428 results about "User friendliness" patented technology

The invention relates to the technical field of process automation, in particular to an RPA service automation method capable of enabling a large language model MCP. The method comprises the following steps: acquiring user input data, and performing intention understanding through a multi-round intention recognition model according to the user input data to obtain semantic instruction data; performing standard semantic protocol conversion according to the semantic instruction data to obtain standard semantic protocol data; performing flow chart node matching according to the standard semantic protocol data to obtain flow chart node data; and generating a business process according to the flow chart node data to obtain business process data. According to the method, the multi-round intention recognition capability of the large language model and the standard semantic protocol conversion are fused, so that the accurate mapping from the natural language to the business process is realized, and the intelligent level and the user friendliness of the RPA system are improved. Through process node matching and process logic verification, the execution effectiveness of the automatic generation process is ensured, and the labor cost and configuration errors are reduced.

The invention discloses a digital intelligent service system for enterprise services, which belongs to the field of enterprise digital services and comprises a user demand analysis module, an intelligent data adaptation module, a service resource matching module, a service efficiency evaluation module and a user-friendly interface. The user demand analysis module is used for semantic analysis and classification decision making; the intelligent data adaptation module identifies and analyzes the protocol type, and establishes an intelligent data transmission channel; the service resource matching module carries out resource pre-screening and accurate matching; the service efficiency evaluation module tracks an identifier and captures a four-dimensional index system in real time, and the dynamic evaluation unit realizes service state grading early warning through a sliding window algorithm; according to the invention, accurate demand identification is realized, the response speed and the data transmission efficiency are improved, the user satisfaction is improved, the service matching accuracy is enhanced, the resource utilization efficiency is optimized, the service capability and the customer experience are improved, and maximization of economic benefits and social values is realized.

The invention relates to the field of legal service management, and discloses a legal service management system based on a block chain, and the system comprises the following modules: a block chain network, an intelligent contract module, a data storage module, a user interface module, a feedback and monitoring module and a user management module, the non-tampering property and the transparency are ensured; the intelligent contract module automatically executes contract terms and supports intelligent management; the data storage module adopts a hierarchical structure, and on-chain data and off-chain data are stored in a distinguished manner, so that the storage and access efficiency is optimized; and the user interface module provides user-friendly operation experience through a visual tool. By using the block chain technology, all contract execution and compliance audit data are encrypted and stored in a distributed mode, it is ensured that tampering is avoided and whole-course traceability is achieved, and a user and related mechanisms can verify the authenticity and integrity of the contract data at any time.

The invention discloses a remote sensing question answering system based on a comparison-generation type pre-training model, which comprises the following steps of: firstly, collecting remote sensing images of tasks such as classification, semantic segmentation, target detection, image-text retrieval and image text generation as original data, and uniformly converting the original data into an image-text pair form; the category area proportion is calculated through segmentation processing, a target category and position information thereof are detected, and zero sample classification is performed through a CLIP model. Thirdly, inputting multi-source information into a multi-modal large language model, generating text description of an image according to a question, and completing construction of a remote sensing global visual question and answer data set; and meanwhile, based on the annotation box, cutting the picture and sending the picture into a multi-modal large language model to obtain a remote sensing local visual question and answer data set. Then, pre-training the comparison-generation type model from a coarse stage to a fine stage, so that the comparison-generation type model has global-local level remote sensing knowledge and visual question and answer ability; and finally, realizing question and answer interaction with the user by constructing a user-friendly system interface.

The invention discloses an intelligent SQL (Structured Query Language) generation method and system based on multistage intention recognition. The method comprises the following steps: receiving a natural language query of a user; vector matching: carrying out vector matching based on a knowledge base to obtain Top-K candidate query objects, the knowledge base containing multilayer structure description information; a large language model intention understanding step: determining a final query object in combination with the candidate query object description; loading a branch workflow, analyzing a field and a table structure, and dynamically configuring a database table and field information; sQL generation: generating SQL statements conforming to grammatical rules, including automatic field addition, time condition conversion and field priority matching operation; and executing the SQL statement and returning a result, and if the result fails, recording a log to prompt correction. By combining a natural language processing technology with a database knowledge base, an efficient, accurate and user-friendly database query solution is provided.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a large model voice question and answer method based on historical dialogue information, which comprises the following specific steps: selecting a large language model GPT for pre-training; taking the historical dialogue information of the user as a current state; learning by using a deep Q network; setting a reward index based on the user satisfaction and the dialogue round; historical information is stored and utilized in combination with a long-term and short-term memory network; and guiding the updating of the large language model by using a DQN network. The method has the advantages that personalized response can be provided, the efficiency is improved, the user experience is enhanced, and high adaptability and accuracy are achieved; through the combined action of the characteristics, the overall performance of the voice question-answering system is remarkably improved, and the voice question-answering system is more effective and user-friendly in practical application.

The invention discloses a self-adaptive resource scheduling method for improving cluster reconstruction efficiency, and relates to the field of resource scheduling distribution, and the method comprises the steps: monitoring the resource use data of each node in a cluster in real time through a monitoring agent, and obtaining the health state of the node through a heartbeat mechanism; collecting input task requests, predicting the resource demand quantity of each task, and performing preliminary queue processing on the tasks to obtain a task queue group; setting a resource competition constraint according to the task queue group and the resource use data and the health state of each node, obtaining dynamic resource scheduling corresponding to each task by using an optimization algorithm, and allocating the tasks to each node; a resource scheduling dynamic graph is constructed, a visual interface is set, and the resource scheduling dynamic graph is arranged on the visual interface and used for displaying resource scheduling, providing a user-friendly interface and realizing high-efficiency scheduling of adaptive resources in a cluster reconstruction process.

The invention presents an energy management system for power distribution networks. It features a hierarchical network with multi-level metering nodes, each measuring energy usage. Data from these nodes are transmitted via a secure communication gateway to a cloud-based platform, which includes servers for processing and storage. A key component is a machine learning algorithm within the server, designed to analyze energy data, normalize and transform inputs, and identify anomalies. The algorithm generates anomaly scores for each power meter, reflecting potential operational issues. A user interface, accessible through client devices, displays the processed data and anomaly scores. This allows users to effectively monitor and manage the energy distribution, making informed decisions for optimization. The system enhances the efficiency and reliability of power distribution, offering advanced analysis and user-friendly monitoring capabilities.

The invention discloses a petroleum industry personnel behavior safety video monitoring system based on artificial intelligence, and the system comprises a front-end equipment layer which is used for collecting physical environment data; the edge computing layer is deployed on a local server of a factory and is used for preprocessing and preliminarily analyzing the data acquired by the front-end equipment layer; the cloud analysis layer is used for carrying out deep analysis on the data uploaded by the edge calculation layer by utilizing deep learning and natural language processing technologies; the cloud analysis layer can integrate data from the front-end equipment layer, the edge computing layer and the cloud analysis layer; and the application service layer is used for presenting the result of the cloud analysis layer to a user in a user-friendly manner. According to the method, video spatio-temporal features are extracted through the CNN-BiLSTM fusion model, risk behaviors such as no helmet wearing and illegal operation are accurately identified, and the false alarm rate is reduced; the NLP analyzes the work order to construct the knowledge graph, the knowledge graph is matched with the video behavior event in a space-time manner, the risk score is dynamically evaluated, and the comprehensive early warning accuracy is improved.

The invention presents an advanced soccer training system designed to revolutionize traditional practice methods through a synergy of technology and interactivity. It features an integration of sensors, Artificial Intelligence, and Augmented Reality technologies, providing real-time feedback, immersive simulations, and personalized training experiences. The system promotes skill development via data-driven insights and dynamic training environments, supported by mobile application connectivity for customized training regimens and performance analysis. Additional attributes include energy-efficient design, user-friendly transport mechanisms, and extensive multimedia capabilities like video recording and photo capture for skill review, establishing a novel paradigm in athletic training and development.

A vehicle safety alert system designed to monitor the interior of a vehicle and alert users about the presence of unattended individuals or pets, such as children or the elderly, left behind inside the vehicle is disclosed. The system includes a smart alert device which can be in a variety of portable forms including stuffed toys and is equipped with a plurality of sensors including an ignition sensor, a motion sensor, a temperature sensor, a sound sensor, and a camera to capture comprehensive visual data of the vehicle's interior. The device utilizes a processor to analyze sensor data and determine the presence of unattended individuals or pets, sending alerts to a user device through a communication network. Alerts can be audio, textual, or video messages, including real-time footage. The system includes a user-friendly application to configure alert preferences and emergency contacts, enhancing the system's utility and user convenience.

The invention provides a code generation method based on an artificial intelligence low-code system. The code generation method can be applied to the technical field of artificial intelligence. The method comprises the following steps: packaging a pre-trained artificial intelligence large model into an artificial intelligence model service to obtain a model application program interface; according to the model application program interface, deploying an artificial intelligence model service into a production environment; based on a production environment, integrating an artificial intelligence model service into a workflow engine of a low-code platform by utilizing a model application program interface so as to obtain an artificial intelligence low-code system; and automatically generating application program codes based on user application requirements by utilizing an artificial intelligence low-code system. According to the artificial intelligence low-code system, automatic decision support is provided, and a more intelligent, user-friendly, efficient and safe low-code application development platform is provided. The invention further provides a code generation device and equipment based on the artificial intelligence low-code system, a storage medium and a program product.

The invention provides a long-range visual question and answer and multi-modal reasoning task agent construction method. For input images and natural language questions, generating answers through orderly calling of an external tool set; the construction process of the intelligent agent is divided into three stages: a global planning stage: analyzing user requirements through a global planning navigator, and screening tool subsets; in the tool autonomous execution stage, visual details are supplemented, background knowledge is retrieved and accurate operation is carried out in the multi-step process by surrounding three types of tools through a tool autonomous executor, and a returned tool result is used for assisting the next step of decision making; in the response synthesis stage, the reasoning process is combed through a model response synthesizer, and user-friendly and clear-format responses are sorted; and finally, the model response synthesis module extracts and obtains answers from the reasoning track and outputs the answers. The problems of global planning insufficiency and visual context forgetting generally existing in complex task reasoning of an existing multi-mode large language model are solved.

The invention discloses a real-time process mining method based on data analysis, which belongs to the technical field of data analysis, and comprises the following steps: providing a user interface, allowing a user to configure input parameters of a data acquisition task, including a target website URL (Uniform Resource Locator) and an acquisition frequency; the data acquisition module is used for realizing pre-definition and comprises a webpage crawler module which is used for automatically accessing and capturing contents of a target website and pre-processing the contents; an API calling module is provided and used for obtaining data from a third-party service or a data provider; the database query supporting module is used for directly extracting data from a database and carrying out encryption transmission on the data; monitoring the state and performance of the data acquisition task in real time; when abnormity or performance reduction is detected, the system automatically triggers an alarm; according to the method, the technical threshold of process mining is remarkably reduced through a user-friendly interface.

The invention provides a charging pile intelligent scheduling system and method, and the system comprises a user management module, a charging pile management module, a real-time monitoring module, an intelligent scheduling module, a data analysis and report module and a system management module, and has the technical characteristics of intelligent scheduling, real-time monitoring, user friendliness, data analysis and optimization and the like. By reasonably dispatching the charging piles, the utilization rate of the charging piles is improved, the waiting time of users is shortened, and intelligent distribution of the charging piles is performed according to user demands and prediction data. The charging piles are intelligently dispatched according to the user requirements and the real-time data, so that the maximum charging pile utilization rate and the maximum user satisfaction degree are achieved. The system analyzes and optimizes data such as user requirements and charging pile states, provides a reasonable charging pile scheduling scheme, can perform real-time adjustment according to data changes, and improves the flexibility and adaptability of the system.

The invention relates to the technical field of 3D development, and discloses a Three.js-based 3D scene low-code construction method and scene construction platform, and the method comprises the steps: a client obtains the operation information of a user, and sends the operation information to a server; the server side is used for mapping the operation information into the structured JSON Schema, updating the JSON Schema on the basis of the operation information, and carrying out persistent storage on the JSON Schema; and the server sends the JSON Schema corresponding to the preview request to the client, so that the client performs real-time rendering. According to the method provided by the embodiment of the invention, the graphical operation interface is provided, so that non-professionals can easily construct the 3D scene without mastering complex programming or graphical knowledge, and therefore, the user-friendly degree of the development process is improved, and the 3D scene construction difficulty is reduced.

This invention relates to systems and methods for real-time dynamic classification and orchestration of test automation components in distributed DevOps environments. The system features an Auto Identify Automation (AIA) engine that leverages supervised learning, Multi-Modal Artificial Intelligence (AI), and Generative AI technologies. It includes a Smart Scenario Designer interface that allows users to author test scenarios using handwriting and voice inputs, which are processed in real-time by AI-driven handwriting recognition, voice recognition, and Natural Language Processing (NLP). The system dynamically suggests relevant automated components via a smart bubble pane, facilitating rapid scenario creation. The architecture is tool-agnostic and scalable, with a Shared Workbench Engine that supports real-time collaboration and conflict resolution. The system continuously adapts and improves, ensuring that the automation suite remains consistent, up-to-date, and aligned with evolving software requirements, enabling efficient and user-friendly management of complex test automation processes.

The invention provides a chip verification method, device and system. The method comprises the following steps: acquiring a configuration file of a current test scene; a constraint strategy involved in the current test scene is configured in the configuration file according to a set data structure; the constraint strategy is a predefined constraint condition corresponding to the test requirement; analyzing the configuration file to obtain an analysis result; generating a hardware programming language simulation data structure corresponding to the chip verification case based on the analysis result; and outputting the hardware programming language simulation data structure to a chip verification platform so as to perform chip function verification in a chip simulation environment. According to the automatic generation and configuration method of the test case in the technical scheme of the invention, the user friendliness of the verification environment is remarkably improved, so that a verification team is assisted to quickly master and efficiently utilize the verification environment.

The invention provides an automatic drawing method and system for a satellite optical fiber transmission data stream, and the method comprises the steps: a user adds an e-mail address through software, and the software detects the uploading state of an interface data sheet, and sends a detection result to the user through an e-mail. And after the mail is successfully sent, the system records and displays a mail notification in a specified area. And identifying the interface data sheet by using GNN and graph embedding technologies. And the software establishes a digital model according to an identification result, forms a mapping relation with the constituent elements, and draws an optical fiber transmission data flow statistical graph according to a rule. According to the invention, automatic satellite data flow drawing is realized, and the efficiency of data processing and error detection is improved. The method has remarkable advantages in the aspects of improving the automation degree, accuracy and user friendliness of data processing.

The invention relates to the technical field of smart power grids, in particular to a smart station building energy management system and method based on a swan monk system, and the system comprises a distributed energy collection module, a data processing and integration module, an energy demand prediction module, an equipment fault prediction module, an energy optimization scheduling module and a user interaction module. Wherein the distributed energy acquisition module is used for acquiring operation data; the data processing and integrating module is used for forming a distributed energy data set; the energy demand prediction module is used for predicting future energy demands; the equipment fault prediction module is used for performing fault prediction; and the energy optimization scheduling module is used for optimizing the operation strategy of each energy device in the scheduling station building. According to the invention, through real-time data acquisition, intelligent prediction and fault early warning mechanisms, energy scheduling is optimized, the equipment operation reliability and the energy utilization efficiency of the system are improved, and the operation transparency and convenience are enhanced through a user-friendly interaction interface.

The invention discloses a decentralized identity authentication method using a DID technology, and the method comprises the following steps: S1, generating a public key and a private key by a user, and generating an identity identifier by using the public key; s2, the user combines the identity data with the identifier, encrypts the identity data and the identifier, and stores the encrypted identity data and identifier on the block chain; s3, the third-party authentication mechanism issues a verifiable certificate based on the identifier; s4, the user manages the verifiable certificate, signs the identity verification request by using a private key, and sends the signed identity verification request to the verifier; s5, the verifier verifies the validity of the signature through the public key on the block chain; s6, recording verification time, a signature and a result, and storing the verification time, the signature and the result on the block chain; s7, the user can recover the lost private key or identity identifier through multiple signatures or other mechanisms; and S8, providing a user-friendly interface, supporting cross-platform migration of identity data, following open standards and protocols, and establishing a transparent governance mechanism. According to the method, the block chain and the advanced encryption technology are combined, and safe storage and privacy protection of identity data are realized.

The invention relates to a reconfigurable equipment simulation system based on software radio, and the system achieves the high-integration, user-friendly and efficient-management reconfigurable equipment simulation system through the modularization and seamless integration of a radio waveform design function, an equipment simulation user operation interface design, a business logic function design and a project management function. Therefore, even if a user does not have a deep programming capability, the user can quickly construct, test, manage and deploy the equipment simulator with complete functions. The system is rich in waveform component and UI component library, customizable in function and good in flexibility, software radio waveform design and equipment simulation are innovatively and seamlessly integrated, automatic non-inductive or manual upgrading can be achieved, the universality is good, various equipment simulators can be designed, the designed equipment simulators have open function expansion, and the system is suitable for popularization and application. And a complete project management process is provided.

The invention relates to an artificial intelligence application service software development terminal, relates to the technical field of computer software, and aims to simplify and accelerate the design, development, test, deployment and management processes of artificial intelligence application services. The terminal integrates a data processing module, a model development module, a service definition module and a deployment management module, and provides a unified integrated development environment. Through a user-friendly graphical interface, a developer can conveniently import, label and preprocess data; an artificial intelligence model is selected or constructed, and training and evaluation are carried out; defining input and output, an interface protocol and runtime configuration of the model, and packaging the model into a callable service; and the services are deployed to various target platforms. According to the method, the development threshold is effectively reduced, the development efficiency is improved, and wider application of the AI technology is promoted.

The invention provides a full-stack observability method for a unified platform, which comprises the following steps of: respectively acquiring logs, indexes and link tracking data by using an application performance monitoring agent, an extended Berkley packet filter agent and an index acquisition agent, and storing and distributing the logs, the indexes and the link tracking data, and performing data association processing by using the request tracking identifier and the timestamp to obtain an original data set which is stored uniformly and is in cross-data association, and performing format standardization and full-stack tracking integration processing respectively to obtain a standardized time sequence index and full-stack link tracking data respectively. By summarizing the data into the same observation system and associating the observation data by using the specific field, all observability data can be observed on the same platform, and the same user interface is used, so that switching among a plurality of system pages is not needed, the problem of data islands is solved, and a user-friendly observable platform is created.

A present invention embodiment provides a Life Cycle Assessment (LCA) system that addresses the limitations of existing systems. The system offers an intuitive, user-friendly interface that simplifies the complexity of LCA methodologies, making environmental impact assessment accessible to a broader audience. It incorporates advanced algorithms and real-time data integration, ensuring accurate and up-to-date assessments. Additionally, the system is designed with a modular architecture and is highly configurable, allowing seamless integration with various industries and accommodating diverse items including products, services, and processes.

The invention discloses a digital twinning-oriented man-machine interaction adaptive method. The method comprises the following steps of 1, data collection and preprocessing: collecting sensor data; step 2, constructing a data twinborn model: modeling; 3, developing an intelligent decision support system: designing a decision algorithm; 4, learning optimization based on time sequence data: time sequence data analysis: performing deep analysis on historical operation data of the mechanical arm by using a time sequence analysis technology; 5, interactive interface design: a dynamic interactive interface: developing a user-friendly dynamic interactive interface; and 6, real-time monitoring and adjustment are conducted, wherein a real-time monitoring system is used for achieving real-time monitoring of the mechanical arm and the operation environment of the mechanical arm. By analyzing the digital twin model and the sensor data in real time, the difference between the current state and the target can be quickly recognized, so that optimization suggestions are generated, the intelligent decision support can help the mechanical arm to efficiently execute tasks in different working modes, and the production efficiency is improved.

This disclosure presents an event management system with real-time, low-latency communication between server and user terminals, facilitating efficient event planning and execution. The system includes an application program interface (API) database with an event execution management API for scenario control, participant messaging, location tracking, progress recording, and resource management API to handle physical assets. A user-friendly interface allows managers to construct event scenarios visually by manipulating graphical elements such as time zones, field zones, and preset layers—enabling quick setup without coding. Event scenarios undergo real-time validation to address scheduling conflicts, resource availability, and participant constraints. The system also includes an event database for program storage and log tracking. A communication processing unit synchronizes participant actions and event status, adjusting in real time based on feedback and location updates. This system enhances event management accuracy and flexibility, responding dynamically to changes in event parameters and participant interactions.

An exchange computer system and methods for using a moneyness index to provide a simplified and user-friendly way for users to trade daily positive or negative returns of an asset. A trade contract is built around a standardized index that tracks the return of an asset over a given period of time.

The invention discloses a sign language-voice conversion system, and belongs to the technical field of auxiliary communication and wearable computing. The system comprises a wearable myoelectricity acquisition module used for acquiring double-arm myoelectricity signals when a user executes sign language; the mobile terminal module is wirelessly connected with the acquisition module and is used for receiving and preprocessing the signal and uploading the signal; the cloud processing module is used for receiving the signal, converting the signal into text information through a sign language recognition model, and further calling a voice synthesis service to convert the text into voice data; and the wearable audio output module is used for receiving and playing the voice data. Through an innovative end-to-end hardware system architecture, natural, accurate and real-time translation and voice output of sign language gestures are realized, communication barriers between hearing-impaired people and healthy hearing people are effectively solved, and the system has the advantages of flexible deployment, user friendliness and privacy protection.

The invention discloses an early tumor screening prediction system based on information analysis, and belongs to the technical field of medical data screening. The invention discloses an early tumor screening prediction system based on information analysis. The system comprises a multi-source data acquisition module, a dynamic model updating module, a reinforcement learning prediction model, a personalized health management scheme generator and a user-friendly display interface. The problems that in the prior art, due to the fact that the model cannot be updated in time, the timeliness and prediction accuracy of the model are low, model optimization cannot be conducted according to user feedback, and a personalized health management scheme cannot be generated according to the tumor risk probability and risk level of the user are solved. According to the method, latest research results are automatically captured from a plurality of databases at regular intervals, a user feedback mechanism is combined, dynamic and real-time updating of the model is realized, and a personalized health management scheme generator is arranged, so that each user can obtain health management suggestions aiming at own conditions.