1388 results about "Distributed ledger" patented technology

An online social wager-based gaming system is disclosed, featuring dynamic cross-provider game filtering and persistent cross-provider voice-interactive group play. The system allows for automated multi-seat group game reservations and incorporates a distributed ledger for bet verification. Features include a Group Connect module for dynamic group formation and live audio across various game providers, enabling real-time play. A Professional Companion Connect module facilitates live webcam or microphone gambling sessions with professional companions, under contractual agreements. The User Games module enhances personalization by integrating user-uploaded images into the gaming environment. A cryptocurrency / blockchain-based bet tracking system ensures transparency and security in managing bet transactions through a controlled digital wallet system. This integrated platform aims to provide a cohesive, interactive, and personalized online casino experience, addressing limitations of traditional solitary online gaming by fostering social connections and enhancing user trust and engagement.

The invention provides an electronic certificate management and supply chain quality tracing method and system based on a block chain, and belongs to the technical field of information. According to the method, encryption storage and tamper-proof protection are carried out on the electronic certificate information through the distributed account book of the block chain and the Hash algorithm, and verification, approval and data updating operations are automatically executed based on the intelligent contract. Fine-grained authority management and abnormal access detection of all parties of the supply chain are realized through a user access control module; and through a tracing query module, performing multi-condition combination query on the electronic certificate information stored in the block chain, and generating a quality tracing report meeting supervision requirements. According to the method, through tamper-proofing, distributed storage and intelligent contracts of the block chain, trusted storage, automatic verification and full-chain quality tracing of the electronic certification are realized, data security and supply chain transparency are improved, trust cost is reduced, and supervision and tracing efficiency is improved.

Systems and methods for controlling rights related to digital knowledge are disclosed. A sample system may include an input system to receive digital knowledge from a user, a tokenization system to tokenize the digital knowledge and a ledger management system to create, manage, and store things on a distributed ledger and provide provable access to the digital knowledge. A smart contract system may create a smart contract including triggering action is and respond with a defined smart contract action on an occurrence of the triggering event. The smart contract system may also process commitments to the smart contract.

A system and method for facilitating collection of Road User Charges (RUC) using a digital currency within a Distributed Ledger Technology (DLT) network are disclosed. The system generates secure digital wallets for Road Users and Facility Owners, receives trip, position, distance, and cost data from vehicles, sensors, and facility systems, and encodes settlement logic into smart contracts. These contracts automatically execute jurisdiction-specific disbursements across blockchain, directed acyclic graph (DAG), or hashgraph frameworks, ensuring scalability and auditability without reliance on centralized tolling infrastructure. An AI Activity Module processes multi-source telemetry—including vehicle sensors, GNSS / PNT data, roadside infrastructure, and third-party traffic feeds—to detect congestion, forecast conditions, optimize routing, and dynamically adjust segment-level RUC pricing in real time. The integration of AI-driven adaptive pricing with distributed ledger settlement provides a decentralized, infrastructure-agnostic framework for secure, transparent, and verifiable road use fee collection across multiple jurisdictions, distinct from conventional tolling systems.

The invention discloses a material batch full-process traceability system based on a production process, particularly relates to the field of production and manufacturing traceability, is used for solving the problems of continuity and accuracy of material batch full-process traceability, and is characterized in that batch tracking coordinates are generated by constructing a process mapping matrix and an assembly topological index; detecting circulation holes in real time and inserting placeholder marks; judging broken chain credibility based on path integrity and structural complexity; compressing traceable chain segments; executing field dynamic alignment to generate batch circulation patches; a material batch whole-process continuous tracing view is established; and furthermore, the abnormity positioning time is remarkably shortened, the real-time performance is improved, the influenced batches are accurately locked, the recall range is reduced, the production line decision-making efficiency is optimized, and efficient and reliable technical support is provided for quality management and batch tracking in the production process.

The present invention relates to a system and method for cross-domain predictive modeling using Bedrock-based foundation models and blockchain-anchored data. The invention integrates large-scale foundation model reasoning with distributed ledger-based data provenance to enable verifiable, secure, and explainable predictive analytics across heterogeneous domains such as finance, healthcare, logistics, and environmental systems. The system comprises a data ingestion unit for receiving and normalizing multi-domain datasets, a blockchain anchoring unit for generating cryptographic hashes and recording data provenance into a distributed ledger, a cross-domain harmonization processor for aligning heterogeneous feature representations into a unified latent space, a foundation model processor configured to execute Bedrock-based predictive inference with adaptive domain contextualization, a verification processor for validating predictions against blockchain-anchored ground truths, and a governance processor for maintaining immutable audit trails of model evolution.

An information technology system for a distributed manufacturing network includes an additive manufacturing management platform configured to manage process and production workflows for a set of distributed manufacturing network entities through design, modeling, printing, and supply chain stages. The information technology system includes an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from the set of distributed manufacturing network entities of the distributed manufacturing network to optimize digital production processes and workflows. The information technology system includes a distributed ledger system integrated with a digital thread configured to provide unified views of workflow and transaction information to entities in the distributed manufacturing network.

The present invention relates to adaptive multi-state encoding and processing in virtualized computing environments. The system includes a virtualized state selection module that dynamically transitions between binary, ternary, quaternary, and higher-order encoding states based on workload, bandwidth, security posture, and compliance requirements. A virtual encoding engine utilizes hardware-accelerated components, such as vFPGAs, vGPUs, and cTPUs, to enhance encoding throughput. A compliance-driven feedback controller continuously monitors encoding efficiency, threat levels, and adherence to mandates such as GDPR, HIPAA, and FIPS 140-3. Additional features include AI-based anomaly detection, federated model refinement, distributed ledger-backed audit trails, and quantum-resistant encoding techniques. By integrating intelligent encoding decisions with scalable compliance enforcement, the system enables high-performance, secure, and regulation-ready data processing across distributed cloud and edge environments, delivering measurable improvements in system responsiveness, data integrity, and operational trust.

The invention discloses a product logistics management scheduling method based on a block chain, a medium and equipment, and the method comprises the steps: generating an initial transportation path scheme through collecting logistics transportation demand information and supply chain node data; constructing a decentralized logistics resource pool, and collecting and verifying transportation fluctuation parameters to generate a credible state matrix; inputting the initial transportation path scheme and the logistics resource credible state matrix into a graph neural network scheduling model, and outputting a dynamic scheduling scheme; compliance verification of task allocation and scheduling instructions is automatically executed through the smart contract; and finally, updating the scheduling execution result and the logistics resource credible state matrix to a distributed account book, and outputting a logistics management report. Through deep cooperation of the intelligent contract and dynamic path optimization, real-time credible scheduling of the transportation process is realized, the problems of insufficient dynamic response and multi-party cooperation trust deficiency of an existing logistics system are solved, and the reliability and efficiency of cold chain and other sensitive commodity transportation are improved.

The invention relates to the technical field of medical information processing, in particular to a health data processing method and system based on a distributed ledger library, and the method comprises the steps: a node firstly links a health data abstract to obtain a differential privacy budget token and a reversible tensor hash key; then, carrying out encryption training on local model parameters by using the key, injecting Gaussian noise according to budget to generate a differential protection gradient, and carrying out uplink together with zero-knowledge proof; the account book end decrypts the threshold value, uses a structural equation model to deduce a causal correction matrix according to the reputation weight aggregation gradient, and automatically adds a budget and turns the key when the concept drifts and the budget is insufficient; the operation mechanism splices the aggregation parameters and local parameters, generates a gating vector in combination with a causal correction matrix and a reputation weight, outputs disease risk prediction, and only uploads prediction hash and error information; chain-level audible privacy protection, dynamic budget management and hybrid deviation suppression are realized, and the safety and accuracy of a cross-institution medical model are improved.

A tokenization system / platform / method for minting asset-class backed tokens on a distributed ledger is described herein. A tokenization system / platform receives a token configuration indicating multiple revenue-generating assets of different types and a minting party. The platform configures smart contracts to manage revenue associated with revenue-generating assets, including a first function to mint asset-class backed tokens backed by the plurality of assets and a second function to computationally apportion and distribute revenue among blockchain addresses of token owners. After deploying the configured smart contracts on the distributed ledger, the platform initiates blockchain transactions to invoke the smart contract functions, including a first transaction that mints tokens and assigns them to purchasing users' blockchain addresses, and one or more second transactions that distribute cryptocurrency corresponding to revenue among token owners. The system / platform / method may provide for fractional ownership and management of different types of revenue-generating assets and / or portfolios of revenue-generating assets.

A blockchain of block entries that can be requested by users from user devices is maintained in a distributed network of nodes. Block entries include a plurality of data portions that are each associated with an access level. A request from an auditor to view one or more data portions of a block entry can includes an access code associated with at least one access level can be evaluated to identify one or more data portions associated with the access level. A customized view of the block entry which includes the one or more data portions associated with the access level can be generated. An artificial intelligence engine can review entries within the distributed ledger, identify earnings information associated with the sales of the commercial inventory, determine tax based on earning information, and pay the tax via fiat or cryptocurrency to government authorities based on earnings information.

The invention provides an AI-based carbon footprint and supply chain carbon emission collaborative management method and platform, and the method comprises the steps: collecting various types of carbon-related data from each link of a supply chain in real time, and carrying out the standardization processing to form a unified data flow. An intelligent sensing technology is combined with a dynamic reference model, and sudden carbon emission fluctuation generated in production operation is automatically recognized. The propagation influence and potential risk of these carbon emission fluctuations in the entire supply chain are analyzed. The risk propagation condition and the processing capacity of each node are comprehensively considered, and an optimal carbon emission distribution processing scheme is formulated through an optimization algorithm. A distributed account book technology and an automatic execution mechanism are utilized, and an excitation system is combined to ensure that each participant completes a corresponding carbon processing task according to an optimal scheme. According to the method, the intelligent level and the overall effect of supply chain carbon management can be effectively improved, and a technical support is provided for an enterprise to realize a carbon emission reduction target.

Systems and methods for decentralized orchestration of event records within decentralized computing environments. A processing system including decentralized execution nodes dynamically allocates microservice instances based upon real-time node performance metrics. Transaction requests including transaction data digitally associated with decentralized identifiers (DIDs) are processed by allocated microservice instances. The processing includes verifying transactions, generating cryptographically-linked immutable memorialization records associated with respective DIDs, and distributing these records to a tamper-evident distributed ledger configured to enforce immutability through consensus nodes. The processing system dynamically reallocates microservice instances among decentralized execution nodes based upon monitored utilization metrics and predefined scaling thresholds. Each memorialization record is cryptographically secured and linked permanently to the DID for data immutability, enhanced security, and dynamic scalability for event data processing in distributed infrastructures.

The invention provides an intelligent actual measurement and quantity management method and system for a building. The method comprises the following steps: capturing environmental parameters, material circulation paths and spatial geometric information of key parts of a building in a construction process in real time to obtain a measurement data set; a distributed ledger technology is combined with a homomorphic encryption algorithm, a graph theory analysis technology is applied to evaluate a dependency relationship among operation points of a construction site, and a data log is generated; according to the data log, using an augmented reality technology to superpose a BIM model, introducing a support vector machine algorithm to carry out automatic classification and risk assessment processing on deviation data between measured data and preset standard data, and generating a rectification suggestion report; and a closed-loop quality management process is formed by continuously collecting rectification effect feedback. According to the technical scheme, high transparency and efficient quality control in the construction process are ensured.

The systems and methods disclosed herein monitor application (e.g., artificial intelligence (AI) model) operations using interactions between the application and a kernel. The systems and methods disclosed herein intercept, using a kernel interface, one or more function invocations transmitted from the application (e.g., an AI model without model modification). Event record(s) are generated for one or more functions to define process identifiers, resource interaction types, timestamps, and / or resource identifiers. Observed pattern(s) for the application are identified by comparing current event record(s) with previous record(s), and the identified observed pattern(s) are evaluated against reference pattern(s) to generate score(s). Data packet(s) that indicate observed pattern(s), corresponding score(s), and / or cryptographic digital fingerprint(s) of the one or more functions are generated. The data packet(s) are transmitted to distributed ledgers for immutable storage.

The invention provides a supply chain product traceability system, method and device based on a block chain, and a medium, and belongs to the technical field of block chains. The system comprises a data acquisition module which is arranged in a plurality of information terminals in a supply chain and is used for collecting product information, carrying out preliminary format conversion and encryption processing, and sending the product information to a block chain network; the block chain network is used for realizing data consistency through a consensus algorithm and storing product information by adopting a distributed account book technology; the data query module is used for providing a product traceability information query service by initiating a query request to a block chain network, and obtaining product supply chain information according to the authority of a query terminal; and the intelligent contract module is deployed on the block chain network and is used for automatically executing the business rules in the supply chain according to predefined intelligent contract code logic. According to the invention, real and reliable recording and efficient query of the full life cycle information of the product are realized by using the block chain technology, and accurate product traceability information is provided for consumers.

A computerized platform enables secure, policy-compliant creation, governance, and monetization of digital artifacts produced by Al-driven “persona” agents in regulated domains (e.g., healthcare, finance). For each agent session, a federated compliance-token generator issues a cryptographically signed token embedding the full delegation chain, credential lineage, real-time policy snapshot, monetization rules, expiration and revocation data. As artifacts or workflows cross organizational or jurisdictional boundaries, a token inheritance module can subdivide, transfer, renew, or revoke the token while appending each event to an immutable, cryptographically linked audit trail. Every agent output is encapsulated as a digitally signed artifact that is indelibly linked to its originating compliance token and enriched with provenance, consent, and service metadata. A permissioned blockchain (or sharded distributed ledger) functions as an asset registry that immutably stores artifacts, tokens, and chronological records of creation, access, transfer, consent change, and policy updates. A smart-contract engine automates revenue allocation and settlement, ensuring continuous traceability, privacy protection, and financial compliance across institutional boundaries.

The invention provides a port tallying vehicle monitoring management method and system, and relates to the technical field of port automation management, and the method comprises the steps: collecting the multi-dimensional tallying feature data of a port tallying vehicle through an Internet of Things sensing network, and carrying out the preprocessing; extracting a multi-dimensional tallying feature vector, and constructing a dynamic weighted directed graph model in combination with the port traffic situation; planning an optimal tallying driving path for the vehicle based on the dynamic weighted directed graph model, generating an optimal tallying operation plan, and pushing the optimal tallying operation plan to the vehicle-mounted intelligent terminal; when the vehicle executes the plan, monitoring vehicle position posture change and cargo state change through a multi-sensor fusion technology, and when an abnormal event is monitored, triggering a grading early warning mechanism and adjusting the plan; and after the vehicle completes the plan, the operation process data is verified based on the block chain distributed account book, and a digital twin report is generated and synchronized to the monitoring end, so that efficient, safe and intelligent monitoring management of the port tallying vehicle can be realized, and the operation efficiency and safety of the port are improved.

The invention discloses a data ownership verification and authorization control method based on zero knowledge proof. The method comprises the following steps: constructing a traceable Merk tree structure on a block chain or a distributed account book; a data owner calculates data fingerprints and packages the data fingerprints into declaration nodes to be inserted into the traceable Merk tree; storing the ownership zero knowledge proof and the traceable Merk tree root hash into a block chain together; the verification party executes the zero-knowledge verifier contract on the chain to complete ownership verification without reading original data or identity plaintext; access control is realized after on-chain verification of the service party; triggering local heavy hash to update the traceable Merk tree root hash, and broadcasting a revocation event on a chain; and confirming legality of evolution and authorization change of all nodes. According to the method, the historical traceability and structural consistency of the data ownership and authorization relationship are ensured, and efficient traceability and anomaly detection of the node evolution chain are also realized.

Various aspects of the subject technology relate to systems, methods, and machine-readable media for improving the privacy of transfers in a distributed ledger. Various aspects may include encrypting a transaction using a first public key corresponding to a first user and a second public key corresponding to a second user. Aspects may also include transmitting the encrypted transaction to a blockchain, the encrypted transaction including at least an encrypted amount, a zero-knowledge proof, and an encrypted balance of the first user. Aspects may also include verifying a correctness of the zero-knowledge proof. Aspects may also include, based on the correctness, executing the transaction through a smart contract of the blockchain and homomorphically updating encrypted balances of the first user and the second user in accordance with the encrypted amount.

The embodiments disclose a cryptographically governed system for contextual memory management in artificial intelligence including a Contextual Orchestration and Scoped Memory Protocol (COSMP) and a Decentralized Memory Wallet (DMW), which enforce secure, auditable, and policy-driven access to AI memory. Traditional token-based memory tracking is replaced by memory capsules secure data units with embedded access policies and tamper-evident logs 5400 organized via a distributed ledger. Access control is managed through decentralized identifiers (DIDs) and private cryptographic keys, ensuring that all memory interactions are signed, verifiable transactions. This architecture establishes a universal trust layer for AI, enabling post-hoc compliance checks and privacy-preserving audits. Applicable across domains such as national security, healthcare, and autonomous systems, the invention enforces rigorous behavioral constraints and access governance within AI memory and decision-making processes.

Systems and methods disclosed herein automatically authorize, audit, and manage usage of protected digital content via agentic artificial intelligence (AI) models. A data access / usage request is received (e.g., from a graphical user interface) that is associated with digital assets licensed from third parties. The system uses a first AI agent set to identify the digital content and retrieve corresponding access policies from a distributed database. The system uses a second AI agent set (same as or different from the first AI agent set) to evaluate the request against the retrieved policy to generate a permission set and / or settlement instructions. The system uses a third AI agent set (same as or different from the first and / or second AI agent sets) to embed digital watermarks and / or cryptographic signatures into the accessed content, and to record an audit trail of access, authorization, and / or settlement events in a distributed ledger or database.

Techniques are described herein for providing artificial intelligence mediated curation of access and content within a cyber threat intelligence platform. An example system includes: one or more memories, and one or more processors. The example system may receive, from a node, an input indicating a cyber threat type; identify, by a trained AI model, cyber threat intelligence content objects, each of the objects being (a) contributed by one or more nodes having access to the distributed ledger or (b) generated by the trained AI model; evaluate, by the trained AI model, each object to: determine relevance values corresponding to each of object, and generate (i) a curated set of cyber threat intelligence content objects based on the relevance values and (ii) a recommended cyber threat practice; and transmit the recommended cyber threat practice and an indication of the curated set of cyber threat intelligence content objects to the 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.

A dynamic real estate valuation system based on multiparametric market indicators, which includes the following: a valuation engine configured to generate real-time results for property valuation; a multitude of distributed data ingestion and processing units configured to capture heterogeneous data sources, including historical property transaction data, real-time property listings, zoning and land use records, macroeconomic indicators, geospatial data, environmental sensor outputs, and sentiment-derived metrics; a model orchestration control unit comprising a stack of machine learning models, wherein the models include at least a gradient boosting decision tree model, a long-short-term memory (LSTM) time series forecaster, and an enhancement learning module that iteratively optimizes the model parameters based on the observed evaluation accuracy; a data contextualization controller configured to apply dynamic weighting to each input parameter based on the geographic, temporal, and market context by executing decay functions and location-specific rule matrices; a physical property valuation terminal (PVT) that includes an edge processing unit (EPU), geolocation circuitry, secure communication interfaces and a touch-based user interface; a valuation book subsystem configured to hash the valuation output, timestamp, and signatures of the input record into a blockchain-based distributed ledger; wherein the system is designed to continuously recalibrate its valuation results by comparing the predicted valuations with the actual sales or rental prices, and wherein the physical terminal is designed to produce a legally certifiable valuation document with embedded provenance data.

The invention provides a double-chain fusion product quality tracing method and system applied to a production line. The method comprises the following steps: firstly, collecting comprehensive data of each production node and attribute information containing a unique stage number; according to the total number of production stages, randomly selecting nodes with different numbers as initial clustering centers, and grouping all the nodes according to stage attributes by using a reverse clustering algorithm to form a node cluster; and constructing a basic traceability chain for each node cluster, and integrating data in corresponding stages to generate a distributed account book. And then screening core nodes from each basic chain to establish a cross-stage quality tracing chain, and realizing synchronous updating and inter-chain data verification of the core nodes on basic account books through an intelligent contract. And finally, a whole-process data tracing service is provided based on a quality tracing chain, and the information credibility is guaranteed by using the non-tampering characteristic of the block chain. According to the invention, product quality tracing with high reliability and high credibility can be realized.

Systems and methods for ingesting data from distributed ledger systems. To ingest data from the distributed ledger systems, all or a portion of the distributed ledger systems can be assigned a connector. One or more connectors can be initialized for a particular distributed ledger system. For example, the data intake and query system can include a first connector that is initialized for a first distributed ledger system and a second connector that is initialized for a second distributed ledger system. The connectors can be initiated with processing schema that can indicate how the connectors ingest, enrich, filter, etc. data from the distributed ledger systems. All or a portion of the connectors can be initiated with different processing schemas. The connectors can obtain data from nodes of the distributed ledger systems according to the processing schemas and route the data to the data intake and query system.

Disclosed are various embodiments for a distributed ledger enabled large language model security protocol. A large language model (LLM) can filter data generated by a distributed agent for a trace of a transaction with a third-party LLM. A trained LLM can analyze any found trace of a transaction and identify at least an anomaly related to the found trace. The trained LLM can block the transaction based on the anomaly.

Systems, methods, and computer-readable storage media to model objects. One method includes receiving, from an application of a user device, a content dataset of an object and capture event parameters of a capture event of the object, generating a three-dimensional (3D) object file based on the content dataset, wherein the 3D object file is a digital twin of the object, corresponding with one or more characteristics of the object, storing the 3D object file and the capture event parameters in a data repository, generating a token including a metadata object based on broadcasting the 3D object file, the content dataset, and the capture event parameters to a distributed ledger, wherein the metadata objects embeds, into the token, the metadata of the object, a pointer to the capture event parameters, and a pointer to the 3D object file, and storing the token at a digital wallet address of a wallet storage.