392 results about "Chain network" patented technology

A value chain network control tower system comprises a processor and memory configured to execute a know your model system that manages the complete lifecycle of Al models in enterprise environments. The know your model system performs model intake and registration actions including model documentation collection, registration procedures, metadata collection, input / output interface standardization, legal and licensing validation checks, and security validation. The system conducts comprehensive model evaluation and risk assessment actions by analyzing foundational properties, task performance, safety and risk management, alignment and compliance characteristics, operational metrics, and tooling transparency capabilities. The know your model system executes model deployment actions through automated environment validation, predeployment approval processes, and controlled production deployment with continuous monitoring.

The invention discloses a digital asset management method and device, equipment, a storage medium and a program product, and the method comprises the steps: carrying out the hash calculation of transaction data when a super SIM card receives a transaction request carrying transaction data sent by first equipment, and generating a transaction hash value; performing hierarchical signature on the transaction hash value through a preset signature algorithm, and triggering personal identification code authentication of the user so as to release signature data of the hierarchical signature after the personal identification code authentication is passed; and sending the verification abstract of the personal identification code and the signature data to a block chain network, so that the block chain network verifies the signature data, stores the signature data after verification is passed, and returns a transaction confirmation event to the first device. According to the embodiment of the invention, the super SIM card is used as a security carrier, and the transaction data hash calculation, the hierarchical signature and the personal identification code authentication are combined, so that the whole-process security protection of the digital asset transaction is realized, and the security of the digital asset transaction can be effectively improved.

The invention relates to the technical field of supply chain risk prediction based on causal reasoning, and discloses a supply chain risk prediction method and device based on causal reasoning, equipment and a medium. The method comprises the following steps: constructing a double-layer knowledge graph of a regulation layer knowledge graph and a logistics physical layer knowledge graph; real-time fusion and characterization of geographical regulation and logistics operation multi-source heterogeneous data are realized, the perception real-time performance and coverage dimension of risk events are improved, then a multi-level causal chain is automatically generated by introducing a large language model, a complex conduction path of risks in a supply chain network can be deeply inferred, and the risk prediction accuracy is improved. According to the method, the defect that hidden association mining is insufficient in a traditional method is overcome, reasoning of risk traceability is improved, and finally a risk prediction result is obtained by mapping causal chain nodes to a logistics physical layer knowledge graph and performing probabilistic calculation. The method has the beneficial effects that the risk prediction of the specified supply chain is realized, and the accuracy of the risk prediction result is improved.

The invention discloses a trusted data sharing method based on a block chain consensus mechanism. The method comprises the following steps: S1, constructing an alliance chain network; s2, completing KZG polynomial commitment generation, ML-KEM algorithm encryption storage and pointer registration; s3, the data provider medical institution completes an evidence storage transaction of the FROST threshold signature; s4, the target medical institution completes the access request transaction; s5, the data provider medical institution sends a KZG unpacking proof and a data item, the target medical institution obtains a storage pointer and a commitment value, KZG verification check is executed, and after verification is passed, an ML-KEM algorithm is executed for depacking to obtain a session key; and S6, the target medical institution completes the audit transaction, and after the alliance chain network broadcast, the consensus node executes rule verification of the access control contract and the audit contract. The multi-node electronic medical record sharing and tamper-proof evidence storage method is high in performance and traceability, and is suitable for credible circulation of sensitive health data among multiple medical institutions.

The invention discloses a clothing supply chain transparent purchasing and collaborative management method and system based on the Internet of Things and a block chain. The method comprises the following steps: monitoring and collecting state data of raw materials in real time through Internet of Things equipment; when the state data meets a preset purchase triggering condition, a purchase demand transaction is automatically generated and broadcasted on the alliance block chain network; a purchase smart contract deployed on the alliance block chain network responds to the purchase demand, screens candidate suppliers, and quantitatively scores the candidate suppliers based on multi-dimensional historical performance data obtained from a distributed account book to automatically determine a target supplier; the purchase smart contract automatically generates a purchase order transaction and performs consensus evidence storage on the alliance block chain network; and continuously tracking order state update on the alliance block chain network, and automatically executing a settlement process when a preset payment condition is satisfied. According to the invention, the problems of opaque information, lagging purchasing decision, low process efficiency and difficulty in multi-party collaboration of the traditional clothing supply chain are solved.

The invention relates to the field of network and information security, and discloses a server security authentication system based on block chain trusted computing. Comprising a block chain network, an intelligent contract module, an authentication service module, a verification node and a to-be-authenticated server. The intelligent contract module records a registration index, a certification public key, a policy version number, a baseline commitment value and a revocation state. The authentication service module generates a challenge parameter and a challenge value based on the block height and the block hash digest. The trusted agent module collects a measurement abstract and forms a certification packet, and the trusted root module derives a staging certification key in a protected environment and signs the certification packet. And the verification node reads the data on the chain to complete signature verification, challenge value re-calculation, window verification and compliance proof verification, and generates an authentication bill containing an effective height range for resource access judgment after passing the verification.

The invention belongs to the technical field of data security and block chains, and discloses a physical infrastructure node continuous data chaining and traceability method and system, and the method comprises the steps: generating a unique asymmetric key pair for each node; continuously collecting physical sensing data and generating a unique data identifier; performing digital signature on the current physical sensing data to form a continuous signature chain; storing the original physical perception data, the corresponding digital signature and the continuous signature chain in an off-chain service platform database; uploading the data identifier, the digital signature and the hash value of the original physical sensing data to a block chain network based on a dynamic anchoring strategy; and comparing the calculated hash value with the hash value of the corresponding original physical sensing data in the block chain network, and backtracking the continuous signature chain. According to the invention, a safe, efficient and traceable complete data guarantee scheme can be provided for a decentralized physical infrastructure network.

The invention relates to the technical field of engineering construction informatization and data security, and provides an engineering supervision transparency platform based on a block chain, the platform adopts a three-layer collaborative architecture of terminal acquisition, edge processing and on-chain consensus: field data and space-time and identity information are bound in a hardware security area through a special intelligent terminal; a local server is used for data buffering and distributed storage; the data fingerprints are stored without being tampered based on the alliance block chain network and the smart contract, and a multi-party verification process is automatically executed. According to the method, the whole process of supervision data from the source to the evidence storage is credible, the authenticity and integrity of the data are guaranteed, the collaboration efficiency is improved, offline synchronization and visual tracing are supported, and transparent and reliable technical support is provided for project quality management.

An information technology system generally includes a cloud-based management platform with a micro-services architecture deploying a set of adaptive intelligence facilities that can be configured to automate a set of capabilities of the platform related to at least one of the value chain network entities and the features of the platform and a set of data storage facilities that can be configured to store data collected and handled by the platform. The data can be related to at least one of the value chain network entities and the features of the platform. A set of monitoring facilities can be configured to monitor the value chain network entities. The platform can be configured to host a set of applications for directing an enterprise to manage the value chain network entities from a point of origin of a product of the enterprise to a point of customer use.

A system includes a fleet resources data store that maintains a fleet resource inventory indicating fleet resources that can be assigned to perform tasks. For each fleet resource, the inventory indicates features of each fleet resource and a respective status. A set of task definitions is accessible to an intelligence layer to facilitate improving task definition based on feedback from task-specific outcomes. The system receives a job request for a robotic fleet to perform a job and determines a job definition data structure indicating a set of tasks to be performed for the job. The system applies an outcome of performing a task by a resource assigned to perform the task to a machine learning system of the intelligence layer that facilitates improving, based on the outcome, the set of task definitions. The system updates the set of task definitions based on a result of applying the machine learning system.

The invention discloses a document proofreading system and method based on artificial intelligence, and relates to the technical field of natural language processing, and the method comprises the steps: analyzing a document, dividing semantic units, and obtaining a document with a context label based on context type library labeling; performing initial error detection by using the corresponding rule set, and comparing the format of the document and the text quality characteristics with a standard sample vector space to obtain an initial error set; constructing a defect conduction chain network, and locating root cause error nodes causing a plurality of secondary errors by tracing the defect conduction chain network; generating an intelligent proofreading report; receiving a new-version document revised by the user, comparing the new-version document with the original-version document, positioning a change area, and analyzing a quality difference of the change area on a related quality dimension; based on the quality difference, an incremental proofreading report is output, and the incremental proofreading report comprises newly introduced errors and unsolved root cause errors.

A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained on the training data set to determine, upon receiving the classification of the at least one of: the operating state, the fault condition, the operating flow, or the behavior, a task to be completed for the value chain network. A VCN process may configure a robotic process automation system to execute the task to facilitate an improvement in the value chain network.

The invention is suitable for the technical field of data processing, and particularly relates to a financial data processing and classification method, system and equipment based on verifiable computing, and the method comprises the steps: obtaining on-chain transaction data verified by a block chain consensus node storage and risk-related index data verified by an under-chain oracle machine; the problems that the authenticity of traditional financial data is difficult to verify and the data is split are solved; calling a risk assessment model through an intelligent contract deployed on a block chain, and placing an assessment process in a decentralized block chain network; performing verifiable calculation through an intelligent contract to determine a total performance score and a risk index, and realizing whole-course tracing and verification of a calculation process by utilizing the characteristics of verifiable calculation of a block chain; the total performance score and the risk index are stored in the block chain as non-tampering records, and the risk rating groups are automatically divided according to the fixed rating rule on the chain through the smart contract, so that the authenticity, objectivity, verifiability and fairness of financial data processing are guaranteed.

The invention relates to the technical field of virtual power plant optimization scheduling, in particular to a low-carbon virtual power plant collaborative optimization method based on digital twinning and deep reinforcement learning, which comprises the following steps: intelligently coupled digital twinning collaborative modeling is carried out, and an aging-efficiency bidirectional coupling mechanism is developed; carbon energy flow coupling dynamic tracking is carried out, a block chain network is established to store carbon emission data, a carbon intensity database is established to guide low-carbon scheduling, and a space-time carbon footprint thermodynamic diagram is generated; constructing a hybrid optimization architecture to realize multi-temporal-spatial-scale collaborative optimization, generating a risk parameter packet and converting the risk parameter packet into risk model features; and establishing a risk assessment system, and developing a risk hedging strategy to realize risk dynamic protection. According to the method, the bottleneck of existing virtual power plant operation management is broken through, efficient equipment management, energy low-carbon scheduling, multi-temporal-spatial-scale collaborative optimization and effective risk prevention and control can be achieved, and the safety, reliability and resource utilization efficiency of virtual power plant operation are improved.

The invention discloses a method and system for generating a financial information graph of a user through a financing platform, and relates to the technical field of financial information. The method is used for solving the problems of weak user operation data association and inaccurate risk assessment in a traditional financing platform. Firstly, multi-dimensional analysis based on transaction semantic recognition is performed on a user bank flow, transaction scene features are extracted, and a supply chain core enterprise fund flow path is recognized; then, a cash flow-supply chain cooperation efficiency coefficient is calculated in combination with order account period information, and enterprise fund turnover efficiency is quantified; then, constructing a dynamic weighted supply chain network topology based on the coefficient, and identifying key fragile nodes through a graph neural network; and finally, fusing cooperation efficiency and risk characteristics, predicting enterprise performance capability through a dynamic attention mechanism, generating an interactive dynamic information graph of a fund flow path, a supply chain state and a risk result, and realizing intelligent analysis and visual presentation of a financing platform on an enterprise operation state.

The invention relates to the technical field of carbon popularity management, in particular to a campus carbon popularity system which writes a carbon emission value into a personal carbon account of a corresponding user and calculates a user hash value; using the user hash value as a leaf node to calculate and obtain a root hash value of a hospital Merkel tree; taking the root hash value of the hospital Merkel tree as a leaf node to calculate and obtain a root hash value of the school-level Merkel tree; when a data verification request initiated by a target user is received, extracting brother node hash values from a hospital Merkel tree and forming a Merkel verification path; and calculating to obtain a verification root hash value by using a locally stored personal carbon emission value and a Merkel verification path, and when the verification root hash value is consistent with a root hash value of a hospital Merkel tree stored in the block chain network, determining that the personal carbon emission data of the target user has been correctly incorporated into hospital aggregation statistics. The problem of how to ensure the data credibility in the multi-level aggregation statistical process of the campus carbon popularity data is effectively solved.

The invention discloses a wharf risk assessment and management method based on artificial intelligence, particularly relates to the field of wharf risk assessment and management, and is used for solving the problems that an existing wharf is difficult to quantify and delay influence on a supply chain network level, and prospective intervention cannot be performed on supply chain risks. According to the method, a comprehensive data platform of wharf operation and supply chain cargo linkage is constructed, and the bottleneck time point of a future delivery window is analyzed and predicted based on the ship arrival density, the operation bearing capacity and the stockpiling structure; searching a historical supply chain interruption event and extracting corresponding cargo and node information; tracking a conduction path of an interruption event in the supply chain network, quantifying the influence of a bottleneck on a downstream node, and establishing a supply chain risk influence model; generating a supply chain risk influence map in combination with future bottleneck prediction; and finally, a composite risk portrait is constructed, and targeted risk intervention is carried out on the wharf and the supply chain node. And intelligent prediction and management of wharf and supply chain full-chain risks are realized.

The invention discloses an anti-Byzantine privacy protection federated learning method and system based on a block chain. The anti-Byzantine privacy protection federated learning method is realized through the federated learning system comprising a key distribution center, a plurality of clients, two non-collusion servers and a block chain network. According to the method, the data privacy of a client side is guaranteed through a safety calculation process of cooperation of double servers, attacks caused by malicious client sides are reduced as much as possible through a self-adaptive clustering and robustness aggregation method, and reputation values of the client sides are managed through intelligent contracts. The reputation value is used to set the award and penalty obtained after the client participates in federal learning, and the blockchain increases transparency and reliability for the system. And updating the global model based on a security calculation process under a non-collusion double-server architecture, and finally obtaining a safe and reliable global model after training is finished.

A robot fleet management platform includes one or more processors configured to execute instructions. The instructions include receiving a job request comprising information descriptive of job deliverable and request-specific constraints for delivering the job deliverable. The instructions include applying content and structural filters to content received in association with a job request to identify portions thereof suitable for robot automation. The instructions include establishing a set of robot tasks, each defining at least a type of robot and a task objective, based on the portions of the job request that are suitable for robot automation and meet a first fleet objective. The instructions include applying fleet configuration services to the job content and the set of robot tasks to produce a fleet resource configuration data structure for the job request that associates at least one robot operating unit with each task in the set of tasks and robot adaptation instructions.

The invention discloses a block chain technology and big data-based data synchronous scheduling management and control system, and relates to the technical field of data synchronous scheduling management and control. Comprising a cross-level dynamic observation module, a causal coherent decomposition module, an anti-fact playback construction module, a double-mirror-image time scale rearrangement module, a time-varying virtual impedance regulation and control module and a time reversal phase traction module. And the cross-level dynamic observation module constructs a cross-level cache link dynamic observation layer, collects cache pressure fluctuation data and link delay pulsation data of each node in the block chain network in real time, and generates a coupling feature baseline for representing a relationship between cache pressure and link delay. According to the invention, through multi-layer time sequence observation and time baseline correction, accurate control of cross-node data synchronization is realized, and repeated confirmation and account book bifurcation are prevented; and resonance energy is absorbed through the time-varying virtual impedance and the energy buffer zone, so that self-balancing and self-repairing of the system are realized, and global consistency and scheduling stability of the block chain are ensured.

The invention discloses an internet protocol address access protection method and equipment, and relates to the technical field of internet. According to the scheme, the method comprises the steps that IP access records and safety related data are recorded in a tampering-free mode through a block chain distributed account book, and after a newly-added block is chained, a block chain node automatically updates a state database through an intelligent contract to maintain safety attribute information of an IP in real time. Before a terminal initiates IP access, a query request is sent to a plurality of nodes in a block chain network, after security attribute information fed back by each node is obtained, distributed verification is completed through a preset consensus algorithm, and finally an access control action is determined. A single central server is replaced by a multi-node distributed architecture, so that the risk of single-point failure is eliminated; secondly, an automatic updating mechanism driven by the smart contract greatly shortens a time window for responding to novel threats and IP redirection; and finally, all access records are publicly and transparently recorded on the block chain, so that the credibility and reliability of the system are enhanced.

The invention discloses a regional supply chain planning surveying and mapping system and surveying and mapping method based on an unmanned aerial vehicle, and relates to the technical field of planning analysis, and the method comprises the steps: carrying out the supply chain network connectivity evaluation and path optimization analysis of supply chain infrastructure data, and obtaining supply chain network connectivity data and path optimization data; carrying out storage position rationality evaluation and transportation efficiency analysis to obtain storage position rationality data and transportation efficiency data; performing supply chain planning strategy generation on the supply chain infrastructure data to obtain supply chain planning strategy data, and performing adjustment learning based on the supply chain planning strategy data to obtain a dynamic supply chain adjustment logic strategy; and performing execution unit design on the dynamic supply chain adjustment logic strategy to obtain a supply chain planning automation unit, and embedding the supply chain planning automation unit into the regional supply chain management system to execute the regional supply chain planning surveying and mapping method. The method has the effect of improving the supply chain planning surveying and mapping efficiency.

The invention discloses a water environment monitoring and early warning method based on multi-agent collaboration and a block chain, and relates to the technical field of water environment monitoring. The method comprises the following steps: collecting water quality parameters through monitoring equipment deployed in a water area, carrying out data cleaning and feature extraction on the water quality parameters through edge nodes, and executing lightweight anomaly detection; generating a data abstract from the monitoring data after edge processing, and writing the data abstract into a block chain network for credible evidence storage; each edge point serves as an independent agent, shares state data, performs task negotiation and distribution through a game theory algorithm based on a utility function, and performs uplink storage evidence on an intermediate result in a collaboration process; when the monitoring data meets a preset condition, each agent performs collaborative voting, and the intelligent contract automatically verifies a voting consensus and triggers an early warning event of a corresponding level; and according to the triggered early warning level, emergency equipment is automatically dispatched based on the priority queue for response, and an equipment execution result is fed back to a chain to form closed-loop management.

The invention discloses a food safety traceability system and method based on a block chain technology, and relates to the technical field of supply chain management, and the system comprises a data collection layer, a block chain network layer, an intelligent contract layer and an application layer. The intelligent contract layer comprises a traceability data contract, a business rule contract, a trusted transaction contract, an authority management contract and an early warning trigger contract; the method comprises the steps of supply chain main body registration and authority configuration, business rule intelligent contract deployment, traceability data acquisition and uplink, business rule automatic verification and execution, credible transaction verification and confirmation, traceability query and credible verification, and abnormity early warning and emergency response. According to the invention, automatic execution and credible transaction verification of the business rules are realized through the smart contract, so that the traceability data cannot be tampered, interconnection and intercommunication of data in each link of the supply chain are realized, real-time early warning of abnormity and rapid emergency response are supported, and the credibility, transparency and efficiency of food traceability are improved.

The invention relates to the technical field of agricultural product traceability, in particular to an agricultural product traceability method and system based on the Internet of Things technology, and the method comprises the steps: obtaining a traceability full-link node of an agricultural product; agricultural product traceability data of each node is collected; performing first encryption processing on the collected agricultural product traceability data to generate encrypted traceability data; uploading the encrypted traceability data to a block chain network for evidence storage, and generating a block chain evidence storage hash value; acquiring an equipment identifier of the Internet of Things acquisition equipment corresponding to each node; generating an agricultural product unique traceability identifier based on the block chain evidence storage hash value and the equipment identifier; receiving a traceability query request of a user; calling corresponding encrypted traceability data from the block chain network based on the unique traceability identifier of the agricultural product; and decrypting the called encrypted traceability data, and obtaining decrypted agricultural product traceability data. According to the invention, the credibility and authenticity of agricultural product traceability information can be improved.

The embodiment of the invention provides a trusted Internet of Things data acquisition and access control method based on TEE and a block chain. The method is applied to the field of network security and Internet of Things data protection, and comprises the following steps: encrypting, signing and binding credible timestamps of collected original data by using a credible execution environment, constructing a credible data packet and generating a block chain transaction; when a user initiates an access request, a trusted execution environment initiates an acquisition request to a block chain network actively, and acquires a preset access control strategy from an intelligent contract deployed on a block chain; the trusted execution environment verifies the access authority of the user according to the obtained access control strategy and request information carried when the user initiates the access request; and if the user permission verification is passed, the trusted execution environment performs decryption operation on the encrypted data requested to be accessed by the user by using the pre-stored decryption key corresponding to data encryption, and provides the decrypted data for the user, so that the security and reliability of data access are improved.

The invention discloses a digital textbook income distribution intelligent contract method supporting dynamic weight, and belongs to the field of block chain and digital education fusion. The method is deployed in a block chain network and comprises the core steps that multi-source heterogeneous data collection and credible chaining are carried out, and multi-dimensional data such as use intensity and user feedback are credibly transmitted to a chain through an oracle machine; a comprehensive popularity index is calculated on the chain, and a credible index reflecting the teaching material value is generated through normalization and weighted aggregation; the income weight is dynamically adjusted based on the popularity index, and the weight is updated in an epochical manner through various adjustable functions; and after the sales event is triggered, automatically completing atomization income distribution and full-link auditing. According to the method, a traditional static sharing mode is broken through, the income distribution and the dynamic presentation of the teaching materials are accurately linked, the distribution fairness and efficiency are improved, the trust cost is reduced, high-quality content creation is effectively stimulated, and an intelligent value distribution infrastructure is provided for digital education ecology.

A robot fleet platform for preparing a job request includes one or more processors configured to execute instructions. The instructions include a job request ingestion system configured to receive job content relating to at least one of picking, packing, moving, storing, warehousing, transporting or delivering of items in a supply chain. The job content includes an electronic job request and related data. The instructions include a job content parsing system configured to apply filters to the received job content to identify candidate portions thereof for robot automation. The instructions include a fleet intelligence layer that activates a set of intelligence services to process terms in the candidate portions of the job content and receive therefrom at least one recommended robot task and associated contextual information. The instructions include a demand intelligence layer that provides real time information relating to a parameter of demand for the items in the supply chain.

The invention relates to the technical field of computers and big data processing, and discloses an electric quantity data processing method based on industrial big data and an electric energy metering system.The method comprises the steps that an intelligent electric energy metering terminal collects and encrypts original electric quantity data; uploading to an alliance chain network for distributed hash evidence storage; the data compliance is verified through zero-knowledge proof without leaking an original value; dynamic noise disturbance is applied to the transaction data in combination with differential privacy; and the intelligent contract automatically completes authority verification and settlement. The system comprises an intelligent metering terminal, an alliance chain network, a zero-knowledge proof verification unit, a differential privacy disturbance unit and a data transaction settlement module. By fusing the alliance chain, the zero-knowledge proof and the differential privacy technology, tampering-free, traceable, strong privacy protection and compliant transaction of the electric quantity data are realized.

The invention discloses a credit business management method and device, electronic equipment and a program product, and relates to the technical field of blockchains, and the method comprises the steps: matching a target credit template from a template library according to business parameters in a credit request, carrying out the parameterization filling, and obtaining an intelligent contract draft, broadcasting the smart contract draft to a plurality of role nodes with authority in the alliance chain network, receiving operation results and signature results fed back by the plurality of role nodes, aggregating the multi-party signature results into a threshold signature under the condition that the operation results indicate that the smart contract draft meets a multi-party threshold signature condition, and sending the threshold signature to the alliance chain network. Writing the signed smart contract into a block chain account book, and updating the state of the smart contract to be an effective state; and in response to the credit request, executing a credit business operation associated with the smart contract. According to the invention, the technical problems of time and labor consumption and easy delay in the credit approval process in the prior art are solved.