3147results about "Payment protocols" patented technology

A system and method for integrated optimization of autonomous electric vehicle fleets across transportation and electricity networks which employs artificial intelligence to dynamically allocate autonomous electric vehicles between mobility services and electricity grid services based on real-time conditions. The platform acquires data including energy mix forecasts, earth observation measurements, vehicle owner schedules, and emission-based route penalties to generate coordinated allocation decisions. Vehicle owners specify availability through a scheduling interface. The system optimizes vehicle utilization through a hierarchical optimization approach implementing mobility demand-side flexibility and electricity demand-side flexibility simultaneously. Multi-objective genetic algorithm optimization balances revenue generation, energy costs, emissions reduction, and battery health. The integrated approach maximizes value creation across both transportation and energy domains, reducing urban emissions while enhancing grid stability through coordinated management of distributed energy resources in autonomous electric vehicle fleets.

To solve the problems of fractured identity across multiple blockchains, these methods and systems allow for a single unified identity to be managed and resolved across multiple chains within an interop network. By leveraging message passing, identity records can exist securely across different chains. The system incorporates counterfactual blockchains, enabling trust-minimized name registration that reduces costs while maintaining decentralization and security. ENS name resolution is supported across both onchain and offchain environments, with verifiable proofs ensuring efficient resolution. By structuring message passing and utilizing decentralized indexers, these methods and systems provide a scalable and reliable framework for cross-chain identity.

A decentralized artificial intelligence platform is disclosed that enables secure sharing and execution of AI modules in sensitive application domains. The platform comprises a knowledge module registry for discovering specialized AI modules, a security framework enforcing structural integrity of AI modules, a zero-knowledge proof validation service for verifying usage conditions without exposing private data, and a blockchain-based value chain for managing smart contracts and payments. In operation, an AI agent can fetch a required AI module from the knowledge module registry, prove the right to use it, execute the AI module on local data, and automatically pay the AI module's provider through a blockchain transaction.

Systems and methods for staking instrument cryptocurrency rewards and validator management are disclosed. The systems and methods include generating validator pods associated with cryptocurrency staking validation and generating validator keys configured to be utilized by the validator pods for validating proof of stake operations. A subsets of the validator keys may be assigned to the validator pods and a request to perform the proof of stake operations may be received. A validator pod may be provisioned for validating proof of stake operations, and the validator node may be utilized to validate proof of stake operations based on the selected validator node being a compliant validator node.

The invention discloses a distributed supply chain traceability system and method supported by a block chain, and relates to the field of data analysis, and the system comprises a collection module which is used for capturing the original data of a supply chain in real time through an Internet of Things sensor, and cleaning the data; the processing module is used for constructing a distributed account book based on a HyperledgerFabric architecture, performing hash encryption on the data, performing uplink storage on the data, packaging the data into blocks according to a time sequence, and completing data verification between nodes through a BFT consensus mechanism; according to the invention, full-link data of production, logistics and the like are captured in real time through the Internet of Things sensor and encrypted and chained, so that the data cannot be tampered and can be traced in the whole process, and the problems of easy data tampering and many breakpoints in traditional traceability are solved.

An artificial intelligence driven system of systems may include a layered architecture for providing transaction support to various types of enterprises. A governance layer implements automated governance and policy enforcement through specialized governance modules utilizing generative AI technology. An enterprise layer supports enterprise functions by integrating management and control platforms with digital infrastructure. An offering layer creates and manages system offerings via content generation, personalization, and smart product modules. A transactions layer enables automated transaction orchestration through API integration, execution, and fulfillment modules. An operations layer manages AI systems through generation, training, verification and orchestration modules. A network layer provides adaptive networking capabilities through routing, protocol selection and communication modules. A data layer processes fused data from multiple sources using machine learning and AI systems. A resource layer manages computing, storage, and other resources through specialized resource modules.

The invention discloses an anti-counterfeiting traceability system and method based on Beidou satellite positioning and a block chain. The method comprises the following steps: generating a current positioning data tuple; performing validity judgment on the satellite signal quality index; generating current event summary information, performing encryption calculation on the event summary information by using a private key embedded in a commodity and improving a verifiable random function, and outputting a random seed and a verification proof; constructing an event fingerprint and generating an event signature by using a private key; a challenge request is generated when the commodity request state is migrated, the commodity end device responds to the challenge request and collects new Beidou positioning information, and a challenge response data packet is constructed; and performing consistency verification on the challenge response data packet according to the virtual state resume smart contract, writing the verified data into a geographic sub-chain, recording an event abstract hash path by a main chain, and updating a commodity state transfer path. According to the invention, based on Beidou positioning and an improved verifiable random function, the credible verification of the commodity position and the traceable management of the state are realized.

The invention relates to the technical field of financial accounting and artificial intelligence combination, in particular to an artificial intelligence-based financial data identification and accounting method, which comprises the following steps of: firstly, calculating a fractal dimension by using a multi-level grid splitting technology, and constructing a fractal financial semantic map covering transaction and exchange entities; and performing interference operation by using a quantum mixing aggregator, fusing fractal atlas attributes and subject candidate results to obtain interference scores, and performing symbol rule screening or manual auditing confirmation to generate calibrated subject information. Then, the subject information is used for automatically generating an accounting entry and performing account book archiving, and the whole decision process is recorded under the quantum hash technology; by continuously analyzing archived decision data, the system can adaptively adjust fractal dimension calculation and interference parameters, and precise recognition and efficient accounting of complex financial data are realized.

The invention discloses a data transaction privacy protection method based on a block chain, belongs to the technical field of data sharing, and aims to solve the technical problem of how to ensure data privacy and ensure traceability and transparency of data transaction in Internet of Things data transaction. Comprising the steps that a data buyer performs data validity verification based on a zero-knowledge proof submitted to a block chain by a data seller, after verification is passed, the data seller generates a re-encryption key based on a private key of the data seller and a public key of the data buyer and uploads the re-encryption key to a proxy node, the proxy node re-encrypts a related ciphertext based on the re-encryption key, and the data seller sends the re-encrypted ciphertext to the data seller; the obtained re-encrypted ciphertext is uploaded to the IPFS, a content identifier returned by the IPFS is written into the block chain, and the block chain writes the content identifier corresponding to the re-encrypted ciphertext into the smart contract; and after the data buyer pays, the re-encrypted ciphertext is obtained from the IPFS based on the content identifier returned by the block chain, and the re-encrypted ciphertext is decrypted based on the private key.

The invention relates to the field of electricity transaction, in particular to an electricity transaction intelligent algorithm platform based on block chain consensus. The method comprises the following steps: acquiring a real-time green electricity encrypted data set, uploading the real-time green electricity encrypted data set to a block chain node, and generating an unactivated digital green certificate data set; based on the non-activated digital green certificate data set, generating a grid-connected verification instruction, updating the non-activated digital green certificate data set to a tradable state, and generating a tradable digital green certificate data set; obtaining a power grid dynamic parameter set, and generating a green certificate time pricing data set through a space-time right dynamic pricing strategy based on the power grid dynamic parameter set and the tradable digital green certificate data set; and according to the green certificate time pricing data set, the digital green certificate is cancelled after verification in the power utilization process of the user, and a green power consumption traceability report is output. In the green electricity transaction process, fair and orderly development of the green electricity transaction market is promoted.

Embodiments are directed toward a blockchain system including a global state and an assemblage of blocks, each block representing a collection of state transformation records, each state transformation record describing a state transformation performed on the global state, where preceding blocks referenced by any given block contain state transformation records describing state transformations performed on the global state prior to the evaluation of the given block, and where at least one state transformation record is a zero-knowledge transformation record encoding a zero-knowledge state transformation description, which zero-knowledge transformation record comprises at least the following elements: paths identifying the locations of the elements of a discrete data subset, a revised data subset, and a transition proof implemented as a non-interactive zero-knowledge proof, which transition proof proves that the transition from the discrete data subset to the revised data subset follows the established rules of the blockchain system.

Token minting environment includes a physical token minter that is accessible to a group of users. A user initiates a session to mint a non-fungible token associated with an image that the physical token minter generates. When the session is established, the physical token minter connects with a digital wallet associated with the user. The physical token minter identifies a physical interaction provided by the user, such as the user pulling a lever or pressing an input button that is proximate to the physical token minter. Upon identifying the user interaction, the physical token minter responds by triggering the creation of an image and the minting of a non-fungible token that links the image to the wallet of the user. The physical token minter then provides a digital representation of the image and an indication that a token for the image has been added to the digital wallet.

The invention relates to the technical field of transaction verification, in particular to a block chain financial transaction tracing method and system, and the method comprises the following steps: calculating a node interaction proportion, recognizing illegal chain segments and marking nodes, analyzing a field combination sequence matching path structure, judging numbering jump and behavior path pairing, and extracting a field corresponding relation and a matching difference. And identifying a node state offset and a structure jump trend, and generating a state chain segment backtracking section record. According to the method, the interaction frequency and the behavior type proportion are introduced to serve as the node state recognition basis, dynamic credible judgment of boundary nodes is achieved, the recognition precision of chain segment structure interruption is enhanced through the path field combination sequence and the serial number continuity, the serial number jumping behavior and node action offset are combined, the chain jumping path recognition capacity is optimized, and the reliability of the system is improved. The field consistency verification effect is improved by adopting field logic pairing and value domain offset comparison, and the backtracking positioning capability of the broken link node is enhanced by using a path state offset and backtracking pointer association strategy.

A system to track to model asset states and access by utilizing non-fungible tokens (NFTs). The system includes a data processing system including memory and one or more processors to receive a stating request for an asset, obtain, based on a plurality of control structures, a plurality of NFTs, each of the plurality of NFTs including a link with a metadata object including metadata of a state of the asset, encapsulate the plurality of NFTs within a container, receive, from the remote device, a state request for an asset state corresponding to a first NFT, the state request including a security token, obtain, from the metadata of the first NFT, one or more recorded security tokens, compare the security token to the one or more security tokens, and, in response to the security token matching the one or more security tokens, transmit the first NFT to the remote device.

The invention provides a block chain dynamic trust evaluation system and method based on artificial intelligence, and the method comprises the steps: carrying out the time sequence modeling of the transaction data of a block chain node and the consensus historical record of the node participation consensus, obtaining the behavior credibility of the block chain node, calculating the resource contribution degree of each transaction node, and carrying out the calculation of the resource contribution degree. Fusing the behavior credibility and each resource contribution degree to obtain a consensus score of each transaction node; constructing a node graph neural network of the block chain based on the transaction topological relation and the interaction frequency between the transaction nodes, detecting a plurality of malicious nodes in the block chain by using the node graph neural network, and further evaluating a consensus influence coefficient of the current malicious node aggregation on the block chain node consensus; and performing punitive correction on the consensus score of each malicious node through the consensus influence coefficient to obtain a final trust score of each transaction node in the block chain. Based on the above scheme, punishment correction of malicious node aggregation in blockchain node trust evaluation can be realized.

The present disclosure provides a method for deal management and blockchain execution is disclosed. The method utilizes a blockchain-based platform to securely store and verify data related to investing entities, including their risk tolerance, investment goals, and regulatory compliance. The system determines a subset of entities with shared interests in a specific investment, generating a set of profiles associated with each entity based on historical deal data. These profiles are used to inform investment decisions and monitor portfolio performance. The platform also verifies accreditation statuses of the investing entities through blockchain-based consensus rules, providing an immutable record of investor accreditation status. Additionally, the system provides real-time transaction records to generate accurate and up-to-date reports for investors and deal sponsors, leveraging blockchain-based data storage and verification capabilities.

The invention discloses an automatic medicine vending machine based on AI inquiry. The automatic medicine vending machine comprises a machine body, an intelligent interaction system, an AI inquiry system, a medicine storage bin, a control system, a payment system and a printing device. A constant-temperature and constant-humidity system and a disinfection and air purification module are arranged in the machine body. The intelligent interaction system collects symptom information in a multi-mode mode, and the AI inquiry system achieves symptom analysis, intelligent triage and personalized medication recommendation based on a medical knowledge graph and a natural language processing technology. The medicine storage bin carries a three-dimensional matrix type medicine cabinet and an intelligent inventory system, and intelligent replenishment is carried out through an LSTM algorithm. And the control system adopts a controller and triple verification to realize high-precision medicine discharging operation. The payment system supports multiple settlement modes and block chain evidence storage data. And the printing device outputs the medication guide sheet and the anti-counterfeit label. According to the invention, AI and automation technologies are deeply integrated, the service of less than or equal to 3 minutes in the whole process of inquiry-payment-medicine dispensing is realized, and the safety and convenience of medicine use are improved.

The invention provides a shared economy separate account checking method based on a block chain, and relates to the technical field of block chains and Internet of Things, and the method comprises the steps: constructing an alliance chain on a block chain platform, and defining business logic and rules through an intelligent contract, so as to ensure the consistency and safety of information. Based on an intelligent chip, data can be automatically linked, and through a zero-knowledge proof technology, consistency of on-chain and off-chain data is verified, and privacy is protected. In this way, the consumption order amount can be automatically divided to the bank account of the related subject, the account balance is generated, and account book synchronization is achieved. Transactions are checked regularly, abnormity is processed, and the accuracy of intelligent account division and account checking is ensured. If the preset subject is changed, the change can be adapted by updating the smart contract, and the flexibility is improved. In addition, a TCC distributed transaction management scheme and a consensus mechanism are introduced, so that the efficiency of account division and account checking is improved, and the stability and reliability of the system are kept.

The invention discloses a virtual power plant operation management and control method based on a block chain, original power data are compressed into Hash fingerprints to be chained through a collaborative architecture of an edge computing layer and an AI pre-decision module, the block chain network load is effectively reduced, and a dynamic elastic PBFT consensus mechanism adjusts the scale of verification nodes in real time based on transaction types, so that the efficiency is improved. And compared with a traditional fixed node consensus mechanism, the network communication overhead is reduced. And a hash value asynchronous pre-verification technology is adopted, so that the interaction rate of the multi-dimensional power data is improved, and the efficiency is improved compared with that of a conventional data uplink mode. Through the decoupling design of the intelligent contract execution flow and the consensus verification flow and in combination with the pre-decision data cache queue, the resource scheduling instruction issuing time delay is reduced. The block chain transaction throughput is improved and is effectively improved compared with a standard alliance chain architecture, and the technical problems that the consensus mechanism processing transaction speed of an existing block chain is limited and the high-frequency real-time data interaction requirement of a virtual power plant is difficult to meet are successfully solved.

Systems and methods are provided for training an artificial intelligence system and generating audible content for output. The method utilizing a system including at least an application plane layer, a control plane layer including a cognitive computing unit, the cognitive computing unit using at least machine learning for training of the cognitive computing unit, a training input to the system including an input for receiving content for training during the machine learning, and a data plane layer, the data plane layer including an input interface to receive and store data input content from one or more data sources other than the control plane layer, the data input content being subject to transformation into audible content for output. Data input content information is used in synthesizing audible output content at least in part by transforming the data input content into the audible output content.

Disclosed herein is a method and system to determine whether a payment terminal has been tampered with based on a comparison of attestation data received from the payment terminal, for example in an offline mode when an otherwise secure remote server cannot be reached. If the determination yields that the request has been approved, the terminal generates an attestation ticket having one or more validity conditions, wherein the validity conditions include expiration time that indicates the time after which the attestation ticket becomes invalid. The attestation ticket can be used as long as it is valid or until another trigger causes the ticket to be invalidated or regenerated.

The present disclosure is related to blockchain technologies, tokenization and non-fungible token (NFT) technologies, identity verification, account verification, information security (InfoSec), and fraud prevention technologies, and in particular, to technologies for creating NFT identities (IDs) for individuals and / or organizations. An NFT ID service interacts with users to obtain ID information such as ID documents, biographical data, biometric data, and / or any other suitable data. The NFT ID service includes an NFT ID engine that generates an NFT-based form of digitized and / or tokenized ID, using blockchain technology, smart contracts, distributed ledgers, digital wallets, and the ID information. Other embodiments may be described and / or claimed.

The invention relates to the technical field of information, and provides a bulk commodity transaction system based on a block chain, and the system comprises a parameter and publishing module which uniformly receives and stores parameters; the unified examination and approval engine performs isomorphic arrangement and gray level updating through a configurable template and a state machine; consistency snapshots and recovery are paused / abnormally collected snapshots and monotonically replayed, and it is guaranteed that the sequence is consistent with a window; the security fund risk control uses DSL + fund DAG to drive freezing / unfreezing / deduction and account checking; and block chain evidence storage and auditing execute field-level hash and pedigree anchoring to realize verifiable traceability. According to the system, an end-to-end consistency and verifiability framework is constructed around the aspects of field-level fingerprinting, unified examination and approval, windowed stable sorting, consistency snapshot and monotone replay, fund event patterning, contract assembling and signature anchoring, settlement / final recalculation and pedigree uplink and offline verification; and under the conditions of abnormity, recovery and version evolution, each link keeps uniform caliber, stable sorting and approvable state.

Disclosed is a smart card including a communication circuit configured to communicate with a reader associated with an authentication service, a memory for storing a program associated with the authentication service, a decentralized identifier, and a VC list, and at least one processor operatively connected to the memory and configured to execute instructions, in which the at least one processor is configured to transmit a VC included in the VC list and associated with the authentication request to the reader when receiving an authentication request from the reader, and generate an electronic signature, when receiving a hash value generated based on at least a piece of information included in the VC, based on the hash value and the decentralized identifier set and transmit the generated electronic signature to the reader. In addition to this, various embodiments grasped through the specification are possible.

The invention relates to the technical field of block chain and smart home data management, discloses a smart home data contribution quantification and excitation method and system based on a block chain identifier, and aims to solve the data source problem of vertical large model training in the smart home industry and guarantee data security and personal privacy. The method comprises the steps of equipment identifier registration and binding, home local data processing and desensitization, data contribution degree quantitative evaluation, intelligent contract incentive execution and standardized data delivery and evidence storage. The system comprises a block chain identifier management module, a home edge data center, a data contribution quantitative evaluation module, an intelligent contract incentive engine and a large model training data delivery interface. According to the technical scheme, accurate tracing of data sources and clear definition of contribution subjects can be achieved, the family computing power is activated, the risk of data privacy disclosure is reduced, high-quality and scenarized credible data sources are provided, and marketization circulation and value conversion of smart home data elements are promoted.

The invention discloses an intelligent payment routing method and device, equipment and a storage medium, and relates to the field of intelligent payment management. The intelligent payment routing method comprises the steps of obtaining a payment bank corresponding to a user bank card in response to a payment request of a user; based on the amount of the payment request and the payment bank, matching an optimal payment route of the payment request pair through a multi-dimensional dynamic weight model; and in response to the matched optimal payment route corresponding to the payment request, performing payment operation of the payment bank through the optimal payment route. Through the above mode, the method can dynamically adjust the selection rule of the payment route.

Systems and methods for source chain management with identity-based tokens and enhanced security are disclosed. A processing system receives input that includes a decentralized identifier (DID) uniquely associated with an entity. The processing system invokes a smart contract deployed on a distributed ledger to mint a non-transferable identity-based token permanently linked to the DID. Metadata generated for the token includes cryptographic references to a hierarchical source chain structure stored in a decentralized data storage system, along with cryptographic verification data. Events associated with the DID are memorialized by appending granular event details, including timestamps, data changes, and origin identifiers, into the hierarchical source chain. Authorized access to event details and tokens is provided via an authenticated interface that securely retrieves and reconstructs encrypted data shards distributed across decentralized nodes, enhancing data security, immutability, and verifiability in decentralized environments.

The Asynchronous Crypto Asset Transfer and Social Aggregating, Fractionally Efficient Transfer Guidance, Conditional Triggered Transaction, Datastructures, Apparatuses, Methods and Systems (“SOCOACT”) transforms transfer of assets (TOA) initiation request inputs via SOCOACT components into TOA confirmation outputs. A crypto asset transfer notification is sent to a first entity from a second entity. Account verification data generated by the second entity is determined. A set of account data stored by the first entity is retrieved and used to generate a hash. It is verified that the determined account verification data matches the generated hash. A requested asset is determined. An API call to generate a crypto token asset for the requested asset in a socially aggregated blockchain datastructure is made. An address of an aggregated crypto transaction trigger entry is determined. Oracle data that satisfies the crypto smart rule is provided.

The invention discloses a self-supervision anomaly detection method based on mask self-encoding, and relates to the technical field of anomaly detection, and the method comprises the steps of S1, data preprocessing, S2, mask self-encoder design, S3, mask strategy, S4, self-supervision training, S5, anomaly detection, S6, evaluation and optimization, and S7, deployment and application. By introducing a dynamic feature importance mask strategy, the model can dynamically adjust the mask probability according to the importance score of the feature, so as to pay more attention to the incidence relation between key features, specifically, the importance score of each feature is calculated through a mutual information method or a gradient saliency method, and then the mask probability is dynamically generated; according to the method, the model can preferentially learn features which contribute more to anomaly detection in the training process, excessive attention to unimportant features is avoided, the model can capture internal rules of data more efficiently, and the accuracy of feature extraction and the learning efficiency of the model are improved.