycle counter. The length of the storage cycle is determined during system deployment, for example, using the number of blocks corresponding to several days as a cycle unit. After the number of consecutive cycles reaches a set value, the smart contract updates the storage unit's status field from "on-chain auction state" to "auction unsold state." After the status update, the allocation logic is initiated. The smart contract first reads the storage unit's geographical location information from its data structure, including the warehouse's geographical coordinates and warehouse code. The system constructs a global inventory map during deployment. This map consists of off-chain synchronized data and on-chain warehouse registration records, storing a list of storage categories and capacities for each warehouse using warehouse codes as indexes. The smart contract filters warehouse nodes with matching categories from the global inventory map based on the categories of the unsold inventory units and reads the remaining capacity field for each candidate warehouse.

[0072] Each warehouse stores its historical quality degradation records for its storage cycles. These records are segmented by storage cycle and include average temperature, average humidity, and the degree of quality change in the inventory under those conditions. This data is generated by statistical analysis of the same type of raw materials during the warehouse's historical operations. After the allocation process is initiated, the smart contract reads the historical degradation records of the target warehouse and averages the quality changes across all cycles to obtain the average quality degradation rate. The average quality degradation rate represents the warehouse's long-term ability to maintain the quality of that type of raw material, and its value is written into the on-chain warehouse state structure during deployment or periodic synchronization. Subsequently, the smart contract calculates the distance between the current warehouse location coordinates of the unsold inventory unit and the geographical coordinates of the target warehouse. The distance calculation uses on-chain coordinate difference, performing only addition and subtraction operations and distance formula expansion when the input parameters are fixed. The average quality degradation rate field and the transportation distance field are two deterministic inputs, which are fused by the smart contract according to a preset weighting method. This weighting method is defined during system deployment, using the average quality degradation rate as the primary influencing factor and the transportation distance as a secondary factor, with the participation of both controlled by a preset numerical ratio. The smart contract reads the remaining capacity field of the target warehouse. If the value of the capacity field is insufficient to store the current inventory units, the allocation priority index corresponding to that warehouse is directly set to an invalid value, indicating that the warehouse does not meet the capacity requirements. For warehouses with sufficient remaining capacity, the smart contract outputs the final allocation priority index according to the weighted fusion formula.

[0073] After generating the allocation priority index for all target warehouses, the smart contract sorts the index records of these warehouses using a built-in numerical comparison logic. It identifies the warehouse with the highest index value through item-by-item comparison. Once the target warehouse is determined, the contract replaces the original owner address field of the inventory unit with its warehouse address field, updating the ownership address of the inventory unit to the on-chain address of the target warehouse. This update is achieved through a state write instruction, directly overwriting the owner field in the inventory unit structure, switching the ownership of the inventory unit from a failed auction state to a warehouse custody state. After completing the ownership modification, the smart contract writes this allocation behavior to the block by generating an on-chain transfer record. The transfer record includes information such as the inventory unit number, original owner address, target warehouse address, allocation trigger reason field (failed auction), allocation time, or block height. The smart contract writes this transfer record to the on-chain log area or a dedicated storage structure, saving it as an immutable historical entry on the blockchain. Through these operations, the inventory unit officially enters the custody state of the target warehouse, and the warehouse continues to participate in the quality monitoring and inventory management process in subsequent cycles.

[0074] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0075] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0076] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0077] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0078] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0079] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0080] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0081] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0082] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A blockchain-based inventory management system for bamboo cellulose raw materials, characterized in that, include: The inventory creation module is used to obtain the quality indicators, origin, and harvest batch information of bamboo cellulose raw materials, and encrypt them together as a digital fingerprint of the raw materials, anchoring it to the blockchain network to create the corresponding inventory unit. The quality prediction module is used to establish a dynamic quality decay model for each inventory unit. Based on the storage environment parameters, it predicts the estimated value of the quality indicators for the next automatic transaction time window. When the decay of the raw material quality indicators of the inventory unit exceeds the set decay threshold, it is automatically marked as an on-chain auction state. The auction monitoring module is used to continuously monitor all inventory units on the blockchain, dynamically reverse auction the inventory units marked as being in an on-chain auction state, and broadcast the raw material data information of the inventory to all certified consumer nodes. The auction election module is used to dynamically set the starting price based on the decay rate of raw material quality indicators of inventory units. It conducts a comprehensive evaluation based on the anonymous bids and historical performance reputation of consumer nodes, elects the winning consumer node, locks the corresponding inventory assets, and generates an on-chain electronic transaction contract. The cross-warehouse transfer module is used to trigger cross-warehouse transfer when the on-chain auction status of an inventory unit enters the auction failure state. It uses the global inventory map to find the optimal target warehouse and automatically completes the on-chain transfer of asset ownership. In the cross-warehouse transfer module, when an on-chain auctioned inventory unit enters a failed auction state, a cross-warehouse transfer is triggered. Based on a global inventory map, the optimal target warehouse is located, and the on-chain transfer of asset ownership is automatically completed. Specifically, this includes: The smart contract continuously monitors the inventory units in the on-chain auction state. When no valid bids are generated within a set number of consecutive storage cycles, the status of the corresponding inventory unit is changed to "unsold". Based on the geographical location information of the unsold inventory units, scan the target warehouses with the same category of inventory and their corresponding capacity lists in the global inventory map; The average quality index decay rate of each target warehouse during its historical storage cycle is retrieved. The average quality index decay rate is then weighted and integrated with the transportation distance from the unsold inventory unit to the target warehouse. The allocation priority index for each target warehouse is generated with capacity as a constraint. The target warehouse with the highest allocation priority index is selected for raw material inventory allocation. The ownership address of the unsold inventory unit is updated to the address of the target warehouse through a smart contract. This update is achieved through a status write instruction, which directly overwrites the owner field in the inventory unit structure, so that the ownership of the inventory unit changes from the auction failure state to the warehouse custody state, and an asset transfer record is generated on the chain.

2. The inventory management system for bamboo cellulose preparation raw materials based on blockchain according to claim 1, characterized in that, The inventory establishment module acquires the quality indicators, origin, and harvest batch information of bamboo cellulose raw materials, and encrypts them together into a digital fingerprint of the raw materials, anchoring it to the blockchain network to create the corresponding inventory unit. Specifically, this includes: The fiber length distribution and cellulose content of bamboo cellulose raw materials were collected as the core physical property dataset. The dispersion of fiber length distribution is fused with cellulose content to calculate and convert it into quantifiable raw material quality indicators. These quality indicators are then combined with the month code and geographical coordinates of the harvest batch. An asymmetric encryption algorithm is used to perform encryption operations on the spliced ​​complete dataset to generate a raw material digital fingerprint. The raw material digital fingerprint and the current blockchain timestamp are submitted to the network node. After consensus verification, a uniquely identified inventory unit is created.

3. The inventory management system for bamboo cellulose preparation raw materials based on blockchain according to claim 1, characterized in that, In the quality prediction module, establishing a dynamic quality decay model for each inventory unit specifically includes: Collect the ambient temperature sequence, ambient humidity sequence, and corresponding raw material quality index sequence for each inventory unit during the historical storage period, and divide the storage period into storage time units of fixed length. Calculate the arithmetic mean of temperature and humidity within each storage time unit, correlate the average value with the change in quality indicators of the corresponding time unit, and establish a correlation dataset. The least squares method was used to fit a multivariate linear equation for the change in quality indicators with respect to the average values ​​of temperature and humidity on the associated dataset, and the multivariate linear equation was used as a dynamic quality degradation model.

4. The inventory management system for bamboo cellulose preparation raw materials based on blockchain according to claim 1, characterized in that, In the quality prediction module, the estimated value of quality indicators for the next automatic transaction time window is predicted based on warehousing environment parameters. When the degradation of the raw material quality indicators of the inventory unit exceeds the set degradation threshold, it is automatically marked as an on-chain auction state, specifically including: Obtain the preset storage environment temperature and humidity parameters for the inventory unit before the next automatic transaction time window arrives; The preset storage environment temperature and humidity parameters are input into the quality dynamic decay model. Based on the initial raw material quality index, the model calculates and outputs the estimated value of the quality index when the next automatic transaction time window arrives. When the decline of the estimated quality index relative to the initial raw material quality index exceeds the preset decline threshold, the status field of the corresponding inventory unit will be automatically updated to the on-chain auction status.

5. The inventory management system for bamboo cellulose preparation raw materials based on blockchain according to claim 1, characterized in that, The auction monitoring module continuously monitors all inventory units on the blockchain, dynamically reverse-bids inventory units marked as being in an on-chain auction state, and broadcasts the raw material data information of the inventory to all certified consumer nodes. Specifically, this includes: The smart contract continuously scans for changes in the state field of all inventory units in the blockchain. When it detects an inventory unit whose state field changes to the on-chain auction state, it immediately creates the corresponding on-chain auction instance. The auction instance calls the raw material data information of the inventory unit to assemble and generate an auction announcement that includes inventory quantity, location information and quality indicator decay rate; The auction instance broadcasts the auction announcement to all consumer node addresses that have completed identity verification via event push on the blockchain network, and then enters the waiting bidding state.

6. The inventory management system for bamboo cellulose preparation raw materials based on blockchain according to claim 1, characterized in that, In the bidding election module, the starting price is dynamically set based on the decay rate of raw material quality indicators in the inventory unit, and a comprehensive score is performed based on anonymous bids and historical performance reputation at the consumption node, specifically including: Obtain the initial quality index data and decay rate of raw materials in the inventory unit that has entered the on-chain auction state, and multiply the base price corresponding to the initial quality index by the decay rate to obtain the adjusted starting price. Extract historical performance records of each bidding consumer node from the blockchain storage, and calculate the reputation weight coefficient based on the proportion of on-time delivery in past transactions. After the auction closes, encrypted bidding is initiated at each node, and the bid price is weighted by the reputation weight coefficient of the corresponding node to calculate the comprehensive score.

7. The inventory management system for bamboo cellulose preparation raw materials based on blockchain according to claim 1, characterized in that, In the auction election module, the process of electing the winning consumer node, locking the corresponding inventory assets, and generating an on-chain electronic transaction contract specifically includes: The bidding nodes are sorted in descending order of their overall scores, and the top-ranked consumer node is selected as the winning consumer node. The smart contract binds the blockchain address of the auction winner to the owner's address field of the inventory unit, and changes the status field of the inventory unit from the on-chain auction status to the locked status, so that the transaction can be carried out when the automatic transaction time window arrives. Based on the transaction price and raw material data of the inventory unit, a detailed transaction terms are generated, and an on-chain electronic transaction contract is created and stored.

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