Warehouse receipt supervision method and platform based on internet of things

Abstract

The application provides a warehouse receipt supervision method and platform based on Internet of Things, and relates to the technical field of warehouse management, which comprises the following steps: deploying Internet of Things equipment in the warehouse, collecting the state information of warehouse goods in real time, preprocessing the collected data, and generating a warehouse receipt; a unique initial hash value is generated for each warehouse receipt, and each time a new warehouse receipt is generated, the warehouse receipt is combined with the current hash value; the application deploys Internet of Things equipment in the warehouse, collects the state information of warehouse goods in real time, generates a warehouse receipt, and realizes real-time processing and verification of the warehouse receipt information through a dynamic hash chain algorithm combined with a block chain, and then stores the warehouse receipt information in the block chain, thereby ensuring the authenticity and integrity of the data; the verification rules and business logic of the warehouse receipt information can be defined through an automatic algorithm, and the data verification and updating operations are automatically executed, which facilitates subsequent query, monitoring and auditing; the overall supervision process is automatically operated in cooperation with the algorithm, thereby saving a large amount of manpower, material resources and financial resources.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of warehouse management, and particularly relates to a warehouse receipt supervision method and platform based on Internet of Things. BACKGROUND

[0002] Warehouse receipt supervision refers to the process of supervision and management of warehouse receipts and the warehouse goods represented by the warehouse receipts. Specifically, the warehouse receipt is a voucher for extracting warehouse goods issued by the warehouse keeper to the depositor after receiving the warehouse goods delivered by the depositor. The warehouse receipt is not only the basis for the depositor to extract the warehouse goods, but also can be circulated through endorsement and other means. Warehouse receipt supervision involves supervision and management of each link such as generation, registration, circulation, pledge and cancellation of the warehouse receipt, so as to ensure the authenticity and validity of the warehouse receipt and protect the rights and interests of both parties. At the same time, warehouse receipt supervision also includes supervision and inspection of the quantity, quality and storage conditions of the warehouse goods, so as to ensure the safety and integrity of the warehouse goods. Through warehouse receipt supervision, the transparency and safety of transactions can be improved, and the risk of transactions can be reduced, thereby providing more reliable and convenient financing and transaction services for market participants.

[0003] However, the existing warehouse receipt supervision also has the following disadvantages:

[0004] Warehouse receipt supervision involves multiple links, including generation, registration, circulation and the like of the warehouse receipt. A large amount of manpower, material resources and financial resources need to be invested for supervision of these links. High supervision cost will become an obstacle for some enterprises to participate in warehouse receipt transactions.

[0005] Although warehouse receipt supervision aims to improve the transparency of transactions, in actual operation, due to poor information circulation or inadequate supervision, the problem of information asymmetry occurs, which will affect the understanding of the real situation of the warehouse goods by both parties, thereby increasing the transaction risk.

[0006] Since warehouse receipt supervision involves complex legal relationships and compliance requirements, if the supervision measures are not in place or the laws and regulations are not perfect, legal risks will occur, including legal disputes involved in the warehouse receipt verification process, rules problems such as the responsibility for damage or loss of the warehouse goods, and the like.

[0007] With the development of science and technology, warehouse receipt supervision also faces technical challenges. How to use modern information technology means to improve the efficiency and accuracy of warehouse receipt supervision, and how to ensure the authenticity and non-tamperability of warehouse receipt information are problems to be solved.

[0008] In the process of warehouse receipt supervision, human operation errors or intentional irregularities may also cause risks, including input errors of warehouse receipt information, which will cause losses to both parties.

[0009] Therefore, the present application proposes a warehouse receipt supervision method and platform based on Internet of Things to solve the problems in the prior art. SUMMARY

[0010] To solve the above problems, the application provides a warehouse warrant supervision method and platform based on Internet of Things, which can save a lot of manpower, material and financial resources through automatic operation of the overall supervision process cooperating with algorithm.

[0011] To achieve the purpose of the application, the application realizes the following technical solutions: a warehouse warrant supervision method based on Internet of Things, comprising the following steps:

[0012] S1: deploying Internet of Things devices inside the warehouse, collecting real-time state information of warehouse goods, and preprocessing the collected data to generate warehouse warrants;

[0013] S2: generating a unique initial hash value for each warehouse warrant, combining the warehouse warrant with the current hash value each time a new warehouse warrant is generated, generating a new hash value through a hash function, and dynamically updating the hash chain;

[0014] S3: when verifying the authenticity of the warehouse warrant information, obtaining the latest hash value from the blockchain, and verifying the integrity of the hash chain through reverse calculation;

[0015] S4: storing the data processed by the dynamic hash chain algorithm on the blockchain, and verifying the data's tamper resistance and transparency using the distributed storage characteristics of the blockchain;

[0016] S5: constructing an automatic algorithm, defining the verification rules and business logic of the warehouse warrant information, and automatically performing data verification and update operations;

[0017] S6: recording the data verified by the automatic algorithm on the blockchain in the form of transactions to form encrypted warehouse warrant information and digital certificates;

[0018] S7: using big data and artificial intelligence technology to analyze, evaluate and mine warehouse warrant data, predict the demand trend of goods, and generate reports;

[0019] S8: connecting the blockchain to a visualization platform to provide query functions, real-time monitoring and auditing functions.

[0020] Further improvement lies in that the S1 comprises the following steps:

[0021] deploying RFID tags and sensors inside the warehouse;

[0022] acquiring real-time location information of the goods through RFID tags or GPS positioning technology;

[0023] using the read-write function of the RFID tag to count the number of goods in real time;

[0024] The quality parameters of the goods are monitored by sensors, including temperature and humidity.

[0025] The temperature and humidity changes in the warehouse are monitored in real time by sensors.

[0026] The Internet of Things gateway is used as a bridge to connect the central processing unit, and the collected data is transmitted from the Internet of Things device to the central processing unit.

[0027] The central processing unit removes noise, repeated and useless information from the data, converts data of different formats into a unified format, and checks the integrity and accuracy of the data through verification rules.

[0028] Data from different sources is integrated to form a complete data set, and the data set constitutes the warehouse receipt.

[0029] Further improvement lies in that the S2 comprises the following steps:

[0030] A unique initial hash value is generated for each warehouse receipt, which is calculated from the basic information of the warehouse receipt and a randomly generated salt value.

[0031] Initialization of hash value calculation:

[0032] H0=Hash(basic information + salt value)

[0033] Wherein, the basic information includes goods ID, quantity, storage location; the salt value is a randomly generated string, which is used to increase the complexity and security of the hash value.

[0034] When the Internet of Things device collects new data to generate a warehouse receipt, the warehouse receipt is combined with the current hash value to generate a new hash value through a hash function, and the hash chain is dynamically updated.

[0035] The new data collected to generate a warehouse receipt is represented as Dt, where t is the timestamp, and the new hash value is calculated as:

[0036] Ht=Hash(Ht−1+Dt+device ID+t)

[0037] Wherein, Ht−1 is the hash value at the previous time point, Dt is the data collected at the current time point, device ID is the identification of the Internet of Things device collecting data, and t is the timestamp at the current time point.

[0038] The timestamp and Internet of Things device ID of each update are recorded to ensure the traceability of the data.

[0039] Further improvement lies in that the S3 comprises the following steps:

[0040] When verifying the authenticity of the warehouse receipt information, the latest hash value is obtained from the blockchain, and the integrity of the hash chain is verified through reverse calculation.

[0041] Hn represents obtaining the latest hash value from the blockchain, and reverse calculation:

[0042] Hn−1=ReverseHash(Hn−(device IDn+n+Dn))

[0043] In turn, reverse calculation to the initial hash value H0, when the final hash value obtained is consistent with the hash value calculated at initialization, it is proved that the hash chain is complete and the data has not been tampered with;

[0044] When any link in the hash chain is tampered with, reverse calculation will not be able to obtain the correct initial hash value, which proves that the data has been tampered with.

[0045] Further improvement lies in that the S4 comprises the following steps:

[0046] The data processed by the dynamic hash chain algorithm is divided into multiple fragments, and each data fragment is encrypted to ensure that only authorized users can access the data;

[0047] A unique hash value is generated according to the data of the fragment, and the hash value is added to the fragment metadata to link the warehouse order sub-data to the stored fragments;

[0048] When verifying the tamper resistance of the data, the hash values are compared to confirm whether the data has been tampered with;

[0049] In the blockchain storage, each fragment is copied to create a redundant copy, and the copy is distributed on different nodes, and all nodes participate in the consensus process;

[0050] Information is synchronized between all nodes, and each node has the latest data copy to verify the transparency of the data.

[0051] Further improvement lies in that the S5 comprises the following steps:

[0052] The rights and obligations of each party are clearly defined by jointly agreeing on the contract by the relevant parties, and these rights and obligations are programmed into machine language to form the code of the automatic algorithm;

[0053] All relevant parties use their own private keys to digitally sign the automatic algorithm, and deploy the signed automatic algorithm to the blockchain network to become part of the blockchain, containing automatically executed logic, data update frequency, and verification conditions, when the preset conditions are triggered, the corresponding operation is automatically executed;

[0054] In the execution of data verification and update operations, the state mechanism evaluates the current state, and when all operations have been sequentially executed, the state is marked as "complete" and removed from the latest block;

[0055] When the operation is not completed, the status is marked as "in progress" and continues to be saved in the latest block, waiting for the next round of processing.

[0056] Further improvements are that the S6 includes the following steps:

[0057] When the data is verified by the automatic algorithm, a transaction record is automatically generated, which contains the hash value of the data, the storage location, and the timestamp;

[0058] The transaction record is added to the blockchain network, and a copy of the transaction record is saved on each node on the blockchain;

[0059] When the transaction record is successfully added to the blockchain, a digital certificate is automatically generated, which contains the hash value of the transaction record, the owner information, the timestamp information, and the warehouse warrant information of the previous step;

[0060] In this process, the user is provided with the function of encrypting, signing, and verifying the digital certificate and warehouse warrant information using a private key.

[0061] Further improvements are that the S7 includes the following steps:

[0062] Statistical and machine learning algorithms are used to analyze warehouse warrant data, extract key features, generate dynamic statistical charts, and identify patterns and trends in the data;

[0063] Based on the analysis results, a prediction model is established using deep learning and neural networks to predict future cargo demand trends.

[0064] According to the prediction results, the inventory management strategy is optimized, including adjusting the inventory quantity and developing a procurement plan;

[0065] The optimized inventory management strategy is converted into a report.

[0066] Further improvements are that in the S8, after accessing the visualization platform, relevant parties can query warehouse warrant information through the blockchain to understand the real-time status of warehouse goods, and supervisors can monitor and audit warehouse warrant information in real time through the blockchain to ensure the compliance and effectiveness of warehouse warrant supervision.

[0067] A warehouse warrant supervision platform based on the Internet of Things includes a data acquisition and processing module, a dynamic algorithm module, a blockchain storage module, an automatic verification unit, an evaluation module, and a visualization platform;

[0068] The data acquisition and processing module is based on the Internet of Things devices deployed in the warehouse to collect real-time status information of warehouse goods, including location, quantity, quality, temperature and humidity data, and to preprocess the collected data, including data cleaning, format conversion and verification, to ensure the accuracy and consistency of the data, and to generate warehouse warrants.

[0069] The dynamic algorithm module is used for generating a unique initial hash value for each warehouse warrant, which is calculated by the basic information of the warehouse warrant and a randomly generated salt value, and each time a new warehouse warrant is generated, the warehouse warrant data is combined with the current hash value to generate a new hash value through a hash function to realize dynamic updating of the hash chain.

[0070] The blockchain storage module is used for storing data processed by the dynamic hash chain algorithm, and the distributed storage characteristics of the blockchain are used to verify the non-tamperability and transparency of the data.

[0071] The automatic verification unit is used to define the verification rules and business logic of the warehouse warrant information, including data update frequency and verification conditions, to automatically perform data verification and update operations, and after verification, the transaction is recorded on the blockchain storage module to form encrypted warehouse warrant information and digital certificates, ensuring the authenticity and integrity of the data.

[0072] The evaluation module uses big data and artificial intelligence technology to deeply analyze and intelligently evaluate the collected data, predicts the demand trend of goods by mining and analyzing historical data, optimizes inventory management strategies, and generates reports.

[0073] The visualization platform is used to display all data of the data acquisition and processing module, the dynamic algorithm module, the blockchain storage module, the automatic verification unit and the evaluation module, and provides visual query function, real-time monitoring and auditing function.

[0074] The beneficial effects of the present application are:

[0075] 1、The present application deploys Internet of Things devices inside the warehouse, collects the state information of the warehouse goods in real time, generates warehouse warrants, and realizes real-time processing and verification of warehouse warrant information through dynamic hash chain algorithm and blockchain, and then stores it in the blockchain to ensure the authenticity and integrity of the data.

[0076] 2、The present application generates a new hash value each time a new warehouse warrant is generated, and records the timestamp and device ID, realizes the traceability of the data, the irreversibility of the hash chain and the non-tamperability of the blockchain ensure the security of the data, and the distributed storage characteristics of the blockchain make the warehouse warrant information transparent, so that stakeholders can query and audit the warehouse warrant information at any time, and facilitate the understanding of the real situation of the warehouse goods by the transaction parties.

[0077] 3、The present application clearly defines the rights and obligations of each party by jointly negotiating contracts with several related parties, and programs these rights and obligations into machine language to form the code of automatic algorithms; all related parties use their own private keys to digitally sign the automatic algorithms, and deploy the signed automatic algorithms into the blockchain network to become part of the blockchain; when the preset conditions are triggered, the corresponding data verification and update operations are automatically executed, reducing legal disputes, warehouse damage or loss of liability and other rule problems, and also reducing manual intervention, improving regulatory efficiency and accuracy.

[0078] 4、The present application uses big data and artificial intelligence technology to analyze, evaluate and mine warehouse receipt data, and predicts the demand trend of goods, thereby optimizing the inventory management strategy and diversifying the functions. BRIEF DESCRIPTION OF DRAWINGS

[0079] Figure 1 The method flowchart of the present application is shown in the figure;

[0080] Figure 2 The platform schematic diagram of the present application is shown in the figure. DETAILED DESCRIPTION

[0081] In order to deepen the understanding of the present application, the present application will be further described in combination with the embodiments below, and the present embodiment is only used to explain the present application and does not constitute a limitation on the protection scope of the present application.

[0082] Embodiment one

[0083] According to Figure 1 The present embodiment proposes a warehouse receipt supervision method based on the Internet of Things, which includes the following steps:

[0084] S1: Deploying Internet of Things devices inside the warehouse, collecting real-time status information of warehouse goods, and preprocessing the collected data to generate warehouse receipts; specifically including the following steps: deploying RFID tags and sensors inside the warehouse; obtaining real-time location information of goods through RFID tags or GPS positioning technology; using the read-write function of RFID tags to count the number of goods in real time; monitoring the quality parameters of goods, including temperature and humidity, through sensors; monitoring the changes in temperature and humidity in the warehouse in real time through sensors; using the Internet of Things gateway as a bridge to connect the central processing unit, transmitting the collected data from the Internet of Things device to the central processing unit; removing noise, repeated items, and other useless information from the data in the central processing unit, converting data of different formats to a unified format, and checking the completeness and accuracy of the data through verification rules; integrating data from different sources to form a complete data set, and using the data set to constitute a warehouse receipt. Data cleaning: remove noise, repeated items, and other useless information from the data to improve data quality. Format conversion: convert data of different formats to a unified format for subsequent analysis and processing. Data verification: check the completeness and accuracy of the data through verification rules to ensure the reliability of the data. Data integration: integrate data from different sources to form a complete data set to support subsequent decision analysis.

[0085] RFID tag: RFID (Radio Frequency Identification) tag is a non-contact automatic identification technology that can automatically identify target objects and obtain related data through radio frequency signals. In the warehouse, RFID tags are usually attached to goods or shelves to track the location and status of goods in real time. Sensors: Sensors are used to monitor environmental parameters in the warehouse, such as temperature and humidity, light intensity, etc. These sensors can collect data in real time and transmit them to the central processing unit for analysis and processing through Internet of Things technology. Through RFID tags or GPS positioning technology, the location information of goods can be obtained in real time to help managers quickly locate goods. Using the read-write function of RFID tags, the number of goods can be counted in real time to ensure the accuracy of inventory data. Through sensors, the quality parameters of goods such as temperature and humidity can be monitored to discover changes in the quality of goods in a timely manner and take appropriate measures. Temperature and humidity sensors can monitor the changes in temperature and humidity in the warehouse in real time to provide suitable environmental conditions for the storage of goods.

[0086] S2: Generate a unique initial hash value for each warehouse receipt, combine the warehouse receipt with the current hash value each time a new warehouse receipt is generated, generate a new hash value through a hash function, and dynamically update the hash chain; specifically including the following steps: generating a unique initial hash value for each warehouse receipt, which is calculated from the basic information of the warehouse receipt and a randomly generated salt value; initializing the hash value calculation:

[0087] H0 = Hash(basic information + salt value)

[0088] The basic information includes cargo ID, quantity, and storage location; the salt value is a randomly generated string used to increase the complexity and security of the hash value; each time an IoT device collects new data and generates a warehouse receipt, the warehouse receipt is combined with the current hash value, and a new hash value is generated through a hash function, dynamically updating the hash chain; the newly collected data generating the warehouse receipt is represented as Dt, where t is the timestamp, and the new hash value is calculated as follows:

[0089] Ht = Hash(Ht−1+Dt+DeviceID+t)

[0090] Where Ht−1 is the hash value of the previous time point, Dt is the data collected at the current time point, Device ID is the IoT device identifier for collecting data, and t is the timestamp of the current time point; the timestamp and IoT device ID of each update are recorded to ensure data traceability.

[0091] S3: When verifying the authenticity of warehouse receipt information, obtain the latest hash value from the blockchain and verify the integrity of the hash chain through reverse calculation; specifically, it includes the following steps: When verifying the authenticity of warehouse receipt information, obtain the latest hash value from the blockchain and verify the integrity of the hash chain through reverse calculation;

[0092] Hn represents the latest hash value obtained from the blockchain, calculated in reverse:

[0093] Hn−1=ReverseHash(Hn−(Device IDn+n+Dn))

[0094] The hash chain is calculated in reverse order back to the initial hash value H0. If the final hash value is consistent with the hash value calculated during initialization, it proves that the hash chain is complete and the data has not been tampered with. If any link in the hash chain is tampered with, the reverse calculation will not yield the correct initial hash value, which proves that the data has been tampered with.

[0095] Dynamic hash chaining is a data integrity verification method based on hash functions. It ensures data integrity and immutability by linking a series of data blocks together to form a continuous hash chain. In scenarios such as warehouse receipt supervision, dynamic hash chaining is used to verify the authenticity of warehouse receipt information and ensure that data has not been tampered with during transmission and storage.

[0096] Initialize hash value calculation

[0097] In the initialization phase of the dynamic hash chain algorithm, an initial hash value H0 needs to be calculated. This hash value is obtained by hashing the basic information (such as goods ID, quantity, storage location, etc.) and a randomly generated salt value. The basic information is the core data in warehouse warrant supervision, while the salt value is used to increase the complexity and security of the hash value, preventing hash collisions and attacks.

[0098] The specific hash operation process can be represented as:

[0099] H0 = Hash(basic information + salt value)

[0100] Where Hash represents the hash function, which can convert an arbitrary length input into a fixed length output (i.e. hash value).

[0101] Dynamic hash value update

[0102] In the update phase of the dynamic hash chain algorithm, the hash value on the hash chain is updated every time the Internet of Things device collects new data. The new hash value is obtained by hashing the hash value at the previous time point, the data collected at the current time point, the device ID, and the timestamp at the current time point.

[0103] The specific hash operation process can be represented as:

[0104] Ht = Hash(Ht-1 + Dt + device ID + t)

[0105] Where Ht represents the hash value at the current time point, Ht-1 represents the hash value at the previous time point, Dt represents the data collected at the current time point, device ID represents the Internet of Things device identifier that collects the data, and t represents the timestamp at the current time point.

[0106] In this way, each new data block will establish a link with the previous data block through the hash value, forming a continuous hash chain. If any data block in the chain is tampered with, its hash value will change, causing all subsequent data blocks to change their hash values, making it easy to be detected.

[0107] Reverse verification

[0108] In the verification phase of the dynamic hash chain algorithm, when the authenticity of the warehouse warrant information needs to be verified, the latest hash value Hn can be obtained from the blockchain, and the hash value at each time point can be calculated in reverse until the initial hash value H0 is obtained. If the final hash value is consistent with the hash value calculated during initialization, it proves that the hash chain is complete and the data has not been tampered with.

[0109] The specific reverse calculation process can be represented as:

[0110] Hn-1 = ReverseHash(Hn - (DeviceIDn + n + Dn))

[0111] where ReverseHash represents the reverse hash function (in fact, the hash function is one-way, but here it is assumed that there is a reverse process for verification, which is actually verified by recalculation). In practical applications, a real reverse hash function is not required. Instead, the integrity of the hash chain is verified by reversing the calculation process of the hash chain from Hn to H0. The reverse verification process is usually performed when data integrity needs to be verified, such as in warehouse receipt transactions, collateral or financing scenarios. Through reverse verification, the authenticity and integrity of warehouse receipt information can be ensured, reducing transaction risks.

[0112] The dynamic hash chain algorithm is an effective data integrity verification method that links a series of data blocks to form a continuous hash chain, ensuring data integrity and tamper resistance. In warehouse supervision scenarios, the dynamic hash chain algorithm can be used to verify the authenticity of warehouse receipt information, ensuring that data is not tampered with during transmission and storage. Through initialization of hash value calculation, dynamic hash value update and reverse verification, the dynamic hash chain algorithm can provide a secure and reliable data integrity verification mechanism.

[0113] S4: Store the data processed by the dynamic hash chain algorithm on the blockchain, and use the distributed storage characteristics of the blockchain to verify the tamper resistance and transparency of the data; Specifically, the following steps are included: divide the data processed by the dynamic hash chain algorithm into multiple shards, encrypt each data shard to ensure that only authorized users can access the data; Generate a unique hash value based on the shard data, and add the hash value to the shard metadata to link the warehouse receipt subdivision data to the stored shard; When verifying the tamper resistance of the data, compare the hash values to confirm whether the data has been tampered with; In the blockchain storage, replicate each shard to create redundant copies, and distribute the copies to different nodes, with all nodes participating in the consensus process; All nodes synchronize information, and each node has the latest data copy to verify the transparency of the data.

[0114] S5: Build an automatic algorithm, define the verification rules and business logic of warehouse receipt information, and automatically perform data verification and update operations; Specifically including the following steps; Through the joint agreement of several relevant parties, the rights and obligations of each party are clearly defined, and these rights and obligations are programmed into machine language to form the code of the automatic algorithm; All relevant parties use their own private keys to digitally sign the automatic algorithm, and deploy the signed automatic algorithm to the blockchain network to become part of the blockchain, containing automatically executed logic, data update frequency, and verification conditions, when the preset conditions are triggered, the corresponding operation is automatically executed; In the execution of data verification and update operations, the state mechanism evaluates the current state, when all operations have been sequentially executed, the state is marked as "completed" and removed from the latest block; When the operation has not been completed, the state is marked as "in progress" and continues to be saved in the latest block, waiting for the next round of processing. The execution of the automatic algorithm does not require the intervention of a third party, and is completely dependent on the consensus mechanism of the blockchain network and the automatic algorithm code. When the conditions are met, the operation will be automatically executed, and a notification of successful execution will be sent to the user. Since the rights and obligations of each party are clearly defined through the joint agreement of several relevant parties, and these rights and obligations are programmed into machine language, legal disputes, responsibility for damage or loss of storage, and other rules can be reduced, and manual intervention can be reduced, improving regulatory efficiency and accuracy.

[0115] S6: The data verified by the automatic algorithm is recorded on the blockchain in the form of a transaction, forming encrypted warehouse receipt information and digital certificates; Specifically including the following steps: When the data is verified by the automatic algorithm, a transaction record is automatically generated, which contains the hash value, storage location, and timestamp of the data; Add the transaction record to the blockchain network, and save a copy of the transaction record on each node on the blockchain; When the transaction record is successfully added to the blockchain, a digital certificate is automatically generated, containing the hash value of the transaction record, owner information, and timestamp information, and is associated with the warehouse receipt of the previous step; In this process, the user is provided with the function of encrypting, signing, and verifying the digital certificate and warehouse receipt information using the private key. Authorized users can query and access the digital certificate through the automatic algorithm or the blockchain network. Users can sign and verify the digital certificate using the private key to ensure the authenticity and integrity of the certificate. The blockchain network uses encryption algorithms and consensus mechanisms to ensure the security and tamper resistance of the data. The automatic algorithm code is strictly tested and audited to avoid security vulnerabilities and errors. Regularly maintain and upgrade the blockchain network and automatic algorithm to ensure the stability and performance of the system. Monitor the running state and abnormal conditions of the system, and respond and handle problems in a timely manner.

[0116] S7: Utilize big data and artificial intelligence technologies to analyze, evaluate, and mine warehouse receipt data, predict demand trends for goods, and generate reports; including the following steps: use statistical and machine learning algorithms to analyze warehouse receipt data, extract key features, generate dynamic statistical charts, and identify patterns and trends in the data; based on the analysis results, use deep learning and neural networks to establish a prediction model to predict future demand trends for goods. Based on the prediction results, optimize inventory management strategies, including adjusting inventory levels and developing procurement plans; translate the optimized inventory management strategies into reports. Establish data indexing and query mechanisms to facilitate quick access and query of data. Implement the optimized inventory management strategies. Monitor the effectiveness of the strategies to ensure their effectiveness and timeliness. Adjust and optimize the strategies based on monitoring results.

[0117] The data preprocessing algorithm includes: missing value processing algorithm: mean filling, median filling, mode filling, etc. Outlier detection algorithm: statistical method (such as 3σ principle), distance-based method (such as K-neighbor algorithm), etc. Data standardization and normalization algorithm: Min-Max normalization, Z-score standardization, etc.

[0118] The data analysis algorithm includes: descriptive statistical analysis algorithm: mean, variance, median, mode, quartile, etc. Correlation analysis algorithm: Pearson correlation coefficient, Spearman rank correlation coefficient, etc. Clustering analysis algorithm: K-means clustering, hierarchical clustering, etc. Classification algorithm: decision tree, support vector machine, naive Bayes, etc.

[0119] The prediction algorithm includes: time series prediction algorithm: ARIMA model, exponential smoothing method, etc. Regression prediction algorithm: such as linear regression, polynomial regression, ridge regression, etc. Machine learning prediction algorithm: such as random forest, gradient boosting tree, neural network, etc.

[0120] The optimization algorithm includes: inventory optimization algorithm: Economic Order Quantity (EOQ) model, safety stock model, etc. Procurement optimization algorithm: supplier selection algorithm, procurement quantity optimization algorithm, etc.

[0121] S8: Link the block chain into the visualization platform, provide query function, real-time monitoring and audit function. After accessing the visualization platform, the relevant parties query the warehouse warrant information through the block chain, understand the real-time state of the warehouse goods, and the supervisors monitor and audit the warehouse warrant information in real time through the block chain to ensure the compliance and effectiveness of the warehouse warrant supervision. Access the visualization platform, including: perception layer: deploy sensors and Internet of Things devices to collect real-time state data of warehouse goods. Network layer: establish a secure and stable communication network to ensure that data is transmitted from the perception layer to the block chain platform. Platform layer: build a block chain-based visualization platform to provide data storage, processing and analysis environment. Application layer: develop user interface, including data visualization tools, query interface, real-time monitoring and audit module. Data access: automatically collect data of warehouse goods through Internet of Things devices and transmit them to the block chain platform in real time. Data is stored in a distributed manner on the block chain to ensure data integrity and tamper resistance. User permission management: assign different query permissions according to user roles (such as consignor, warehousing party, supervisor, etc.). After identity verification, users can access warehouse warrant information within their permission scope. The visualization platform displays warehouse warrant information in the form of charts, dashboards, etc. to users. Users can visually understand the quantity, location, status and other key information of warehouse goods. Users can query specific warehouse warrant information by inputting keywords or selecting filtering conditions. The query results will be displayed in real time on the visualization platform, making it easy for users to quickly obtain the required information. Real-time data collected by Internet of Things devices will be uploaded to the block chain platform in a timely manner. The visualization platform will display the latest warehouse goods status information in real time. When the warehouse goods state is abnormal (such as temperature, humidity exceeding the standard), the visualization platform will trigger an alarm. Alarm information will be displayed to users in the form of charts, text, etc. and sent through SMS, email, etc. The visualization platform will record user monitoring operation logs, including the time, user ID, etc. of operations such as query, alarm, etc. Monitoring logs can be used to audit and trace user operation behavior: auditors can access warehouse warrant information and monitoring logs on the block chain through the visualization platform. Auditors can export audit data for offline analysis and review. The visualization platform allows auditors to configure audit rules, such as setting sensitive data ranges, abnormal behavior patterns, etc. When audit data triggers audit rules, the visualization platform will issue a warning to alert auditors. Auditors can generate audit reports based on audit results, including audit scope, audit method, audit findings, audit recommendations, etc. In summary: block chain technology ensures the integrity and tamper resistance of warehouse warrant information, improving data credibility. The visualization platform makes warehouse warrant information more transparent, reducing the risk of information asymmetry. Through real-time monitoring and audit functions, supervisors can ensure the compliance of warehouse warrant supervision and timely discover and correct irregularities. The visualization platform improves the efficiency of data query, monitoring and audit, reducing labor and time costs.

[0122] Embodiment two

[0123] According to Figure 2 The embodiment shown proposes a warehouse warrant supervision platform based on Internet of Things, including data acquisition and processing module, dynamic algorithm module, blockchain storage module, automatic verification unit, evaluation module and visualization platform;

[0124] The data acquisition and processing module is based on the Internet of Things device deployed in the warehouse, which can collect the state information of the warehouse goods in real time, including location, quantity, quality, temperature and humidity data, and preprocess the collected data, including data cleaning, format conversion and verification, to ensure the accuracy and consistency of the data, and generate warehouse warrants; a large amount of manpower, material resources and financial resources are saved;

[0125] The dynamic algorithm module is used to generate a unique initial hash value for each warehouse warrant, which is calculated by the basic information of the warehouse warrant and a randomly generated salt value, and each time a new warehouse warrant is generated, the warehouse warrant data is combined with the current hash value to generate a new hash value through a hash function, realizing the dynamic update of the hash chain. At the same time, record the timestamp and Internet of Things device ID of each update to verify the authenticity of the warehouse warrant information; realize the traceability of data and ensure the security of data;

[0126] The blockchain storage module is used to store the data processed by the dynamic hash chain algorithm, and the distributed storage characteristics of the blockchain are used to verify the data's tamper resistance and transparency; the distributed storage characteristics of the blockchain make the warehouse warrant information transparent, and the stakeholders can query and audit the warehouse warrant information at any time, which is convenient for the transaction parties to understand the real situation of the warehouse goods;

[0127] The automatic verification unit is used to define the verification rules and business logic of the warehouse warrant information, including data update frequency and verification conditions, to automatically perform data verification and update operations, and record the encrypted warehouse warrant information and digital certificate on the blockchain storage module after verification, ensuring the authenticity and integrity of the data; automatically performing data verification and update operations saves a lot of manpower, material resources and financial resources, reduces legal disputes, responsibility for damage or loss of warehouse goods, and reduces manual intervention, improves supervision efficiency and accuracy;

[0128] The evaluation module uses big data and artificial intelligence technology to deeply analyze and intelligently evaluate the collected data, predicts the demand trend of goods by mining and analyzing historical data, optimizes inventory management strategies, and generates reports; the function is diversified;

[0129] The visualization platform is used to display all data of the data acquisition processing module, the dynamic algorithm module, the blockchain storage module, the automatic verification unit and the evaluation module, and provides visual query function, real-time monitoring and auditing function; the visualization platform makes the warehouse receipt information more transparent, reduces the risk of information asymmetry. Through the real-time monitoring and auditing function, the supervisory party can ensure the compliance of the warehouse receipt supervision, and timely discover and correct irregularities. The visualization platform improves the efficiency of data query, monitoring and auditing, and reduces the labor and time cost.

[0130] The warehouse interior is deployed with an Internet of Things device, real-time collection of the state information of the warehouse goods is performed, a warehouse receipt is generated, real-time processing and verification of the warehouse receipt information are realized through a dynamic hash chain algorithm and a blockchain, and then the warehouse receipt information is stored in the blockchain, so that the authenticity and integrity of the data are ensured, the verification rules and business logic of the warehouse receipt information can be defined through an automatic algorithm, automatic data verification and updating operations are performed, subsequent query, monitoring and auditing are facilitated, the overall supervision process is automatically operated in cooperation with the algorithm, a large amount of manpower, material resources and financial resources are saved. Moreover, a new hash value is generated each time a new warehouse receipt is generated, and a time stamp and a device ID are recorded, so that the traceability of the data is realized, the safety of the data is ensured by the irreversibility of the hash chain and the non-tamperability of the blockchain, the transparency of the warehouse receipt information is ensured by the distributed storage feature of the blockchain, the interested parties can query and audit the warehouse receipt information at any time, and the real situation of the warehouse goods is facilitated to be understood by the transaction parties. Meanwhile, the rights and obligations of the parties are clearly defined through a contract agreed by the parties, the rights and obligations are programmed into machine language to form the code of the automatic algorithm, the automatic algorithm is digitally signed by the parties using respective private keys, the signed automatic algorithm is deployed into the blockchain network to become part of the blockchain, and when a preset condition is triggered, corresponding data verification and updating operations are automatically performed, the legal disputes, the responsibility attribution of the damage or loss of the warehouse goods and other rule problems are reduced, manual intervention is reduced, and the supervision efficiency and accuracy are improved. In addition, the warehouse receipt data are analyzed, evaluated and mined by using big data and artificial intelligence technology, the demand trend of the goods is predicted, and the inventory management strategy is optimized, and the functions are diversified.

[0131] The basic principles, main features and advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above examples, and the above examples and descriptions in the specification are only to illustrate the principles of the present application, and various changes and improvements can be made to the present application without departing from the spirit and scope of the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. An Internet of Things-based warehouse warrant supervision method, characterized in that, The method comprises the following steps: S1: deploying Internet of Things devices inside the warehouse, collecting real-time status information of warehouse goods, and preprocessing the collected data to generate warehouse receipts; S2: generating a unique initial hash value for each warehouse receipt, combining the warehouse receipt with the current hash value each time a new warehouse receipt is generated, and generating a new hash value through a hash function to dynamically update the hash chain; S3: when verifying the authenticity of the warehouse receipt information, obtaining the latest hash value from the blockchain and verifying the integrity of the hash chain through reverse calculation; S4: storing the data processed by the dynamic hash chain algorithm on the blockchain, and verifying the data's tamper resistance and transparency using the distributed storage characteristics of the blockchain; S5: constructing an automatic algorithm, defining the verification rules and business logic of the warehouse receipt information, and automatically performing data verification and update operations; S6: recording the data verified by the automatic algorithm on the blockchain in the form of a transaction to form encrypted warehouse receipt information and digital certificates; S7: using big data and artificial intelligence technology to analyze, evaluate and mine warehouse receipt data, predict the demand trend of goods, and generate reports; S8: linking the blockchain to a visualization platform to provide query functions, real-time monitoring and auditing functions; The S5 comprises the following steps: The rights and obligations of the parties are clearly defined by jointly agreeing on a contract, and the rights and obligations are programmed into machine language to form the code of the automatic algorithm; All parties use their own private keys to digitally sign the automatic algorithm, and the signed automatic algorithm is deployed to the blockchain network to become part of the blockchain, containing automatically executed logic, data update frequency, and verification conditions, and when the preset conditions are triggered, the corresponding operations are automatically executed; In the execution of data verification and update operations, the state mechanism evaluates the current state, and when all operations have been sequentially executed, the state is marked as "completed" and removed from the latest block; When the operation is not yet completed, the state is marked as "in progress" and continues to be saved in the latest block, waiting for the next round of processing.

2. The warehouse receipt supervision method based on the Internet of Things according to claim 1, characterized in that: The S1 comprises the following steps: Deploying RFID tags and sensors inside the warehouse; Real-time acquisition of the location information of goods through RFID tags or GPS positioning technology; Real-time statistics of the quantity of goods using the read-write function of RFID tags; Monitoring the quality parameters of goods, including temperature and humidity, through sensors; Real-time monitoring of temperature and humidity changes in the warehouse through sensors; Using the Internet of Things gateway as a bridge to connect the central processing unit, transmitting the collected data from the Internet of Things devices to the central processing unit; Removing noise, repeated and useless information from the data in the central processing unit, converting different formats of data into a unified format, and checking the integrity and accuracy of the data through verification rules; Integrating data from different sources to form a complete data set, and using the data set to constitute the warehouse receipt.

3. The warehouse receipt supervision method based on the Internet of Things according to claim 1, characterized in that: The S2 comprises the following steps: A unique initial hash value is generated for each warehouse receipt, which is calculated from the basic information of the warehouse receipt and a randomly generated salt value; Initialization of hash value calculation: H0=Hash(basic information+salt value) The basic information includes cargo ID, quantity, and storage location. The salt value is a randomly generated string, which increases the complexity and security of the hash value. Each time the Internet of Things device collects new data and generates a warehouse receipt, the receipt is combined with the current hash value to generate a new hash value through a hash function, dynamically updating the hash chain. The new hash value is calculated as follows: H t = Hash(H t-1 + D t + device ID + t) Wherein, H t-1 is the hash value of the previous time point, D t is the data collected at the current time point, the device ID is the identification of the Internet of Things device collecting the data, and t is the timestamp of the current time point. The timestamp and Internet of Things device ID of each update are recorded to ensure data traceability.

4. The warehouse receipt supervision method based on the Internet of Things according to claim 3, characterized in that: The S3 includes the following steps: When verifying the authenticity of the warehouse receipt information, obtain the latest hash value from the blockchain and verify the integrity of the hash chain through reverse calculation; H n represents obtaining the latest hash value from the blockchain, and reverse calculation: H n-1 = ReverseHash(H n - (Device ID n + n + D n )) Reverse calculation is performed sequentially to the initial hash value H0. When the final hash value is consistent with the hash value calculated at the initialization, it is proved that the hash chain is complete and the data has not been tampered with. When any link in the hash chain is tampered with, reverse calculation will not be able to obtain the correct initial hash value, proving that the data has been tampered with.

5. The warehouse receipt supervision method based on the Internet of Things according to claim 1, characterized in that: The S4 includes the following steps: The data processed by the dynamic hash chain algorithm is divided into multiple shards, and each data shard is encrypted to ensure that only authorized users can access the data; A unique hash value is generated based on the shard data, and the hash value is added to the shard metadata to link the warehouse receipt sub-data to the stored shard; When verifying the tamper-proof nature of the data, compare the hash values to confirm whether the data has been tampered with; In the blockchain storage, each shard is copied to create a redundant copy, and the copies are distributed across different nodes, with all nodes participating in the consensus process; All nodes synchronize information, and each node has the latest data copy to verify the transparency of the data.

6. The warehouse receipt supervision method based on the Internet of Things according to claim 1, characterized in that: The S6 includes the following steps: After the data is verified by the automatic algorithm, a transaction record is automatically generated, which contains the hash value, storage location, and timestamp of the data; The transaction record is added to the blockchain network, and each node on the blockchain saves a copy of the transaction record; After the transaction record is successfully added to the blockchain, a digital certificate is automatically generated, containing the hash value of the transaction record, owner information, and timestamp information, and is associated with the warehouse receipt of the previous step; In this process, the user is provided with the function of encrypting, signing, and verifying the digital certificate and warehouse receipt information using a private key.

7. The warehouse receipt supervision method based on the Internet of Things according to claim 1, characterized in that: The S7 includes the following steps: Use statistical and machine learning algorithms to analyze warehouse receipt data, extract key features, generate dynamic statistical charts, and identify patterns and trends in the data; Based on the analysis results, use deep learning and neural networks to establish a prediction model to predict future cargo demand trends; Based on the prediction results, optimize inventory management strategies, including adjusting inventory levels and developing procurement plans; Convert the optimized inventory management strategies into reports. 8.The warehouse receipt supervision method based on the Internet of Things according to claim 1, characterized in that: In S8, after accessing the visualization platform, relevant parties can query warehouse receipt information through the blockchain to understand the real-time status of warehouse goods, and supervisors can monitor and audit warehouse receipt information in real time through the blockchain to ensure the compliance and effectiveness of warehouse receipt supervision.

9. A warehouse receipt supervision platform based on the Internet of Things, applied to the warehouse receipt supervision method based on the Internet of Things in any one of claims 1-8, characterized in that: The warehouse management system comprises a data collection and processing module, a dynamic algorithm module, a blockchain storage module, an automatic verification unit, an evaluation module and a visualization platform. The data collection and processing module collects real-time state information of warehouse goods based on the Internet of Things devices deployed in the warehouse, including location, quantity, quality, temperature and humidity data, and preprocesses the collected data, including data cleaning, format conversion and verification, to ensure data accuracy and consistency, and generates warehouse receipts. The dynamic algorithm module is used to generate a unique initial hash value for each warehouse receipt, which is calculated from the basic information of the warehouse receipt and a randomly generated salt value. Each time a new warehouse receipt is generated, the warehouse receipt data is combined with the current hash value to generate a new hash value through a hash function, which realizes dynamic updating of the hash chain. At the same time, the time stamp and Internet of Things device ID of each update are recorded to verify the authenticity of the warehouse receipt information. The blockchain storage module is used to store data processed by the dynamic hash chain algorithm, and uses the distributed storage characteristics of the blockchain to verify the data's non-tamperability and transparency. The automatic verification unit is used to define the verification rules and business logic of the warehouse receipt information, including data update frequency and verification conditions, to automatically perform data verification and update operations. After verification, the data is recorded in the form of a transaction on the blockchain storage module, forming encrypted warehouse receipt information and digital certificates to ensure data authenticity and integrity. The evaluation module uses big data and artificial intelligence technology to conduct in-depth analysis and intelligent evaluation of the collected data, predicts the demand trend of goods by mining and analyzing historical data, optimizes inventory management strategies, and generates reports. The visualization platform is used to display all data of the data collection and processing module, dynamic algorithm module, blockchain storage module, automatic verification unit and evaluation module, providing visual query functions, real-time monitoring and auditing functions.

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