21results about How to "Improve traceability efficiency" patented technology

The invention discloses a milk traceability method based on NFC, relates to the technical field of milk traceability, and comprises the following steps: combining an NFC tag with a block chain, performing encryption transmission on data of each link, storing through a distributed account book technology of the block chain, ensuring that the data is transparent and cannot be tampered, and based on the NFC tag, obtaining a milk traceability result; the monitoring data of each stage of milk production, processing and transportation is updated to the block chain, the traceability efficiency is significantly improved, manual participation is reduced, a deep learning model is introduced, prediction and identification of potential quality problems of milk are realized, enterprises are helped to take corrective measures in advance, loss is reduced, a risk early warning mechanism is provided for a supervision mechanism, and the risk of the supervision mechanism is reduced. The overall safety of the supply chain is improved, the consumer can check the complete traceability information of the product by using the NFC scanning device through the NFC label and the block chain technology, the sense of trust of the consumer to the product is greatly improved, and the credibility of the brand can be enhanced.

The invention relates to the technical field of big data management and data analysis, and discloses a visual data platform full-link data flow traceability method, system and device and a medium, and the method comprises the steps: monitoring a job scheduling process submission event, analyzing the input and output configuration information of each job node, converting the information into a data flow model, and storing the data flow model in a traceability database; static analysis is conducted on node scripts and codes, and analysis results are stored in a traceability database; generating a unique identifier for each data record, and recording related information in a data circulation process; and writing the data flow relationship into a graph database Neo4j through a Kafka asynchronous message, and performing data traceability query by a user through a visual interface. The method has the beneficial effects that the data quality and safety are improved, and the limitation and complexity of a mainstream open source tool in the aspect of a data blood relationship analysis function are solved.

The invention relates to the technical field of data processing, in particular to a food traceability method based on intelligent Internet of Things information, and the method comprises the steps: pre-storing sample information corresponding to a plurality of monitoring subjects, and obtaining seed information, producing area information and an initial subject actual image of the monitoring subjects uploaded by a user side; based on the uploaded IP and the initial subject sample image, judging whether the monitored subject meets a continuous verification standard or not, calling growth rule features, predicting verification time nodes, sending verification demand information to a user side at the corresponding verification time nodes, obtaining feedback information, calling the subject sample image of the corresponding verification time nodes for comparison, and sending verification request information to the user side; and judging whether the growth process of the monitoring subject meets the standard or not, judging a mature feature difference value, and evaluating the storability of the monitoring subject based on the mature feature difference value so as to store the information for the monitoring subject into the block chain. The data authenticity of each uploading node is controlled, and the accuracy of food traceability is ensured.

The present invention provides a drug traceability system and access optimization method based on blockchain, which relates to the technical field of drug traceability. The user's storage instructions and the drug data to be stored are input into the system through an input module; the input module transmits the received drug data to the classification storage module; the classification storage module stores different types of data in a database or blockchain; the input module transmits the user's query instructions and the information to be queried to the query module; the query module inputs the query results into a transaction graph construction module or an output module according to the query instruction type; the transaction graph construction module constructs the transaction graph required for drug traceability, and transmits the transaction graph to the output module in the form of data information and image information; the output module feeds back all the received information to the user; the system and method combine the centralized database with the blockchain technology, which not only ensures the high efficiency of storage and query, but also ensures that the key information of drug transactions cannot be easily tampered with.

The invention provides an unstructured data tracing method and apparatus, and an electronic device. The method comprises the steps of creating matching information; acquiring network traffic; performing reduction processing on the unstructured data to obtain a to-be-matched file; searching mark data from the to-be-matched file, if the to-be-matched file comprises the mark data, adding a data element label for the mark data, and setting the to-be-matched file as a mark file; storing first traceability information of the marked file; and executing search according to the first traceability field to obtain traceability mark data or a traceability label, and obtaining a first traceability file. The method comprises the following steps: marking corresponding traceability data in unstructured data according to matching information; setting a file including the traceability data in the unstructured data as a tag file and storing the tag file; search is executed through the traceability field in the traceability stage to obtain the tag file including the traceability data, and the efficiency, the real-time performance and the comprehensiveness of unstructured data traceability are improved.

The invention relates to the field of food traceability, in particular to a food traceability system based on a block chain, and the system is provided with a feature storage module which is used for storing the packaging features of to-be-transported food; the package analysis module is used for analyzing the damage tendency characterization value of the inclusion in the transportation process based on the package characteristics of the to-be-transported food contained in the single inclusion in combination with the volume of the inclusion, and dividing the damage tendency risk category of the inclusion in the transportation process; the identification module is used for adaptively detecting each inclusion according to the damage tendency risk category; the tracing module is used for judging whether the food in the inclusion needs to be subjected to fragmentation detection or not based on the data label stored in the block chain for each inclusion; and the fragmentation detection module is used for scanning the food contour in the food package, identifying scattered food fragments and judging whether the food meets the fragmentation standard. The food traceability efficiency can be improved, the inclusion with risks can be positioned in time, and the intact degree and quality of the food are ensured.

The invention belongs to a sewage monitoring technology, and particularly provides a multi-source risk aggregation tracing method and system for sewage poison monitoring, and the tracing method comprises the steps: A1, collecting the current monitoring data of sewage at each point (i, j), the data comprising a poison content detection value D (i, j), time and a place; a2, obtaining a traceability matrix M (i, j) according to the detection value matrix Dk (i, j) of each point location in N rounds; a3, a point location with a value greater than 0 in the matrix M (i, j) is a traceable point location; and A4, visually displaying the point location of the traceability and the mark of the M value corresponding to the point location. The method has the advantages of accurate traceability and the like.

This invention relates to the field of power quality monitoring technology and provides a power quality disturbance tracing method based on a workflow platform using an intelligent diagnostic model. The method includes: collecting three-phase voltage and current waveform data from each monitoring node; when a power quality indicator exceeds a preset threshold, the workflow platform performs feature extraction to obtain a disturbance feature vector; performs disturbance pattern discrimination and selects the corresponding tracing sub-algorithm branch based on the discrimination result to obtain branch tracing results; performs hierarchical event mapping to aggregate abnormal indicators of each monitoring node into disturbance events according to spatiotemporal clustering and constructs a directed acyclic graph-like disturbance propagation chain based on the branch tracing results; inputs the disturbance feature vector and disturbance propagation chain into a trained target hybrid model; outputs the corrected disturbance propagation chain and root cause node; and finally outputs the tracing results. This invention effectively improves the tracing accuracy and efficiency in complex disturbance scenarios.

The application discloses a cross-industry supply chain supervision method based on multi-chain cooperation, a business sub-chain is used for recording internal information of enterprise transaction subjects and business data of various supply processes; a transaction main chain is mainly responsible for transaction implementation and interaction between different businesses, and records circulation states and transaction data of commodities at various links of the supply chain; and a supervision chain is used for supervising and auditing transaction data between different businesses of the supply chain. The application combines an identity-based encryption mechanism based on fine-grained privacy protection, protects the privacy of multi-party cooperative transaction data in the supply chain process, and solves the contradiction between the privacy of supply chain transaction data and the implementation of supervision. The application designs two verification methods of transaction types based on an aggregated signature protocol, so as to realize aggregated verification of on-chain transactions and rapid tracking of abnormal transactions, and effectively improves the performance of system supervision and traceability.

The present disclosure relates to a traffic classification method, device, electronic device and computer-readable medium, and belongs to the field of Internet technology. The method includes: obtaining a traffic sequence collected from a client, and segmenting the traffic sequence according to a pre-trained traffic segmentation model to obtain a traffic time series segment corresponding to the traffic sequence; determining the sequence similarity distance between the traffic time series segment and the historical traffic time series segment in the historical traffic template library; and determining the traffic type of the traffic time series segment according to the sequence similarity distance between the traffic time series segment and the historical traffic time series segment. The present disclosure reasonably segments the traffic sequence through a traffic segmentation model to obtain traffic time series segments, and determines the traffic type of the traffic time series segment by similarity matching, which can improve the accuracy and efficiency of traffic tracing.

This invention discloses an event aggregation and attribution method based on attack chain homology analysis, comprising the following steps: Step 1, multi-source heterogeneous data fusion and standardization processing; Step 2, dynamic subject-object relationship modeling; Step 3, attack event homology analysis; Step 4, homology attack event aggregation; Step 5, attack path deduction and visualization; Step 6, dynamic threat adaptive optimization. This invention improves the completeness of attack path reconstruction and solves the defect of static modeling in failing to capture attack chain evolution by using a dynamic subject-object relationship model and homology analysis algorithm; it presents the attack process through visualization technology, shortening the analysis time and improving the efficiency of source tracing; it improves the robustness of homology determination and the accuracy of entity relationship identification by using a multi-feature weighted fusion hierarchical clustering mechanism combined with code string features and vulnerability exploitation methods for auxiliary verification; and it enhances the adaptability of dynamic threats and shortens the response window for new threats through a dynamic weight update mechanism.

The invention provides an industrial control network security risk tracing method. The method comprises the following steps: S1, data acquisition and alarm processing; s2, real-time data acquisition and analysis; s3, log analysis and vulnerability scanning; s4, malicious software analysis and network evidence obtaining; s5, obtaining evidence by the host; s6, data traces are reserved; s7, copying the data; and S8, carrying out reverse transmission. According to the industrial control network security risk tracing method provided by the invention, the information of the hardware equipment used by a user who steals the data is obtained through the data trace, then the information of the hardware equipment is copied by data copying, and finally the copied hardware information is transmitted to the equipment of which the information is stolen through reverse transmission, so that the tracing efficiency is accelerated.

The present application relates to the technical field of game data processing, in particular to a background game log information tracing method and system and a medium. The method comprises: obtaining the problem category of the feedback opinions of game users and corresponding log data; obtaining the data skew jam degree of each log source set based on the difference in data occupancy of different log source shards of each log source set; determining the jump delay burden factor of each log information path according to the interaction of the service area in each log information path in each log source set and the data skew jam degree; obtaining the shard delay adjustment parameter of each log source shard according to the jump delay burden factor of the log information path of different game users involved in the log source shard of each log source set, re-dividing the memory of the log source shard, and then obtaining the source path of each problem category. The present application improves the tracing efficiency of game log information.

The invention discloses an evidence obtaining rule determination method and device, electronic equipment and a storage medium. The evidence obtaining rule determination method comprises the steps of obtaining attack behavior data of at least one attack scene; processing the attack behavior data by using a forensic analysis model to generate a forensic rule set corresponding to each attack scene in the at least one attack scene; the invention further discloses a model training method and device. The model training method comprises the steps that the knowledge base in the field of computer forensics is acquired; training an initial forensic analysis model by using the knowledge base to obtain a forensic analysis model; the forensic analysis model is used for processing attack behavior data of at least one attack scene to generate a forensic rule set corresponding to each attack scene in the at least one attack scene.

The embodiment of the invention provides an abnormal data processing method and device, equipment, a storage medium and a program product, and relates to the field of financial science and technology. The method comprises the steps of obtaining a to-be-processed data table; extracting a blood relationship corresponding to the to-be-processed data table according to a to-be-executed script corresponding to the to-be-processed data table; according to the blood relationship, constructing a blood relationship topology network through a graph neural network in combination with a preset verification rule; and when it is detected that the abnormal data exists in the to-be-processed data table, determining a source node corresponding to the abnormal data by using the blood relationship topology network, and repairing the abnormal data by using the preset knowledge base. According to the method provided by the invention, through combination of data blood relationship modeling and graph neural network dynamic analysis, the efficiency and accuracy of financial data governance are remarkably improved; the range of occurrence of the abnormal data can be quickly delineated, the time of tracing the abnormal data is greatly shortened, and the efficiency of tracing the abnormal data is greatly improved.

This invention relates to the field of blockchain technology and provides a method, apparatus, electronic device, and storage medium for tracing electricity consumption data. The implementation scheme is as follows: A preset electricity traceability model is invoked to standardize and model the electricity consumption data of each user, obtaining various triplet data sets, which are then stored on the blockchain; a composite index structure is constructed based on the first field of each triplet data set, wherein the composite index structure includes a traceability positioning table and a multi-bucket index structure; responding to a query request from a target user, cross-block positioning is performed based on the second field in the query request and the traceability positioning table to obtain a cross-block traceability link; according to the second field and the multi-bucket index structure, intra-block data extraction is performed on each block in the cross-block traceability link to obtain the target traceability result; the target traceability result is then sent to the target user. This invention can improve traceability efficiency.

The application discloses a kind of based on instruction domain-vibration mapping numerical control processing quality determination method, comprising: obtaining the multi-source data in standard numerical control processing process;Multiple-channel vibration signals in the multi-source data in multiple spatial position units and execution numerical control program line are combined as instruction domain-vibration mapping unit;The instruction domain-vibration mapping unit in the spatial position unit is carried out multi-feature extraction, and the feature is combined to form standard feature vector;Multi-source data in real-time numerical control processing process are acquired, and multi-feature extraction is carried out to obtain real-time feature vector;The real-time feature vector is compared with the standard feature vector, and the numerical control processing abnormal degree of real-time numerical control processing process is determined.The application establishes the corresponding relationship of vibration signal and program line number by constructing instruction domain-vibration mapping unit, and realizes accurate determination and accurate tracing of numerical control processing abnormal degree by combining multi-dimensional feature vector comparison.

This invention discloses a method for assessing enterprise ESG environmental indicators based on IoT data, belonging to the field of intelligent industrial environmental management technology. It addresses the technical problems of ambiguous correlations between production factors and environmental indicators, lack of scientific basis for anomaly judgment, and low efficiency in source tracing and handling in existing technologies. The method establishes a ledger for the coding of equipment, processes, and ESG environmental indicators throughout the entire production process; collects IoT data to filter core correlation groups; builds a three-level correlation mapping table and establishes a dynamic update and traceability mechanism; establishes a threshold ledger for different operating conditions; constructs an abnormal feature library of enterprise ESG environmental indicators; and uses threshold comparison and cosine similarity methods to determine true anomalies; generates a source tracing list based on the three-level correlation mapping table; filters abnormal elements hierarchically; and integrates information to form an anomaly root cause location report. This invention achieves standardized and quantitative binding of production factors and ESG indicators, improves the rationality and accuracy of anomaly judgment, and effectively enhances the efficiency and scientific basis of enterprise ESG environmental indicator assessment and anomaly handling.

This invention discloses a collaborative intelligent water quality monitoring method using a dual-platform approach combining a drone and a biomimetic fish. It includes the following steps: The drone subsystem transmits the location and extent information of the initially screened contaminated area, along with spectral data, back to an intelligent remote monitoring platform in real time; a biomimetic fish precision detection task is generated, and the coordinates of the initially screened contaminated area and a preset monitoring path are sent to the biomimetic fish subsystem; the biomimetic fish subsystem collects measured data from the initially screened contaminated area and transmits the collected data back to the intelligent remote monitoring platform; based on the spectral data from the drone and the measured data from the biomimetic fish, data fusion is performed using spatiotemporal registration to obtain the fused contamination concentration inside and outside the contaminated area; an early warning level is automatically triggered according to the water quality anomaly level, and the coordinates of the contaminated area are pushed to the operation and maintenance terminal, completing the early warning response closed loop. This invention not only enables rapid response to pollution events and improves source tracing efficiency but also shortens the monitoring cycle.

The embodiment of the application provides a kind of groundwater pollution isotope tracing method and device, electronic equipment and medium, belong to pollution tracing technical field.The method comprises: obtaining the natural pollutant information of groundwater, obtains the artificial pollutant information of pollution source;Based on natural pollutant information and artificial pollutant information, carry out traceable isotope screening, obtain candidate isotope set;Based on groundwater and pollution source, to candidate isotope set carries out isotope difference evaluation, obtains isotope distinguishability;Candidate isotope set is carried out isotope resource consumption evaluation, obtains isotope resource consumption data;Based on isotope distinguishability and isotope resource consumption data, to candidate isotope set carries out isotope screening, obtains target isotope combination;Based on target isotope combination, to groundwater carries out pollution source tracing.The embodiment of the application can improve the tracing accuracy of groundwater pollution.

The present invention belongs to the technical field of hazardous waste traceability. The present invention provides a hazardous waste treatment traceability system and method based on the Internet of Things technology, including: marking actual transportation sections, obtaining performance data of abnormal actual transportation sections in real time, and analyzing to obtain traceability demand values, judging whether it is necessary to trace the hazardous waste during transportation based on the traceability demand values, which is beneficial to improving the safety of transportation and the targeted demand for hazardous waste traceability, obtaining the transportation deviation performance value of the abnormal actual transportation section based on the traceability request signal, and determining the traceability path, obtaining the historical transportation performance value of the abnormal actual transportation section, obtaining the optimization demand value based on the historical transportation performance value of the abnormal actual transportation section, judging whether it is necessary to optimize the traceability path, and if necessary, obtaining the traceability sequence value, and optimizing the traceability path based on the traceability sequence value. The present invention is beneficial to improving the traceability efficiency.