40 results about "Contextual awareness" patented technology

Examples are disclosed for systems and methods for increasing a performance of a driver monitoring system (DMS) based on contextual information within a cabin of the vehicle. In one embodiment, a method comprises, during operation of a vehicle by a driver, collecting vehicle environment status information inside a cabin of the vehicle, the vehicle environment status information related to environmental factors that may impact a cognitive load of the driver and including at least one of information regarding one or more passengers of the vehicle; and information from one or more dashboard controls of the vehicle; and based on the vehicle environment status information and an estimated physiological state of the driver, adjusting one or more environmental controls of the vehicle.

The invention discloses a small-amount data fine tuning and self-repairing generative model compression method for specific tasks of an electric power system, which reduces calculation requirements through knowledge distillation and model compression technologies and enables an electric power system model to operate efficiently in a resource-limited environment. Knowledge distillation extracts core knowledge of a large model and migrates the core knowledge to a small model, then pruning and quantification are combined, the parameter quantity is optimized, and lightweight deployment is ensured. Meanwhile, through context awareness, self-repairing and anti-fact GAN, the model generation and adaptive capacity is further enhanced. The context-aware GAN can adjust a model in real time to cope with environmental changes, and the self-repairing GAN generates a replacement sample when data is abnormal, so that the data input quality is ensured; the anti-factual GAN simulates different strategies in a hypothesis situation, and provides support for risk assessment and optimization. Through the mechanism, the model maintains high-precision prediction and response in various scenes, and efficient and stable operation of a power system is guaranteed.

A method for utilizing radar from wireless earpieces includes activating one or more radar sensors of the wireless earpieces, performing radar measurements of a user using the one or more radar sensors of the wireless earpieces, and analyzing the radar measurements to determine pulsatile measurements associated with the user, the analyzing performed using a processor of the wireless earpieces.

Systems, devices, and methods related to provisioning services to a user are provided. An example of a user device worn by a visually impaired user is configured to obtain an image of a current scene surrounding the user, identify an object in the image, detect a plurality of texts associated with the object, detect a plurality of visual features and semantic features related to the text, determine an identity of the object and one or more attributes of the object based at least in part on the visual features and the semantic features, select one or more texts for presentation from the plurality of texts, and present the selected texts in an audio form to the user to allow the user to perceive the identity and one or more attributes of the object.

An audio, video and control ("AVC") operating system is implemented on an AVC processing core coupled to one or more peripheral devices. Using a large learning model ("LLM") module, the AVC system detects audio signals obtained from a user and infers oral commands from the audio signals. Thereafter, one or more actions corresponding to the oral commands are performed on the peripheral devices and / or the AVC processing core. In another embodiment, the AVC system obtains contextual awareness data of a room environment in which the AVC operating system functions. Thereafter, based upon the contextual awareness data, the system performs actions on the peripheral devices or AVC processing core.

A computer-implemented method includes receiving a natural language command from a user that requests a digital assistant to provide a notification to a user device associated with the user upon occurrence of a particular event. The method also includes processing the natural language command using a natural language understanding module to determine one or more event conditions that each indicate the occurrence of the particular event and obtaining event information of the particular event. While the user device is in a notification silencing mode, the method includes determining that at least one of the one or more event conditions is satisfied and providing the notification for output from the user device in response to determining that at least one of the one or more event conditions is satisfied. The notification, when output from the user device, notifies the user of the occurrence of the particular event.

A system and method for generating and delivering personalized promotional offers in real time in response to user voice input. The system processes natural language queries and analyzes prior purchase history, inferred preferences, historical interactions, environmental context including device type, location, and time, and ongoing behavioral signals. Machine learning models adapt future offers based on accumulated user data to provide evolving personalization. The system supports multilingual speech recognition and can operate across smartphones, voice assistants, wearables, smart televisions, extended reality environments, and large language models. Offers may be delivered through audio, visual, or haptic interfaces to enable integration into commerce and advertising platforms. The combination of speech-triggered interaction, adaptive personalization, and contextual awareness enables dynamic, AI-driven promotional flows that operate consistently across multiple platforms and languages.

An embodiment includes identifying, from among the plurality of digital content datasets, a set of candidate textual items based on relevance to a specified subtopic using one or more natural language processing techniques. The embodiment groups candidate textual items into a predetermined number of groups using relevance scores and feature vectors. The embodiment trains a pre-trained encoder-decoder model using a designated group of selected textual items, where the pre-trained encoder-decoder model is pretrained to generate textual content according to a particular style of writing. The embodiment generates, using the pre-trained encoder-decoder model, machine-authored textual content in the particular style of writing resulting in an article about the specified subtopic based on the designated group of selected textual items. The embodiment also includes transmitting the article to a remote web server as an update for a website.

The invention relates to the technical field of intelligent medical information processing, and discloses an intelligent voice interaction robot based on natural language processing, which comprises a robot body and an interaction system mounted on the robot body, the interaction system comprises a voice receiving module, an optimization recognition module, a semantic analysis module, an intention recognition module, a task execution module and a content output module. According to the method, the robustness in a complex medical environment and a special user group is improved through a noise suppression and self-adaptive interaction strategy; through deep semantic analysis and a multi-task risk identification model, precise judgment and context perception of medical intentions and risk levels thereof are realized; and through task execution based on risk grading and multiple compliance check, high unification of intelligence and differentiation of medical service content generation and medical safety is ensured, so that efficient and reliable technical support is provided for medical fields such as medical consultation, pre-inquiry and triage processes.

Various systems (100) and methods (500) are provided for displaying information indicating whether a distance between a location of a feature in a region of interest of a subject and a location of a medical device (140) in the region of interest is within a safe range corresponding to the feature. The location of the feature in the region of interest may be determined (520). The position of the medical device (140) in the region of interest may be determined (530). The distance between the position of the feature and the position of the medical device (140) may be determined (540). Whether the distance is within the safety range may be determined (550). A display (218) may be controlled to display an ultrasound image (560) of the region of interest including the feature and the medical device (140) and to display the information (570) indicating whether the distance is within the safe range.

A method is provided. The method is executed by an interface engine implemented as a computer program within a computing environment. The interface engine executes detection and automation of computer activity. The method includes recording the computer activity across user interfaces (Uls) and automatically processing the computer activity utilizing a generative Al model to extract patterns. The patterns include portions of the computer activity that are similar or resilient to changes. The method includes determining existing automations according to the patterns.

An audio, video and control (“AVC”) operating system is implemented on an AVC processing core coupled to one or more peripheral devices. Using a large learning model (“LLM”) module, the AVC system detects audio signals obtained from a user and infers oral commands from the audio signals. Thereafter, one or more actions corresponding to the oral commands are performed on the peripheral devices and / or the AVC processing core. In another embodiment, the AVC system obtains contextual awareness data of a room environment in which the AVC operating system functions. Thereafter, based upon the contextual awareness data, the system performs actions on the peripheral devices or AVC processing core.

Context aware trajectory forecasting is disclosed. A mobile entity operating in an environment may be performing a task or be associated with a context. The task or context of the mobile entity is determined and filtered with respect to a structure that stores context or task-based typical or rich trajectories. Candidate trajectories are identified and similarity scores are determined for the candidate trajectories. The similarity scores account for attribute importances. This allows a trajectory of the mobile device to be forecast with respect to the historical data of other mobile devices performing the same or similar tasks or that have a similar context.

A method for generating context information for a video stream includes selecting a set of frames of a video stream, applying a first machine learning model to the set of frames to extract action information from the set of frames, applying natural language learning to the set of frames to identify dialogue associated with the set of frames, and generating context information to categorize the dialogue and action information for the set of frames.

The invention discloses a smart home control method, device and equipment, a medium and a product. The method comprises the following steps: acquiring multi-modal sensing data, and converting the multi-modal sensing data into a discrete feature descriptor sequence; constructing first prompt information according to the situation state definition information and the discrete feature descriptor sequence, and guiding a micro language model to generate a current situation state based on the first prompt information; and generating a control instruction sequence corresponding to the controlled household equipment according to the current situation state, and controlling the controlled household equipment to execute corresponding operation according to the control instruction sequence. By introducing a hierarchical context awareness mechanism, conversion from an original perception signal to a discrete semantic state is completed by using low-power-consumption signal processing and a miniature semantic model, and accurate recognition of a complex life situation under a low-computing-power condition is realized by using a zero-sample logical reasoning capability of the miniature semantic model. And the energy efficiency ratio and the response speed of edge calculation are improved.

This invention relates to the field of intelligent customer service, specifically disclosing a method and system for constructing a customer service knowledge base based on a knowledge graph. The method includes: identifying implicit needs by analyzing the spatiotemporal correlation between user actions and customer service dialogues, generating enhanced knowledge units that integrate explicit and implicit knowledge; constructing a knowledge graph, achieving adaptive optimization of the knowledge graph through real-time monitoring of relationship strength changes, forming a dynamic knowledge graph; capturing the user's current contextual information, matching it with the dynamic knowledge graph to generate contextualized knowledge subgraphs, and using multi-path reasoning to generate personalized response content; the system includes modules for implementing the above steps. This invention effectively solves the shortcomings of traditional customer service knowledge bases in implicit knowledge mining, dynamic updating, and deep contextual awareness, achieving improvements in knowledge acquisition from partial to comprehensive, knowledge base from static to dynamic, and responses from general to personalized, significantly enhancing the cognitive depth and service quality of intelligent customer service systems.

This invention discloses a method, apparatus, device, and medium for digital human live streaming interactive processing that integrates a large language model. It relates to the technical field of digital human live streaming interactive processing, including multimodal data acquisition and preprocessing steps, sentiment analysis and semantic understanding steps, response content generation and personalization enhancement steps, and multimodal interactive output steps. By constructing a multimodal data acquisition and preprocessing mechanism, it integrates input information from three modalities: voice, text, and video / image, achieving comprehensive perception of the audience's interactive intent in the live streaming scenario. Based on this, it utilizes a large language model for deep semantic understanding and contextual awareness, and combines a multimodal sentiment analysis module to comprehensively infer the audience's tone, speech rate, facial micro-expressions, and bullet screen text, enabling the digital human to accurately capture the audience's fine-grained emotional state changes, thereby generating highly human-like, context-appropriate response content.

A method for contextual awareness of a vehicle using perception-inspired event generation includes: receiving perception input data from vehicle sensors; and processing the perception input data to classify and generate parameters related to external entities near the vehicle. The method includes generating a hierarchical event structure that classifies and prioritizes the perception input data by categorizing external entities into regions of interest and prioritizing external entities within those regions based on a risk level value. Higher risk level values ​​indicate higher priority within the region of interest. The method also includes developing vehicle behavior planning based on the hierarchical event structure.

A method for generating a contextually aware non-player character in a video game includes executing the video game to enable game play using a player character controlled by a player. The game proceeding generates game state data. Scene interaction data may be identified from the game state data during execution of the video game. The scene interaction data may be filtered based on a filtering setting, the filtering configured to identify target interaction data that is processed to generate context aware logic. The context aware logic may be applied to a non-player character (NPC) associated with a current scene in which the game is performed. The contextual awareness logic transforms behavior of the NPC to contextual interaction with the player character during progress of the game by the player. A method for generating a non-player character for a video game is also described.

The invention relates to a multi-language learning interaction system, and the system comprises a multi-mode input processing module which receives voice, text, image and motion data; the situation sensing module is used for constructing a three-dimensional scene model through an environment sensor; the multi-language knowledge graph database is used for storing cross-language semantic networks and culture rules; the AI interaction engine is used for generating a dynamic task based on the user capability portrait; the AR feedback module is used for superposing interactive virtual language elements in a physical space; and the adaptive evaluation system optimizes the learning path in real time. The method is characterized in that a real scene is dynamically bound through a sensor array and a knowledge graph to generate a training task, and the problem of learning disjunction is solved; a sensitive semantic recognition engine is used for inserting culture annotations in real time, and the cross-culture error rate is reduced; gamification modes are dynamically switched based on physiological signal analysis to maintain learning efficiency; and full-function off-line support is realized by adopting a knowledge distillation technology.

A method, apparatus, and product to provide a parser for property graph queries with precise error reporting and auto-completion based on information from property graph schemas. The approach generally comprises analysis of graph queries prior to their execution to identify issues prior to execution. In some embodiments, the approach includes any of: use of a property graph schema to determine whether names in a received property graph query exist within a corresponding property graph; determining whether the property graph query includes a comparison of mismatched data types; providing an autocomplete suggestion feature for assistance in resolving errors or corresponding to a cursor position within a query string; or evaluation of a property graph query to determine whether it would return an empty result. In some embodiments, property graph query analysis is performed using a context aware approach.

A method for utilizing radar from wireless earpieces includes activating one or more radar sensors of the wireless earpieces, performing radar measurements of a user using the one or more radar sensors of the wireless earpieces, and analyzing the radar measurements to determine pulsatile measurements associated with the user, the analyzing performed using a processor of the wireless earpieces.

A system for self-tuning operation of a node-based logistics receptacle based upon contextual awareness. The node-based logistics receptacle has a plurality of storage receptacle components and a temporary storage area. A retrieval door provides selective access to a delivery item. The system includes a wireless accessory sensor node, a bridge node that includes a bridge node processor, a bridge node memory, and a communication interface operative to communicate with at least a backend server, and an external sensor. The bridge node is operative to receive external sensor data, predict a change in future interactions with the one or more of storage receptacle components based upon the external sensor data, update a management profile based upon the predicted change in future interactions, and alter, using the updated management profile, an operational task related to monitoring for and reporting a change in state of the one or more storage receptacle components.

The invention provides a system for real-time, context-aware targeted advertising in public spaces. Utilizing a combination of neural networks, object recognition software, and a hardware setup of cameras and display screens, the system identifies specific objects in the vicinity. Based on this real-time data, the system selects and displays advertisements that are most relevant to the individuals present. Advanced versions integrate facial recognition and online data analysis for more precise targeting. The system offers advertisers the ability to reach their intended audience more effectively while minimizing intrusion on those not interested in the displayed content.

Techniques for using an artificial intelligent (AI) agent to modify audiovisual data is described herein. The system can obtain audiovisual data descriptive of one or more segments of audiovisual content. Additionally, the system can generate a semantic contextual description of each of the one or more segments of audiovisual content, the semantic contextual description generated based on one or more content understanding models. Moreover, the system can provide the semantic contextual description to a user. Furthermore, the system can receive a prompt from the user comprising one or more user-requested modifications to the semantic contextual description. The system can provide the prompt from the user and the semantic contextual description to the one or more content understanding models. Subsequently, the system can receive a second semantic contextual description from the one or more content understanding models, the second semantic contextual description reflecting the one or more user-requested modifications.

A method to use a pull request scoring and prioritization (PRSP) engine to incorporate contextual awareness when reviewing a pull request (PR) of code from a developer is described. Using The PRSP engine addresses the contextual complexities of software development and frees up reviewer time by incorporating contextual awareness into a quality and scoring process. The PRSP engine uses a machine learning model to develop scores for the PR which are used to calculate a quality for the PR. Based on the quality, the PRSP engine after review by a PR reviewer either merges the code of the PR with a main code or sends the code back to the developer to be corrected.

A method (400) includes receiving a natural language command (106) from a user that requests a digital assistant (50) to provide a notification (165) to a user device (110) upon occurrence of a particular event. The method also includes processing the natural language command using a natural language understanding module (150) to determine one or more event conditions that each indicate the occurrence of the particular event and obtaining event information (104) of the particular event. While the user device is in a notification silencing mode (108), the method includes determining that at least one of the one or more event conditions is satisfied and providing the notification for output from the user device in response to determining that at least one of the one or more event conditions is satisfied. The notification, when output from the user device, notifies the user of the occurrence of the particular event.

A system and method for selectively outputting content on a head-mounted wearable computing device is provided. The system may determine a context associated with operation of the head-mounted wearable computing device, and selectively output the content on the head-mounted wearable computing device based on the context, or delay output of the content. Content may be displayed in one or more specified portions of a display of the head-mounted wearable computing device, thereby reducing distraction of a user and enhancing contextual awareness and contextual security during use of the head-mounted wearable computing device.