A method, system and device for processing multi-dimensional supervision evaluation data

Abstract

The present invention discloses a method, system and device for processing multi-dimensional supervision and evaluation data, and belongs to the technical field of supervision data processing. The method comprises the following steps: obtaining processing supervision information and preset scores of regulations; constructing an aquatic product processing quality and safety assessment model, obtaining an aquatic product processing quality and safety assessment index, and performing an aquatic product processing plant alarm and a processing process early warning according to the index. The present invention obtains an aquatic product processing quality and safety assessment index according to the aquatic product processing quality and safety assessment model, and early warnings the processing process of the aquatic product processing plant according to the aquatic product processing quality and safety assessment index, so as to timely warn of processing quality and safety anomalies in the aquatic product processing process, thereby timely discovering safety hazards, and solving the problem that the current multi-dimensional supervision data processing method for aquatic products has the problem that the supervision data of the aquatic product processing process is not transparent and easy to falsify, resulting in an increase in the quality and safety hazards of aquatic products.

Description

Technical Field

[0001] The present invention relates to the technical field of regulatory data processing, and in particular to a method, system and device for processing multi-dimensional regulatory evaluation data. Background Art

[0002] With the development of social economy and the increase of regulatory needs, regulatory data has become increasingly large and complex. Multi-dimensional data processing methods can help regulatory authorities better understand and use these data, identify problems, optimize resource allocation, and improve regulatory efficiency. Multi-dimensional data processing methods are closely related to the quality and safety of aquatic products. The quality and safety of aquatic products involves many aspects, such as water quality, breeding environment, processing technology, etc., which require comprehensive consideration of data from multiple dimensions.

[0003] The multi-dimensional regulatory data processing methods currently commonly used for aquatic products include: first, through data collection and uploading, collect data related to aquatic product quality and safety, and upload it to the management platform; second, use the management platform to integrate and manage data, and conduct analysis and evaluation, such as making a distribution map of the qualified rate; then, monitor the data in real time, and issue reminders to areas with low qualified rates to guide the adoption of regulatory measures.

[0004] For example, the invention patent with publication number: CN105678630A discloses a smart marine environment and aquatic product quality and safety supervision system, including: aquatic product rapid inspection application, aquatic product laboratory application and aquatic product geographic information management platform; the aquatic product rapid inspection application uses rapid inspection equipment to quickly inspect aquatic products in various regions, and uploads the inspection data to the aquatic product geographic information management platform; the aquatic product laboratory application uses laboratory instruments to accurately inspect aquatic products, and uploads the inspection data to the aquatic product geographic information management platform; the aquatic product geographic information management platform makes a geographical location distribution map of the qualified rate of the items to be inspected, and highlights the three production sea areas with the lowest qualified rate and issues reminders to the marine environment supervision department.

[0005] For example, the invention patent with publication number: CN101162512A discloses a method and system for the whole-process management and traceability of aquaculture product quality and safety, which includes: by solidifying the pollution-free aquaculture standard production database, adopting the Hazard Analysis and Critical Control Point (HACCP) system, and managing the whole process of aquaculture production of aquaculture products (fish, shrimp, crab) from seedling cultivation to stocking, from feed feeding to drug use, providing an aquaculture management and traceability solution supported by barcode automatic recognition technology that is in line with the global unified coding (EAN / UCC), realizing the organic combination of production process coding and individual identification of aquaculture products, and achieving seamless integration of production information and barcode identification information.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] However, there are many safety issues in the processing of aquatic products that may cause the deterioration of aquatic products. For example, some processing companies may use unqualified additives in pursuit of profits, or fail to strictly control sanitary conditions during processing. In addition, most aquatic product processing plants on the market manually manage the supervision records or electronic data of the aquatic product processing process. Such electronic records are easily modified and falsified by humans, resulting in opaque safety supervision of the processing process and increased risks to the quality and safety of aquatic products.

[0008] In summary, the current multi-dimensional regulatory data processing methods for aquatic products have the problem that the regulatory data of the aquatic product processing process is opaque and easy to falsify, which leads to increased risks to the quality and safety of aquatic products. Summary of the invention

[0009] The embodiments of the present application provide a method, system and device for processing multi-dimensional supervision and evaluation data, thereby solving the problem that the supervision data of the aquatic product processing process is opaque and easy to falsify, which leads to increased quality and safety risks of aquatic products. This method can provide early warning of processing quality and safety anomalies in the aquatic product processing process, thereby timely discovering safety hazards.

[0010] The embodiment of the present application provides a method for processing multi-dimensional supervision and evaluation data, including the following steps: obtaining processing supervision information of aquatic product processing plants from the blockchain; obtaining designated regulations and preset scores corresponding to the regulations; inputting aquatic product processing quality and safety assessment model according to the processing supervision information and the preset scores of the regulations to obtain aquatic product processing quality and safety assessment index; issuing an alarm on the processing quality and safety situation of the aquatic product processing plant according to the aquatic product processing quality and safety assessment index; sending the aquatic product processing quality and safety assessment model to the aquatic product processing plant, which directly obtains a real-time aquatic product processing quality and safety assessment index based on the real-time obtained processing supervision information and the preset scores of the regulations, and issues an alarm on the processing quality and safety situation of the aquatic product processing plant according to the aquatic product processing quality and safety assessment index. The process is warned; feedback information from the aquatic product processing plant is obtained and the aquatic product processing quality and safety assessment model is retrained to obtain an updated aquatic product processing quality and safety assessment model, and the updated aquatic product processing quality and safety assessment model is sent to the aquatic product processing plant again: when the aquatic product processing plant obtains real-time processing supervision information, a specified hash function is used to generate a hash value corresponding to the real-time processing supervision information, and a timestamp is added, and the real-time processing supervision information, hash value and timestamp are uploaded to the blockchain together. When the blockchain obtains the real-time processing supervision information, hash value and timestamp, the specified hash function is used to verify the integrity of the hash value. If it is complete, it is saved in the blockchain. If it is incomplete, the hash verification is unsuccessful and the real-time processing supervision information is questionable.

[0011] Furthermore, the alerting of the processing quality and safety situation of aquatic product processing plants refers to: counting and numbering all aquatic product processing plants; using the IP address used by the aquatic product processing plant to upload data to the blockchain as the unique identifier of the aquatic product processing plant, and associating the unique identifier with the aquatic product processing quality and safety assessment index one by one; setting a limit value according to the aquatic product processing quality and safety assessment index uploaded by each aquatic product processing plant; recording the aquatic product processing plants whose aquatic product processing quality and safety assessment index exceeds the limit value, and when the number of excesses reaches a specified value, alerting the aquatic product processing plant and marking the aquatic product processing plant.

[0012] Furthermore, the method for setting the boundary value is: obtaining the aquatic product processing quality and safety assessment index of all historical aquatic product processing plants and the problem records of processing problems occurring in the aquatic product processing plants, and performing data preprocessing and standardization on them; performing feature extraction based on the data after data preprocessing, performing cluster analysis on the extracted features according to the K-means clustering algorithm to obtain the cluster center, and setting the boundary value according to the aquatic product processing quality and safety assessment index of the cluster center.

[0013] Furthermore, the early warning of the processing process of the aquatic product processing plant refers to: conducting classified observations through sensors based on the processing flow within the aquatic product processing plant, and obtaining processing supervision information obtained from the classified observations; inputting the processing supervision information obtained in real time into an aquatic product processing quality and safety assessment model to obtain an aquatic product processing quality and safety assessment index; when the aquatic product processing quality and safety assessment index is lower than a preset threshold, issuing a processing process safety early warning notice to the aquatic product processing plant.

[0014] Furthermore, the processing supervision information includes: processing workshop temperature, processing workshop humidity, additive qualification rate, operating status of processing equipment, number of processing personnel's operating specification records, number of processing personnel's hygiene and cleaning records, and processing video monitoring data.

[0015] Furthermore, the construction process of the aquatic product processing quality and safety assessment model is as follows: preprocessing and standardizing the processing supervision information; numbering each device in the aquatic product processing plant; obtaining the total preset score of the processing supervision information in accordance with the regulations, including the total preset score of the production workshop environmental safety monitoring standards corresponding to the regulations, the total preset score of the processing personnel operation standard safety traceability monitoring standards, the total preset score of the workshop production equipment monitoring standards, and the total preset score of the biochemical property risk monitoring standards; obtaining the total score of the preset scores of each regulation of the specified regulations; constructing the aquatic product processing quality and safety assessment model based on the preprocessed and standardized processing supervision information and the total preset score to obtain the aquatic product processing quality and safety assessment index; the aquatic product processing quality and safety assessment model is:

[0016]

[0017] In the formula, FI is the aquatic product processing quality and safety assessment index, GH is the processing workshop temperature, RH is the processing workshop humidity, RFH is the processing personnel operation standard index, EH i is the operating status of the i-th processing equipment, i is the number of the processing equipment, i=1,2,3,...,N, N is the total number of processing equipment numbers, EH=1 indicates normal operating status, EH=0 indicates abnormal operating status, TER is the qualified rate of additives, Y1 is the sum of the preset scores of the regulations corresponding to the production workshop environmental safety monitoring standards, Y2 is the sum of the preset scores corresponding to the processing personnel operation specification safety traceability monitoring standards, Y3 is the sum of the preset scores corresponding to the workshop production equipment monitoring standards, and Y4 is the sum of the preset scores corresponding to the biochemical property risk monitoring standards.

[0018] Furthermore, the processing personnel operation specification index is obtained by: extracting the number of processing personnel operation specification records, the number of processing personnel hygiene and cleaning records, and the processing video monitoring data from the processing supervision information; extracting the number of processing personnel operation specification verifications and the number of processing personnel hygiene and cleaning verifications from the processing video monitoring data; constructing a processing personnel operation specification evaluation model for calculating the processing personnel operation specification index based on the number of processing personnel operation specification records, the number of processing personnel hygiene and cleaning records, and the number of processing personnel operation specification verifications and the number of processing personnel hygiene and cleaning verifications extracted from the processing supervision information.

[0019] Furthermore, the process of retraining the aquatic product processing quality and safety assessment model is as follows: at regular time intervals, based on the boundary value of the aquatic product processing quality and safety assessment index and the historical aquatic product processing quality and safety assessment index, the cloud supervision platform calculates the standard deviation of the aquatic product processing quality and safety assessment index; based on the expert experience method, the boundary value based on the aquatic product processing quality and safety assessment index and the preset scores corresponding to the specified regulations and regulations are reset according to the standard deviation; and they are re-introduced into the aquatic product processing quality and safety assessment model to obtain a new aquatic product processing quality and safety assessment model.

[0020] The embodiment of the present application provides a processing device for multi-dimensional supervision and evaluation data, including: a supervision information acquisition module, a preset score acquisition module, an evaluation index calculation module, an early warning module, a model distribution module, and a model update module; the supervision information acquisition module is used to obtain processing supervision information of aquatic product processing plants from a blockchain; the preset score acquisition module is used to obtain preset scores corresponding to specified regulations and regulations; the evaluation index calculation module is used to input aquatic product processing quality and safety evaluation model according to the processing supervision information and the preset scores of the regulations to obtain the aquatic product processing quality and safety evaluation index; the early warning module is used to evaluate the quality and safety of aquatic products according to the aquatic product processing quality and safety evaluation index. The model distribution module is used to send the aquatic product processing quality and safety assessment model to the aquatic product processing plant, which directly derives a real-time aquatic product processing quality and safety assessment index based on the real-time processing supervision information and the preset scores of the regulations, and issues an early warning for the processing process of the aquatic product processing plant based on the aquatic product processing quality and safety assessment index; the model updating module is used to obtain feedback information from the aquatic product processing plant and retrain the aquatic product processing quality and safety assessment model to obtain an updated aquatic product processing quality and safety assessment model, and send the updated aquatic product processing quality and safety assessment model to the aquatic product processing plant again.

[0021] The embodiment of the present application provides a processing device for multi-dimensional supervision and evaluation data, including: a cloud supervision platform, a data processing terminal of an aquatic product processing plant, and a sensor module; wherein the cloud supervision platform is used to obtain processing supervision information from a blockchain, and to construct an aquatic product processing quality and safety assessment model based on the processing supervision information, and is also used to receive the aquatic product processing quality and safety assessment index of each aquatic product processing plant data processing terminal, and to issue an early warning to each aquatic product processing plant data processing terminal; the aquatic product processing plant data processing terminal is used to receive the processing supervision information sent by the sensor module, and transmit all processing supervision information to the blockchain, and is also used to obtain the aquatic product processing quality and safety assessment model of the cloud supervision platform, derive the aquatic product processing quality and safety assessment index according to the aquatic product processing quality and safety assessment model, and issue an early warning to the processing process of the aquatic product processing plant according to the aquatic product processing quality and safety assessment index; the sensor module is used to obtain the processing supervision information in the aquatic product processing process in real time through a sensor, and transmit it to the data processing terminal of the aquatic product processing plant.

[0022] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0023] 1. By deriving the aquatic product processing quality and safety assessment index based on the aquatic product processing quality and safety assessment model, and issuing early warnings for the processing process of aquatic product processing plants based on the aquatic product processing quality and safety assessment index, early warnings can be issued for abnormal processing quality and safety in the aquatic product processing process in a timely manner, thereby promptly discovering potential safety hazards. This effectively solves the problem that the current multi-dimensional regulatory data processing method for aquatic products has the problem that the regulatory data in the aquatic product processing process is opaque and easy to falsify, leading to increased potential safety hazards in aquatic product quality.

[0024] 2. By recording and alerting processing plants whose evaluation index exceeds the defined value, potential risk points can be discovered in time and preventive measures can be taken to reduce the occurrence of safety accidents, encourage processing plants to consciously abide by relevant regulations and standards, and improve the level of processing quality and safety.

[0025] 3. Receive the aquatic product processing quality and safety assessment index through the cloud supervision platform, and issue early warnings to the data processing terminals of each aquatic product processing plant. Through the analysis of the aquatic product processing quality and safety assessment model, safety hazards and problems in the processing process can be discovered in a timely manner, and early warning notifications can be issued to prevent accidents and reduce risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A flowchart of a method for processing multi-dimensional supervision and evaluation data provided in an embodiment of the present application;

[0027] Figure 2 This is an example chart of the aquatic product processing quality and safety assessment index;

[0028] Figure 3 A structural diagram of a multi-dimensional supervision and evaluation data processing system provided in an embodiment of the present application;

[0029] Figure 4 A schematic diagram of the structure of a device for processing multi-dimensional regulatory evaluation data provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The embodiments of the present application provide a method, system and device for processing multi-dimensional supervision and evaluation data, thereby solving the problem that the supervision data of the aquatic product processing process is opaque and easy to falsify, which leads to increased quality and safety risks of aquatic products. By deriving an aquatic product processing quality and safety assessment index based on an aquatic product processing quality and safety assessment model, and issuing an early warning for the processing process of the aquatic product processing plant based on the aquatic product processing quality and safety assessment index, timely early warning of processing quality and safety anomalies in the aquatic product processing process is achieved, thereby timely discovering safety hazards.

[0031] The technical solution in the embodiment of the present application is to solve the problem that the current multi-dimensional supervision data processing method for aquatic products has the problem that the supervision data of the aquatic product processing process is not transparent and easy to be falsified, which increases the potential safety risks of aquatic products. The overall idea is as follows:

[0032] Each aquatic product processing plant obtains various values ​​of aquatic products in the processing environment through sensors, obtains processing videos of the processing process in real time through surveillance cameras in the processing workshop, and obtains equipment data of various equipment on the production line through Bluetooth or wired transmission. The above data are used according to the preset scores corresponding to the various regulations of the "Aquatic Product Processing Quality Management Standards" and the aquatic product processing quality and safety assessment model to derive the aquatic product processing quality and safety assessment index. All the obtained aquatic product values, processing videos, equipment data and assessment results are transmitted to the blockchain.

[0033] The cloud supervision platform obtains the IP address of each aquatic product processing plant's network transmission as its ID name.

[0034] The cloud supervision platform obtains various values ​​of aquatic products, processing videos, equipment data and aquatic product processing quality and safety assessment index from the blockchain; and issues early warnings in real time based on the aquatic product processing quality and safety assessment index. At each interval, the untrained values ​​of aquatic products, processing videos, equipment data and aquatic product processing quality and safety assessment index are input into the aquatic product processing quality and safety assessment model for retraining to obtain a new aquatic product processing quality and safety assessment model, and the aquatic product processing plant is notified to update the aquatic product processing quality and safety assessment model in a timely manner, so as to timely issue early warnings for abnormal processing quality and safety in the aquatic product processing process, thereby promptly discovering safety hazards.

[0035] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0036] like Figure 1 As shown, it is a flow chart of a method for processing multi-dimensional supervision and evaluation data provided by an embodiment of the present application. The method is applied to a system for processing multi-dimensional supervision and evaluation data. The method includes the following steps: obtaining processing supervision information of aquatic product processing plants from blockchain; obtaining specified regulatory regulations and preset scores corresponding to the regulations; inputting aquatic product processing quality and safety assessment model according to the processing supervision information and the preset scores of the regulations to obtain aquatic product processing quality and safety assessment index; issuing an alarm for the processing quality and safety situation of the aquatic product processing plant according to the aquatic product processing quality and safety assessment index; sending the aquatic product processing quality and safety assessment model to the aquatic product processing plant, which directly obtains a real-time aquatic product processing quality and safety assessment index based on the real-time obtained processing supervision information and the preset scores of the regulations, and The quality safety assessment index provides early warning for the processing process of the aquatic product processing plant; obtains feedback information from the aquatic product processing plant and retrains the aquatic product processing quality safety assessment model to obtain an updated aquatic product processing quality safety assessment model, and sends the updated aquatic product processing quality safety assessment model to the aquatic product processing plant again: when the aquatic product processing plant obtains real-time processing supervision information, it uses a specified hash function to generate a hash value corresponding to the real-time processing supervision information, and adds a timestamp, and uploads the real-time processing supervision information, hash value and timestamp to the blockchain together. When the blockchain obtains the real-time processing supervision information, hash value and timestamp, it uses a specified hash function to verify the integrity of the hash value. If it is complete, it will be saved in the blockchain. If it is incomplete, the hash verification is unsuccessful and the real-time processing supervision information is questionable.

[0037] In this embodiment, the hash value is used as the unique fingerprint of the data, and any modification to the data will result in a change in the hash value. Therefore, by comparing the hash values, data tampering or damage can be very effectively detected, whether it is a deliberate attack or accidental data damage. If the hash value obtained by verification is completely consistent with the transmitted hash value, it means that the data has not been tampered with during the transmission process.

[0038] The Delphi method is used to set scores for each regulation in the designated regulations. The blockchain technology and real-time processing supervision information are combined to evaluate the quality and safety of aquatic product processing, achieving the timeliness, automation and transparency of supervision, and improving the management efficiency and quality of aquatic product processing quality and safety.

[0039] Furthermore, issuing an alert on the processing quality and safety situation of aquatic product processing plants means: counting and numbering all aquatic product processing plants; using the IP address used by the aquatic product processing plant to upload data to the blockchain as the unique identifier of the aquatic product processing plant, and associating the unique identifier with the aquatic product processing quality and safety assessment index one by one; setting a limit value based on the aquatic product processing quality and safety assessment index uploaded by each aquatic product processing plant; recording the aquatic product processing plants whose aquatic product processing quality and safety assessment index exceeds the limit value, and when the number of violations reaches the specified value, issuing an alert to the aquatic product processing plant and marking the aquatic product processing plant.

[0040] In this embodiment, blockchain technology and unique identification are used to track the processing quality and safety assessment index of each aquatic product processing plant in real time, so as to understand its safety status in a timely manner. By recording and alerting processing plants whose assessment index exceeds the defined value, potential risk points can be discovered in a timely manner, and measures can be taken to prevent them, so as to reduce the occurrence of safety accidents, prompt processing plants to consciously abide by relevant regulations and standards, and improve the level of processing quality and safety. Through effective alarm management of processing quality and safety, it can help regulatory authorities allocate resources more accurately, give priority to processing plants with risks, and improve resource utilization efficiency.

[0041] Furthermore, the method for setting the boundary value is as follows: obtaining the aquatic product processing quality and safety assessment index of all historical aquatic product processing plants and the problem records of processing problems occurring in the aquatic product processing plants, and performing data preprocessing and standardization on them; performing feature extraction based on the preprocessed data, performing cluster analysis on the extracted features according to the K-means clustering algorithm, obtaining the cluster center, and setting the boundary value according to the aquatic product processing quality and safety assessment index of the cluster center.

[0042] In this embodiment, preprocessing includes missing value processing, outlier processing, feature scaling, etc. Standardization processing can eliminate the impact of dimension on data. The K-means algorithm (k-means clustering algorithm) updates the cluster center through iterative calculation, assigns data points to the nearest cluster center, and continuously adjusts the position of the cluster center until the convergence condition is reached, and selects the center value of each cluster as the boundary value. Since the boundary values ​​are based on historical data and cluster analysis, they can be dynamically adjusted as the data changes. If the distribution characteristics of the processing quality safety assessment index change, the boundary value can also be adjusted accordingly to maintain its accuracy and applicability. By personalizing the boundary value, the false alarm rate can be reduced, avoiding excessive alarms and management of some normal processing plants, and improving the accuracy and credibility of the alarm.

[0043] Furthermore, early warning of the processing process of aquatic product processing plants refers to: conducting classified observations through sensors based on the processing flow within the aquatic product processing plants, and obtaining processing supervision information obtained from the classified observations; inputting the processing supervision information obtained in real time into an aquatic product processing quality and safety assessment model to obtain an aquatic product processing quality and safety assessment index; when the aquatic product processing quality and safety assessment index is lower than a preset threshold, issuing a processing process safety early warning notice to the aquatic product processing plant.

[0044] In this embodiment, through the real-time early warning system, abnormal conditions in the processing process can be discovered in time, and corresponding measures can be taken to deal with them, thereby reducing the losses caused by abnormal conditions, including product quality degradation, equipment damage, etc. Through continuous monitoring and early warning, a large amount of data can be collected, and these data can be used to analyze and optimize the processing process, improve processing efficiency and product quality, and achieve continuous improvement and optimization.

[0045] Furthermore, the processing supervision information includes: processing workshop temperature, processing workshop humidity, additive qualification rate, operating status of processing equipment, number of processing personnel's operating specification records, number of processing personnel's hygiene and cleaning records, and processing video monitoring data.

[0046] Furthermore, the construction process of the aquatic product processing quality and safety assessment model is as follows: preprocessing and standardizing the processing supervision information; numbering each piece of equipment in the aquatic product processing plant; obtaining the total preset score of the processing supervision information in accordance with the regulations, including the total preset score of the production workshop environmental safety monitoring standards corresponding to the regulations, the total preset score of the processing personnel operation standard safety traceability monitoring standards, the total preset score of the workshop production equipment monitoring standards, and the total preset score of the biochemical property risk monitoring standards; obtaining the total score of the preset scores of each regulation of the specified regulations; constructing the aquatic product processing quality and safety assessment model based on the preprocessed and standardized processing supervision information and the total preset score to obtain the aquatic product processing quality and safety assessment index; the aquatic product processing quality and safety assessment model is:

[0047]

[0048] In the formula, FI is the aquatic product processing quality and safety assessment index, GH is the processing workshop temperature, RH is the processing workshop humidity, RFH is the processing personnel operation standard index, EH iis the operating status of the i-th processing equipment, i is the number of the processing equipment, i = 1, 2, 3, ..., N, N is the total number of processing equipment numbers, EH = 1 indicates normal operating status, EH = 0 indicates abnormal operating status, TER is the qualified rate of additives, Y1 is the sum of the preset scores of the corresponding regulations of the production workshop environmental safety monitoring standards, Y2 is the sum of the preset scores corresponding to the safety traceability monitoring standards of the processing personnel operation specifications, Y3 is the sum of the preset scores corresponding to the workshop production equipment monitoring standards, Y4 is the sum of the preset scores corresponding to the biochemical property risk monitoring standards, and Y0 = Y1 + Y2 + Y3 + Y4. Table 1 is an example table of the quality and safety assessment index of aquatic product processing, where N = 3, EH1 = 1, EH2 = 0, and EH3 = 1, as shown in the following table.

[0049] Table 1 Example of aquatic product processing quality and safety assessment index

[0050]

[0051]

[0052] like Figure 2 The following is an example of the aquatic product processing quality safety assessment index. Figure 2 It can be seen that the higher the temperature and humidity in the processing workshop, the higher the aquatic product processing quality and safety assessment index, and compliance with operating specifications and equipment status will improve the assessment index. The impact of the additive qualification rate on the assessment index is relatively small, but it is still an important factor. A higher additive qualification rate will increase the assessment index.

[0053] In this embodiment, the aquatic product processing quality and safety assessment index can also be obtained by conducting chemical analysis, sensory evaluation, biological testing, etc. on the processed aquatic products, and weighted averaging the analysis results to obtain the aquatic product processing quality and safety assessment index. The processing workshop temperature GH and the processing workshop humidity RH are monitored in real time by installing temperature and humidity sensors in the processing workshop. The sensors can transmit environmental data to the monitoring system in real time for use by the evaluation model. The operating status of the processing equipment EH i The normal operation status means that the various parameters of the equipment are within the normal range, while the abnormal operation status may mean that the equipment is faulty or abnormal. The type and quality of additives are recorded in real time, and the quality and qualified rate of additives are obtained by using sensors or laboratory tests during the processing.

[0054] Furthermore, the processing personnel operation specification index is obtained in the following manner: extracting the number of processing personnel operation specification records, the number of processing personnel hygiene and cleaning records, and the processing video monitoring data from the processing supervision information; extracting the number of processing personnel operation specification verifications and the number of processing personnel hygiene and cleaning verifications from the processing video monitoring data; constructing a processing personnel operation specification evaluation model for calculating the processing personnel operation specification index based on the number of processing personnel operation specification records, the number of processing personnel hygiene and cleaning records, and the number of processing personnel operation specification verifications and the number of processing personnel hygiene and cleaning verifications extracted from the processing supervision information and the processing video monitoring data.

[0055] In this embodiment, the processing personnel operation specification evaluation model is:

[0056]

[0057] In the formula, RFH is the processing personnel operation specification index, which is used to reflect the processing personnel's operation specification during the processing process, e is a natural constant, DS is the number of processing personnel operation specification records extracted from the processing supervision information, AS is the number of processing personnel hygiene and cleaning records, DOS is the number of processing personnel operation specification verifications extracted from the processing video monitoring data, AOS is the number of processing personnel hygiene and cleaning verifications, R1 is the weight of the preset processing personnel operation specification obtained from the database, R2 is the weight of the preset processing personnel hygiene and cleaning obtained from the database, R1+R2=1, and the database of the cloud supervision platform is used to store various weights and various data obtained from the blockchain.

[0058] In a specific embodiment, a mapping set is formed according to the processing personnel's operating specification records and processing personnel's hygiene and cleaning records and the weights of the processing personnel's operating specifications and the weights of the processing personnel's hygiene and cleaning. The corresponding weights are obtained by inputting the mapping set according to the real-time processing personnel's operating specification records and processing personnel's hygiene and cleaning records to adjust the degree of influence of different factors.

[0059] In a specific embodiment, a standard comparison table is obtained, which covers the operation record comparison specifications and the hygiene standard comparison specifications, and is used to determine whether the processing operation and hygiene cleaning of the personnel meet the specifications. The processing personnel's operation standard records and processing personnel's hygiene cleaning records are obtained according to the standard comparison table to obtain the standard judgment result, and the standard judgment result can be in the form of a regulation compliance number or a total score. The above-mentioned processing personnel's operation standard records, processing personnel's hygiene cleaning records and standard judgment results are all one-dimensional arrays. The one-dimensional array processing personnel's operation standard records and processing personnel's hygiene cleaning records are converted into a two-dimensional array, and then the standard judgment result is used as the target variable of the one-dimensional array; then the two-dimensional array processing personnel's operation standard records and processing personnel's hygiene cleaning records are horizontally stacked to obtain a feature matrix; a linear regression model is constructed based on the feature matrix and the target variable to obtain a weight; then a mapping set is determined based on the weight.

[0060] The processing personnel operation standard index RFH can also be designed to ask processing personnel about their behavioral standards, hygiene and cleanliness during the operation process, and understand the processing personnel's own understanding and implementation of the operation standards based on direct feedback. Documents or databases that record processing personnel's operating standards and information on processing personnel's hygiene and cleanliness are usually recorded and managed by regulatory agencies or the quality management department within the enterprise, from which information can be extracted. Video data of the processing process is recorded by monitoring cameras, and then the video is analyzed frame by frame to extract information related to processing personnel's operating standards and hygiene and cleanliness.

[0061] Furthermore, the process of retraining the aquatic product processing quality and safety assessment model is as follows: at regular time intervals, based on the boundary value of the aquatic product processing quality and safety assessment index and the historical aquatic product processing quality and safety assessment index, the cloud supervision platform calculates the standard deviation of the aquatic product processing quality and safety assessment index; based on the expert experience method, the boundary value based on the aquatic product processing quality and safety assessment index and the preset scores corresponding to the specified regulations and regulations are reset according to the standard deviation; they are re-introduced into the aquatic product processing quality and safety assessment model to obtain a new aquatic product processing quality and safety assessment model.

[0062] In this embodiment, the accuracy and precision of the model are optimized by resetting the evaluation indicators and specifications based on historical data and standard deviations, and the expert experience method is used to provide more reasonable and representative indicators so that the model can better reflect the actual situation.

[0063] like Figure 3As shown, it is a structural diagram of a processing system for multi-dimensional supervision and evaluation data provided by an embodiment of the present application. A processing system for multi-dimensional supervision and evaluation data provided by an embodiment of the present application includes: a supervision information acquisition module, a preset score acquisition module, an evaluation index calculation module, an early warning module, a model distribution module, and a model update module; the supervision information acquisition module is used to obtain processing supervision information of aquatic product processing plants from the blockchain; the preset score acquisition module is used to obtain the preset scores corresponding to the specified regulations and regulations; the evaluation index calculation module is used to input the aquatic product processing quality and safety evaluation model according to the processing supervision information and the preset scores of the regulations to obtain the aquatic product processing quality and safety evaluation index; the early warning module is used to calculate the processing quality and safety evaluation index of aquatic products according to the processing supervision information and the preset scores of the regulations The product processing quality and safety assessment index warns the processing quality and safety situation of the aquatic product processing plant; the model distribution module is used to send the aquatic product processing quality and safety assessment model to the aquatic product processing plant, which directly derives the real-time aquatic product processing quality and safety assessment index based on the real-time processing supervision information and the preset scores of the regulations, and warns the processing process of the aquatic product processing plant based on the aquatic product processing quality and safety assessment index; the model update module is used to obtain feedback information from the aquatic product processing plant and retrain the aquatic product processing quality and safety assessment model to obtain an updated aquatic product processing quality and safety assessment model, and send the updated aquatic product processing quality and safety assessment model to the aquatic product processing plant again.

[0064] like Figure 4 As shown, it is a structural schematic diagram of a processing device for multi-dimensional supervision and evaluation data provided in an embodiment of the present application. A processing device for multi-dimensional supervision and evaluation data provided in an embodiment of the present application includes: a cloud supervision platform, a data processing terminal of an aquatic product processing plant and a sensor module; wherein the cloud supervision platform is used to obtain processing supervision information from the blockchain, and to construct an aquatic product processing quality and safety assessment model based on the processing supervision information, and is also used to receive the aquatic product processing quality and safety assessment index of each aquatic product processing plant data processing terminal, and to issue an early warning to each aquatic product processing plant data processing terminal; the aquatic product processing plant data processing terminal is used to receive the processing supervision information sent by the sensor module, and transmit all processing supervision information to the blockchain, and is also used to obtain the aquatic product processing quality and safety assessment model of the cloud supervision platform, derive the aquatic product processing quality and safety assessment index according to the aquatic product processing quality and safety assessment model, and issue an early warning to the processing process of the aquatic product processing plant according to the aquatic product processing quality and safety assessment index; the sensor module is used to obtain the processing supervision information in the aquatic product processing process in real time through a sensor, and transmit it to the data processing terminal of the aquatic product processing plant.

[0065] In summary, the embodiment of the present application derives an aquatic product processing quality and safety assessment index based on an aquatic product processing quality and safety assessment model, and issues an early warning for the processing process of the aquatic product processing plant based on the aquatic product processing quality and safety assessment index, thereby timely issuing an early warning for processing quality and safety anomalies in the aquatic product processing process, and further promptly discovering safety hazards.

[0066] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0070] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0071] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for processing multi-dimensional supervision evaluation data, characterized in that: The following steps are involved: Obtaining processing supervision information of aquatic product processing plants from blockchain: When aquatic product processing plants obtain real-time processing supervision information, they use a specified hash function to generate a hash value corresponding to the real-time processing supervision information, add a timestamp, and upload the real-time processing supervision information, hash value, and timestamp to the blockchain. When obtaining the real-time processing supervision information, hash value, and timestamp on the blockchain, they use a specified hash function to verify the integrity of the hash value. If it is complete, it is saved in the blockchain. If it is incomplete, the hash verification is unsuccessful and the real-time processing supervision information is questionable. Get the specified regulations and their corresponding preset scores; Input the aquatic product processing quality and safety assessment model according to the processing supervision information and the preset scores of the regulations to obtain the aquatic product processing quality and safety assessment index; Alert the processing quality and safety of aquatic product processing plants based on the aquatic product processing quality and safety assessment index; The aquatic product processing quality and safety assessment model is sent to the aquatic product processing plant, which directly calculates the real-time aquatic product processing quality and safety assessment index based on the real-time processing supervision information and the preset scores of the regulations, and issues early warnings for the processing process of the aquatic product processing plant based on the aquatic product processing quality and safety assessment index; Obtaining feedback information from the aquatic product processing plant and retraining the aquatic product processing quality and safety assessment model to obtain an updated aquatic product processing quality and safety assessment model, and sending the updated aquatic product processing quality and safety assessment model to the aquatic product processing plant again; The processing supervision information includes: Processing workshop temperature, processing workshop humidity, additive qualification rate, operating status of processing equipment, number of processing personnel's operation specification records, number of processing personnel's hygiene and cleaning records, and processing video monitoring data; The construction process of the aquatic product processing quality and safety assessment model is as follows: Pre-process and standardize processing supervision information; Number each piece of equipment in the aquatic product processing plant; Obtain the sum of preset scores for processing supervision information in accordance with the regulations, including the sum of preset scores for production workshop environmental safety monitoring standards corresponding to the regulations, the sum of preset scores for processing personnel operation specification safety traceability monitoring standards, the sum of preset scores for workshop production equipment monitoring standards, and the sum of preset scores for biochemical property risk monitoring standards; Get the total score of the preset scores of each regulation in the specified specification; Constructing an aquatic product processing quality and safety assessment model based on the pre-processed and standardized processing supervision information and the sum of preset scores to derive an aquatic product processing quality and safety assessment index; The aquatic product processing quality safety assessment model is: In the formula, FI is the aquatic product processing quality and safety assessment index, GH is the processing workshop temperature, RH is the processing workshop humidity, RFH is the processing personnel operation standard index, EH i is the operating status of the i-th processing equipment, i is the number of the processing equipment, i=1,2,3,...,N, N is the total number of processing equipment numbers, EH=1 indicates normal operating status, EH=0 indicates abnormal operating status, TER is the qualified rate of additives, Y1 is the sum of the preset scores of the corresponding regulations of the production workshop environmental safety monitoring standard, Y2 is the sum of the preset scores of the corresponding safety traceability monitoring standard of the processing personnel operation specification, Y3 is the sum of the preset scores of the corresponding workshop production equipment monitoring standard, Y4 is the sum of the preset scores of the corresponding biochemical property risk monitoring standard, Y0=Y1+Y2+Y3+Y4; The method for obtaining the processing personnel operation standard index is as follows: Extract the number of processing personnel's operation standard records, the number of processing personnel's sanitation and cleaning records, and processing video monitoring data from the processing supervision information; Extract the number of times the processing personnel have checked the operating specifications and the number of times the processing personnel have checked the hygiene and cleaning from the processing video monitoring data; According to the number of processing personnel's operation specification records and the number of processing personnel's sanitation and cleaning records extracted from the processing supervision information, and the number of processing personnel's operation specification verifications and the number of processing personnel's sanitation and cleaning verifications extracted from the processing video monitoring data, a processing personnel operation specification evaluation model for calculating the processing personnel's operation specification index is constructed; The evaluation model for processing personnel's operation specifications is: In the formula, RFH is the processing personnel operation specification index, e is a natural constant, DS is the number of processing personnel operation specification records extracted from the processing supervision information, AS is the number of processing personnel hygiene and cleaning records, DOS is the number of processing personnel operation specification verifications extracted from the processing video monitoring data, AOS is the number of processing personnel hygiene and cleaning verifications, R1 is the weight of the preset processing personnel operation specifications obtained from the database, R2 is the weight of the preset processing personnel hygiene and cleaning obtained from the database, and R1+R2=1.

2. A method for processing multi-dimensional supervision and evaluation data as claimed in claim 1, characterized in that: The aforementioned warning of the processing quality and safety situation of aquatic product processing plants refers to: Count and number all aquatic product processing plants; The IP address used by the aquatic product processing plant to upload data to the blockchain is used as the unique identifier of the aquatic product processing plant, and the unique identifier is associated with the aquatic product processing quality and safety assessment index one by one; Set thresholds based on the aquatic product processing quality and safety assessment index uploaded by each aquatic product processing plant; Records will be kept of aquatic product processing plants whose aquatic product processing quality safety assessment index exceeds the limit value. When the number of excesses reaches a specified value, the aquatic product processing plant will be alarmed and marked.

3. A method for processing multi-dimensional supervision and evaluation data as claimed in claim 2, characterized in that: The method for setting the limit value is: Obtain the aquatic product processing quality and safety assessment index of all historical aquatic product processing plants and the problem records of processing problems in aquatic product processing plants, and perform data preprocessing and standardization on them; Feature extraction is performed on the data after data preprocessing, and the extracted features are clustered according to the K-means clustering algorithm to obtain the cluster center. The boundary value is set according to the aquatic product processing quality safety assessment index of the cluster center.

4. A method for processing multi-dimensional supervision and evaluation data as claimed in claim 1, characterized in that: The aforementioned early warning of the processing process of the aquatic product processing plant refers to: Based on the processing flow in the aquatic product processing plant, the processing supervision information obtained by the classified observation is obtained through the sensor; Input the processing supervision information obtained in real time into the aquatic product processing quality and safety assessment model to obtain the aquatic product processing quality and safety assessment index; When the aquatic product processing quality safety assessment index is lower than the preset threshold, a processing process safety warning notice will be issued to the aquatic product processing plant.

5. A method for processing multi-dimensional supervision and evaluation data as claimed in claim 1, characterized in that: The process of retraining the aquatic product processing quality and safety assessment model is as follows: At regular intervals, based on the defined value of the aquatic product processing quality and safety assessment index and the historical aquatic product processing quality and safety assessment index, the cloud supervision platform calculates the standard deviation of the aquatic product processing quality and safety assessment index; Based on the expert experience method, the definition value of the aquatic product processing quality and safety assessment index and the preset scores corresponding to the designated regulations and their regulations are reset according to the standard deviation; Re-introduce it into the aquatic product processing quality and safety assessment model to derive a new aquatic product processing quality and safety assessment model.

6. A multi-dimensional supervision and evaluation data processing system, characterized in that: It includes a regulatory information acquisition module, a preset score acquisition module, an evaluation index calculation module, an early warning module, a model distribution module, and a model update module; The supervision information acquisition module is used to obtain the processing supervision information of the aquatic product processing plant from the blockchain; The preset score acquisition module is used to acquire the preset scores corresponding to the specified regulations and regulations; The evaluation index calculation module is used to input the aquatic product processing quality and safety evaluation model according to the processing supervision information and the preset scores of the regulations to obtain the aquatic product processing quality and safety evaluation index; The early warning module is used to warn the processing quality and safety situation of the aquatic product processing plant according to the aquatic product processing quality and safety assessment index; The model distribution module is used to send the aquatic product processing quality and safety assessment model to the aquatic product processing plant, which directly obtains the real-time processing supervision information and the preset scores of the regulations to obtain the real-time aquatic product processing quality and safety assessment index, and issues early warning for the processing process of the aquatic product processing plant based on the aquatic product processing quality and safety assessment index; The model updating module is used to obtain feedback information from the aquatic product processing plant and retrain the aquatic product processing quality and safety assessment model to obtain an updated aquatic product processing quality and safety assessment model, and send the updated aquatic product processing quality and safety assessment model to the aquatic product processing plant again; The processing supervision information includes: Processing workshop temperature, processing workshop humidity, additive qualification rate, operating status of processing equipment, number of processing personnel's operation specification records, number of processing personnel's hygiene and cleaning records, and processing video monitoring data; The construction process of the aquatic product processing quality and safety assessment model is as follows: Pre-process and standardize processing supervision information; Number each piece of equipment in the aquatic product processing plant; Obtain the sum of preset scores for processing supervision information in accordance with the regulations, including the sum of preset scores for production workshop environmental safety monitoring standards corresponding to the regulations, the sum of preset scores for processing personnel operation specification safety traceability monitoring standards, the sum of preset scores for workshop production equipment monitoring standards, and the sum of preset scores for biochemical property risk monitoring standards; Get the total score of the preset scores of each regulation in the specified specification; Constructing an aquatic product processing quality and safety assessment model based on the pre-processed and standardized processing supervision information and the sum of preset scores to derive an aquatic product processing quality and safety assessment index; The aquatic product processing quality safety assessment model is: In the formula, FI is the aquatic product processing quality and safety assessment index, GH is the processing workshop temperature, RH is the processing workshop humidity, RFH is the processing personnel operation standard index, EH i is the operating status of the i-th processing equipment, i is the number of the processing equipment, i=1,2,3,...,N, N is the total number of processing equipment numbers, EH=1 indicates normal operating status, EH=0 indicates abnormal operating status, TER is the qualified rate of additives, Y1 is the sum of the preset scores of the corresponding regulations of the production workshop environmental safety monitoring standard, Y2 is the sum of the preset scores of the corresponding safety traceability monitoring standard of the processing personnel operation specification, Y3 is the sum of the preset scores of the corresponding workshop production equipment monitoring standard, Y4 is the sum of the preset scores of the corresponding biochemical property risk monitoring standard, Y0=Y1+Y2+Y3+Y4; The processing personnel operation standard index is obtained in the following way: Extract the number of processing personnel's operation standard records, the number of processing personnel's sanitation and cleaning records, and processing video monitoring data from the processing supervision information; Extract the number of times the processing personnel have checked the operating specifications and the number of times the processing personnel have checked the hygiene and cleaning from the processing video monitoring data; According to the number of processing personnel's operation specification records and the number of processing personnel's sanitation and cleaning records extracted from the processing supervision information, and the number of processing personnel's operation specification verifications and the number of processing personnel's sanitation and cleaning verifications extracted from the processing video monitoring data, a processing personnel operation specification evaluation model for calculating the processing personnel's operation specification index is constructed; The evaluation model for processing personnel's operation specifications is: In the formula, RFH is the processing personnel operation specification index, e is a natural constant, DS is the number of processing personnel operation specification records extracted from the processing supervision information, AS is the number of processing personnel hygiene and cleaning records, DOS is the number of processing personnel operation specification verifications extracted from the processing video monitoring data, AOS is the number of processing personnel hygiene and cleaning verifications, R1 is the weight of the preset processing personnel operation specifications obtained from the database, R2 is the weight of the preset processing personnel hygiene and cleaning obtained from the database, and R1+R2=1.

7. A device for applying the method for processing multi-dimensional supervision and evaluation data as claimed in any one of claims 1 to 5, characterized in that: include: Cloud supervision platform, aquatic product processing plant data processing terminal and sensor module; The cloud supervision platform is used to obtain processing supervision information from the blockchain, and to construct an aquatic product processing quality and safety assessment model based on the processing supervision information. It is also used to receive the aquatic product processing quality and safety assessment index of each aquatic product processing plant data processing terminal, and to issue early warnings to each aquatic product processing plant data processing terminal; The aquatic product processing plant data processing terminal is used to receive the processing supervision information sent by the sensor module, and transmit all the processing supervision information to the blockchain, and is also used to obtain the aquatic product processing quality and safety assessment model of the cloud supervision platform, obtain the aquatic product processing quality and safety assessment index according to the aquatic product processing quality and safety assessment model, and issue an early warning for the processing process of the aquatic product processing plant according to the aquatic product processing quality and safety assessment index; The sensor module is used to obtain processing supervision information during the aquatic product processing process in real time through sensors, and transmit it to the data processing terminal of the aquatic product processing plant.

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