Industrial internet data sharing method, system, equipment and medium

Abstract

The invention provides an industrial internet data sharing method, system and device and a medium, and belongs to the field of identification analysis. The method comprises the following steps: carrying out identification code distribution on a physical entity in an industrial internet, and recording a corresponding identification code on a block chain through a smart contract; collecting related data of each link of the industrial internet, and binding the related data with the identification code to form a complete chain; when a certain physical entity needs to be inquired or traced, an API interface of the analysis engine is called to retrieve corresponding related data and state information according to the identification code of the physical entity, and deep analysis and mining are carried out on the related data and state information, obtained through analysis, of the physical entity so as to provide production decisions and market prediction. By constructing a unified identification system and designing an efficient analysis engine, cross-platform data intercommunication and full-chain tracing management functions are realized, and the overall efficiency and security of the industrial internet are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of identification and resolution, and particularly relates to a method, system, device and medium for sharing industrial Internet data. Background Art

[0002] With the booming rise of the industrial Internet, various industrial devices, precision sensors and complex systems are generating a large amount of data resources at an unprecedented speed. These data are of inestimable value for promoting the deepening of intelligent manufacturing, optimizing energy management, realizing accurate logistics tracking, strengthening industrial safety protection and promoting intelligent operation and maintenance and other key applications. Therefore, how to safely and efficiently share these data has become the core bottleneck restricting the industrial Internet from moving towards a higher level of development.

[0003] The identification and resolution technology, as the core support technology in the industrial Internet, can effectively bind and exchange data by assigning unique identifiers to each device, product and process flow.

[0004] However, when the existing identification and resolution technology realizes cross-system and cross-platform data sharing, due to the small scale of enterprises and limited investment in informatization, heterogeneous protocols and closed data formats are often adopted between the devices and software systems provided by different suppliers, resulting in production data, equipment status and supply chain information being scattered in multiple "data islands", making it difficult for data to communicate with each other and restricting the further development of the industrial Internet. Summary of the Invention

[0005] The purpose of the embodiments of the present invention is to provide a method, system, device and medium for sharing industrial Internet data, which is used to completely or at least partially solve the technical problem of data non-communication existing in the above-mentioned prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for sharing industrial Internet data, including: Allocating identification codes to physical entities in the industrial Internet, and recording the corresponding identification codes on the blockchain through a smart contract; Collecting relevant data in each link of the industrial Internet, and binding the relevant data with the identification code to form a complete chain; When it is necessary to query or trace a certain physical entity, call the API interface of the parsing engine to retrieve the corresponding relevant data and status information according to the identification code of the physical entity, and conduct in-depth analysis and mining on the relevant data and status information of the parsed physical entity to provide production decision-making and market prediction.

[0007] Optionally, the construction process of the parsing engine includes: Analyze the requirements for the parsing engine, and determine the identifier type, data format, and protocol of the parsing engine to clarify the functional and performance requirements of the parsing engine; Define the response time and throughput requirements of the parsing engine to ensure that massive data can be processed in a large-scale industrial environment; Through blockchain technology, store the relevant data of physical entities in a decentralized network, and distribute an indexing mechanism on the blockchain to access data related to identifiers, where the indexing mechanism includes a hash index and a relational index; Optimize the query algorithm and distributed structure of the parsing engine in a distributed environment; Design API interfaces for service integration.

[0008] Optionally, optimizing the query algorithm and distributed structure of the parsing engine includes: data query optimization including hash table optimization and bitmap index optimization, distributed structure optimization including MapReduce algorithm optimization and load balancing optimization, intelligent query optimization including knowledge graph and semantic query optimization and query cache and pre-computation optimization, and data compression and storage optimization including data compression optimization and cross-platform data interoperability.

[0009] Optionally, the process of designing API interfaces for service integration includes: Design API interfaces based on the RESTful architecture to support external systems to query and update data related to identifiers through the HTTP protocol; Provide the WebSocket protocol to provide continuous data stream transmission and instant feedback; Integrate the parsing engine with the smart contract on the blockchain to ensure that each data query and update is verified and controlled by the smart contract.

[0010] Optionally, the verification process of the smart contract includes: When the relevant data in each link of the industrial Internet enters the blockchain, the smart contract will automatically verify whether the data conforms to the preset rules. If it conforms, the relevant data will be packaged into the blockchain, and the data status will be updated on the blockchain. If it does not conform, the data will be rejected; When the relevant data is packaged into the blockchain, the blockchain nodes verify the validity of the relevant data through the consensus mechanism. After most nodes verify and pass, the relevant data will be stored in the blockchain; Among them, the preset rules include data format verification, time window rules, data integrity rules, permission control rules, and anomaly detection rules.

[0011] Optionally, conduct in-depth analysis and mining on the relevant data and status information of the parsed physical entities to provide production decisions and market forecasts, including: After the identifier is bound to the relevant data of each link of the industrial Internet, the parsing engine is called to query and match the relevant data of the device from the decentralized storage through the identifier; Select the corresponding parsing method according to the type of the identifier, the attributes of the physical entity, and the format of the data; among them, for real-time data, the parsing engine parses it in real time, performs data cleaning and denoising processing, and immediately feeds it back to the device management system or the production scheduling system; for historical data, the parsing engine will perform data aggregation and analysis to generate corresponding reports or trend analysis results; Record the data processed by the parsing engine in the blockchain through a smart contract, and perform auditing and compliance checks. If the device status is abnormal, the parsing engine will trigger an alarm and automatically execute corresponding operations through the smart contract; According to the data parsing results, the parsing engine generates periodic reports for management decision-making reference.

[0012] In a second aspect, an embodiment of the present application further provides a sharing system for industrial Internet data, including: An allocation unit for allocating identification codes to physical entities in the industrial Internet and recording the corresponding identification codes on the blockchain through a smart contract; A binding unit for collecting the relevant data of each link of the industrial Internet and binding the relevant data to the identification code to form a complete chain; A retrieval unit for, when it is necessary to query or trace a certain physical entity, calling the API interface of the parsing engine to retrieve the corresponding relevant data and status information according to the identification code of the physical entity, and performing in-depth analysis and mining on the relevant data and status information of the parsed physical entity to provide production decision-making and market prediction.

[0013] Optionally, the retrieval unit is specifically used for: After the identifier is bound to the relevant data of each link of the industrial Internet, the parsing engine is called to query and match the relevant data of the device from the decentralized storage through the identifier; Select the corresponding parsing method according to the type of the identifier, the attributes of the physical entity, and the format of the data; among them, for real-time data, the parsing engine parses it in real time, performs data cleaning and denoising processing, and immediately feeds it back to the device management system or the production scheduling system; for historical data, the parsing engine will perform data aggregation and analysis to generate corresponding reports or trend analysis results; Record the data processed by the parsing engine in the blockchain through a smart contract, and perform auditing and compliance checks. If the device status is abnormal, the parsing engine will trigger an alarm and automatically execute corresponding operations through the smart contract; According to the data parsing result, the parsing engine generates a periodic report for management decision-making reference.

[0014] In a third aspect, an embodiment of the present application further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the above-mentioned industrial Internet data sharing method are implemented.

[0015] In a fourth aspect, an embodiment of the present application further provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned industrial Internet data sharing method are implemented.

[0016] It can be seen from the above technical solutions that the present invention has the following advantages: In the industrial Internet data sharing method, system, device and medium provided by the present application, by constructing a unified identification system, designing an efficient parsing engine, realizing cross-platform data interconnection and full-chain traceability management functions, the overall efficiency and security of the industrial Internet are improved. At the same time, it can meet the development needs of the future industrial Internet and provide strong support for the digital transformation and industrial upgrading of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a flowchart of a method for sharing industrial Internet data provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the construction process of an analysis engine provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of a data parsing process provided by an embodiment of the present invention; Figure 4 It is a schematic diagram of the structure of a system for sharing industrial Internet data provided by an embodiment of the present invention; Figure 5 It is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In the following detailed description, various embodiments of the present disclosure will be more fully described. The present disclosure can have various embodiments, and adjustments and changes can be made therein. However, it should be understood that there is no intention to limit the various embodiments of the present disclosure to the specific embodiments disclosed herein, but the present disclosure should be understood to cover all adjustments, equivalents, and / or alternative solutions that fall within the spirit and scope of the various embodiments of the present disclosure.

[0020] In the following, the term "comprising" or "may comprise" that can be used in various embodiments of the present disclosure indicates the presence of the disclosed function or operation, and does not limit the addition of one or more functions or operations. Further, as used in various embodiments of the present disclosure, the terms "comprising", "having" and their cognates are only intended to indicate a specific feature, number, step, operation, or combination of the foregoing items, and should not be construed as precluding the existence or addition of one or more other features, numbers, steps, operations, or combinations of the foregoing items.

[0021] In various embodiments of the present disclosure, the expression "or" or "at least one of A or / and B" includes any combination or all combinations of the listed words. For example, the expression "A or B" or "at least one of A or / and B" may include A, may include B, or may include both A and B.

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0023] Refer to Figure 1 The following is a flowchart of a method for sharing industrial Internet data in a specific embodiment, including the following execution steps: Step 100: Assign identification codes to physical entities in the industrial Internet, and record the corresponding identification codes on the blockchain through a smart contract.

[0024] In a specific embodiment, a unified identification system based on the industrial Internet is established to assign unique and identifiable identification codes to industrial equipment, products, raw materials, etc. First, determine the identifier standards and specifications: Define the format, type, and standards of device identifiers. The identifier should be unique, scalable, and compatible, capable of covering different types of devices, sensors, raw materials, etc. Design an identifier registration and management mechanism: According to the selected identifier standards, establish an identifier registration center responsible for the allocation and management of all device and item identifiers. Compatibility and integration with existing systems: Ensure that the new identification system can be smoothly applied in the existing industrial Internet platform, and it is necessary to ensure the compatibility and integration of the identifiers. Association management of identifiers and data: The identifier is not just a simple ID, but is associated with relevant data such as devices, products, and materials. Security and privacy protection of identifiers: To ensure the security of device identifiers and their related data, especially in industrial Internet scenarios involving cross-platform or multiple parties, the following security measures must be taken: encryption technology, permission control, and multi-party authentication mechanisms.

[0025] It should be understood that this identification system is compatible with existing standards and at the same time has scalability and flexibility to meet the development needs of the future industrial Internet.

[0026] Step 101: Collect relevant data from all links of the industrial Internet and bind the relevant data with the identification code to form a complete chain.

[0027] Exemplarily, in each link such as device operation, production line operation, and logistics transportation, data will be collected in real time and bound to the unique identifier of the device. Whenever a new identifier is associated with a device or product, the data collection device will send relevant data (such as device status, sensor readings, production records, etc.) to the parsing engine. Among them, sensor data collection includes: sensors or other data collection terminals of the device will collect data regularly or on demand and transmit it to the parsing engine together with the device identifier.

[0028] Data synchronization and update: The parsing engine will regularly synchronize data with the data on the blockchain to ensure that all new data is updated to the blockchain in a timely manner to avoid data lag.

[0029] Step 102: When it is necessary to query or trace a physical entity, call the API interface of the parsing engine to retrieve the corresponding relevant data and status information according to the identification code of the physical entity, and conduct in-depth analysis and mining on the relevant data and status information of the parsed physical entity to provide production decisions and market forecasts.

[0030] In a specific embodiment, the core task of the parsing engine is to quickly and accurately retrieve and process data related to the device or product according to the identifier. To achieve this goal, the parsing engine needs to have efficient data processing capabilities, intelligent data parsing, and automated decision-making functions. Refer to Figure 2 As shown, the construction process of the parsing engine includes the following steps: S200: Analyze the requirements of the parsing engine and determine the identifier type, data format, and protocol of the parsing engine to clarify the functional and performance requirements of the parsing engine.

[0031] Specifically, it is necessary to analyze the requirements of the parsing engine, clarify its functional and performance requirements: determine the identifier type, data format, and protocol that the parsing engine needs to support (such as UUID, QR code, RFID, barcode, etc.), and design appropriate parsing modules.

[0032] S201: Define the response time and throughput requirements of the parsing engine to ensure that massive data can be processed in a large-scale industrial environment.

[0033] S202: Through blockchain technology, store the relevant data of physical entities in a decentralized network, and distribute an indexing mechanism on the blockchain to access data related to the identifier. Among them, the indexing mechanism includes a hash index and a relational index.

[0034] Specifically, decentralized storage: Through blockchain technology, ensure that all device information, sensor data, production history, etc. are stored in a decentralized network, thus ensuring the security, transparency, and immutability of the data. Indexing mechanism: To improve data query efficiency, the parsing engine needs to implement a distributed indexing structure on the blockchain. By creating indexes for identifiers, device data, sensor data, etc., the query process can be made more efficient. Hash index: Generate hash values according to the identifier and create a fast query index for these hash values on the storage layer of the blockchain. Relational index: For data that requires multi-dimensional queries (such as device status, maintenance records, etc.), create an efficient index structure through a relational data model to facilitate fast query and parsing.

[0035] In a specific embodiment, after the identifier is bound to the data, the parsing engine will parse and process the data: Data matching and association: The parsing engine queries and matches the relevant data of the device from the decentralized storage through the identifier. At this time, the parsing engine will select an appropriate parsing method according to the type of the identifier, the attributes of the device, and the format of the data. Real-time data processing: For real-time data (such as sensor data, device monitoring data), the parsing engine needs to parse it in real time and perform data cleaning and denoising. The data can be immediately fed back to the device management system or the production scheduling system. Historical data analysis: For historical data (such as device maintenance records, production plan data), the parsing engine will perform data aggregation and analysis to generate corresponding reports or trend analysis results. Data response and intelligent decision-making: Based on the data processed by the parsing engine, the system can generate decision-making information or automatic responses: Alarm and notification: If the device status is abnormal (such as exceeding the preset threshold), the parsing engine will trigger an alarm and automatically execute corresponding operations through the smart contract (such as starting maintenance, adjusting the production plan, etc.). Prediction and optimization: Through long-term analysis of the device data, the parsing engine can provide intelligent decision-making support such as device failure prediction and production efficiency optimization. Report generation: According to the data parsing results, the parsing engine can generate periodic reports for management decision-making reference. Data storage and auditing: The results of each data processing will be updated to the blockchain system according to the device identifier: Decentralized storage: All processing results, device status, and operation records will be recorded in the blockchain through the smart contract to ensure the immutability and transparency of the data. Auditing and compliance check: The execution process of each operation will be automatically recorded to provide a comprehensive audit log for regulatory and compliance checks.

[0036] S203: Optimize the query algorithm and distributed structure of the parsing engine in a distributed environment.

[0037] Specifically, optimizing the query algorithm and distributed structure of the parsing engine includes: data query optimization including hash table optimization and bitmap index optimization, distributed structure optimization including MapReduce algorithm optimization and load balancing optimization, intelligent query optimization including knowledge graph and semantic query optimization and query cache and pre-computation optimization, and data compression and storage optimization including data compression optimization and cross-platform data interoperability.

[0038] Exemplarily, for hash table optimization: The hash table is a common optimization method for fast lookup, which can quickly query the device or data associated with the identifier with a constant time complexity (O(1)). Hash function design: Ensure the uniform distribution of the hash function to avoid collisions and improve the query efficiency. Distributed hash table: In the blockchain network, each node maintains a partial hash table to avoid single-point bottlenecks and improve the parallel processing ability of large-scale data queries.

[0039] Exemplarily, for bitmap index optimization: Bitmap Index is suitable for low-cardinality queries (e.g., the on / off state of a device, type identifier, etc.). It uses bit arrays to represent certain attributes of identifiers, making queries very efficient.

[0040] Optimization for data parallelism and distributed processing: a) MapReduce algorithm: MapReduce is a common distributed data processing algorithm suitable for processing large-scale data sets. It can share the workload of the parsing engine and improve the data processing speed. Data sharding: Shard the identifier data according to certain rules (such as time, device type, etc.) and distribute it to different computing nodes. Parallel computing: Each node processes the assigned data and executes the identifier parsing and related data calculation tasks. Aggregate results: The Reduce node aggregates the calculation results of each node to generate the final query response. b) Load balancing optimization: In a distributed environment, load balancing optimization of the parsing engine can ensure even distribution of system load, improve the overall system processing capacity, and avoid single-point overload. Resource monitoring: Real-time monitor the resource usage of each node (such as CPU, memory, bandwidth, etc.). Dynamic scheduling: Dynamically adjust the task allocation according to the load information and evenly distribute the requests to the nodes with lower load. Request queue optimization: Queue or delay the requests of high-load nodes to ensure system stability.

[0041] Exemplarily, for intelligent query optimization: a) Knowledge graph and semantic query optimization: Build a knowledge graph: Collect information on all devices, sensors, operation data, etc., and build a knowledge graph based on the relationships between them. Semantic analysis: Perform semantic analysis on the user's query request, identify the entities and relationships in the query, and automatically generate graph queries. Optimize the query path: According to the relationships between nodes in the graph, optimize the query path to reduce the time overhead caused by multi-level queries. b) Query caching and pre-computation optimization: Query caching technology can significantly improve the response speed of the parsing engine, especially when the same or similar query requests occur frequently. Pre-computation technology can execute complex calculation tasks in advance to reduce the calculation burden during real-time queries. Caching strategy: Adopt cache eviction algorithms such as LRU (Least Recently Used) to cache frequently queried data in memory to avoid repeated calculations. Pre-computation mechanism: Periodically pre-compute complex query tasks and store the results in the database. When a query is needed, directly return the pre-computed results to reduce the burden of real-time calculations.

[0042] Exemplarily, for data compression and storage optimization: a) Data compression optimization: Data redundancy analysis: Analyze the redundant information in device data and use appropriate compression algorithms (such as GZIP, LZ4) for data compression. Compressed storage: Store the compressed data in a blockchain or a distributed database to reduce storage costs and accelerate the query process. b) Cross-platform data interoperability: 1) Implement cross-platform and cross-system data interoperability functions. Through standardized interfaces and protocols, identification data between different systems can be seamlessly docked and shared. 2) Break the information silo phenomenon and enhance the overall collaborative ability of the industrial Internet.

[0043] S204: Design API interfaces and service integration.

[0044] Specifically, the API interface and service integration design process includes: Designing API interfaces based on the RESTful architecture to support external systems to query and update identifier-related data through the HTTP protocol; Providing the WebSocket protocol to provide continuous data stream transmission and instant feedback; Integrating the parsing engine with smart contracts on the blockchain to ensure that each data query and update passes the verification and control of the smart contract.

[0045] Among them, the verification process of the smart contract includes the following steps: S1: When the relevant data of each link of the industrial Internet enters the blockchain, the smart contract will automatically verify whether the data conforms to the preset rules. If it conforms, the relevant data will be packaged into the blockchain, and the data status will be updated on the blockchain. If it does not conform, the data will be rejected.

[0046] S2: When the relevant data is packaged into the blockchain, the blockchain nodes verify the validity of the relevant data through the consensus mechanism. After most nodes verify and pass, the relevant data will be stored in the blockchain.

[0047] Among them, the preset rules include data format verification, time window rules, data integrity rules, permission control rules, and anomaly detection rules.

[0048] It should be understood that data format verification stipulates that the collected data must conform to a certain specific format (such as JSON, XML, etc.), and the content of the data fields must be filled in accordance with preset rules. For example, the range of sensor temperature data must be between -50°C and 150°C. If the data exceeds this range, the smart contract will reject the data. Time window rule: The collection and recording of data must conform to specific time limits. For example, each operation record of production equipment must be completed within a certain time, and data that exceeds the time limit is regarded as invalid data. Data integrity rule: Each piece of data must contain key information such as device identifier, production batch, sensor ID, collection timestamp, etc. Data lacking any required fields will be rejected from entering the blockchain. Permission control rule: Only authorized users or systems can submit data, modify data, or query data. The smart contract will automatically perform authentication and permission control to prevent unauthorized operations. Anomaly detection rule: The smart contract can set some data anomaly detection rules to detect and automatically mark abnormal data. For example, when the operating state of the device shows abnormal fluctuations, an alarm is automatically triggered, and the data is reviewed.

[0049] In one embodiment of the present invention, referring to Figure 3 as shown, based on step 102, a possible embodiment will be given below to non-restrictively elaborate on its specific implementation scheme.

[0050] S300: After the identifier is bound to the relevant data in each link of the industrial Internet, call the parsing engine to query and match the relevant data of the device from the decentralized storage through the identifier.

[0051] S301: Select the corresponding parsing method according to the type of identifier, the attributes of the physical entity, and the format of the data; among them, for real-time data, the parsing engine parses it in real time and performs data cleaning and denoising processing, and immediately feedbacks it to the device management system or the production scheduling system; for historical data, the parsing engine will perform data aggregation and analysis to generate corresponding reports or trend analysis results.

[0052] S302: Record the data processed by the parsing engine in the blockchain through the smart contract, and perform auditing and compliance checks. If the device status is abnormal, the parsing engine will trigger an alarm and automatically execute corresponding operations through the smart contract.

[0053] S303: According to the data parsing result, the parsing engine generates a periodic report for the management to refer to for decision-making.

[0054] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0055] In a specific embodiment, based on the parsed data, in-depth analysis and mining are carried out to provide strong support for the production decision-making, market prediction, etc. of enterprises, including data collection and cleaning: Obtain data related to equipment, production, and supply chain from the blockchain. These data are cleaned, standardized, and preprocessed to remove outliers and noise data and ensure their unified format. Data integration and modeling: Integrate equipment historical data, real-time sensor data, production process data, etc. to build a multi-dimensional data model. These models may include time series analysis models, prediction models, and trend analysis models. Feature engineering and data mining: Use machine learning and data mining techniques to extract key features from a large amount of historical data. For example, by analyzing the operating state of the equipment, identify which variables (such as temperature, humidity, vibration frequency, etc.) have an important impact on equipment failures. Prediction analysis and optimization algorithms: Based on historical data and real-time data, use prediction analysis models to predict the future behavior of the equipment. For example, use techniques such as regression analysis, decision trees, and neural networks to predict possible equipment failures or production bottlenecks. Through optimization algorithms (such as linear programming, genetic algorithms, etc.), optimize the production process, scheduling strategy, and resource allocation. Decision support and automated execution: According to the analysis results, the smart contract can automatically execute the preset optimization decisions. For example, automatically schedule the equipment on the production line, adjust the inventory level, and formulate a maintenance plan. At the same time, the management can view the data analysis results through a visual interface to assist in decision-making.

[0056] Exemplarily, using regression analysis techniques to predict possible equipment failures or production bottlenecks includes: collecting sensor data (temperature, vibration, pressure, current, etc.), equipment historical operation logs, failure time, failure type, repair records, production volume, yield, downtime, production speed, raw material characteristics, temperature and humidity, operator information, etc. Define the regression problem: Predict the remaining useful life (RUL): The remaining operating time of the equipment before failure and predict the trend of the decline in production yield: Predict the yield of future batches based on the current parameters. And extract the time-domain features of the above data: mean, variance, maximum value, minimum value, kurtosis, skewness. Frequency-domain features: Use Fourier transform to extract the spectral features of the vibration signal. Lag features: Construct the average temperature, vibration amplitude, etc. in the past N hours. Domain knowledge features: For example, the equipment load rate (power / rated power). Divide the above feature data into a training set (70%), a validation set (15%), and a test set (15%) in chronological order, and use the training set, validation set, and test set to train the regression model respectively to obtain the optimal regression model. Input the temperature mean, vibration maximum value, and current variance feature data in the past 24 hours, and output the time (hours) label from the current moment to the failure of the equipment.

[0057] In this embodiment, the problem that it is difficult for data to be interoperable among multiple applications on the platform due to different suppliers and application types, and it is difficult for enterprise informatization personnel to uniformly manage the interoperability of application data is solved. Moreover, through the immutability of the blockchain, it is ensured that once all device data, operation logs, production records and other information are written into the blockchain, they cannot be tampered with or deleted. This is crucial for data sharing in the industrial Internet because it guarantees the reliability and credibility of the data. The blockchain eliminates single points of failure and dependence on intermediaries through a decentralized structure, making the data sharing process more efficient. The recording and sharing of all data are transparent, and participants can view the historical records of the data at any time to ensure the credibility of the data source. Moreover, smart contracts automatically execute predefined protocols and can achieve automated data exchange, resource scheduling and device management in the industrial Internet. For example, once the maintenance cycle of a device is reached, the smart contract will automatically trigger a maintenance notice to ensure that the device is always in the best operating state.

[0058] As Figure 4 shown, the following is an embodiment of the industrial Internet data sharing system provided by the embodiments of the present disclosure. It belongs to the same inventive concept as the industrial Internet data sharing method of the above embodiments. For the details not described in detail in the embodiment of the industrial Internet data sharing system, reference can be made to the embodiment of the industrial Internet data sharing method.

[0059] The industrial Internet data sharing system includes: An allocation unit for allocating identification codes to physical entities in the industrial Internet and recording the corresponding identification codes on the blockchain through a smart contract; A binding unit for collecting relevant data of each link in the industrial Internet and binding the relevant data with the identification code to form a complete chain; A retrieval unit for, when it is necessary to query or trace a certain physical entity, calling the API interface of the parsing engine to retrieve the corresponding relevant data and status information according to the identification code of the physical entity, and performing in-depth analysis and mining on the relevant data and status information of the parsed physical entity to provide production decision-making and market prediction.

[0060] In a specific embodiment, the retrieval unit is specifically used for: After the identifier is bound to the relevant data of each link in the industrial Internet, calling the parsing engine to query and match the relevant data of the device from the decentralized storage through the identifier; Select the corresponding parsing method according to the type of identifier, the attributes of the physical entity, and the format of the data. Among them, for real-time data, the parsing engine parses it in real time, performs data cleaning and denoising, and immediately feeds back to the device management system or production scheduling system. For historical data, the parsing engine will perform data aggregation and analysis to generate corresponding reports or trend analysis results. Record the data processed by the parsing engine in the blockchain through a smart contract, and perform auditing and compliance checks. If the device status is abnormal, the parsing engine will trigger an alarm and automatically execute corresponding operations through the smart contract. According to the data parsing results, the parsing engine generates periodic reports for management decision-making reference.

[0061] Figure 5 It is a schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention.

[0062] The method for sharing industrial Internet data provided by the embodiments of the present application can be applied to an electronic device. Those skilled in the art can understand that the structure of the electronic device involved in the embodiments of the present invention does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements. In the embodiments of the present invention, the electronic device includes, but is not limited to, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present application described herein and / or required.

[0063] The electronic device may include a processor, an external memory interface, an internal memory, a universal serial bus (USB) interface, a charging management module, a power management module, a battery, a wireless communication module, an audio module, a speaker, a microphone, a sensor module, a key, a camera, a display screen, and a SIM card interface, etc.

[0064] It can be understood that the structure schematically shown in the embodiments of the present application does not constitute a specific limitation on the electronic device. In other embodiments of the present application, the electronic device may include more or fewer components than shown, or combine certain components, or split certain components, or have different component arrangements. The components shown can be implemented in hardware, software, or a combination of software and hardware.

[0065] The processor may include one or more processing units. For example, the processor may include a central processing unit (CPU), an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Among them, different processing units may be independent devices or integrated in one or more processors.

[0066] Among them, the processor may be the nerve center and command center of the electronic device. The controller can generate operation control signals according to the instruction operation code and timing signal to complete the control of fetching and executing instructions.

[0067] A memory may also be provided in the processor for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. This memory can store the instructions or data just used or recycled by the processor. If the processor needs to use the instruction or data again, it can directly call it from this memory. This avoids repeated accesses, reduces the waiting time of the processor, and thus improves the system efficiency.

[0068] The external memory interface can be used to connect an external memory card, such as a MicroSD card, to expand the storage capacity of the electronic device. The external memory card communicates with the processor through the external memory interface to achieve the data storage function. For example, files such as music and videos are saved in the external memory card.

[0069] The internal memory can be used to store computer-executable program code, and the computer-executable program code includes instructions. The processor executes various functional applications and data processing of the electronic device by running the instructions stored in the internal memory. The internal memory may include a program storage area and a data storage area. The internal memory may include a high-speed random access memory and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, a universal flash storage (UFS), etc.

[0070] The wireless communication function of the electronic device can be implemented through an antenna, a wireless communication module, a modem processor, a baseband processor, etc.

[0071] The wireless communication module can provide solutions for wireless communications applied to electronic devices, including wireless local area networks (WLANs) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite systems (GNSSs), frequency modulation (FM), near field communication (NFC), infrared technology (IR), etc.

[0072] The electronic device can implement audio functions through an audio module, a speaker, a receiver, a microphone, a headphone jack, an application processor, etc.

[0073] The electronic device can implement a shooting function through an ISP, a camera, a video codec, a GPU, a display screen, an application processor, etc.

[0074] The electronic device can implement a display function through a GPU, a display screen, an application processor, etc.

[0075] The GPU is a microprocessor for image processing, connecting the display screen and the application processor. The GPU is used to execute mathematical and geometric calculations for graphics rendering. The processor may include one or more GPUs, which execute program instructions to generate or change display information.

[0076] The display screen is used to display images, videos, etc. The display screen includes a display panel.

[0077] In the storage medium provided in this application, there is a program product capable of implementing the method for sharing industrial Internet data.

[0078] The method for sharing industrial Internet data includes: allocating identification codes to physical entities in the industrial Internet and recording the corresponding identification codes on the blockchain through a smart contract; collecting relevant data of each link in the industrial Internet and binding the relevant data with the identification codes to form a complete chain; when it is necessary to query or trace a certain physical entity, calling the API interface of the parsing engine to retrieve the corresponding relevant data and status information according to the identification code of the physical entity, and performing in-depth analysis and mining on the relevant data and status information of the parsed physical entity to provide production decisions and market forecasts.

[0079] In some possible implementations, the subject matter of the present disclosure, a method and system for sharing industrial Internet data, may be implemented in the form of a program product that includes program code. When the program product runs on a terminal device, the program code is used to cause the terminal device to execute the steps according to various exemplary embodiments of the present disclosure described in the above "Exemplary Method" section of this specification.

[0080] The storage medium of the present disclosure may employ any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0081] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for sharing industrial Internet data, characterized in that: include: Assign identification codes to physical entities in the Industrial Internet and record the corresponding identification codes on the blockchain through smart contracts; Collect relevant data from all links of the industrial Internet, and bind the relevant data with the identification code to form a complete chain; When there is a need to query or trace a physical entity, the API interface of the parsing engine is called to retrieve the corresponding relevant data and status information based on the identification code of the physical entity, and the relevant data and status information of the physical entity obtained through parsing is deeply analyzed and mined to provide production decisions and market forecasts.

2. The method for sharing industrial Internet data according to claim 1, characterized in that: The construction process of the parsing engine includes: Analyze the requirements of the parsing engine and determine the identifier type, data format and protocol of the parsing engine to clarify the function and performance requirements of the parsing engine; Defining the response time and throughput requirements of the parsing engine to ensure the processing of massive amounts of data in a large-scale industrial environment; By using blockchain technology, the relevant data of the physical entity is stored in a decentralized network, and an index mechanism is distributed on the blockchain to access the data related to the identifier, wherein the index mechanism includes a hash index and a relational index; In a distributed environment, optimizing the query algorithm and distributed structure of the parsing engine; Design API interfaces and service integration.

3. The method for sharing industrial Internet data according to claim 2, characterized in that: Optimization of the query algorithm and distributed structure of the parsing engine includes: data query optimization including hash table optimization and bitmap index optimization, distributed structure optimization including MapReduce algorithm optimization and load balancing optimization, intelligent query optimization including knowledge graph and semantic query optimization and query cache and pre-computation optimization, and data compression and storage optimization including data compression optimization and cross-platform data interoperability.

4. The method for sharing industrial Internet data according to claim 2, characterized in that: The API interface and service integration design process includes: Design an API interface based on RESTful architecture to support external systems to query and update identifier-related data through HTTP protocol; Provides WebSocket protocol to provide continuous data streaming and instant feedback; Integrate the parsing engine with the smart contract on the blockchain to ensure that each data query and update is verified and controlled by the smart contract.

5. The method for sharing industrial Internet data according to claim 4 is characterized in that: The verification process of smart contracts includes: When relevant data from various links of the industrial Internet enter the blockchain, the smart contract will automatically verify whether the data complies with the preset rules. If so, the relevant data will be packaged into the blockchain and the data status will be updated on the blockchain. If not, the data will be rejected. When the relevant data is packaged into the blockchain, the blockchain nodes verify the validity of the relevant data through the consensus mechanism. After the majority of nodes pass the verification, the relevant data will be stored in the blockchain; Among them, the preset rules include data format verification, time window rules, data integrity rules, authority control rules and anomaly detection rules.

6. The method for sharing industrial Internet data according to claim 1, characterized in that: The relevant data and status information of the physical entities obtained by analysis are deeply analyzed and mined to provide production decisions and market forecasts, including: When the identifier is bound to the relevant data of each link of the industrial Internet, the parsing engine is called to query and match the relevant data of the device from the decentralized storage through the identifier; Select the corresponding parsing method according to the type of identifier, the attributes of the physical entity and the format of the data. For real-time data, the parsing engine will parse and clean the data, remove noise and provide immediate feedback to the equipment management system or production scheduling system. For historical data, the parsing engine will aggregate and analyze the data and generate corresponding reports or trend analysis results. The data processed by the parsing engine is recorded in the blockchain through smart contracts, and audits and compliance checks are carried out. If the device status is abnormal, the parsing engine will trigger an alarm and automatically perform corresponding operations through smart contracts; Based on the data analysis results, the analysis engine generates periodic reports for management to make reference for decision-making.

7. An industrial Internet data sharing system, characterized in that: include: An allocation unit, which is used to allocate identification codes to physical entities in the industrial Internet and record the corresponding identification codes on the blockchain through smart contracts; A binding unit, used to collect relevant data of each link of the industrial Internet, and bind the relevant data with the identification code to form a complete chain; The retrieval unit is used to call the API interface of the parsing engine to retrieve the corresponding relevant data and status information according to the identification code of the physical entity when a physical entity needs to be queried or traced, and to conduct in-depth analysis and mining of the relevant data and status information of the physical entity obtained by parsing, so as to provide production decisions and market forecasts.

8. The industrial Internet data sharing system according to claim 7 is characterized in that: The retrieval unit is specifically used for: When the identifier is bound to the relevant data of each link of the industrial Internet, the parsing engine is called to query and match the relevant data of the device from the decentralized storage through the identifier; Select the corresponding parsing method according to the type of identifier, the attributes of the physical entity and the format of the data. For real-time data, the parsing engine will parse and clean the data, remove noise and provide immediate feedback to the equipment management system or production scheduling system. For historical data, the parsing engine will aggregate and analyze the data and generate corresponding reports or trend analysis results. The data processed by the parsing engine is recorded in the blockchain through smart contracts, and audits and compliance checks are carried out. If the device status is abnormal, the parsing engine will trigger an alarm and automatically perform corresponding operations through smart contracts; Based on the data analysis results, the analysis engine generates periodic reports for management to make reference for decision-making.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the industrial Internet data sharing method as described in any one of claims 1 to 6 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for sharing industrial Internet data as described in any one of claims 1 to 6 are implemented.

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