7100results about "Cryptography processing" patented technology

An emergency response and crisis management system comprises a computing system which performs steps comprising: aggregating real-time and historical data from multiple data sources; processing the data using artificial intelligence techniques; analyzing the processed data to detect and classify active crises to predict the likely development and trajectory of the ongoing crises, and assess potential short-term and long-term impacts across one or more sectors comprising one or more of public health, economy, infrastructure, environment, and social stability; generating multi-dimensional, interactive visualizations of the analysis results comprising one or more of geospatial maps, time series charts, and network diagrams; providing recommendations for crisis management and response tailored to different stakeholder roles; facilitating integration with external systems and applications through a comprehensive application programming interface (API) layer; and continuously adapting the system's models and algorithms based on one or more of real-world outcomes, expert input, and user feedback.

This invention presents a multisensor-connected, AI-enabled telehealth system for assisting healthcare providers with differential diagnosis and patients with early health concern detection. The system comprises a multi-sensor medical device with at least seven sensors, a secure cloud-based platform, and an interactive telehealth module. The device preprocesses and securely transmits patient information to the cloud platform, where an ensemble of deep learning models analyzes the data to generate ranked potential diagnoses with likelihood scores. The telehealth module facilitates communication between providers, patients, and the cloud platform, presenting visualizations and receiving feedback. The system continuously updates and fine-tunes its models using incremental learning algorithms, adapting to new data while retaining previous knowledge. It also generates alerts for providers and patients when deviations from normal physiological patterns are detected, accompanied by explainable AI visualizations.

The present disclosure relates to systems and methods for facilitating interoperability between blockchain networks to facilitate bridging of non-fungible tokens (NFTs) across chains. In embodiments, a method includes receiving a bridging request at a first bridge smart contract to transfer a source NFT from a first blockchain to a second blockchain. Upon verification, the first bridge smart contract locks the source NFT. An oracle server determines whether a clone NFT associated with the source NFT exists on the second blockchain. If so, the oracle instructs a second bridge smart contract to unlock the clone NFT. If no clone NFT exists, the oracle instructs minting of the clone NFT and assigning ownership of the clone NFT to the user's account on the second blockchain. The clone NFT remains controllable by the user while the source NFT stays locked on the first blockchain, maintaining a one-to-one relationship between the tokens across chains.

Methods and systems are described for facilitating lending of NFTs through an NFT marketplace system. In some embodiments a token marketplace system receives a request from a lender to create an NFT loan listing, verifies the lender's ownership of the token, and creates the listing. When a potential borrower requests to borrow the NFT, the system initiates a series of verification steps. These include requesting permission for a retrieval smart contract to act on behalf of the borrower's account and confirming that these permissions have been granted by the lendee. Upon successful verification, the system initiates a blockchain transaction to transfer the NFT to the borrower's account. The foregoing allows NFT owners to lend their NFTs to lendees in a trustless ecosystem.

An example operation may include one or more of storing transaction content from transactions executed via one or more fiat payment accounts and one or more crypto accounts of a digital wallet of a user, and determining, via execution of a machine learning model on the stored transaction content, a recurring expense value of the user and a next point in time in which the recurring expense value, dividing the recurring expense value into a plurality of sub-values; generating a plurality of transactions which transfer the plurality of sub-values from a fiat payment account to a crypto account from among the one or more crypto accounts and store the plurality of transactions within a queue, initiating a plurality of time-to-live jobs for the plurality of transactions, respectively, wherein the plurality of time-to-live jobs comprise a plurality of different respective expiration times that are staggered such that the plurality of time-to live jobs expire in incremental intervals from a current time to the next point in time in which the recurring expense value is due and executing the plurality of transactions at the plurality of different expiration times to incrementally transfer the plurality of sub-values from the fiat account to a crypt account via an application programming interface (API).

A system for serving personalized advertisements based on biometric and identifying data captured by sensors. The system employs pre-processing, feature extraction, and recognition modules to identify individuals. A context-aware processing module adapts recognition strategies based on environmental data and analyzes personal information to confirm the identity of the targeted individual and send targeted advertisements. The system includes display and speaker modules for visual and audio advertisements, a predictive interaction modeling module for generating personalized advertisements, and a cross-platform behavior analysis module for analyzing user behavior across offline and online platforms.

An example operation may include one or more of receiving content from a conversation between a user on a user device and a second user on a second user device that is connected to the user device via a network, identifying a topic of the conversation based on execution of a generative artificial intelligence (GenAI) model on the received content from the conversation, identifying a call list that is previously stored in memory that is associated with the topic of the conversation based on keywords included in the identified topic of the conversation, and adding an identifier of the user to the call list stored in memory.

An example operation may include one or more of storing transaction content from transactions executed via one or more fiat payment accounts and one or more crypto accounts of a digital wallet of a user, and determining, via execution of a machine learning model on the stored transaction content, a recurring expense value of the user and a next point in time in which the recurring expense value, dividing the recurring expense value into a plurality of sub-values; generating a plurality of transactions which transfer the plurality of sub-values from a fiat payment account to a crypto account from among the one or more crypto accounts and store the plurality of transactions within a queue, initiating a plurality of time-to-live jobs for the plurality of transactions, respectively, wherein the plurality of time-to-live jobs comprise a plurality of different respective expiration times that are staggered such that the plurality of time-to live jobs expire in incremental intervals from a current time to the next point in time in which the recurring expense value is due and executing the plurality of transactions at the plurality of different expiration times to incrementally transfer the plurality of sub-values from the fiat account to a crypt account via an application programming interface (API).

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 present invention provides a vertiport system that can be implemented at a VTOL hotel for managing unmanned vehicles in delivering goods or passengers from a source location to a destination location smartly. The system includes smart aiml vertiport and vtol hotel, smart kitchen and casino autonomous intelligent infrastructure.

The present invention provides a large language model-based system and method for data processing in application developed by codeless platform. The invention includes identification of intent of a user to process procurement, supply chain, application integration, application restructuring or development scenarios.

The present invention generally relates to computer systems, methods and program products that allow a digital asset exchange to provide an option to customers to lend all or a portion of the digital assets associated with at least a first blockchain and held by the exchange on behalf of the customer in exchange for payments such as interest.

A system and method for multi-scale temporal attention processing in multimodal technology deep learning systems. This system processes time-series, textual, sentiment, and structured tabular data across three hierarchically-organized temporal streams—quarterly, weekly, and intraday levels—with bidirectional cross-temporal information flow. Scale-specific attention mechanisms are optimized for respective temporal granularities, while an adaptive controller dynamically weights each temporal level based on real-time market volatility indicators. A multi-scale fusion processor integrates attention-weighted representations to generate temporally unified representations preserving both short-term market dynamics and long-term trends. This approach enables superior forecasting and risk assessment by leveraging temporal correlations across multiple time scales while automatically adapting to changing market conditions. The system facilitates interpretable AI analysis through attention visualization and enables synthetic scenario generation for model testing.

The invention is an AI-driven blockchain platform for automated trade management, featuring smart contract customization, cross-chain interoperability, and quantum-resistant security. It tokenizes legal rights, obligations, and asset ownership as NFTs on the blockchain for transparency. The platform adapts contracts in real-time based on market data, compliance, and IoT-monitored trade conditions. It includes automated cryptocurrency payments with privacy controls, a decentralized dispute resolution system, and modules for modular automation and risk management. The platform supports dynamic compliance adjustments and ethical trade metrics, enhancing international trade operations through AI-driven matchmaking and behavioral analytics for partner vetting. By integrating advanced cryptographic techniques and IoT data, the platform ensures secure, efficient, and adaptable trade processes across multiple blockchain networks, optimizing workflows and safeguarding transactions against future technological threats.

Disclosed are embodiments for fractionalized NFTs by displaying a non-fungible token (NFT); determining ownership of the NFT by a first user; identifying NFT splitting options based on one or more rules for the NFT; displaying NFT splitting options to the first user; receiving input from the first user to perform a particular splitting operation on the NFT; and executing a first smart contract, the execution of the first smart contract causing operations including: applying the one or more rules to the NFT to generate at least a first fractionalized NFT and a second fractionalized NFT; initiating recordation onto a blockchain of a removal of ownership by the first user of the NFT; and initiating recordation onto the blockchain of the ownership by the first user of the first fractionalized NFT and the second fractionalized NFT.

An Al -based energy edge platform is provided herein with a wide range of features, components and capabilities for management and improvement of legacy infrastructure, coordination, and orchestration with distributed systems to support important use cases for a range of enterprises. An Al -based energy edge platform may include a graph neural network including a set of nodes respectively representing at least one distributed energy resource (DER) and a set of edges respectively interconnecting the set of nodes, wherein each edge represents at least one energy - related feature among at least two nodes of the set of nodes. The platform may incorporate emerging technologies to enable ecosystem and individual energy edge node efficiencies, agility, engagement, and profitability. Embodiments may forecast, plan for, and manage the demand and utilization of energy in greater distributed environments. Embodiments may employ intelligent provisioning, data aggregation, and analytics to leverage energy market connection, communication, and transaction enablement platforms.

Systems and methods for decentralized data management across interoperable distributed platforms are disclosed. A computing system receives input data associated with a unique decentralized identifier (DID) representing an entity or event. The computing system segments the input data into encrypted data segments, each cryptographically linked to the DID, and distributes these encrypted segments across decentralized storage nodes according to a redundancy scheme. A cryptographic lineage record, including segment identifiers, timestamps, and hashes linked to the DID, is stored in a decentralized ledger. In response to authenticated access requests, the computing system reconstructs the input data by retrieving, decrypting, and cryptographically verifying the distributed data segments against the lineage record. Authorized entities access the reconstructed data through interfaces enforcing cryptographically secured access permissions defined within the decentralized ledger, providing enhanced security, provenance verification, and data resilience.

A system and methods for processing diverse financial data types using a jointly trained Vector-quantized Variational Autoencoder (VQ-VAE) and neural upsampler. This system efficiently handles time-series, textual, sentiment, and structured tabular data through specialized encoding modules. A novel fusion module integrates these encodings, capturing cross-modal relationships via attention mechanisms and gated fusion units. The fused representation is compressed into a discrete latent space by the VQ-VAE encoder, then reconstructed and enhanced by the VQ-VAE decoder and neural upsampler, respectively. Joint training optimizes all components simultaneously, using a comprehensive loss function that balances reconstruction quality across modalities with upsampling performance. This approach enables superior data compression, reconstruction, and analysis, leveraging inter-modal correlations to improve financial forecasting, risk assessment, and decision-making. The system's ability to explore the latent space facilitates generation of new, synthetic financial scenarios for robust model testing and strategy development.

Systems, methods, and computer-readable storage media to protect non-fungible tokens (NFTs) using a protection architecture. One method includes receiving an NFT, authenticating the NFT including authenticating or verifying the NFT using a key and authenticating the link of the NFT, and protecting the NFT including generating a public-private key pair, encapsulating the NFT within a control structure, updating an NFT account in an overlay ledger, generating and storing a cold storage object in a cold storage ledger, and broadcasting the NFT to a blockchain storage.

A system may include an Al convergence system of systems for a value chain network environment.

A system may include a robotic control circuit configured to control one or more robotic functions of a robot. A system may include a plurality of sensors configured to collect data. A system may include a governance analysis circuit configured to analyze the data and select one or more governance frameworks based on the analyzed data. A system may include a governance model circuit configured to generate a model that applies the one or more governance frameworks to determine one or more governance actions, wherein the robotic control circuit is configured to control the one or more robotic functions in accordance with the one or more governance actions, wherein the robotic control circuit, the governance analysis circuit, and the governance model circuit are integrated on a single substrate.

A system and methods for implementing adversarial-robust compression and reconstruction using a vector quantized variational autoencoder (VQ-VAE) with secure latent space management. The system provides comprehensive protection against adversarial attacks through multi-channel threat detection, adaptive defensive parameters, and coordinated response mechanisms. Input data is continuously monitored for potential threats, and defensive parameters are dynamically adjusted based on detected threat levels. The system implements bounded constraints and hierarchical projections to maintain latent space security while preserving compression efficiency. Multi-stage reconstruction with progressive validation ensures reliable data recovery even under adversarial conditions. The system coordinates defensive responses across all compression and reconstruction processes, implementing various recovery mechanisms when security violations are detected. This approach enables robust compression and reconstruction of time-series data while maintaining protection against various forms of adversarial manipulation.

The present invention generally relates to the use of stable value digital assets and / or fiat-backed digital assets as cryptocurrencies that can be linked to other digital assets using blockchain technology and / or through a peer-to-peer network. In embodiments, the present invention relates to specific applications of fiat-backed digital assets and / or stable value digital asset tokens tied to a peer-to-peer network, such as a blockchain network.

Described is a system for a decentralized protocol for token-based resource allocation by receiving a real estate possession record for a real estate from a real estate possessor, identifying a value of the real estate, transmitting generated digital tokens to a digital token storage associated with the real estate possessor, and recording a lien on the real estate possession record. The system initiates a first digital token relocation for a real estate recipient, and periodically, during a real estate utilization period for a real estate user: receives an indication of a second digital token relocation from the real estate user, transmits the first portion of the second digital token relocation to the possessor, transmits a second portion to the real estate recipient, and records a record of the first and second portions being transmitted onto the distributed ledger of the blockchain.

The embodiments disclose a file management and database system including a database system server configured to track user asset transactions and asset-related activities, at least one digital electronic device coupled to the database system server configured to allow the user to access the asset transactions and asset-related activities, a plurality of distributed databases coupled to the database system server configured to collectively manage and interlink data of plural operational components, a file management system coupled to the database system server configured to maintain and identify the plural operational components data, at least one processor coupled to the database system server configured to identify and match the plural operational components in the file management system with the plurality of distributed databases and data of the plural operational components, at least one communication device wirelessly coupled to the database system server and a digital device application wirelessly coupled to the at least one communication device.

A subscriber establishes or acquires an NFT token concerning a specific sports player. The subscriber can be a player, a coach, a fan, a sports writer, advertiser, or the like. The player history is updated on the NET token by different data sources. An NFT engine mints NFT tokens and processes and secures transactions. The NFT token can be accessed by a third party to review and use embedded data for player scouting, advertising, promotion and other purposes.

AI data and datasets that are represented as NFTs and carry all applicable data for a dataset's provenance, authenticity, and ownership. NFTs are used to validate datasets useful in AI training and can also be used to identify datasets that include faulty, biased, or otherwise erroneous data to improve predictive usefulness and reliability in decision making from the AI models.

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.

Disclosed herein is a method for facilitating tailoring experiences of users, in accordance with some embodiments. Accordingly, the method includes receiving, using a communication device, a data from a device. Further, the method includes analyzing, using a processing device, the data. Further, the method includes determining, using the processing device, a context associated with a user based on the analyzing of the data. Further, the method includes adjusting, using the processing device, at least one of a plurality of reality layers of an artificial environment based on the context. Further, the method includes provisioning, using the processing device, a content corresponding to at least one of the plurality of reality layers of the artificial environment based on the adjusting. Further, the method includes storing, using a storage device, the data and the context.