4850 results about "Third party" patented technology

A system and method of calculating an estimated time of arrival for a traveler is provided, along with a notification of this estimated time that is sent to a third party. The traveler is equipped with a navigation unit having a global positioning sensor and a wireless communications device. The navigation unit communicates with a service center equipped with a server capable of generating a preferred navigational route for the traveler. The service center also includes a traffic database for maintaining current traffic information. Once the traveler has selected a predetermined time and frequency of notifications based upon a selected criterion, the navigation unit transmits the traveler's position and velocity to the service center. The service center then calculates the estimated time of arrival based upon the traveler's position, velocity, distance to be traveled and traffic and weather conditions. Once this time is calculated, the service center sends a notification to the third party.

The present invention discloses a third party registration processing method based on the IMS network, which comprises that a UE completes the registration on a S-CSCF entity; the S-CSCF entity starts a waiting timer; the UE and a P-CSCF entity initiate and complete a registration status subscribing respectively to the S-CSCF entity; the S-CSCF entity initiate a third party registration to an AS when the waiting time of the waiting timer is enough. Through the present invention, the S-CSCF entity performs a waiting after the UE is successfully registered, to make the subscribing success of the registration status of the P-CSCF and the UE take precedence over the third party registration and avoid the situation of conflicting data of the UE, the P-CSCF, the S-CSCF and an HSS, to make the UE, the P-CSCF and the S-CSCF effectively process the abnormal circumstance occurred when the third party registration fails.

The present invention introduces a universal AI-powered pet management platform that establishes an entirely new category of technology, transcending conventional pet training systems. This comprehensive system integrates a modular wearable pet device with interchangeable sensors, sophisticated AI processing capabilities, and diverse output modules to create a unified ecosystem for holistic pet care. Unlike traditional training devices focused solely on behavior modification, this platform simultaneously manages multiple domains including real-time health monitoring, environmental safety assessment, emotional well-being analysis, autonomous training, emergency response, and seamless integration with external systems. The platform's universal architecture enables dynamic adaptation across diverse applications from companion animals to service animals, wildlife monitoring, and specialized deployments. By leveraging advanced artificial intelligence models, multimodal communication pathways, and a universal API for third-party integration, the system creates an interconnected technological framework that fundamentally transforms the relationship between pets, technology, and human interaction, rendering isolated pet devices obsolete.

Systems, methods, and / or computer readable storage media for protecting data. A system can include one or more processing circuits configured to receive or identify at least one token including cyber resilience data of at least one entity and corresponding with at least one posture or compliance parameter of at least one third party The one or more processing circuits can perform a zero-knowledge proof (ZKP) on the cyber resilience data, determine at least one posture or compliance parameter of the at least one third party is satisfied based on the cyber resilience data, and / or generate at least one ZKP including at least one cryptographic commitment obfuscating the cyber resilience data. The one or more processing circuits can provide, to at least one third party computing system of the at least one third party, the at least one ZKP or indication of performance of the at least one ZKP.

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.

Various systems and methods are described for obtaining compensation for tasks performed by a humanoid robot, where the humanoid robot is associated with a first party. The method includes a first party providing a humanoid robot for use in an operating location. The humanoid robot engaged in performing a plurality of tasks at the operating location. A third party compensates the first party with a specified amount of currency for a pre-determined time interval during which said humanoid robot has engaged in performing the plurality of tasks at the operating location.

The invention relates to a federated learning system based on multi-key homomorphic encryption and adaptive differential privacy, and belongs to the technical field of privacy computing. According to the system, on the premise that no trusted third party exists, a multi-client collaborative key generation and threshold decryption mechanism is achieved, it is ensured that model parameters are always in an encrypted state in the aggregation process, and leakage of a single node is prevented. By introducing a parameter sensitivity analysis and selective encryption strategy, the system only encrypts high-risk parameters, and the encryption burden is effectively reduced. Meanwhile, in combination with an adaptive privacy budget allocation mechanism, the system dynamically adjusts noise intensity according to a model training state, and model performance and convergence speed are maintained while privacy protection capability is improved. According to the method, high robustness and collusion resistance are realized, stable operation under the condition that part of clients are offline is supported, and the method is suitable for application scenes such as medical treatment and finance with high data sensitivity and strict performance requirements.

The present disclosure describes systems and methods for detecting and preventing data misconfigurations within a security-focused data fabric platform. The system integrates an advanced script migration engine designed to streamline the translation of security rules and scripts across different scripting languages while ensuring alignment with the fabric's unified schema. The method involves receiving inputs from data sources, mapping these inputs to entities of a target schema, monitoring real-time data changes, and simulating impacts on operational dependencies to detect misconfigurations proactively. Leveraging AI-driven mechanisms, including Large Language Models (LLMs), the system dynamically identifies breaking changes in third-party data streams, issues alerts, and provides suggested fixes. The script migration engine further enhances the platform's functionality by automating cross-platform script translations and enabling faster onboarding of security tools. Together, these innovations ensure scalable, accurate, and resilient integration and management of security data across heterogeneous sources, strengthening operational integrity and minimizing security risks.

The disclosure belongs to the technical field of network security, and provides a method for constructing a feature knowledge base of mapping behavior based on deep learning, which includes: data acquisition and preprocessing: extracting five-tuple information and behavior features from network traffic. The disclosure automatically extracts the spatio-temporal features through the deep learning model, and enhances the sensitivity to abnormal behaviors by combining the attention mechanism, thus significantly improving the detection accuracy. The explanatory AI technology is used to automatically generate detection rules, the maintenance cost of manual rules is greatly reduced and the efficiency of rule generation is significantly improved. The feature knowledge base supports dynamic updating, may integrate third-party threat information in real time, and ensures the continuous defense ability against new attacks and variant detection means.

Systems, methods, and devices to detect unauthorized third-party connections within a network infrastructure, such as by analyzing network traffic data using fuzzy matching and machine learning techniques. One aspect includes receiving network traffic data comprising records of communication events involving network identifiers, determining communication relationships between network entities identified by the network identifiers, accessing entity identifiers associated with known third-party systems, and determining associations between the network identifiers and the entity identifiers using a fuzzy matching process. Other aspects include identifying communication relationships involving the third-party systems based on the associations and detecting unregistered or unknown third-party connections within the network infrastructure. Further aspects include normalizing identifiers, computing string similarity metrics, assigning confidence scores, incorporating external data sources, building network association patterns, comparing current patterns to baseline patterns to detect anomalies, and updating security policies or firewall rules in response to detected anomalies. Additional aspects are provided.

Systems, methods, and computer-readable storage media for providing a composable cyber resilience object. A method can include identifying, by one or more processing circuits, a posture state of at least one entity, generating or selecting a first plurality of code blocks corresponding with a parameters of at least one third-party, and determining the entity qualifies for protection based on the posture state and the rules or conditions. The method can include generating or selecting a second plurality of code blocks including functions to provide the protection based on the rules or conditions and generating the composable cyber resilience object by integrating a portion of the first plurality of code blocks and the second plurality of code blocks into at least one data structure. The method can include linking the composable cyber resilience object and a computing or networking infrastructure of the entity using a communication interface or structure.

The invention discloses a verifiable medical data query method based on a DAG block chain architecture, and belongs to the technical field of block chains and medical information management. According to the method, medical events such as diagnosis and treatment records and image reports are modeled into DAG nodes, an on-chain topology with time sequence and causal association is constructed by encrypting a hash pointer, dynamic indexing and multi-keyword verifiable query are achieved in combination with an off-chain authentication data structure, a verification object containing a matching node set and a verification path is received, and the verification object is subjected to dynamic indexing and multi-keyword verifiable query. The authenticity, integrity and timeliness verification of the result is independently completed based on the authentication root stored on the chain without depending on a third party. According to the method, through an on-chain and off-chain collaborative storage and incremental authentication updating mechanism, on the premise of ensuring privacy and tamper-proofing of medical data, query efficiency, verification performance and expandability under high concurrency are remarkably improved, communication and resource expenses are lower, and the method is suitable for large-scale popularization and application. The method is suitable for application scenes such as cross-institution medical data sharing, remote diagnosis and treatment and compliance auditing.

A system and method for real-time, identity-free personalization using deformable emotional trait vectors to dynamically adapt digital and voice-based experiences. Each user session is modeled as a behavioral object known as a Vectra, composed of fluidic traits—such as mass, viscosity, temperature, volatility, and texture—that evolve continuously in response to live behavioral, contextual, environmental, and voice-derived signals. These Vectras traverse a dynamically warped emotional space, the Vectraverse, influenced by ambient conditions including time of day, noise level, inventory urgency, and engagement rhythm. Gravitational pull toward predefined emotional goal attractors modulates system behavior, while a goal mutation engine reclassifies session intent when confidence decays or friction spikes. Outputs include tone modulation, content pacing, offer framing, and gamified reward logic—all executed without storing identity, login credentials, or historical profiles. The system supports modular deployment across voice, screen, signage, mobile, and in-room environments, and integrates with large language models, AI agents, and third-party personalization stacks via privacy-safe APIs and federated learning. Designed for zero-ID personalization, the platform enables emotionally intelligent, context-aware engagement across any surface or session.

The invention discloses an order-driven cross-factory collaborative production system, and relates to the technical field of intelligent manufacturing and supply chain collaboration, and the system obtains the productivity data, logistics cost and tax policies of a plurality of production bases such as Ningbo, Thailand and America in real time, and carries out the intelligent splitting and distribution of orders through a multi-base productivity game algorithm. And dynamic optimal matching of the order and the productivity is realized. Meanwhile, the system integrates WMS inventory data and third-party logistics real-time quotation, a transportation scheme with the lowest total cost is generated by adopting a genetic algorithm, and cross-border logistics and tax expenditure are remarkably reduced. The system overcomes the problems of information isolated island, response lag, extensive cost control and the like in traditional multi-factory production, realizes global productivity collaborative optimization and supply chain integrated intelligent decision, and improves the enterprise order performance efficiency and the overall resource utilization rate.

Various systems, computer-readable media, and computer-implemented methods of providing improved data privacy, anonymity and security by enabling subjects to which data pertains to remain “dynamically anonymous,” i.e., anonymous for as long as is desired—and to the extent that is desired—are disclosed herein. Embodiments include systems that create, access, use, store and / or erase data with increased privacy, anonymity, and security—thereby facilitating the availability of more qualified and accurate information. When personal data is authorized by data subjects to be shared with third parties, embodiments described herein may facilitate the sharing of information in a dynamically-controlled manner that also enables the delivery of temporally-, geographically-, and / or purpose-limited information to the receiving party. In one example, the disclosed techniques may be used to functionally separate geospatial information, such that it remains “dynamically anonymous,” i.e., anonymous for as long as is desired—and to the extent or degree that is desired.

The invention relates to the field of enterprise industry chain evaluation, and discloses an artificial intelligence-based enterprise industry chain multi-dimensional evaluation system and method, and the system comprises a data collection module which is used for obtaining industry chain data from a structured database, an unstructured text and a third-party platform; the data fusion module is used for constructing a dynamically updated industrial chain knowledge graph through a natural language processing technology; the multi-dimensional evaluation module comprises a financial health evaluation sub-module, a supply chain toughness evaluation sub-module, an innovation power evaluation sub-module and a carbon emission evaluation sub-module, and each sub-module generates quantitative scores by adopting an LSTM neural network, a PageRank algorithm and a space-time diagram convolutional network model and weights the quantitative scores to obtain comprehensive scores; the risk early warning module is used for simulating a triple conduction effect of an external event on an industrial chain based on a graph neural network and generating a risk index and a coping strategy; and the visual interaction interface dynamically displays the evaluation result. According to the method, the problems of data splitting and poor dynamic adaptability in a traditional evaluation method are solved, and accurate evaluation of the industrial chain is realized.

A method, apparatus, and system of activating and using a contactless card via unique activation codes are disclosed. A system includes a memory and a processor configured to: receive an account number for a contactless card from a third party computing system; generate a card activation code for the contactless card, the card activation code being unique to the contactless card; generate a customer-specific uniform resource locator (URL) by appending the card activation code to a general URL, the general URL being associated with an entity of the system; transmit the customer-specific URL to the third party computing system with instructions to write the customer-specific URL into a wireless chip of the contactless card; associate the card activation code with the account number and information regarding a customer associated with the contactless card; and store the card activation code within the memory to be referenced during activation.

The invention relates to the technical field of information authentication management, and discloses an information processing method and system based on authentication and admission assessment, and the method comprises the steps: achieving the automatic extraction of key index data in enterprise registration information and data information based on an OCR technology, and carrying out the consistency verification of the relation between the two, and obtaining a verification result; the authenticity and integrity of submitted information are ensured; then, the system performs difference field marking in combination with third-party registration information and index data, and accurately identifies data inconsistent items; performing quantitative risk scoring based on the index data, and dynamically determining an auditing queue to which the enterprise belongs; finally, the risk score and the difference field marking result are integrated to judge whether to trigger a manual auditing process or not, approval, filing and storage are automatically completed for enterprises needing to be audited, closed-loop automatic management from information collection and verification to risk assessment and approval is achieved, and the authentication efficiency and risk control accuracy are remarkably improved.

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.

The invention discloses an industrial communication protocol conversion system and conversion method. The method comprises the following steps: acquiring data of an industrial communication source protocol; protocol conversion: converting the source protocol data into target protocol data according to a sequence of protocol analysis, standardized modeling and protocol repackaging; according to protocol analysis, original data transmitted from different hardware interfaces are analyzed according to corresponding industrial protocols; the standardized modeling parses the data into a data model in a unified format; protocol repackaging: recoding the data model into a data frame conforming to a communication specification according to a target protocol rule; and data output: pushing the obtained target protocol data to a third-party server through an MQTT protocol or directly storing the target protocol data in a database for a third-party system to access. Through three core technologies of protocol analysis, unified data modeling and protocol packaging, lossless conversion among different industrial protocols is realized, and an efficient and reliable data communication infrastructure is provided for an industrial automation system.

The invention discloses an advertisement putting strategy optimization method and system based on preference data collaboration, and relates to the technical field of advertisement putting, and the method comprises the steps: collecting the internal user data of a local advertisement putting platform, obtaining the external user data of a third-party platform through a safety data interface, carrying out the integration and preprocessing of the data, and obtaining an advertisement putting strategy; extracting explicit preference data and implicit preference data; a user-advertisement scoring matrix is constructed based on the preference data, and user preference vectors are generated after decomposition; acquiring copywriting text, image and category information of an advertisement to be put, constructing an advertisement feature expression model and generating an advertisement feature vector; calculating a matching degree score based on the user preference vector and the advertisement characteristic vector, and dynamically optimizing an advertisement putting strategy according to the score; according to the method, through comprehensive utilization of explicit and implicit preferences of the user, more accurate user interest modeling and advertisement matching are realized, and the advertisement putting effect and putting efficiency are effectively improved.

The invention discloses a multi-device high-resolution audio stream intelligent pushing method and device, equipment and a storage medium, which are applied to a multi-device audio system, and the method comprises the following steps: acquiring a current audio stream format and adjusting system working parameters; dynamically adjusting a multi-stage buffer area based on a tone quality priority strategy; operation parameters of multiple devices are synchronously monitored in real time, and data are sent in advance for the device with large delay based on the delay characteristic and the synchronization capability of each device in the system; and dynamically switching system service levels based on the quality of the current audio stream. A protection strategy can be flexibly adjusted according to different audio formats through a format perception pre-detection thread mechanism; the sound quality is kept to the greatest extent while the stability is ensured by the multi-stage buffer region protection with the sound quality priority; a multi-device coordination and timing monitoring mechanism ensures perfect cooperation with a third-party device, and the stability challenge in high-resolution audio transmission is comprehensively solved.

The invention relates to a cargo transportation track real-time tracking method based on the Internet of Things, and the method comprises the steps: carrying out the node collection and multi-source fusion of sensor data (including GPS, RFID, timestamps and the like) of all links of logistics, and employing data standardization and time sequence verification, thereby achieving the consistency processing of different devices and node data. The method is characterized in that standardized trajectory data and breakpoint detection data are stored in a distributed manner by using a block chain non-tampering and multi-party consensus mechanism, third-party multi-source data and a fuzzy reasoning model are fused, and confidence completion is performed on trajectory breakpoints. The system can output a complete and traceable trajectory path, anomaly recognition and responsibility attribution result, and provides a visual and third-party notarization interface. According to the method, the authenticity, the integrity, the space-time consistency and the responsibility traceability of the logistics track data flow are remarkably improved, and the logistics full-link monitoring and risk management capabilities are enhanced.

The invention relates to a carbon emission checking system and method based on a block chain, and the system comprises a basic resource layer which collects enterprise energy consumption data in real time, employs cloud computing resources to provide data storage and computing capability, and employs a Hash algorithm to process the enterprise energy consumption data, and obtains a data abstract; the block chain network layer carries out distributed storage through an alliance chain architecture, carries out consensus evidence storage on the data abstract by adopting a PBFT consensus algorithm, and generates an encrypted data abstract; the intelligent contract layer receives the encrypted data abstract transmitted by the block chain network layer, and executes verification, calculation and supervision rules; and the application service layer calls the processing result of the intelligent contract layer, and respectively provides an enterprise carbon checking terminal service interface, an institution carbon checking terminal service interface and a competent department carbon supervision terminal service interface for the enterprise, a third-party checking institution and the competent department to check the carbon emission. According to the invention, high-efficiency check, high-credibility verification and whole-process traceable supervision of the carbon emission data are realized.

The invention discloses a multi-mode driven cross-industry digital twinning universal platform architecture and an implementation method, and relates to the technical field of digital twinning and artificial intelligence. The method comprises the following steps: establishing a multi-modal driven cross-industry digital twinning universal platform, deploying a multi-source heterogeneous data acquisition component in a data access layer to access text, image and time series data, and converting unstructured data into a unified feature space by adopting a Transform-GNN cross-modal encoder in a multi-modal fusion layer; in the large model scheduling layer, feature vectors are analyzed through a multi-modal large model center based on an industry knowledge graph, an algorithm is dynamically matched, and an initial decision strategy is generated; the method comprises the following steps of: establishing a parameterized template library, and supporting security cooperative training of a third-party algorithm scheduling engine on a third-party algorithm, and deploying a lightweight digital twin engine in a twin engine layer: establishing the parameterized template library: pre-defining three templates of geographic space, equipment assets and business processes; deploying the twin model to an edge node by adopting a knowledge distillation method; in the interactive application layer, loading the BIM / GIS model in a lightweight manner through a low-code tool, and completing scene construction through a dragging component; and rendering a twin state in real time through a three-dimensional cockpit, analyzing a natural language instruction and performing corresponding operation.

The present invention provides a system and method for generating proposals for infrastructure modalities, such as electrical substations, using advanced artificial intelligence. It includes an input interface for data collection, a lightweight generative or rendering pipeline for creating preliminary 2D designs, and a generative model selected from diffusion, transformer-based, GAN or other architectures for refining these into detailed 3D models and generating preliminary designs. The system evaluates designs against predefined criteria to ensure compliance and feasibility. Supported by a cloud-based infrastructure for robust data processing and integration with third-party services, this system enhances the efficiency, accuracy, and compliance of modality planning and proposal generation.

The invention discloses a gallery integrated internal production software system based on a modular low-coupling architecture, which is characterized in that a system function is divided into a plurality of modularized modules and the modularized modules are packaged and deployed by a uniform interface, so that the coupling degree between the modules is remarkably reduced, and the problem of global code change caused by module dependence in a traditional single architecture is avoided; direct calling is replaced by an event-driven mechanism, asynchronous communication and decoupling cooperation between modules are realized, and the stability and maintainability of the system during function change or addition are improved; the configuration driving mechanism enables the business process to be dynamically adjusted, different business requirements can be met without modifying a program source code, the plug-in management mechanism provides a standardized third-party extension access channel and supports function loading according to requirements, and the limitation that a traditional system is fixed in function and closed in development is broken through; according to the method, the software can run consistently in Windows, Linux, MacOS and other environments, and the key problems that in the prior art, the coupling degree is high, the expansibility is poor, configuration is not flexible, and the platform adaptation capacity is weak can be effectively solved.

The invention provides a brain tumor survival prediction method and system based on a multi-modal medical knowledge graph, and belongs to the technical field of brain tumor survival prediction. The multi-modal medical knowledge graph based on third-party knowledge base fusion is constructed; performing feature extraction on the brain tumor multi-modal data; searching an entity corresponding to the brain tumor related data in the multi-modal medical knowledge graph, and converting the entity into feature representation by using an entity representation learning method; the learned feature representation related to the brain tumor type complements the missing data mode, and finally the complemented features are input into a pre-trained survival prediction model to achieve brain tumor survival prediction. According to the multi-modal medical knowledge graph, comprehensive medical knowledge support meeting clinical requirements is provided; the multi-modal mapping knowledge domain is used for missing modal completion of brain tumor survival prediction, and a completion feature is generated by querying an associated entity through the mapping knowledge domain, so that the problem of weak modal missing processing capability in the prior art is solved.

A method of provisioning a credential for a transaction between a payment device of a user and a transaction processing device is described. The method is implemented a third-party server remote from the payment device and the transaction processing device. The method comprises assigning the credential to the transaction and the user and provisioning the credential into the payment device for subsequent retrieval by the payment device. Assigning the credential to the transaction comprises: determining unique identifying information of the user; allocating a first user-identifying portion of the credential to correspond to the unique identifying information; determining a plurality of properties intrinsic to the transaction and encoding the plurality of properties into transaction-identifying information; and allocating a second transaction-identifying portion of the credential to correspond to the transaction-identifying information. The credential is associated with encrypted authentication data that is generated by the payment device during the transaction, and used for subsequent authentication of the transaction by the remote third-party server.

The package holder incorporates a front cover having several rungs assembled in a cascading, accordion style that when the front cover is in its expanded position to cover the interior cavity of the package holder, the several rungs are fully expanded and when the front cover is in its collapsed position, the several rungs fit together. The package holder includes a frame structure having one or more back surfaces and a bottom surface. The back surface is mountable using fasteners to a physical surface of a property. The package holder incorporates electronic and computer based locking mechanisms as well as non-electronic locking mechanisms. The package holder incorporates tracking sensing systems to track a package from a third-party delivery service that can automatically access the interior cavity of the package holder. A user can access the package from an interior of a property through an opening of the package holder.