227 results about "Smart applications" patented technology

The invention discloses a multi-modal knowledge-based automotive body innovative design system, which comprises a multi-modal data fusion module, a multi-modal data fusion module, a multi-modal data fusion module, a multi-modal data fusion module and a multi-modal data fusion module, wherein the multi-modal data fusion module is used for receiving text data, picture data, a three-dimensional CAD (Computer Aided Design) model file and an engineering symbol expression from an automotive body design process and is used for carrying out feature extraction and semantic alignment on input data of four modals; generating a unified semantic vector representation; the cross-modal knowledge mining and graph construction module is used for extracting multi-level entities and relationships from the unified semantic vector and constructing a dynamically weighted multi-modal knowledge graph; the large-model-driven multi-hop collaborative reasoning module is used for analyzing the multi-modal design requirement of a user, carrying out multi-hop reasoning on a knowledge graph, and outputting design parameter recommendation and an interpretable reasoning chain. The method aims at breaking through the limitation of an existing design system in the aspects of multi-modal processing and shallow semantic understanding, and deep fusion and intelligent application of multi-source heterogeneous design data are achieved.

The invention discloses an intelligent question answering system based on a large language model and a knowledge base, and particularly relates to the technical field of artificial intelligence application, comprising a large language model module, a knowledge base module, a retrieval and matching module, an answer generation module and a user interaction module; according to the method, on the basis of a pre-trained large language model and a structured knowledge base, key entities and semantic intentions in user questions are extracted through a multi-level text analysis technology, and preliminary answers are generated; the system combines domain knowledge in a knowledge base, uses vector retrieval and a graph database to efficiently retrieve related information, dynamically fuses retrieval results and generates answers through an attention mechanism and a gating mechanism, and ensures logic consistency and fact accuracy. The system supports multi-modal input and output, and realizes continuity of multiple rounds of dialogues through a memory network; user feedback data optimizes system performance through strategy gradient, and continuously improves answer quality and field adaptability.

The invention discloses an industry knowledge graph automatic construction method oriented to multi-source heterogeneous data, and relates to the technical field of knowledge engineering. Structured, semi-structured, unstructured and distributed data are supported, and high-concurrency data are cached through Kafka; preprocessing and standardizing, and executing cleaning, field unification, text conversion and format conversion; a pre-training model and a rule engine are adopted to cover entities and relations of multiple industries; designing a dynamic Schema, storing the dynamic Schema in a graph database, and constructing an index; evaluating and correcting from multiple dimensions; and dynamic updating and maintenance, incremental updating based on data change, and support of version management and knowledge service. According to the method, the knowledge graph is automatically constructed through multi-source heterogeneous data, the construction efficiency and quality are improved, cross-domain fusion is supported, dynamic updating is adapted, and multi-industry intelligent application is assisted.

An exemplary system and method are disclosed that is configured to detect cognitive impairment (e.g., early cognitive impairment) or assess cognitive function by analyzing, via machine learning and artificial intelligence analysis, behavioral metadata collected from a smart app during the course when a subject is using a cognitive test instrument for cognitive tests that incorporate motor activity (e.g., drawing or writing). The machine learning and artificial intelligence analysis can execute features associated with the test taker's metadata (e.g., time spent on task or questions, changing answers, referring back to the previous question), drawing qualities (e.g., line straightness, completeness), among others.

The invention provides a data driving and multi-element cloud edge cooperative computing method for intelligent workshop construction, which comprises the functions of multi-protocol heterogeneous equipment sensing, edge node adaptive load balancing, lightweight real-time edge computing processing, cloud centralized management control, industrial intelligent application service deployment scheduling, cloud edge task unloading and the like. The system comprises a data acquisition and transmission middleware, an edge stream processing engine and a cloud service center. The method has the characteristics of real-time performance, low delay, flexibility, expandability, loose coupling, low resource occupancy, high availability and privacy security.

Systems and methods are provided for establishing a network session with a device during which network session data is provided to the device via a network. The device may be connected to an LAN, and portions of data are configured to be selectively provided to the device via the network using a first queue for preferential network traffic or a second queue for non-preferential network traffic. During the network session, the systems and methods may identify characteristic(s) of a portion of the network session data, and determine, based on the characteristic(s), whether to provide the portion of the network session data to the device using the first queue or the second queue. Based on determining to provide the portion of the network session data using the first queue, the systems and method may provide the portion of the network session data to the device using the first queue.

The invention discloses a hand-eye coordination and attention evaluation method based on a mobile phone, and relates to the technical field of man-machine interaction and user behavior evaluation, and the method comprises the following steps: S1, in the process that a user executes a symbol matching test task of a mobile phone terminal, obtaining a heart rate variability sequence and an operation sequence interruption frequency, filtering and segmenting the pupil diameter change and the brain wave rhythm to obtain an original feature set; according to the hand-eye coordination and attention evaluation method based on the mobile phone, the continuity, reliability and objectivity of an evaluation conclusion are improved, the method is suitable for cognitive evaluation, man-machine interaction analysis and related intelligent application scenes, and the scientificity and practical value of hand-eye coordination and attention evaluation based on the mobile phone are improved.

The invention discloses a detachable glasses leg interface assembly, a connector assembly, a detachable glasses leg and an earphone, the interface assembly comprises an interface assembly body and an interface arranged on the interface assembly body, the interface comprises a magnetic attraction seat and a base, and the magnetic attraction seat is arranged on the base. The detachable structure capable of realizing quick insertion and extraction between the front frame and the glasses legs of common glasses can be realized, so that the front frame and the glasses legs can be produced in a labor division manner, the common glasses and the intelligent glasses legs are promoted to be subjected to batch and systematic production according to a detachable standard, the production efficiency and large-scale application of the intelligent glasses are effectively improved, and the production cost is reduced. The front frames and the glasses legs of various types, which are produced according to detachable standards, can be freely adapted, so that high interchangeability is achieved, social resources are saved, and the economic burden of consumers is reduced; particularly, a more convenient scheme is provided for people with glasses wearing requirements such as myopia, hyperopia and the like to upgrade common glasses into intelligent glasses, and intelligent application upgrade of the common glasses can be expanded.

The invention relates to the technical field of internet data services, and particularly discloses a multi-graph hidden danger prediction method based on retrieval enhancement and full-graph sub-graphs. The method constructs a complete technical closed loop from data preparation, model training to intelligent application by combining external knowledge retrieval, multi-granularity visual perception and hierarchical reasoning, and specifically comprises three core stages: firstly, automatically constructing a high-quality field specific training data set by using a pre-training large model; secondly, specialized cultivation of a lightweight target multi-modal large model is carried out through supervised fine tuning and reinforcement learning alignment; and finally, introducing'full graph-sub graph 'multi-vision input and regulation knowledge retrieval enhancement in a prediction stage, performing hierarchical reasoning, and outputting a structured hidden danger report.

The invention discloses infrared night vision AR (Augmented Reality) intelligent glasses based on multispectral fusion, and relates to the technical field of infrared intelligent application. High-precision scene perception in a low-light / light-free environment is realized by fusing dual-channel data of low-light imaging and infrared thermal imaging and combining cross-modal feature matching and dynamic pose compensation; an environment detail structure is restored by a low-light image enhancement technology, thermal feature targets such as organisms are accurately recognized through thermal imaging target segmentation, and a three-dimensional environment model with space geometric information and target attributes is constructed through heterogeneous feature fusion; and dynamically adjusting the display transparency of the key target in the AR view field through a virtual information layer adaptive mixing mechanism driven by a hot target attribute, and finally outputting a virtual-real fused enhanced view, thereby breaking through the illumination limitation of the traditional AR glasses, and improving the visual effect of the AR glasses. And immersive augmented reality experience with panoramic detail perception and hot target accurate positioning is provided for the user in a dark environment.

The invention discloses a fire-fighting spatial-temporal trajectory data processing and off-line data warehouse construction method based on a stream batch fusion architecture, and relates to the field of digital fire fighting, and the core steps of the method are as follows: after multi-source data are collected by an edge gateway, high throughput distribution and storage are realized by Kafka; real-time optimization such as track cross repair and offset correction is completed through Flink streaming calculation; performing offline batch processing on the historical data by the Spark to generate an analysis result; generating an optimal rescue path through a distributed Dijkstra algorithm in combination with road topology, real-time traffic and fire fighting truck parameters; the method comprises the following steps: realizing mixed storage by adopting ElasticSearch secondary index and HBase total storage; based on hot and cold data hierarchical management, intelligent applications such as fire-fighting commanding and dispatching, battle comment and review and the like are supported. Practice verifies that the method can shorten the fire control time of the main urban area by 60%, significantly improves the fire emergency response capability, and is suitable for large-scale fire track data scenes.

The invention discloses an enterprise-level agent system and a data processing method. The system mainly comprises a sensing module, a memory module, a planning module, a Routine agent planning engine, an arrangement engine and an execution module. According to the enterprise-level agent system provided by the embodiment of the invention, short-term memory, long-term memory and enterprise-level memory are combined through a complete closed-loop architecture of the sensing module, the memory module, the planning module and the execution module, and precipitation of personalized and organization-level knowledge is supported; and meanwhile, in combination with a standard business process template provided for an enterprise by a Routine agent planning engine and splitting of a task process by an orchestration engine, role agents are allocated for each sub-task, so that coordination and cross-system orchestration of complex tasks are realized, the construction threshold of intelligent applications is reduced, and the business efficiency is improved.

The invention belongs to the technical field of ancient book digital processing, and discloses a training knowledge-fused ancient book word sense disambiguation deep learning method, which comprises the following steps of: constructing a training knowledge graph; preprocessing ancient book image texts; constructing a deep semantic disambiguation model fusing training knowledge; word sense disambiguation reasoning and result output; and system integration and intelligent application interface design. The high-precision word sense disambiguation method oriented to ancient books and texts is constructed by fusing training knowledge and a deep learning technology, so that the recognition capability of complex semantic phenomena such as polysemy words, ancient and modern heterosemy and common and false characters is remarkably improved, the interpretability and field adaptability of the model are enhanced, the dependence on manual training is reduced, and the training efficiency is improved. The method realizes efficient understanding and intelligent processing of the semantics of the ancient books under the condition of low resources, and has good popularization and application prospects and culture inheritance value.

A hybrid quantum-classical computing system designed to enhance AI applications by integrating classical computational methods with quantum computing power. The system incorporates a classical computing unit and multiple quantum computing units, each specialized for distinct algorithmic tasks. A control module within the classical unit, using predetermined decision logic, manages the distribution of tasks, selectively engaging quantum units for their unique capabilities to optimize efficiency. This scalable architecture allows for significant advances in AI, tackling complex, resource-intensive tasks by effectively harnessing the strengths of both quantum superposition and classical processing.

The invention relates to the technical field of artificial intelligence scheduling, in particular to an artificial intelligence task scheduling method and scheduling system based on big data analysis. The system comprises a data acquisition module, a data processing module, a data prediction module, a scheduling generation module and an anomaly detection module. The data acquisition module acquires performance parameters and resource state parameters of task execution and real-time load data of a task queue in real time; the data processing module performs feature extraction on the acquired data to form a task feature matrix; the prediction module predicts task execution time according to the matrix and outputs a prediction execution time parameter; the scheduling generation module generates an initial task scheduling scheme in combination with the prediction parameters and the real-time load data; and the anomaly detection module monitors task execution anomaly indexes, and dynamically adjusts the initial scheme according to the indexes to obtain an optimized scheduling scheme. The system can adapt to task and resource states in real time, improve scheduling rationality, enhance system operation stability and adapt to complex artificial intelligence application scenes.

A computer-implemented method for facilitating telemedicine service is provided. The method includes receiving, by a server computer from a client device over a network, a user request for telemedicine services, wherein the user request is received through a chatbot application for facilitating the telemedicine service. The method includes analyzing the user request using an AI application on the server computer, wherein the AI application includes machine learning algorithms configured to interpret the user request. The method includes generating a response to the user request based on the analysis. The method includes transmitting the generated response to the client device through the chatbot application.

The invention provides a knowledge graph construction method based on parameter calculation logic, and relates to the technical field of graph construction, and the method comprises the following steps: S1, basic data set creation: collecting and sorting domain knowledge data, carrying out systematic classification and organization on the domain knowledge data, and creating corresponding basic data sets for different categories; according to the knowledge graph construction method based on the parameter calculation logic, the knowledge graph with dynamic calculation and reasoning capabilities is realized through parameter calculation logic expression and parameter, formula and index model construction, and the limitation of a traditional knowledge graph in processing a mathematical calculation relation is solved; effective technical support is provided for intelligent decision making in the vertical field, domain knowledge is disassembled into parameters, formulas and attributes based on the first principle by establishing domain knowledge basic data, the knowledge graph is constructed through the entity-relation, and accurate graph reasoning support can be provided for downstream large models and intelligent application.

The invention discloses an intelligent scheduling method and system for concurrent requests of a multi-tenant cloud computer operation management platform, belongs to the technical field of AI intelligent application, and aims at solving the technical problem of how to overcome the defects of resource preemption and low service quality of the multi-tenant cloud computer platform in a high-concurrency scene. According to the technical scheme, the resource utilization efficiency and the service quality guarantee capability of a multi-tenant cloud computer platform are improved, and the method comprises the steps of tenant behavior intelligent analysis: collecting related original data of each tenant in real time, constructing a tenant portrait model, and achieving multi-dimensional priority dynamic evaluation; resource demand time sequence prediction: predicting resource demands of a CPU, a GPU and a memory in a set period through a Prophet prediction model in combination with historical data and a real-time load, establishing a resource demand early warning mechanism, and performing resource pre-allocation in advance; an elastic resource allocation strategy is established, resource sufficiency and shortage scenes are distinguished, dynamic resource quota adjustment is achieved, and response time is shortened; and abnormal behaviors are monitored in real time and rapidly isolated.

The embodiment of the invention provides a code checking method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence application, and the method comprises the steps: obtaining a code file and a project document, and carrying out the content extraction of the project document through a literary and physical agent, the method comprises the steps of obtaining function requirement information and programming specification requirements for a code file, conducting code analysis on the code file through a programming agent according to the function requirement information and the programming specification requirements, extracting a first code block needing to be modified from the code file, and outputting a code suggestion for the first code block, the code suggestions are evaluated through the review intelligent agent and the literary and sports intelligent agent, the evaluation result for the code suggestions is obtained, and the review report file corresponding to the evaluation result is output, so that the comprehensiveness and accuracy of inspection are improved, the inspection efficiency is effectively improved, developers can visually and effectively learn based on the review report file, and the development efficiency is improved. And the programming capability is improved.

The invention discloses an intelligent street lamp system based on renewable energy and a control method, the system comprises a street lamp, a renewable energy power generation module, an energy storage module and an intelligent control unit, and the intelligent control unit comprises an intelligent sensing layer, an intelligent application layer and a cloud platform management layer; the intelligent sensing layer comprises a high-precision environment sensor, a human body / traffic flow detection sensor, an equipment state detection module and a controller; the cloud platform management layer comprises an adaptive dimming control module, an equipment management module, a data analysis module, an AI decision module and a visual monitoring module; the intelligent application layer comprises an intelligent operation and maintenance module, a multi-energy coupling module and a city data service module. By the adoption of the system, the management efficiency, the energy utilization rate and the operation and maintenance intelligent level of urban lighting facilities are improved, renewable energy sources such as solar energy and wind energy are combined, energy is collected through multi-energy coupling, regional cooperative control is optimized, and passive power utilization is achieved in the environment with sufficient natural energy.

The invention provides an intelligent port and navigation AI application system under digital twin enabling, and belongs to the technical field of artificial intelligence application systems. The system comprises an inland river exclusive AI model module, a strong noise voice interaction module, an instruction-scene mapping interaction module and a digital twinborn fusion module. And the inland river exclusive AI model module is used for realizing real-time sensing and accurate decision-making of the navigation channel situation. According to the system, an inland river exclusive AI model module, a strong noise voice interaction module, an instruction-scene mapping interaction module and a digital twinborn fusion module cooperate with each other; real-time sensing and accurate decision making of channel situations, effective voice interaction in a strong noise environment, accurate mapping of voice instructions and virtual scenes and fusion of a high-precision channel model, meteorology and monitoring are achieved, and the problems that traditional inland river shipping management is low in efficiency, inconvenient to interact and poor in scene restoration degree are effectively solved through the design. And the inland river shipping efficiency is improved, the navigation safety is guaranteed, and the operation cost is reduced.

The invention discloses a desktop and application intelligent management method and system based on AI desktop cloud, and belongs to the technical field of AI intelligent application, and the method comprises the following steps: data collection and preprocessing: collecting application use data of a user in a desktop cloud environment, and carrying out cleaning, conversion and integration; user grouping based on AI: analyzing the preprocessed application use data by using a machine learning algorithm, extracting user behavior characteristics, dividing users into different groups and generating group portraits; personalized recommendation and management: providing personalized application recommendation and desktop management strategies in combination with an AI recommendation algorithm based on the user group portrait and the historical use data of the individual user; and abnormal monitoring and early warning: setting various index thresholds of application management, monitoring application use data in real time, and giving out early warning when the indexes exceed the thresholds. According to the invention, user grouping, personalized recommendation management and abnormity early warning are realized, and the intelligent level of application management and the user experience are improved.

The present invention relates to an artificial intelligence application development system for enabling easy development of an artificial intelligence application on the basis of graphics. The artificial intelligence application development system according to the present invention comprises: an IDE providing device (1) for providing an IDE through which a developer can develop an application in a graphic base; and a storage device having a node library and a project library. The IDE providing device (1) includes a user interface (20) which enables a developer to generate a flow graph by using nodes and edges, wherein the user interface (20) includes a node calling means for enabling the developer to call the nodes to a workspace and an edge connection means for connecting the edges for setting a process flow or a data flow between the nodes. In addition, the IDE providing device (1) comprises a hyperparameter engine (13) for setting hyperparameters for the nodes and a flow-graph engine (12) for interpreting and executing the flow graph.

This utility model provides an industrial internet network operation and maintenance training platform, including a training platform, a network module, an intelligent application module, and a network management terminal. The training platform includes an open vertical platform and a horizontal platform. The network module is located on the vertical platform and is used to realize network data communication between the intelligent sensing module and the network management terminal. It includes a security network, a backbone network, and a production network arranged sequentially from top to bottom. The intelligent application module is located on the horizontal platform and is used to build various industrial internet application scenarios and collect data. The network management terminal is located on one side of the training platform and is used for network debugging and network management. The network module, intelligent application module, and network management terminal are interconnected to realize practical training in various industrial internet application scenarios. This utility model adopts an open structure with a clear network structure hierarchy, which facilitates practical training; it can also build various industrial internet application scenarios, providing rich teaching application scenarios.

The present invention discloses a method for using a medical smart bed cabinet, comprising: obtaining relevant information data of people using the bed cabinet in a fixed area, and classifying and storing the relevant data in a database; collecting feature data required by a sorting and classification model, and sorting and classifying the feature data using the sorting and classification model; performing feature matching based on the sorted and classified data with the classified data stored in the database. If the matching degree is higher than a preset value, the match is successful, and accompanying personnel are assigned. When an emergency event occurs in the fixed area, a screening algorithm is used to quickly screen out vacant bed cabinets and corresponding accompanying personnel, thereby realizing the intelligent application of medical bed cabinets. The present invention combines smart bed cabinets with accompanying services to achieve the rational allocation and full utilization of hospital bed resources, improve the quality of accompanying services, and reduce patient expenses.

The application discloses a kind of organic silicon composite functional materials and its wireless monitoring system and method for intelligent application, the interface film includes by outer to inner sequentially stacked anti-fouling and wetting-resistant surface layer, hydrogen bond enhanced dynamic adaptive layer and inorganic filler modulus enhanced protective layer.Anti-fouling and wetting-resistant surface layer is composed of organic silicon elastomer composite material, hydrogen bond enhanced dynamic adaptive layer is introduced by blending in organic silicon matrix into the modified component containing urea group and the like can form hydrogen bond functional group, and inorganic filler modulus enhanced protective layer is introduced by inorganic filler such as barium titanate to improve modulus and compression resistance.The interface film is integrated with pressure sensor module, wireless communication module and host computer system, to form a complete wireless pressure monitoring system, realize real-time transmission of pressure signal, visual display, threshold alarm and data management.The application is suitable for wearable health monitoring, medical care, child companion guardianship and robot touch and the like fields.

The application provides a digital twin architecture of a network, a network session processing method and device, the method comprising: a data acquisition and control entity configured to acquire characteristic data of a physical network corresponding to a virtual network; a core entity connected to the data acquisition and control entity, configured to construct a network-related model corresponding to the physical network according to the characteristic data acquired by the data acquisition and control entity, the network-related model being configured to perform convergent processing on a network session event; and a user entity connected to the core entity, configured to visually display the network based on the network-related model. In the embodiment of the application, the digital twin architecture comprehensively uses perception, calculation, modeling, simulation and other technologies, realizes virtual-real mapping and interaction, can fully train and efficiently simulate more intelligent applications with high error cost, reduces the risk generated when a new technology is verified in a physical space, and reduces the possibility of errors occurring when the new technology is deployed in a real environment.

The invention discloses a multi-target execution plan optimization method, system and product oriented to intelligent application, and belongs to the technical field of intelligent application. A logic application diagram and context information are obtained, and the context information comprises a service level target and a load feature; the method comprises the steps that a logic application diagram, a service level target, load characteristics and a pre-constructed operator performance model are integrated to obtain a constraint optimization problem, a multi-target constraint optimization solver is used for solving the constraint optimization problem, an optimal physical execution plan is generated, and an execution engine is used for executing the optimal physical execution plan. According to the method, the multi-dimensional service target can be understood and adjusted in real time by obtaining the service level target set by the user, the hysteresis is avoided by generating the optimal physical execution plan before plan execution, the self-adaptive capability and the quality of the generated result are improved by using the pre-constructed operator performance model and the multi-target constraint optimization solver, and the method has the advantages of being high in practicability and the like. And the scientificity, the globality and the reproducibility of a scheduling decision are ensured.

Methods and systems for managing data, resources, services, or the like in a distributed service system (e.g., a distributed service platform) are disclosed. Application programming interface (API) requests (e.g., API calls) may be automatically generated from user intents detected in natural language statements provided by a user. Resource providers within the distributed service platforms that the user intended for the API requests to be transmitted to are also automatically identified based on the user intents. One or more resource proxies may then automatically route the generated API requests to these resource providers using a directory of the distributed service platform.

An electronic device according to an embodiment of the present disclosure comprises: a camera; a microphone; at least one sensor; a communication circuit; a memory that stores at least one AI application that provides an AI-based voice service; and at least one processor, wherein the memory may store instructions that, when executed by the at least one processor, cause the electronic device to: acquire, by using the camera, an image including at least one external object; receive a user input specifying a first object among the at least one external object; recognize information related to the first object by using at least one of the image, the at least one sensor, or the communication circuit; generate a first conversation session for the first object through the at least one AI application; determine an audio output path of the first conversation session on the basis of information related to the electronic device or the information related to the first object; receive a first voice input of a user related to the AI-based voice service through the microphone; generate a response to the first voice input on the basis of the first conversation session through the at least one AI application; and provide the response to the first voice input through the audio output path of the first conversation session. Various other embodiments understood through the specification are also possible.