3000 results about "Data exchange" patented technology

A federated distributed computational system enables secure oncological therapy optimization through robotic integration. The system establishes a distributed graph architecture with secure communication channels connecting computational nodes, implementing encryption protocols for cross-institutional data exchange. Each node contains processing capabilities for fluorescence-guided imaging, uncertainty quantification, and expert knowledge integration while maintaining hierarchical knowledge graphs of oncological biomarkers, interventions, and outcomes. The system coordinates domain-specific knowledge through token-space communication and implements an advanced robotic integration system for surgical interventions using spatiotemporal tumor mapping, multi-modal fluorescence imaging, surgical robot coordination, and space-time stabilized mesh management. Key capabilities include wavelength-specific multi-modal fluorescence detection, combined epistemic and aleatoric uncertainty estimation, tensor-based data integration with adaptive dimensionality control, and light cone search for adaptive treatment optimization—all while maintaining strict privacy controls.

A federated distributed computational system enables secure, privacy-preserving biological data analysis and engineering through interconnected nodes coordinated in a distributed graph architecture. A federation manager allocates resources, manages data flow and lineage, establishes privacy boundaries, and maintains cross-institutional knowledge relationships. Each node contains a processing unit for biological data analysis, privacy preservation protocols for secure multi-party computation, a knowledge graph structure with supporting data stores, and encrypted network connections. The federation manager enforces all computation and data exchange through secure channels while maintaining privacy, security, and contractual boundaries. This architecture enables research institutions to collaborate on complex biological analyses without compromising sensitive data, facilitating breakthrough discoveries through shared computational resources while maintaining strict data privacy and security controls.

The disclosed embodiments include computer-implemented systems and processes that generate and provision, in real time, directed digital content based on decomposed structured messaging data. For example, an apparatus may receive a plurality of messages that characterize first data exchanges initiated between a first counterparty and second counterparties during a first temporal interval. Each of the messages includes elements of message data associated with a real-time payment requested from the first counterparty by a corresponding one of the second counterparties. Based on the elements of message data, that apparatus may predict an occurrence of a second exchange of data that involves the first counterparty during a second temporal interval, and may transmit notification data that includes product data characterizing an available product associated with the predicted occurrence of the second data exchange to a device operable by the first counterparty for presentation within a digital interface.

The invention relates to the technical field of data exchange, in particular to a data exchange system of a nested tag structure, which comprises a data carrier adaptation module, a structure analysis module, a field mapping module, a logic driving module and a script generation module. According to the method, carrier identifiers are generated through comparison of MIME types, file header features are positioned through pattern matching, the recognition accuracy and adaptability are improved, a nesting relation is calculated through depth-first traversal of file paths, node sequences are generated through analysis in combination with a DOM tree, the label analysis efficiency is optimized, and a mapping table is generated through algorithm matching of field identifiers and database codes; the method comprises the following steps: dynamically constructing a field mapping relation, reducing manual configuration, constructing a decision matrix based on a mapping table, executing logical operation to generate a status bit and triggering a threshold write-in instruction, enhancing strategy dynamic adjustment capability, reducing semantic ambiguity through multi-algorithm collaboration and a dynamic decision mechanism, improving data exchange robustness, and supporting real-time state response. And the transmission timeliness of the industrial Internet of Things is ensured.

The invention discloses a data real-time analysis and decision-making system based on an edge intelligent Internet of Things, belongs to the technical field of Internet of Things, and aims to solve the technical problems of insufficient real-time performance, high delay, large bandwidth occupation and high dependence on a central server in data processing of Internet of Things equipment. Comprising an edge device layer, an edge computing node layer, a cloud edge collaboration module and a central server layer, each edge computing node is used for taking data after local analysis processing as input, performing prediction analysis through a local model, making a decision through a decision generation mechanism based on an analysis result, and performing cloud edge collaboration. Generating decision optimization through an adaptive decision optimization algorithm, and performing data exchange with the central server layer through a cloud edge collaboration module; and the central server layer is used for carrying out model updating based on the real situation and the analysis result corresponding to the analyzed and processed data uploaded by each edge computing node, and returning the updated model parameters to the edge computing node layer.

A federated distributed computational system enables secure oncological therapy optimization through multi-expert integration and advanced uncertainty quantification. The system implements a multi-expert integration framework that coordinates domain-specific knowledge through token-space communication for precision oncological treatment, while maintaining secure cross-institutional data exchange. The architecture coordinates multi-scale spatiotemporal synchronization across computational nodes, with each node containing local processing capabilities for fluorescence-guided imaging, uncertainty quantification, and expert knowledge integration. Through a distributed graph architecture, the system enables advanced fluorescence imaging with wavelength-specific targeting, multi-level uncertainty estimation combining epistemic and aleatoric approaches, and multi-scale tensor-based integration with adaptive dimensionality control. The system implements light cone search and planning for adaptive treatment strategy optimization, enabling medical institutions and research organizations to collaborate on complex oncological therapy projects while maintaining strict data privacy controls.

This disclosure relates to a lending system comprising a processor, a memory, and at least one network interface controller configured to enable data exchange with external systems. The memory includes lending management logic configured to execute a personal loan-lending system wherein one or more loans are generated by collecting and preprocessing borrower data from multiple sources, conducting risk assessment and scoring, generating one or more scores based on the conducted risk assessment, and approving loans based on the generated scores. The system leverages machine learning processes to refine scoring accuracy and dynamically adapt to borrower profiles and external conditions. The system may integrate with third-party data sources for enhanced verification and incorporate compliance logic to ensure adherence to regulatory standards. By employing automated, data-driven processes, the system improves efficiency, accuracy, and security in loan origination, servicing, and compliance while enabling dynamic risk management and tailored loan product offerings.

A federated distributed computational system enables secure biological data analysis and genomic medicine through hybrid simulation capabilities. The system implements a hybrid simulation orchestrator that coordinates classical numerical simulations with machine learning models for biological system analysis, while maintaining secure cross-institutional data exchange. The architecture coordinates multi-scale spatiotemporal synchronization across computational nodes, with each node containing local processing capabilities for biological data analysis and privacy preservation protocols. The system implements cellular machinery assembly analysis, real-time patient data integration, and multi-modal image integration with spatiotemporal health data annotation. Through a distributed graph architecture, the system enables cross-species genetic analysis, environmental response modeling, and multi-scale tensor-based data integration with adaptive dimensionality control. The system implements real-time therapeutic response prediction through multi-modal data analysis, enabling research institutions to collaborate on complex biological analyses while maintaining strict data privacy controls.

The invention provides an electronic information data association method and system based on the Internet of Things. The method comprises the steps that a parallel processing architecture is adopted to execute rapid protocol conversion on a high-priority data packet, data recombination is directly carried out through a pre-compiled conversion rule template, a complex format verification link is skipped, and the integrity and format correctness of the converted data packet are determined; response time and error rate statistical information in the data transmission process are obtained, protocol conversion rules and scheduling strategies are optimized through a feedback mechanism, and if the success rate of certain protocol conversion is lower than a standard value, corresponding mapping rules and verification algorithms are updated; and carrying out standardized packaging on all converted data by adopting a unified data exchange standard, adding an equipment identifier, a timestamp and a data type label, establishing a cross-protocol general data format, and carrying out final distribution after judging whether a data packet meets a standard format requirement.

The invention relates to a personalized healthcare management system and method. The system integrates advanced technologies, immersive technology, and a data exchange platform to provide dynamic, personalized health insights and proactive management in a secure, interactive environment. It employs machine learning techniques to examine health-related data, forecast health risks, and propose preventive actions. The system also provides customised content based on user's progress, comprehension, and evolving health conditions. It combines health data, monitoring devices, and continuous health monitoring, and uses environmental data to forecast and alert users of potential health risks. The system also employs secure data technology for data privacy and security, and a machine learning framework for developing and deploying predictive models.

An intelligent system for the joint detection of anomalies in distributed systems, comprising the following: an anomaly detection module deployed on distributed nodes, with each agent configured to monitor local system metrics, detect deviations from expected behavior, and identify potential anomalies using machine learning models; a collaborative learning machine that can be operated to facilitate peer-to-peer communication between the anomaly detection module, with the module working together to verify detected anomalies and correlate cross-node behaviors in real time; a centralized aggregation server configured to aggregate anomaly data from the distributed nodes, update a global anomaly detection model, and redistribute the updated model to each of the anomaly detection modules; a federated learning module configured to enable secure data exchange between distributed nodes without disclosing sensitive data, exchanging only updates to the machine learning model to protect privacy; a warning and mitigation module configured to send real-time alerts to system administrators or automated incident response systems when an anomaly is detected; categorizes alerts by severity and initiates automatic mitigation protocols to address critical threats; a self-learning and adaptation module capable of continuously updating local and global machine learning models, learning from past anomalies to detect emerging threats, and adjusting detection thresholds based on evolving threat landscapes; the global anomaly detection model refines local detection capabilities by incorporating insights from system-wide anomaly data across all nodes.

The invention discloses an urban safety risk assessment method and system based on big data, and relates to the technical field of big data, and the method comprises the steps: constructing a multi-source data collection network, and obtaining data from a government department database, Internet of Things equipment, a social media platform and a traffic monitoring system in real time; preprocessing the collected multi-source data, wherein the preprocessing comprises data cleaning, format standardization, unstructured data semantic analysis and sentiment analysis; a cross-department data security sharing mechanism is established, and the traceability and security of data exchange are ensured through a block chain technology; constructing a dynamic risk assessment model, analyzing multi-source data relevance based on a deep learning algorithm, and dynamically adjusting the weight of each risk factor; and generating a visual risk assessment report, and pushing the visual risk assessment report to related departments in real time through an early warning system. According to the invention, through multi-technology fusion and a dynamic optimization mechanism, the accuracy, real-time performance and cooperation efficiency of urban safety risk assessment are significantly improved.

The invention discloses a project-level visualization display method and system for highway multi-source data fusion, and the method comprises the following steps: 1, constructing a multi-source heterogeneous data exchange and integration frame, and carrying out the seamless connection and mapping of a BIM model, GIS space geographic information and an oblique photography three-dimensional point cloud model; 2, formulating a standardized interface specification, and performing specification processing on data from different sources through a data analysis and conversion engine; 3, dynamically and synchronously updating the multi-source engineering data and the project progress in real time; 4, gathering engineering data to construct a digital twinborn model of the expressway project to realize centralized management, multi-dimensional analysis and dynamic presentation in a visual scene; 5, carding and extracting management business logic to construct a flexibly expanded professional application module so as to realize intelligent analysis of the engineering project; and step 6, performing visual immersive display on the multi-source data fusion project by adopting visual man-machine interaction. According to the invention, visual comprehensive management and traceability of each element of the project are realized.

Embodiments of the present invention provide a computer-implemented method for Artificial Intelligence (AI) based provision of management consulting. The computer-implemented method includes dividing the provision of management consulting into a plurality of tasks, the plurality of tasks defined as a plurality of respective workflows. Furthermore, the computer-implemented method includes assigning a plurality of Artificial Intelligence (AI) agents to the plurality of tasks with each one of the plurality of tasks assigned at least one AI agent. The computer-implemented method further includes providing the plurality of AI agents with characteristic reference data obtained from a plurality of data sources. Furthermore, the computer-implemented method includes providing a plurality of interfaces to the plurality of AI agents for enabling exchanges of data amongst the plurality of AI agents. The computer-implemented method also includes generating a plurality of deliverables in a plurality of user-readable formats, the plurality of deliverables constituting management consulting.

The invention provides an Internet of Things data processing method and system based on a block chain, and relates to the technical field of block chains, and the method comprises the steps that an Internet of Things device carries out the digital signature of an authentication request through employing a pre-stored private key, and generates a signed authentication request; the smart contract in the block chain network receives the signed authentication request, and the smart contract generates an authentication token including an authentication result, a validity period and an authorization level based on the historical authentication record, the credit score, the current timestamp and the challenge value; the Internet of Things equipment receives the encrypted authentication token and the intelligent contract address; the Internet of Things equipment configures own access authority and function limitation according to the authentication result, the validity period and the authorization level; and the Internet of Things equipment takes the intelligent contract address as an identity credential within the period of validity, and is used for subsequent secure communication and data exchange with other Internet of Things equipment or application programs.

A system for real-time data aggregation and analysis within an Internet of Things (IoT) network, consisting of: a multitude of IoT sensor nodes configured to collect data from multiple sources, each sensor node comprising a data acquisition unit for capturing data in real time and a local processing unit for preprocessing the captured data by performing data filtering, normalization and compression prior to transmission; a centralized aggregation server communicating with the multitude of IoT sensor nodes, the aggregation server comprising: a data aggregation module configured to receive, integrate, and synchronize pre-processed data streams from the multitude of sensor nodes, thereby enabling consolidated data storage; a timestamped metadata indexing unit coupled with the data aggregation module and configured to add metadata to each data entry, including a unique identifier, a geographic location, and a timestamp; an analysis engine integrated into the aggregation server, which includes the following: a data processing unit configured to perform real-time analysis of the aggregated data by applying pattern recognition and anomaly detection techniques and to generate processed results based on predefined parameters; a predictive analytics module that is connected to the data processing unit and configured to perform predictive modeling tasks by extrapolating trends from historical and real-time data; a communication interface connected to the aggregation server, configured to enable bidirectional data exchange with external monitoring devices, user interfaces, or remote management systems via secure communication protocols; and a dynamic load balancing unit embedded in the aggregation server, configured to dynamically distribute computing resources between the data processing unit and the predictive analytics module depending on data volume and complexity.

The invention relates to the technical field of distributed file processing, in particular to a distributed file processing method and system, and the method comprises the following steps: based on a task distribution node and a data exchange interface, extracting path characteristics of a task input / output file, analyzing a file exchange sequence of a task path, and calculating a topological structure and length of the path. According to the method, the flexibility and the adaptability of task allocation are realized by combining task state monitoring and real-time adjustment of dependent path weights and task priority marks, resource allocation and a short-time task sequence are optimized by utilizing request frequency and time period records, high-frequency request resource conflicts are effectively relieved, the resource allocation efficiency is improved, and the resource allocation efficiency is improved. Through node historical resource distribution data and time distribution trend analysis, task distribution is adjusted and resource loads are balanced in combination with differences, the stability and balance of the system are enhanced, a file transmission path is optimized based on a load state and a task execution path, and a concurrent task distribution strategy is improved.

The invention relates to the technical field of target detection, and discloses a personnel state recognition method and system based on target recognition detection. The method comprises the steps of performing parameterization processing on collected original image data to obtain intelligent BIM data; performing multidisciplinary data exchange processing on the intelligent BIM data to obtain target detection data; performing intelligent posture analysis processing on human body information in the target detection data to obtain optimized posture data; behavior recognition processing is carried out on the optimized attitude data to obtain behavior analysis data, and the behavior analysis data comprises violation behavior types, climbing state judgment and risk level evaluation; performing fuzzy logic evaluation processing on the behavior analysis data to obtain safety compliance data; and performing intelligent early warning processing on the safety compliance data and the real-time monitoring data to obtain full-life-cycle management data. According to the invention, the efficiency of personnel state recognition based on target recognition detection is improved.

The invention provides a whole-process engineering consultation management design method, which comprises the following steps of: constructing a unified data exchange standard and protocol, converting heterogeneous data output by design tools of different professions and different units into a standardized data format, realizing seamless joint and real-time sharing of data through data middleware, eliminating data barriers, and improving the data exchange efficiency. The collaborative design efficiency is improved; according to the method, digital technologies such as BIM are adopted, a digital twin model of an engineering project is constructed in a design stage, a design scheme is deepened through virtual construction simulation and optimization, factors such as a construction process, construction procedures and resource allocation are fully considered, and the construction feasibility and economic rationality of design are improved; a collaborative mechanism of a design stage and a construction stage is established, experienced construction managers and technicians are invited to participate in design review, improvement suggestions and suggestions are provided from the construction perspective for a design scheme, a designer is helped to comprehensively understand construction requirements, and the design scheme is optimized.

The invention relates to the technical field of digital information processing, and provides a photovoltaic power station data operation and maintenance management system, and a data exchange network service management system comprises a server, a cloud management module, an edge calculation module, a data exchange module, a performance evaluation module, an intelligent routing module and a self-adaptive data synchronization module. The performance evaluation module is used for monitoring key performance indexes of the network state of the whole system, evaluating the current running states of the cloud, the edge nodes and the network state through the key performance indexes to form an evaluation result, and feeding back the result to the cloud management module, the edge calculation module, the self-adaptive data synchronization module and the intelligent routing module; and the data exchange module is responsible for data synchronization and exchange between the cloud and the edge nodes, so that the data consistency of the edge nodes in the system is ensured.

The invention discloses a park data exchange intelligent management system based on block chain and computing network fusion. The system comprises a directory chain subsystem, a data probe subsystem, a computing network fusion scheduling subsystem, an auditing subsystem, an intelligent contract subsystem, a computing network cooperative processing subsystem, a security sand box subsystem and a trusted exchange subsystem. The directory chain subsystem is responsible for receiving data directory information and carrying out uplink evidence storage to ensure that the data directory cannot be tampered; the auditing subsystem completes data access permission auditing according to the computing power distribution scheme and the access strategy; the intelligent contract subsystem generates an intelligent contract containing data processing logic and a computing power scheduling strategy, and triggers computing power resource scheduling; the computing network cooperative processing subsystem coordinates edges and cloud computing resources to complete cooperative computing; the security sandbox system protects data privacy through multi-stage isolation and encryption; and the trusted exchange subsystem safely pushes an encryption processing result and releases computing power resources after the encryption processing result is completed, so that the security and efficiency of data processing are improved.

The invention discloses a market supervision data exchange platform migration and security enhancement method and system based on a credential environment, and relates to the technical field of network security. In the data migration process, the consistency and privacy protection of the data are ensured through Hash check and a multi-party security computing technology; a domestic commercial cryptographic algorithm and a quantum resistance encryption technology are introduced, so that the protection capability of the platform to existing security threats is effectively improved, and the resistance to future quantum computing threats is enhanced; an intrusion detection system and a virtual honeypot node are integrated, and a defense strategy is monitored and updated in real time in combination with a deep learning model, so that novel attack behaviors can be detected and coped with in real time; according to an intrusion detection alarm and a block chain audit result, a security policy and resource allocation are dynamically adjusted in combination with a machine learning technology, it is ensured that high-risk nodes are monitored in time, resource allocation is automatically optimized, and the resource utilization efficiency and security of the system are improved.

Computerized systems and methods are described for integrating real-time insights across various entities involved in distribution processes. The system includes a Real-Time Data Mesh module for ingesting and harmonizing data from multiple sources, a Data Lake for storing harmonized data, and an Advanced Analytics and Machine Learning (AAML) module for generating insights using predictive analytics, anomaly detection, and recommendation engines. A Single Pane of Glass User Interface (SPoG UI) provides visualizations of these insights through interactive dashboards. The system supports customer, vendor, reseller, and associate systems, enabling efficient data exchange and synchronization. It employs natural language processing (NLP) for sentiment analysis, topic modeling for key theme identification, and clustering algorithms for customer segmentation. Continuous learning mechanisms ensure the system adapts to new data in real-time, enhancing decision-making and operational efficiency.

Systems, apparatus, and methods of managing access to private data via tokens are disclosed. The disclosed techniques provide for constructing digital tokens that represent a right-to-access private data where the tokens can be managed as individual objects. Further, such digital access tokens (DATs) can be recorded on a notarized ledger, a blockchain for example. Additionally, the rights-to-access can be embodied as a non-fungible token (NFT), which could further include support for establishing homomorphic encryption workspaces in which private data can be accessed or manipulated without exposing the private data.

The invention belongs to the field of video monitoring systems, and particularly relates to a cascade-based multi-platform data synchronization method and system, and the method comprises the steps: designing an interface security mechanism of cross-platform data exchange; constructing a data synchronization service architecture, namely deploying corresponding data synchronization services at different levels of platforms to realize resource data synchronization, and supporting data synchronization of multi-level cascade or platform interconnection; performing data initialization synchronization; real-time synchronization of data change is realized; establishing a service heartbeat keep-alive mechanism; service multi-instance deployment is carried out, and efficient data processing and flexible load balancing are achieved. According to the invention, many defects of a data synchronization mechanism of an existing video monitoring system are effectively solved, and the stability, expansibility and data processing efficiency of the system are improved.

The invention provides a cross-platform low-code application development system based on a Flutter framework. Comprising a login registration module, a project management module, an interface design module, a state management module, a route management module, a team management module, a help document module, an AI page design module, a development document generation module, a hardware integration module, a code generation module, a multi-user collaborative development module, a communication module, an online simulator module, an AI generation application module and an interface management module. An asset management module, a developer forum module, an application market module and an application packaging module. The communication module supports various communication protocols and secure transmission modes, and ensures that data exchange applied to cross-platform and cross-system environments is secure and reliable. Through component dragging and graphical configuration, the low-code platform automatically analyzes configuration data to generate an App, a development document and a source code. And meanwhile, multi-person collaborative development is supported, so that the development threshold is reduced and the development speed is increased.

Systems, apparatus, and methods of managing access to private data via tokens are disclosed. The disclosed techniques provide for constructing digital tokens that represent a right-to-access private data where the tokens can be managed as individual objects. Further, such digital access tokens (DATs) can be recorded on a notarized ledger, a blockchain for example. Additionally, the rights-to-access can be embodied as a non-fungible token (NFT), which could further include support for establishing homomorphic encryption workspaces in which private data can be accessed or manipulated without exposing the private data.

The invention relates to the technical field of data exchange, in particular to a TCP-IP protocol-based application program data interaction method, which comprises the following steps of: collecting a signal quality index of application program data in a physical layer, capturing signal quality data of each node through real-time network monitoring, and performing time sequence analysis; and extracting a signal quality trend and an abnormal point, and generating an initial signal analysis result. According to the invention, through real-time analysis and trend prediction, potential problems in the network path can be effectively predicted, network path optimization is realized, the data are analyzed through the reinforcement learning model, the network path is predicted and optimized in real time, the adaptive adjustment capability of the network is enhanced, and the data transmission efficiency is greatly improved. Through simulation testing and real-time monitoring, delay reduction of data transmission and bandwidth utilization maximization are ensured, and then through dynamic adjustment of the size of a TCP window, adjustment is performed according to real-time network congestion conditions, and the overall performance of the network is greatly optimized.

The invention relates to the technical field of network and information security, in particular to a zero-trust multi-party security data exchange method, which comprises the following steps of: generating a zero-trust token and a capability authorization bill and constructing context description data; authentication encryption is performed on the plaintext fragment, attribute-based encryption is performed on the data one-time key, and a policy bearing ciphertext container is assembled; in the trusted execution environment, authentication decryption is completed through a one-time secret key of data recovery through joint challenge and threshold deblocking, or strategy migration and transfer are achieved through proxy re-encryption; and aggregating the decryption event and the forwarding event by vector commitment, generating a time anchor, and mapping the time anchor into a next round of random base. According to the invention, fine-grained authorization of the key layer, no plaintext transfer, event-level verifiable auditing and rapid revocation are realized.

The invention relates to a single-photon transmission device for enabling secure authentication, said device comprising a plurality of single-photon sources, a control device which is configured to actuate each of the single-photon sources separately, and an optical subdevice which is configured to combine single-photon streams of photons emitted by the at least one single-photon source into a QKD coupling beam consisting of a common stream of single photons. The invention also relates to a single-photon receiving device for receiving a QKD coupling beam transmitted from a single-photon transmission device. The invention also relates to a method for generating a common quantum key for a single-photon transmission device and a single-photon receiving device. The invention also relates to an integrated QKD circuit. The invention also relates to a car key comprising a single-photon transmission device and / or a single-photon receiving device. The invention also relates to a car comprising a single-photon transmission device and / or a single-photon receiving device. The invention also relates to the use of a single-photon transmission device and / or a single-photon receiving device for data exchange. The invention also relates to a SPAD diode for a sensor element of a single-photon detector for a single-photon transmission device and / or for a single-photon receiving device.