17 results about "Intelligence system" patented technology

Aspects of the disclosure relate to software systems of a tracking system (100) configured to process data from tracking tags ( 102, 104) affixed to assets to be tracked. The software systems may be used to process data such as payloads, interact with various systems including client facing systems, and make predictions regarding tracked assets. The predictions may provide information regarding the status of the tracked, assets during trips. Tire predictions regarding the trips may include destinations of the assets during the trips, events occurring during the trips, conditions of the assets during the trip, estimated, time of arrival at the one or more destinations. etc. The software systems may be robust such that these predictions may be made with minimal or no information pertaining to the trips beyond payloads from tracking tags (102, 104) affixed to the assets to be tracked.

A computer-implemented whole-health intelligence system and method providing personalized clinical and integrative health guidance based on multimodal data including medical history, lifestyle behaviors, psychosocial factors, environmental inputs, and biological metrics. The system constructs a hybrid digital health twin combining graph-based physiological relationships and vectorized embeddings, then generates personalized recommendations via generative AI models and clinical rule-based logic. Safety gating logic evaluates risk patterns and escalates medically significant findings to clinician review. The system supports longitudinal health optimization, annual precision-health evaluations, home-care coordination, and clinician co-pilot review workflows.

A surgical intelligence system can configure positioning and orientation of a surgical instrument during a surgical procedure by considering a current surgical step and a subsequent surgical step. The system can include a processor configured to identify a current acting surgical step and a subsequent surgical step associated with a surgical instrument. The system can determine a plurality of possible position configurations for the current acting step, evaluate an orientation of the instrument and an orientation of the patient, and calculate a corresponding downstream configuration for the subsequent step. Based on the determination, the system can adjust a current configuration and select a suitable configuration for the current acting step.

Described are an intelligence system and process for material blending in the gasification. The system includes a subsystem for material blending in the gasification, wherein the subsystem for material blending in the gasification includes a raw material property rapid analysis module, for obtaining raw material property parameters of raw materials according to characteristic spectral line intensities of in-furnace raw materials; a blended material property prediction module, for establishing a prediction model, and predicting blended material property parameters by means of the prediction model according to raw material property parameters and raw material proportions; a blending scheme optimization module, for establishing an optimization model, and obtaining an optimized blending scheme by means of the optimization model according to blended material property parameters; a blending scheme economy evaluation module, for outputting a blending scheme with the optimum technical economy.

This disclosure describes techniques to distinguish between attack traffic and legitimate user traffic at a site and take action on those findings. A system monitors traffic volumes to the site to determine whether it falls within predicted levels based on historical patterns. If traffic volume deviates from predicted levels, then traffic is analyzed by client signatures (such as a tuple of operating system and user agent) to determine whether the deviation is due to a subset of client signatures rather than factors that are more broadly applicable across clients. A subset of client types driving increased traffic levels may indicate an attack. Based on this intelligence the system can take action to mitigate the traffic or, if legitimate traffic, adjust the general forecasting model.

Aspects of the disclosure relate to software systems of a tracking system configured to process data from tracking tags affixed to assets to be tracked. The software systems may be used to process data such as payloads, interact with various systems including client facing systems, and make predictions regarding tracked assets. The predictions may provide information regarding the status of the tracked assets during trips. The predictions regarding the trips may include destinations of the assets during the trips, events occurring during the trips, conditions of the assets during the trip, estimated time of arrival at the one or more destinations, etc. The software systems may be robust such that these predictions may be made with minimal or no information pertaining to the trips beyond payloads from tracking tags affixed to the assets to be tracked.

A method may include obtaining, from a user device, an electronic document to be processed by a model. The method may also include obtaining an optical character recognition output of the electronic document. The method may further include obtaining, from the user device, an output configuration. The method may also include generating a first output and a second output based on the electronic document and the optical character recognition output. The first output and the second output may be defined by the output configuration. The method may further include transmitting the first output and the second output to the user device. The method may also include obtaining a feedback from the user device. The method may further include updating the model using the feedback from the user device.

Example systems and methods permit threat intelligence to be determined and used at a local, regional, and / or global level in a communications network. A threat intelligence system may collect traffic information from local computing systems and analyze it for malicious traffic. If a measure of malicious traffic in a local computing system is reached, mitigation actions may be taken in that local computing system. In addition, threat measures may be amplified in other local computing systems, other regions, or globally in the network, in order to more quickly react to a known threat as it may spread in a network.

An autonomous operational health intelligence system for mission-critical SAP cloud workloads and method thereof is disclosed. The invention relates to a device-based structure configured to continuously monitor, analyze, predict, and regulate operational conditions of enterprise workloads deployed across distributed cloud infrastructure environments. The system comprises at least one processing unit coupled with a non-transitory memory unit, a telemetry acquisition unit for receiving real-time operational data from application execution systems, database systems, and infrastructure resources, a data harmonization processor for transforming heterogeneous telemetry signals into structured operational datasets, an analytical processing unit for deriving workload health indicators, a predictive assessment processor for generating forward-looking stability indicators based on historical and real-time execution patterns, a control determination unit for identifying deviations and producing corrective directives, and a response execution unit configured to transmit operational control signals to remote computing elements.

A system and method for identifying and tracking one or more targets of interest. The system may include multiple collection systems for capturing information related to visual identifiers and / or electronic signatures associated with the targets at selected locations. The system may also include an intelligence system for determining a target of interest based on information related to visual identifiers and / or electronic signatures and for tracking the target of interest.

The present invention relates to an autonomous risk intelligence system and corresponding method configured to provide adaptive compliance enforcement for financial and medical data systems. The invention enables continuous, real-time evaluation of financial and medical data records against applicable regulatory conditions by correlating data behavior characteristics with dynamically selected regulatory requirements. The system automatically generates risk characterizations and executes compliance control actions without manual intervention, thereby preventing regulatory violations before completion of non-compliant activities. Adaptive learning logic recalibrates risk determination thresholds based on historical compliance outcomes, enabling sustained accuracy under evolving institutional behavior and regulatory change. The invention further ensures secure data handling, multi-jurisdictional regulatory applicability, proportional enforcement, and comprehensive audit traceability through cryptographically protected records.

This invention discloses a tool intelligence system, comprising: an analysis module for parsing user-input task requirements and generating a structured task summary and evaluation objectives; a planning module for analyzing and generating the first subtask to be executed based on the task summary; and a planning module for judging the overall task completion rate based on the execution score of the current subtask and generating subsequent subtasks if the overall task is not completed; an execution module for analyzing the capability preferences of the current subtask, matching the best-performing tool from the tool library based on preference weights to execute the current subtask, and obtaining the execution result; and an evaluation module for performing multi-dimensional quantitative evaluation of the execution result based on the evaluation objectives, generating an execution score for the current subtask and a textual result evaluation. This system enables effective tool selection, fundamentally reducing tool selection and task execution errors caused by misjudgment of tool capabilities.

A vehicle repair intelligence system including a transceiver, a memory and a processor is disclosed. The transceiver may receive vehicle information and user inputs associated with the repair of a vehicle. The memory may store a trained machine model that may be trained using a training data. The processor may obtain a trigger signal, and then obtain the vehicle information and the user inputs associated with the repair of the vehicle responsive to obtaining the trigger signal. The processor may further identify a vehicle part to be replaced in the vehicle based on the vehicle information and the user inputs by executing instructions stored in the trained machine model. The processor may additionally transmit an order form associated with the vehicle part to a vehicle part supplier to ship the vehicle part to a vehicle service center.

The method for adaptive automatic selection of text content search modes based on entity distribution in generative artificial intelligence systems has as a novelty a phase for preparing text data with: step (100) for receiving text documents, step (101) for segmenting text content into segments of smaller length, step (102) for converting segments into vector representations using a language model based on deep learning, step (103) for storing the obtained vectors, step (104) where triples in the form of subject-relation-object are generated using a large language model for automatic recognition of entities and relations between them, step (105) for forming a map that assigns to each unique entity a list of identifiers of segments, and step (106) for constructing a knowledge graph based on separated triplets. Method also includes a phase for processing a user query with: step (200) for receiving a user query, step (201) for identifying an entity in the user query, step (202) for obtaining segment identifiers based on the entity using the map from step (105), step (203) for automatically selecting a text content search mode for generating a response.

A sovereignty-bound, transparent, and controllable evolutionary-intelligence system based on micro-model nuclei operating under integrated governance mechanisms. Each micro-model nucleus evolves through governed stages into intelligent entities and meta-communities while retaining independence, collaboration, and traceable control. Sovereignty anchors, admission protocols, proof-first validation, and lineage logs ensure lawful evolution, while evolutionary gates and feedback governance regulate progression and adaptation. Cross-domain interaction and application registration enable interoperable operation across electronic, photonic, quantum, biological, and bio-inspired carriers using analog, digital, optical, frequency-domain, quantum, and biochemical communication channels. The framework prohibits bypass side-loading and silent upgrading, records every governed event immutably, and supports both topological and non-topological structures for deterministic, auditable evolution applicable to all current and future equivalent systems and domains.

The application discloses a kind of real-time industrial dynamic event clustering method and intelligence system based on industrial knowledge graph.The method comprises the following steps: continuously obtaining near real-time updated industrial information documents from field industrial information data source;For each document, use a general large language model to identify event type and event feature argument, form a unique event feature description;Entity linking is carried out in the industrial knowledge graph, and the event subject name is linked to the enterprise standard name, and is reconstructed into a feature-enhanced event description text and vectorization;Calculate its time decay semantic similarity with the existing events in the dynamic event library, determine whether it is a new event by a judgment model, and update the event library accordingly.The present application extracts fine-grained event elements and disambiguates knowledge graph entities to generate consistent and unique event expressions, effectively improving the accuracy and robustness of event clustering, can process incremental information in near real time, realize real-time monitoring and clustering of dynamic events, and has the advantages of high timeliness and strong interpretability.