Tea industry chain operation monitoring system based on big data sharing and exchange

Abstract

The invention relates to the technical field of agricultural big data, and particularly discloses a tea industry chain operation monitoring system based on big data sharing exchange, which comprises a sensing acquisition module, a sharing exchange module, an operation analysis module and an application display module. According to the scheme, a multi-source sensing system covering upstream, middle and downstream of a tea industry chain is constructed, a unified data format standard is established to realize structure aggregation of multi-source heterogeneous data, data integrity is ensured, full-life-cycle tracing and transverse comparative analysis of tea are facilitated, and accurate data support is provided for quality management, cost optimization and process reconstruction; dynamic mapping, block chain storage and authority control are introduced, standardized conversion, secure sharing and multi-node collaborative management of tea industry chain operation data are realized, a distributed account book based on a block chain technology is constructed, data consistency and non-tampering performance are ensured, security and compliance in a data access process are improved, and data access efficiency is improved. And the data rights and interests of all participants in the tea industry chain are effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural big data, and in particular to a tea industry chain operation monitoring system based on big data sharing and exchange. Background Art

[0002] The tea industry chain involves multiple links, including planting, processing, circulation, and sales. Using big data technology to achieve data sharing and collaborative management across these links is crucial for improving the overall operational efficiency of the tea industry chain. However, the existing tea industry chain suffers from severe data silos, poor information flow, invisibility of operational status, and delayed risk warnings. Traditional data sharing methods carry risks of data tampering, loss, or leakage, and sharing paths are difficult to trace. Increased data volumes can lead to response delays and uneven node loads, and the collaborative process lacks quantitative standards. Summary of the Invention

[0003] In view of the above situation, in order to overcome the defects of the existing technology, the present invention provides a tea industry chain operation monitoring system based on big data sharing and exchange. In view of the problems of serious data islands, poor information flow, invisible operation status and delayed risk warning in the existing tea industry chain, this solution constructs a multi-source perception system covering the upstream, midstream and downstream of the tea industry chain, establishes a unified data format standard to achieve structural aggregation of multi-source heterogeneous data, ensures data integrity, helps to trace the entire life cycle of tea and conduct horizontal comparative analysis, and provides accurate data support for quality management, cost optimization and process reengineering; in view of the problems of data tampering, loss or The risk of leakage is eliminated, and the shared path is difficult to trace. When the amount of data increases, response delays and uneven node loads are prone to occur. There is a lack of quantitative standards in the collaborative process. This solution introduces dynamic mapping, blockchain storage and permission control to achieve standardized conversion, secure sharing and multi-node collaborative management of tea industry chain operation data, improve data parseability, build a distributed ledger based on blockchain technology, ensure data consistency and non-tamperability, and perform logical sharding according to node roles. This significantly improves the concurrency and operating efficiency of the blockchain network, improves the security and compliance of data access, and effectively protects the data rights and interests of all participants in the tea industry chain.

[0004] The present invention provides a tea industry chain operation monitoring system based on big data sharing and exchange, which includes a perception and collection module, a sharing and exchange module, an operation analysis module, and an application display module;

[0005] The sensing and collection module collects basic data from upstream, midstream and downstream links of the tea industry chain, converts the basic data into aggregated data through a unified data format standard and preliminary aggregation, calculates statistical eigenvalues, and sends the aggregated data and statistical eigenvalues ​​to the shared exchange module;

[0006] The shared exchange module dynamically maps the aggregated data to generate a data view of the entire tea industry chain, uses blockchain technology to achieve secure sharing of the data view, and controls the permissions of all participants in accessing the data view.

[0007] The operation analysis module uses a time series analysis model to analyze the data view, evaluate whether the operation status of each link is abnormal, identify deviations and generate early warning information, and generate a trend report and send it to the application display module;

[0008] The application display module presents the operating status of each link in the tea industry chain through a visual interface. Users view monitoring parameters through interactive instructions and generate interactive logs to feed back to the operation analysis module.

[0009] Furthermore, the perception acquisition module includes a data acquisition unit, a data processing unit, and a data aggregation unit;

[0010] The data collection unit covers the upstream, midstream and downstream of the tea industry chain: the upstream involves the planting of tea, the midstream involves the processing and circulation of tea, and the downstream involves the consumer service link; the basic data of each link is collected and sent to the data processing unit;

[0011] The data processing unit defines a unified data format standard, converts the basic data into structured data containing four basic fields: timestamp, geographic location, data type, and numerical field, and performs preliminary cleaning on the structured data to remove outliers and duplicate data;

[0012] The data aggregation unit aggregates the structured data according to the timestamp to obtain aggregated data, calculates statistical characteristic values, and uploads the aggregated data and the statistical characteristic values ​​to the shared exchange module while retaining a local cache copy.

[0013] Furthermore, the shared exchange module includes a dynamic mapping unit, a blockchain storage unit, and a permission control unit;

[0014] The dynamic mapping unit constructs a mapping relationship table for the aggregated data, selects the core unit to express the semantics of the data in each link, and generates a data view of the entire tea industry chain;

[0015] The blockchain storage unit uses blockchain technology to achieve secure storage and sharing of data views, build a blockchain network, and use all participants in the tea industry chain as nodes to access the blockchain network;

[0016] The authority control unit performs authority control on the nodes in the blockchain.

[0017] Furthermore, the dynamic mapping unit constructs a mapping relationship table for the aggregated data, including the following steps:

[0018] Step S1: Standard definition, pre-define the data standards of each link in the tea industry chain;

[0019] Step S2: Unit decomposition, perform unit-level decomposition on the aggregated data and calculate the importance weight of each unit in the aggregated structure;

[0020] Step S3: View generation: Use a similarity matching algorithm to compare each unit with predefined data standards. Set a threshold to select core units that express the semantics of the overall data. The number of core units should be no less than 30% of the total number of units. Build a mapping relationship table and generate a data view based on the mapping relationship table. The formula used is as follows: ;

[0021] Where, Represents the similarity score of the mapping relationship, Represents the index of the unit, Indicates the number of units, represents the actual value of the unit, Represents a predefined data standard, Indicates the The importance weight of each unit, Indicates the The distance of each unit from a predefined data standard.

[0022] Furthermore, the blockchain storage unit implements secure storage and sharing of data views through blockchain technology, including the following steps:

[0023] Step P1: Initialize the blockchain network, use all participants in the tea industry chain as nodes, and assign a unique identity to each node;

[0024] Step P2: Build a distributed ledger. The data view is stored in the ledger in the form of blocks. Each node maintains a complete copy of the ledger. Each block contains the block number, timestamp, data view hash value, previous block hash, and current block hash.

[0025] Step P3: Data sharding: logically shard the block according to the node role. Each shard is composed of some nodes, and the newly added data is mapped to the corresponding shard according to the link to which it belongs;

[0026] Step P4: Generate a sharing report and regularly count the data contribution and access frequency of each node.

[0027] Furthermore, the application display module includes a chart display unit, an event-driven unit, a queue monitoring unit, and an interactive feedback unit;

[0028] The chart display unit periodically reads the trend report of the operation analysis module and the data view of the shared exchange module, and displays the operation status of each link of the upstream, midstream and downstream of the tea industry chain through visual charts;

[0029] The event-driven unit uses an event-driven mechanism to update the visual chart in real time, stores the data change events generated in each cycle in a queue, and calls the data update function to modify the data in the visual interface;

[0030] The queue monitoring unit monitors the status of the queue through a heartbeat detection mechanism and automatically triggers a recovery mechanism when the queue is blocked or delayed;

[0031] The interactive feedback unit sets interactive instructions, and the user views the monitoring parameters through the interactive instructions. At the same time, the user's operation behavior is recorded and an interactive log is generated to be fed back to the operation analysis module.

[0032] The beneficial effects achieved by the present invention using the above scheme are as follows:

[0033] (1) In response to the problems of serious data silos, poor information flow, invisible operation status, and delayed risk warning in the existing tea industry chain, this solution builds a multi-source perception system covering the upstream, midstream, and downstream of the tea industry chain, establishes a unified data format standard to achieve structural aggregation of multi-source heterogeneous data, ensures data integrity, and facilitates traceability and horizontal comparative analysis of the entire life cycle of tea, providing accurate data support for quality management, cost optimization, and process reengineering.

[0034] (2) Traditional data sharing methods have the risk of data tampering, loss or leakage, and the sharing path is difficult to trace. When the amount of data increases, it is easy to have response delays and uneven node load problems. There is also a lack of quantitative standards in the collaborative process. This solution introduces dynamic mapping, blockchain storage and permission control to achieve standardized conversion, secure sharing and multi-node collaborative management of tea industry chain operation data, improve data parsability, build a distributed ledger based on blockchain technology, ensure data consistency and immutability, and perform logical sharding according to node roles to significantly improve the concurrency and operating efficiency of the blockchain network, improve the security and compliance of data access, and effectively protect the data rights and interests of all participants in the tea industry chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a schematic diagram of a tea industry chain operation monitoring system based on big data sharing and exchange proposed by the present invention;

[0036] Figure 2 is a schematic diagram of a shared switching module;

[0037] Figure 3This is a schematic diagram of the process of constructing a mapping relationship table for aggregated data in Example 6;

[0038] Figure 4 This is a flowchart illustrating the secure storage and sharing of data views using blockchain technology in Example 7.

[0039] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0041] Example 1, see Figure 1 The present invention provides a tea industry chain operation monitoring system based on big data sharing and exchange, including a perception and collection module, a sharing and exchange module, an operation analysis module, and an application display module;

[0042] The sensing and collection module collects basic data from upstream, midstream and downstream links of the tea industry chain, converts the basic data into aggregated data through a unified data format standard and preliminary aggregation, calculates statistical eigenvalues, and sends the aggregated data and statistical eigenvalues ​​to the shared exchange module;

[0043] The shared exchange module dynamically maps the aggregated data to generate a data view of the entire tea industry chain, uses blockchain technology to achieve secure sharing of the data view, and controls the permissions of all participants in accessing the data view.

[0044] The operation analysis module uses a time series analysis model to analyze the data view, evaluate whether the operation status of each link is abnormal, identify deviations and generate early warning information, and generate a trend report and send it to the application display module;

[0045] The application display module presents the operating status of each link in the tea industry chain through a visual interface. Users view monitoring parameters through interactive instructions and generate interactive logs to feed back to the operation analysis module.

[0046] Example 2, see Figure 1 ,This embodiment is based on the above embodiment, and the perception acquisition module includes a data acquisition unit, a data processing unit, and a data aggregation unit;

[0047] The data collection unit covers the upstream, midstream and downstream of the tea industry chain: the upstream involves the planting of tea, the midstream involves the processing and circulation of tea, and the downstream involves the consumer service link; the basic data of each link is collected and sent to the data processing unit;

[0048] The data processing unit defines a unified data format standard, converts the basic data into structured data containing four basic fields: timestamp, geographic location, data type, and numerical field, and performs preliminary cleaning on the structured data to remove outliers and duplicate data;

[0049] The data aggregation unit aggregates the structured data according to the timestamp to obtain aggregated data, calculates statistical characteristic values, and uploads the aggregated data and the statistical characteristic values ​​to the shared exchange module while retaining a local cache copy.

[0050] Example 3, see Figure 1 This embodiment is based on the above embodiment, and the data acquisition unit collects basic data of each link, specifically:

[0051] Environmental sensors and RFID harvest recorders are deployed upstream of the tea industry chain to collect upstream basic data on tea cultivation, including environmental parameters, equipment operating status, tea harvesting time, harvesters, and harvesting batches. These data are then sent to the data processing unit via a LoRa wireless communication interface.

[0052] Video surveillance equipment is used to collect key parameters in the tea processing process, including withering temperature, drying temperature and humidity, processing time, equipment operating status, processing batch number, and operator information. RFID tags and cold chain sensors are deployed in the tea circulation process to monitor the environmental and logistics status during tea storage and transportation. Key processing parameters and storage and transportation information are aggregated into midstream basic data and sent to the data processing unit via the Internet of Things transmission protocol.

[0053] Collect consumption data from terminal sales platforms and user ends, including order data, sales quantity, inventory changes, and customer reviews, organize them into downstream basic data, connect the API interface and send them to the data processing unit.

[0054] Example 4, see Figure 1This embodiment is based on the above embodiment. The data aggregation unit aggregates the structured data according to the timestamp, specifically: using a sliding window algorithm to process the time series data in the structured data, and using an incremental calculation algorithm to process the non-time series data in the structured data to generate aggregated data; grouping the aggregated data according to the timestamp, each group of data corresponds to a time window, performing statistical calculations on the data in each time window, generating statistical characteristic values, including the mean, variance, maximum value and minimum value, storing the aggregated data and statistical characteristic values ​​in the local cache, and uploading them to the shared exchange module at the same time.

[0055] By executing the above operations, this solution aims to address the problems of serious data silos, poor information flow, invisible operating status, and delayed risk warning in the existing tea industry chain. It builds a multi-source perception system covering the upstream, midstream, and downstream of the tea industry chain, establishes a unified data format standard to achieve structural aggregation of multi-source heterogeneous data, ensures data integrity, facilitates full life cycle traceability and horizontal comparative analysis of tea, and provides accurate data support for quality management, cost optimization, and process reengineering.

[0056] Example 5, see Figure 1 and Figure 2 , this embodiment is based on the above embodiment, and the shared exchange module includes a dynamic mapping unit, a blockchain storage unit, and a permission control unit;

[0057] The dynamic mapping unit constructs a mapping relationship table for the aggregated data, selects the core unit to express the semantics of the data in each link, and generates a data view of the entire tea industry chain;

[0058] The blockchain storage unit uses blockchain technology to achieve secure storage and sharing of data views, build a blockchain network, and use all participants in the tea industry chain as nodes to access the blockchain network;

[0059] The authority control unit performs authority control on the nodes in the blockchain.

[0060] Example 6, see Figure 1 、 Figure 2 and Figure 3 This embodiment is based on the above embodiment, and the dynamic mapping unit constructs a mapping relationship table for the aggregated data, including the following steps:

[0061] Step S1: Standard definition, pre-define the data standards for each link in the tea industry chain, including environmental parameters in the planting stage, process indicators in the processing stage, logistics information in the circulation stage, and market data in the consumption stage;

[0062] Step S2: Unit decomposition, perform unit-level decomposition on the aggregated data and calculate the importance weight of each unit in the aggregated structure;

[0063] Step S3: View generation: Use a similarity matching algorithm to compare each unit with predefined data standards. Set a threshold to select core units to express the semantics of the overall data. The number of core units is set to 50% of the total number of units. Build a mapping relationship table and generate a data view based on the mapping relationship table. The formula used is as follows: ;

[0064] Where, Represents the similarity score of the mapping relationship, Represents the index of the unit, Indicates the number of units, represents the actual value of the unit, Represents a predefined data standard, Indicates the The importance weight of each unit, Indicates the The distance of each unit from a predefined data standard.

[0065] Example 7, see Figure 1 、 Figure 2 and Figure 4 This embodiment is based on the above embodiment. The blockchain storage unit implements secure storage and sharing of data views through blockchain technology, including the following steps:

[0066] Step P1: Initialize the blockchain network and use all participants in the tea industry chain as nodes, including tea garden manager nodes, processing factory nodes, logistics and warehousing nodes, and sales terminal nodes. Each node is assigned a unique identity.

[0067] Step P2: Build a distributed ledger. The data view is stored in the ledger in the form of blocks. Each node maintains a complete copy of the ledger. Each block contains the block number, timestamp, data view hash value, previous block hash, and current block hash.

[0068] Step P3: Data sharding: logically shard the block according to the node role. Each shard is composed of some nodes, and the newly added data is mapped to the corresponding shard according to the link to which it belongs;

[0069] Step P4: Generate a sharing report and regularly count the data contribution and access frequency of each node.

[0070] By performing the above operations, traditional data sharing methods have the risk of data tampering, loss or leakage, and the sharing path is difficult to trace. When the amount of data increases, it is easy to have response delays and uneven node load problems, and there is a lack of quantitative standards in the collaboration process. This solution introduces dynamic mapping, blockchain storage and permission control to achieve standardized conversion, secure sharing and multi-node collaborative management of tea industry chain operation data, improve data parseability, build a distributed ledger based on blockchain technology, ensure data consistency and non-tamperability, and perform logical sharding according to node roles to significantly improve the concurrency and operation efficiency of the blockchain network, improve the security and compliance of the data access process, and effectively protect the data rights and interests of all participants in the tea industry chain.

[0071] Example 8, see Figure 1 This embodiment is based on the above embodiment. The permission control unit controls the permissions of nodes in the blockchain. Specifically, a smart contract is designed. Each node accesses the required data in the data view through the smart contract. According to the access path and target data requested by the node, an access token containing user identity information, access time window and data range restriction is dynamically generated, and the access record is automatically written to the blockchain. Zero-knowledge proof is introduced. The node verifies the authenticity of the data without leaking the original data. The permission rules are updated regularly to adjust the node permissions according to user behavior patterns and business needs.

[0072] Example 9, see Figure 1 This embodiment is based on the above embodiment. The operation analysis module uses a time series analysis model to analyze the data view. Specifically, the data view is received, a pre-trained long short-term memory network is accessed to learn the historical data in the data view, the market demand and sales fluctuation trend of the downstream tea industry chain are predicted, a trend report is generated, the deviation between the trend report and the real-time data in the data view is calculated, and whether the operation status of each link in the tea industry chain is abnormal is determined. If the deviation exceeds the set threshold, an early warning message is generated.

[0073] Example 10, see Figure 1 ,This embodiment is based on the above embodiment, and the application display module includes a chart display unit, an event-driven unit, a queue monitoring unit and an interactive feedback unit;

[0074] The chart display unit periodically reads the trend report of the operation analysis module and the data view of the shared exchange module, and displays the operation status of each link of the upstream, midstream and downstream of the tea industry chain through visual charts;

[0075] The event-driven unit uses an event-driven mechanism to update the visual chart in real time, stores the data change events generated in each cycle in a queue, and calls the data update function to modify the data in the visual interface;

[0076] The queue monitoring unit monitors the status of the queue through a heartbeat detection mechanism and automatically triggers a recovery mechanism when the queue is blocked or delayed;

[0077] The interactive feedback unit sets interactive instructions, and the user views the monitoring parameters through the interactive instructions. At the same time, the user's operation behavior is recorded and an interactive log is generated to be fed back to the operation analysis module.

[0078] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0079] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

[0080] The present invention and its embodiments are described above. This description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs structures and embodiments similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

Claims

1. A tea industry chain operation monitoring system based on big data sharing and exchange, characterized by: It includes perception and collection module, sharing and exchange module, operation analysis module, and application display module; The sensing and collection module collects basic data from upstream, midstream and downstream links of the tea industry chain, converts the basic data into aggregated data through a unified data format standard and preliminary aggregation, calculates statistical eigenvalues, and sends the aggregated data and statistical eigenvalues ​​to the shared exchange module; The shared exchange module dynamically maps the aggregated data to generate a data view of the entire tea industry chain, uses blockchain technology to achieve secure sharing of the data view, and controls the permissions of all participants in accessing the data view. The operation analysis module uses a time series analysis model to analyze the data view, evaluate whether the operation status of each link is abnormal, identify deviations and generate early warning information, and generate a trend report and send it to the application display module; The application display module presents the operating status of each link in the tea industry chain through a visual interface. Users view monitoring parameters through interactive instructions and generate interactive logs to feed back to the operation analysis module.

2. A tea industry chain operation monitoring system based on big data sharing and exchange according to claim 1, characterized in that: The perception acquisition module includes a data acquisition unit, a data processing unit, and a data aggregation unit; The data collection unit covers the upstream, midstream and downstream of the tea industry chain: the upstream involves the planting of tea, the midstream involves the processing and circulation of tea, and the downstream involves the consumer service link; the basic data of each link is collected and sent to the data processing unit; The data processing unit defines a unified data format standard, converts the basic data into structured data containing four basic fields: timestamp, geographic location, data type, and numerical field, and performs preliminary cleaning on the structured data to remove outliers and duplicate data; The data aggregation unit aggregates the structured data according to the timestamp to obtain aggregated data, calculates statistical characteristic values, and uploads the aggregated data and the statistical characteristic values ​​to the shared exchange module while retaining a local cache copy.

3. The tea industry chain operation monitoring system based on big data sharing and exchange according to claim 1 is characterized in that: The shared exchange module includes a dynamic mapping unit, a blockchain storage unit, and a permission control unit; The dynamic mapping unit constructs a mapping relationship table for the aggregated data, selects the core unit to express the semantics of the data in each link, and generates a data view of the entire tea industry chain; The blockchain storage unit uses blockchain technology to achieve secure storage and sharing of data views, build a blockchain network, and use all participants in the tea industry chain as nodes to access the blockchain network; The authority control unit performs authority control on the nodes in the blockchain.

4. The tea industry chain operation monitoring system based on big data sharing and exchange according to claim 3 is characterized by: The dynamic mapping unit constructs a mapping relationship table for the aggregated data, including the following steps: Step S1: Standard definition, pre-define the data standards of each link in the tea industry chain; Step S2: Unit decomposition, perform unit-level decomposition on the aggregated data and calculate the importance weight of each unit in the aggregated structure; Step S3: View generation: Use a similarity matching algorithm to compare each unit with predefined data standards, set a threshold to filter core units to express the semantics of the overall data, and the number of core units should be no less than 30% of the total number of units. Build a mapping relationship table and generate a data view based on the mapping relationship table.

5. The tea industry chain operation monitoring system based on big data sharing and exchange according to claim 1 is characterized by: The application display module includes a chart display unit, an event driving unit, a queue monitoring unit and an interactive feedback unit; The chart display unit periodically reads the trend report of the operation analysis module and the data view of the shared exchange module, and displays the operation status of each link of the upstream, midstream and downstream of the tea industry chain through visual charts; The event-driven unit uses an event-driven mechanism to update the visual chart in real time, stores the data change events generated in each cycle in a queue, and calls the data update function to modify the data in the visual interface; The queue monitoring unit monitors the status of the queue through a heartbeat detection mechanism and automatically triggers a recovery mechanism when the queue is blocked or delayed; The interactive feedback unit sets interactive instructions, and the user views the monitoring parameters through the interactive instructions. At the same time, the user's operation behavior is recorded and an interactive log is generated to be fed back to the operation analysis module.

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