Traditional Chinese medicinal material processing and production monitoring management system

Abstract

The invention belongs to the field of production monitoring management, and provides a traditional Chinese medicinal material processing production monitoring management system, which comprises a data acquisition module used for acquiring environment parameter data at each flow node of traditional Chinese medicinal material processing production; the encryption and signature module is used for performing end-to-end encryption on the acquired data and the image data; the edge calculation module is used for receiving the encrypted data from the data acquisition module; the block chain storage module is used for uploading the data verification record of each process node to a block chain main chain through a smart contract; the out-of-chain storage module is used for storing the encrypted data and generating a unique distributed storage address; the intelligent contract module is used for checking at each process node; the anomaly detection and alarm module is used for triggering an anomaly alarm when the verification of the smart contract fails; and the tracing module is used for tracing the processing links of each batch of traditional Chinese medicinal materials based on the whole process record stored by the block chain.

Description

Technical Field

[0001] The invention belongs to the field of production monitoring and management, and in particular relates to a Chinese medicinal material processing production monitoring and management system. Background Art

[0002] The processing of Chinese medicinal materials is the core link in the preparation of Chinese medicine. Its process is complex and has a certain degree of traditional dependence. During the processing, the environmental parameters, equipment status and changes in the appearance of medicinal materials in different process steps (such as drying, slicing, extraction, etc.) have an important impact on the processing quality. However, the current traditional Chinese medicinal materials processing management methods still have many shortcomings in terms of technical support. These problems directly affect the controllability of the quality of Chinese medicinal materials processing, the transparency of data and the quality traceability, which are mainly reflected in the following aspects: In the traditional Chinese medicine processing, key indicators such as environmental parameters (such as temperature, humidity, and air pressure), equipment status (such as operating power and vibration frequency), and appearance of medicinal materials (such as color, shape, and texture) at each link cannot be monitored in real time. The lack of effective connection between data flows between processing links makes process optimization and anomaly detection lack scientific basis.

[0003] The large amount of data generated during the processing (such as environmental parameters, equipment status and medicinal material images) usually relies on manual recording or decentralized storage, which can easily lead to data loss or tampering. Once the processing data is missing or modified, it will directly affect the accuracy of quality management. At the same time, it is difficult to verify the source of the data, which weakens the reliability of quality traceability.

[0004] In the traditional mode, when the equipment operation status, process parameters or processing results are abnormal, they often rely on manual discovery and processing. Due to the lack of automated abnormality detection and alarm mechanism, the response speed of the problem is slow, which may cause further processing quality problems.

[0005] Due to the lack of unified records and data chains in the processing process, the current processing of traditional Chinese medicines mostly relies on post-process testing, and it is impossible to track and manage the quality of each link in real time during the production process. Once a problem occurs in the finished product, it is difficult to quickly locate the responsible node and take corresponding improvement measures.

[0006] The existing processing methods of Chinese medicinal materials lack data transparency, and it is difficult to meet the needs of consumers, regulatory authorities and companies for visual supervision and tamper-proof records of the entire processing process. Summary of the invention In order to solve the problems in the prior art, the present invention provides a Chinese medicinal material processing and production monitoring and management system, including the following modules: A data acquisition module is used to collect environmental parameter data, processing equipment operation status data and medicinal material image data at each process node of the Chinese medicinal material processing and production. The data is acquired in real time through sensor equipment and industrial cameras; The encryption and signature module is used to perform end-to-end encryption on the collected data and image data, and generate digital signatures for the data and images to verify the authenticity of the data source; The edge computing module is used to receive the encrypted data from the data acquisition module, verify its digital signature, and generate a verification record containing a hash value and a timestamp of the data content; The blockchain storage module is used to upload the data verification record of each process node to the blockchain main chain through the smart contract. The data recorded in the main chain includes the data content hash value, timestamp, device identification and the verification record hash value of the previous process node; An off-chain storage module is used to store the encrypted data and generate a unique distributed storage address, which is bound to the corresponding data verification record and stored in the blockchain; Smart contract module, used to verify the consistency of timestamps of uploaded data and images, the legitimacy of parameter ranges, and compliance with process requirements at each process node; Anomaly detection and alarm module, used to trigger anomaly alarm when smart contract verification fails, and record the abnormal status to the blockchain; The traceability module is used to trace the processing links of each batch of Chinese medicinal materials based on the full process records stored in the blockchain. The traceability includes environmental parameters, equipment status, image data storage address and verification records.

[0007] Furthermore, when acquiring the image data, multispectral imaging technology is used to acquire subtle quality features of the medicinal material.

[0008] Furthermore, the encryption and signature module automatically embeds timestamp information each time encryption and signature are performed.

[0009] Furthermore, the edge computing module uploads the abnormal mark to the blockchain for abnormal data that fails signature verification or other verification; triggers an abnormal alarm to notify relevant personnel for manual review.

[0010] Furthermore, the data verification record of each process node in the blockchain storage module is associated with the current node record through the hash value of the previous node to form a continuous chain data structure.

[0011] Furthermore, the distributed storage address of the file in the off-chain storage module serves as the unique identifier of the off-chain storage and is bound to the on-chain data verification record through a smart contract; when the data is uploaded to the off-chain storage, the smart contract automatically writes the generated storage address and data verification record into the blockchain main chain.

[0012] Furthermore, the timestamp consistency check includes: verifying whether the timestamps of uploaded data and images are consistent with the processing flow time expected by the system; ensuring that the timestamps of multiple data files at the same process node are consistent; when data or images are uploaded, the smart contract is triggered to automatically check the timestamp field; comparing the timestamp of the current node with the timestamp of the previous node record to ensure that the time sequence is correct; if the timestamps are inconsistent or exceed the error range, mark the record as abnormal and trigger an alarm.

[0013] Furthermore, the parameter range validity check includes: Clarify the input and output parameter ranges of each processing node, and set the parameter ranges according to process requirements, experimental data, and historical data; When the actual output parameter range falls within the set range, it means the parameters are legal; If it is out of range, it is due to process abnormality, equipment failure or data collection error, which requires further verification.

[0014] Furthermore, the compliance check of the process requirements includes: Determine the color change range of the medicinal material after the current node according to the process requirements; Combined with historical processing data, the color distribution characteristics of the nodes before and after each step are counted to form a benchmark range; Use industrial cameras at each node to collect high-resolution images of medicinal materials and perform preprocessing; Perform color distribution analysis, color histogram, and statistically analyze the distribution of colors in different channels; Calculate the color mean and variance, calculate the average value and distribution range of the color, and represent the overall characteristics of the color; Perform feature point matching, extract color and texture feature points, and perform before-after comparison; Compare the color features of the current node image with the color features of the previous node image and calculate the degree of change; Determine whether the color distribution change of the current node image is within the process standard range; Thresholds are set based on experimental data. If the color change exceeds the process range, it is marked as abnormal and recorded.

[0015] Further, in the traceability module, the batch number, time range or node identification provided by the user; Query all relevant records from the blockchain; Acquire image data through a distributed storage system; Verify the matching of data and storage address; Returns a traceability report covering all processing steps, including detailed information for each node.

[0016] The present invention provides a monitoring and management system for the processing and production of Chinese medicinal materials, which achieves the following beneficial effects through the deep integration of modern information technology and traditional Chinese medicinal materials processing technology: The system uses the data acquisition module to achieve high-precision real-time monitoring of environmental parameters (such as temperature, humidity, and air pressure), equipment status (such as power and vibration frequency), and medicinal material appearance (such as color, shape, and texture), ensuring that every link in the processing process is within a controllable range and providing data support for process optimization and quality improvement.

[0017] The system uses edge computing modules and smart contract modules to perform real-time analysis on collected data. It can automatically detect abnormal situations in the processing process (such as parameter exceeding the limit or process not meeting the requirements), trigger abnormal alarms, and notify relevant personnel to handle them in a timely manner, significantly improving problem response speed and quality management efficiency.

[0018] The system uses blockchain technology to record the entire processing process and supports the traceability of each batch of Chinese herbal medicines, including environmental parameters, equipment status, image data and verification records. The traceability function can quickly locate problem links and clarify responsibilities, thereby improving the transparency of production management and quality controllability.

[0019] By combining blockchain storage with off-chain storage, the system achieves transparent data management. The distributed ledger records and smart contract execution of blockchain ensure the openness and credibility of processing data, meeting the visual supervision needs of consumers, enterprises and regulatory authorities for the processing process.

[0020] Through intelligent monitoring, analysis and recording methods, the system significantly reduces the need for manual intervention and avoids human errors. At the same time, it improves the automation level of the processing process, improves management efficiency and overall production capacity.

[0021] In summary, the system of the present invention can comprehensively improve the refined management, data security and quality traceability of the Chinese medicinal materials processing process, provide effective technical support for the digitalization, intelligence and standardization of the Chinese medicinal materials industry, and has significant economic value and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 It is a system diagram of the method of the present invention. DETAILED DESCRIPTION

[0024] Below, the invention is preferably described in conjunction with the accompanying drawings and specific implementation methods.

[0025] This embodiment solves the above problem through the following steps: In one embodiment, reference Figure 1 The present invention provides a monitoring and management system for the processing and production of Chinese medicinal materials. The system is suitable for real-time monitoring, data collection, intelligent analysis and quality traceability of each link in the processing and production of Chinese medicinal materials. It aims to achieve refined management of the processing process, transparent data storage and tamper-proof quality assurance of the entire process through the deep integration of modern information technology and traditional Chinese medicinal materials processing technology.

[0026] The data acquisition module is used to collect environmental parameter data, processing equipment operation status data and medicinal material image data at each process node of Chinese medicinal material processing and production. The data is acquired in real time through sensor equipment and industrial cameras.

[0027] Through the deployment of this module, high-precision data collection can be achieved throughout the entire process of Chinese medicinal materials processing and production, providing strong data support for process optimization, equipment maintenance, quality monitoring and abnormality tracing, and ensuring the transparency and controllability of the processing process. Specifically: Environmental parameter data collection, including temperature, humidity, air pressure, air velocity and other environmental conditions closely related to the processing technology of Chinese medicinal materials. High-precision environmental sensors (such as temperature and humidity sensors, air pressure sensors) are used to obtain the changes in environmental parameters of each node in real time through multi-point distributed layout.

[0028] Data collection of processing equipment operation status includes equipment operation parameters, such as operation speed, power, vibration frequency, equipment temperature and processing status, etc. The operation status of the equipment is monitored in real time through the IoT sensors built into the equipment (such as vibration sensors, current sensors, temperature sensors), and transmitted to the data processing center through standardized protocols.

[0029] The image data collection of medicinal materials includes the appearance characteristics of medicinal materials at different process nodes, such as shape, color, texture, and particle uniformity, etc., and supports the visual recording of the status of medicinal materials during processing. The industrial cameras deployed at each node use high-resolution imaging technology and autofocus functions to capture real-time images of medicinal materials; combined with multi-spectral imaging technology (such as infrared and ultraviolet) to obtain subtle quality characteristics of medicinal materials.

[0030] The encryption and signature module is used to perform end-to-end encryption on the collected data and image data, and generate digital signatures for the data and images to verify the authenticity of the data source.

[0031] In this module, all data collected by the data acquisition module are encrypted, including: environmental parameter data (such as temperature, humidity, and air pressure); equipment operation status data (such as vibration frequency and power value); and medicinal material image data (including static pictures and dynamic videos).

[0032] Use symmetric encryption algorithms (such as AES-256) to quickly encrypt large amounts of data to ensure efficient processing; the encrypted data is then encrypted using an asymmetric encryption algorithm (such as RSA) to ensure data security during transmission.

[0033] Furthermore, the data is initially encrypted at the collection device; after reaching the edge node or blockchain node via the transmission network, it is decrypted and verified.

[0034] Generate a unique digital signature for all collected data and image data to verify the source and integrity of the data. Use a hash algorithm (such as SHA-256) to generate a summary of the collected data; use the private key on the device to encrypt the data summary and generate a digital signature; the digital signature is uploaded to the blockchain or data center along with the encrypted data.

[0035] The blockchain node or edge node uses the corresponding public key to verify the digital signature; if the data summary is inconsistent with the signature verification result, it is considered that the data has been tampered with or the source is unreliable.

[0036] Furthermore, timestamp information is automatically embedded during each encryption and signing to ensure the timing of data and prevent replay attacks.

[0037] Encryption and signing are performed at the sensor end; secondary signing is performed at the edge node to ensure the security of data in the transmission path.

[0038] Through the deployment of this module, the data security and credibility in the processing and production of Chinese medicinal materials can be fully guaranteed, thereby improving the transparency and management efficiency of the processing process.

[0039] The edge computing module is used to receive encrypted data from the data acquisition module, verify its digital signature, and generate a verification record containing a hash value and a timestamp of the data content.

[0040] The data acquisition module uploads all environmental parameter data, processing equipment operation status data, and medicinal material image data. The data is sent to the edge computing module in an encrypted format through a secure transmission protocol (such as TLS, DTLS).

[0041] Furthermore, the public key of the sensor device or camera device is used to verify the digital signature of the data to confirm the legitimacy of the data source.

[0042] After decrypting the digital signature, the hash value of the data content is compared to ensure that the data has not been tampered with. If the verification fails (such as signature mismatch or illegal source), an alarm is immediately triggered and the data batch is marked as abnormal.

[0043] Use a secure hash algorithm (such as SHA-256) to generate a unique hash value for the data content. The hash value is used as the unique identifier of the data content and is used for subsequent blockchain storage and verification. Ensure that the data in each link is consistent with the hash value it generates to avoid data tampering during transmission or storage.

[0044] Furthermore, the edge computing module is connected to a trusted time server to ensure that the generated timestamps are accurate and unified. The generation time of each piece of data is recorded to ensure the consistency of data timing and prevent data reuse or replay attacks.

[0045] Upload the verification record to the blockchain main chain to form an unalterable evidence. For large-scale image data, generate an off-chain storage address (such as an IPFS link) and bind the address to the verification record and store it on the blockchain.

[0046] Furthermore, for abnormal data that fails signature verification or other checks, the abnormal mark is uploaded to the blockchain; an abnormal alarm is triggered to notify relevant personnel for manual review; and the abnormal data is stored for subsequent analysis.

[0047] The blockchain storage module is used to upload the data verification records of each process node to the blockchain main chain through smart contracts. The data recorded on the main chain includes the data content hash value, timestamp, device identification and the verification record hash value of the previous process node.

[0048] In this module, smart contracts are used to automatically perform the storage operation of data verification records to ensure that each record uploaded to the blockchain is verified according to predefined rules. Data format check, timestamp consistency check, hash value verification, chain association check with the previous node record, etc. When the edge computing module generates a verification record, the smart contract is triggered and the data upload to the main chain is automatically completed.

[0049] In this module, the data content contained in each record is processed by a hash algorithm (such as SHA-256) to generate a unique hash value, which is used to identify the content and integrity of the data. Each record is accompanied by an accurate timestamp to mark the time when the data was generated and uploaded, ensuring the time sequence consistency of the processing flow. Each record contains the unique identifier of the device that generated the data (such as a sensor ID or camera ID) to track the source of the data. Each record is chained with the verification record of the previous process node through a hash value to ensure the integrity and traceability of the entire processing flow.

[0050] The data verification record of each process node is associated with the current node record through the hash value of the previous node, forming a continuous chain data structure. This chain structure ensures the integrity and consistency of the data in the time series and prevents data loss or forgery. The blockchain storage module supports tracing the processing records of each process node through the main chain, covering raw material acceptance, processing operations, quality inspection and finished product packaging.

[0051] In this module, once the data in the main chain is written, it cannot be tampered with or deleted, ensuring the authenticity of all processing flow records.

[0052] The hash value chain structure further ensures the continuity of data. Even if the data of a certain node is tampered with, the entire chain will be destroyed. The data of each process node is recorded in the main chain, forming a complete chain data structure, which supports transparent supervision of the processing flow by multiple parties (such as internal management of the enterprise, regulatory authorities and consumers). The timestamps and verification records stored in the main chain can quickly locate abnormal nodes, making it easier to take corrective measures in a timely manner.

[0053] Through this blockchain storage module, trusted recording and chain storage of data can be achieved at each process node of Chinese medicinal materials processing and production, thereby ensuring data security, integrity and traceability throughout the entire process, and providing technical support for Chinese medicinal materials processing management.

[0054] The off-chain storage module is used to store the encrypted data and generate a unique distributed storage address, which is bound to the corresponding data verification record and stored in the blockchain.

[0055] In this module, blockchain records are bound to corresponding data verification records to achieve a secure association between off-chain data and on-chain information.

[0056] The storage content includes high-capacity encrypted data generated during the processing of Chinese medicinal materials: high-resolution images of medicinal materials; data on the process operation process, etc.

[0057] Furthermore, large files are sharded to improve distributed storage efficiency while enhancing data redundancy and fault tolerance.

[0058] Each file generates a unique hash value through a hash algorithm (such as SHA-256 or Blake2) as the storage identifier of the file. Combined with a distributed storage system (such as IPFS, Filecoin or other similar technologies), a globally unique storage address is generated for each file.

[0059] The file storage address is bound to the data verification record (including data content hash value, timestamp and device identification) through the on-chain smart contract to ensure the unique correspondence between the off-chain file and the on-chain record.

[0060] Furthermore, based on the distributed file system, data can be stored off-chain, and files can be distributed and stored on multiple nodes to avoid single-point storage risks; data can be stored in shards, and the failure of any node will not affect the integrity of the file. Support blockchain-driven storage systems, combined with economic incentive mechanisms to ensure the stability of storage nodes.

[0061] The distributed storage address of the file is used as the unique identifier of the off-chain storage and is bound to the on-chain data verification record through a smart contract. When the data is uploaded to the off-chain storage, the smart contract automatically writes the generated storage address and data verification record to the blockchain main chain. The storage address of the off-chain data is verified by multiple parties on the blockchain to prevent tampering and forgery. When accessing off-chain data, the hash value recorded on the blockchain is compared with the hash value of the actual stored file to ensure that the file has not been tampered with.

[0062] Through this module, large-scale data (such as videos and images) no longer need to be stored directly on the blockchain main chain, but are stored in an off-chain distributed system, significantly reducing the computing and storage burden of blockchain storage.

[0063] The distributed storage system can support high-concurrency access and meet the real-time requirements of Chinese herbal medicine processing and production.

[0064] Through the design and implementation of this off-chain storage module, it can effectively support the storage and traceability needs of large-scale data in the processing and production of Chinese medicinal materials while ensuring data integrity and security. At the same time, it can significantly optimize the storage performance of the blockchain main chain and improve the overall operating efficiency and reliability of the system.

[0065] The smart contract module is used to verify the consistency of timestamps of uploaded data and images, the legality of parameter ranges, and compliance with process requirements at each process node.

[0066] This module is deployed on the blockchain main chain and is dedicated to automatically verifying the uploaded data and image information at each process node. The core content of the verification includes timestamp consistency, parameter range legitimacy, and compliance with the requirements of Chinese herbal medicine processing technology, thereby ensuring the accuracy of the data and the standardization of the entire process.

[0067] First, perform a timestamp consistency check to verify whether the timestamps of the uploaded data and images are consistent with the system's expected processing flow time; ensure that multiple data files (such as images and sensor data) at the same process node have consistent timestamps. When data or images are uploaded, the smart contract is triggered to automatically check the timestamp field. Compare the timestamp of the current node with the timestamp of the previous node record to ensure that the time sequence is correct. The allowable error range of the timestamp can be set to Δt (such as ±5 seconds). If the timestamp is inconsistent or exceeds the error range, mark the record as abnormal and trigger an alarm.

[0068] Then perform the parameter range validity check. In the parameter range validity check, it is necessary to clarify the input parameter and output parameter range of each processing flow node. These ranges can be set according to process requirements, experimental data and historical data. Take the drying step as an example: The input parameters mainly come from the output of the previous node, including: The weight of the medicinal materials, record the weight of the raw materials before drying.

[0069] The moisture content of medicinal materials indicates the proportion of water in the medicinal materials, which is usually collected through testing equipment.

[0070] The output parameters of the drying step need to be defined by the process model and set within a reasonable range based on experimental data, including: The weight after drying usually decreases due to water evaporation, so a normal weight range needs to be set. For example, the weight after drying should be slightly less than the weight of the raw material, and the extent of the weight reduction depends on the process requirements.

[0071] The moisture content after drying refers to the proportion of water remaining in the medicinal material after drying. A reasonable target range needs to be set. For example, the moisture content should be reduced to a certain proportion to meet the drying effect.

[0072] Refer to process requirements, such as the expected rate of water evaporation, drying time and temperature standards.

[0073] Historical batch data, collect input and output parameters from past production, analyze the actual range and summarize the reasonable range.

[0074] Equipment capacity. The performance of the drying equipment determines the possible water evaporation efficiency.

[0075] When the actual output weight or moisture content falls within the set range, it means that the parameters are legal; if it exceeds the range, it may be a process abnormality, equipment failure or data collection error, which requires further verification.

[0076] By setting the parameter variation range of each processing node, the standardization and consistency of the operation of each node can be ensured, and the quality control capability of the production process can be improved. The drying step is just an example. Other nodes such as slicing, extraction, packaging, etc. also need to define the corresponding input and output ranges according to the specific process characteristics.

[0077] Then, the compliance check of the process requirements is carried out. This step is to ensure that the uploaded data and images meet the process requirements of the processing technology, such as the processing sequence between nodes, the law of environmental parameter changes, etc. When recording data on the chain, verification is carried out according to the process sequence rules. Verify the sequence and dependency of the process nodes, and confirm whether the processing status of the medicinal materials meets the requirements through images.

[0078] Specifically, in the processing of traditional Chinese medicine, different process steps (such as drying, extraction, and calcination) may cause significant changes in the color of the medicine. By analyzing the color distribution of the medicine image at the previous and next nodes and judging whether its change meets the process requirements, the processing quality can be effectively monitored.

[0079] Determine the color range of the medicinal material after the current node based on the process requirements. For example, the color of the medicinal material after drying should change from a lighter wet tone to a darker dry tone. The medicinal material may need to present a specific color (such as light brown or dark red) after extraction.

[0080] Combined with historical processing data, the color distribution characteristics of the nodes before and after each step are counted to form a benchmark range.

[0081] Use industrial cameras to collect high-resolution images of medicinal materials at each node. Ensure that the image acquisition environment is consistent (such as lighting and background) to avoid external factors affecting color features. Denoise the image to filter out noise in the acquired image. Convert the color space to convert the image from RGB color space to Lab or HSV color space to facilitate color feature extraction. Crop the image to extract the main area of ​​the medicinal material and remove background interference.

[0082] Then perform color distribution analysis and color histogram to count the distribution of colors in different channels, such as the frequency distribution of red, green, and blue channels. Color mean and variance, calculate the average value and distribution range of colors, and represent the overall characteristics of colors. Feature point matching, for some medicinal materials with complex textures, color texture feature points can be extracted for before and after comparison. Compare the color features of the current node image with the color features of the previous node image to calculate the degree of change.

[0083] Determine whether the color distribution change of the current node image is within the process standard range. For example, the change range of the color mean should be within a specific range. The histogram difference of the color distribution should meet the process requirements. Set thresholds based on experimental data, such as the color distribution change does not exceed a certain ratio or the color mean change does not exceed a certain range. If the color change exceeds the process range, mark it as abnormal and record it.

[0084] By analyzing the changes in image color distribution at the previous and next nodes and combining it with the color range set by the process standards, it is possible to accurately verify the processing status and ensure that the processing quality of Chinese medicinal materials meets the expected requirements.

[0085] The anomaly detection and alarm module is used to trigger an abnormal alarm when the smart contract verification fails and record the abnormal status to the blockchain.

[0086] The anomaly detection and alarm module is used to automatically trigger an abnormal alarm through a smart contract when it is found that the parameters, process or image status do not meet the requirements during the processing of traditional Chinese medicines. At the same time, the abnormal status and related data are recorded in the blockchain to ensure that the problem is handled in a timely manner and has a complete traceability chain.

[0087] When verifying processing data, process parameters or image features, the smart contract detects that it does not comply with the preset rules or exceeds the parameter range.

[0088] Including but not limited to: Parameters are out of legal range (such as temperature is too high, humidity is too low). Image color distribution or shape characteristics do not meet process standards. Timestamp sequence is abnormal or process dependency verification fails.

[0089] When an abnormality is detected by the smart contract, the system automatically triggers an alarm without manual intervention. Through the abnormality detection and alarm module, dynamic monitoring of the entire process of Chinese herbal medicine processing can be achieved, abnormal situations can be quickly responded to, and problems can be recorded in the blockchain, providing technical support for processing quality control and process optimization.

[0090] The traceability module is used to trace the processing links of each batch of Chinese medicinal materials based on the full process records stored in the blockchain. The traceability includes environmental parameters, equipment status, image data storage address and verification records.

[0091] The traceability module is used to comprehensively trace and analyze the processing links of each batch of Chinese herbal medicines through the full-process processing records stored in blockchain. Based on the immutability and distributed storage characteristics of blockchain, this module can provide detailed processing information, including environmental parameters, equipment status, image data storage address and smart contract verification records, providing reliable technical support for quality control, problem location and responsibility tracing.

[0092] Specifically, according to the batch number, the corresponding processing link records are retrieved from the blockchain. The verification records, environmental parameters, equipment status and image data storage address of each node are extracted. The data of each node are integrated to form a complete processing chain. The on-chain records and off-chain image data are associated to generate a complete traceability report.

[0093] Further, the batch number, time range or node ID provided by the user. Query all relevant records from the blockchain. Obtain image data through a distributed storage system (such as IPFS). Verify the matching of data with the storage address. Return a traceability report containing all processing links, including detailed information for each node.

[0094] Through the deployment of the traceability module, detailed tracking and comprehensive monitoring of the entire process of Chinese medicinal materials processing can be achieved, providing reliable support for quality management, problem troubleshooting and responsibility traceability, and improving processing transparency and customer trust.

[0095] The prior art mentioned in the above background technology section and specific embodiment section of the present invention can be used as part of the present invention to understand the meaning of some technical features or parameters.

Claims

1. A monitoring and management system for processing and production of Chinese medicinal materials, characterized in that: The system comprises: A data acquisition module is used to collect environmental parameter data, processing equipment operation status data and medicinal material image data at each process node of the Chinese medicinal material processing and production. The data is acquired in real time through sensor equipment and industrial cameras; The encryption and signature module is used to perform end-to-end encryption on the collected data and image data, and generate digital signatures for the data and images to verify the authenticity of the data source; The edge computing module is used to receive the encrypted data from the data acquisition module, verify its digital signature, and generate a verification record containing a hash value and a timestamp of the data content; The blockchain storage module is used to upload the data verification record of each process node to the blockchain main chain through the smart contract. The data recorded in the main chain includes the data content hash value, timestamp, device identification and the verification record hash value of the previous process node; An off-chain storage module is used to store the encrypted data and generate a unique distributed storage address, which is bound to the corresponding data verification record and stored in the blockchain; Smart contract module, used to verify the consistency of timestamps of uploaded data and images, the legitimacy of parameter ranges, and compliance with process requirements at each process node; Anomaly detection and alarm module, used to trigger anomaly alarm when smart contract verification fails, and record the abnormal status to the blockchain; The traceability module is used to trace the processing links of each batch of Chinese medicinal materials based on the full process records stored in the blockchain. The traceability includes environmental parameters, equipment status, image data storage address and verification records.

2. The Chinese medicinal materials processing and production monitoring and management system according to claim 1, characterized in that: When acquiring the image data, multispectral imaging technology is used to acquire subtle quality features of the medicinal materials.

3. The Chinese herbal medicine processing and production monitoring and management system according to claim 1, characterized in that: The encryption and signature module automatically embeds timestamp information each time encryption and signature are performed.

4. The Chinese medicinal materials processing and production monitoring and management system according to claim 1, characterized in that: The edge computing module uploads the abnormal mark to the blockchain for abnormal data that fails signature verification or other verification; triggers an abnormal alarm to notify relevant personnel for manual review.

5. The Chinese medicinal materials processing and production monitoring and management system according to claim 1, characterized in that: The data verification record of each process node in the blockchain storage module is associated with the current node record through the hash value of the previous node to form a continuous chain data structure.

6. The Chinese herbal medicine processing and production monitoring and management system according to claim 1, characterized in that: The distributed storage address of the file in the off-chain storage module serves as the unique identifier of the off-chain storage and is bound to the on-chain data verification record through a smart contract; when the data is uploaded to the off-chain storage, the smart contract automatically writes the generated storage address and data verification record into the blockchain main chain.

7. The Chinese herbal medicine processing and production monitoring and management system according to claim 1, characterized in that: The timestamp consistency check includes: verifying whether the timestamps of uploaded data and images are consistent with the processing flow time expected by the system; ensuring that the timestamps of multiple data files at the same process node are consistent; when data or images are uploaded, the smart contract is triggered to automatically check the timestamp field; comparing the timestamp of the current node with the timestamp of the previous node record to ensure that the time sequence is correct; if the timestamps are inconsistent or exceed the error range, mark the record as abnormal and trigger an alarm.

8. The monitoring and management system for processing and producing Chinese medicinal materials according to claim 1, characterized in that: The parameter range legality check includes: Clarify the input and output parameter ranges of each processing node, and set the parameter ranges according to process requirements, experimental data, and historical data; When the actual output parameter range falls within the set range, it means the parameters are legal; If it is out of range, it is due to process abnormality, equipment failure or data collection error, which requires further verification.

9. The Chinese herbal medicine processing and production monitoring and management system according to claim 1, characterized in that: The compliance check of the process requirements includes: Determine the color change range of the medicinal material after the current node according to the process requirements; Combined with historical processing data, the color distribution characteristics of the nodes before and after each step are counted to form a benchmark range; Use industrial cameras at each node to collect high-resolution images of medicinal materials and perform preprocessing; Perform color distribution analysis, color histogram, and statistically analyze the distribution of colors in different channels; Calculate the color mean and variance, calculate the average value and distribution range of the color, and represent the overall characteristics of the color; Perform feature point matching, extract color and texture feature points, and perform before-after comparison; Compare the color features of the current node image with the color features of the previous node image and calculate the degree of change; Determine whether the color distribution change of the current node image is within the process standard range; Thresholds are set based on experimental data. If the color change exceeds the process range, it is marked as abnormal and recorded.

10. The Chinese medicinal materials processing and production monitoring and management system according to claim 1, characterized in that: In the traceability module, the batch number, time range or node identifier provided by the user; Query all relevant records from the blockchain; Acquire image data through a distributed storage system; Verify the matching of data and storage address; Returns a traceability report covering all processing steps, including detailed information for each node.

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