1780 results about "Interaction control" patented technology

The invention relates to the technical field of monitoring and early warning of power equipment, in particular to a monitoring and early warning method and system for substation power equipment. Comprising a data acquisition module, an intelligent diagnosis module, a risk assessment module, a collaborative early warning module and an interaction control module. The data acquisition module acquires equipment operation data including current, voltage, temperature and humidity and vibration signals. And the intelligent diagnosis module identifies equipment abnormity through the generative adversarial network and the graph neural network. The risk assessment module generates a risk assessment curve based on a fractional order differential model and a reinforcement learning algorithm. And the collaborative early warning module generates a graded early warning scheme by utilizing edge calculation. And the interaction control module displays a state and optimizes a control strategy through a human-computer interface. The intelligent monitoring and management level of the power equipment of the transformer substation is improved, the service life of the equipment is prolonged, and the operation and maintenance cost is reduced.

The invention provides a digital human interaction control method and device fusing emotion semantics and logical reasoning and a storage medium. The method comprises the following steps: analyzing multi-modal input data of a user, constructing emotion-semantics joint representation, and generating a logic decision path; and through a cognitive fusion module, emotion-semantic representation and a logic decision path are fused, and an interaction response adapting to emotion and logic consistency is generated. The system optimizes an emotion semantic model and a logical reasoning rule on line according to user feedback and interaction history, and real-time interaction of emotion dynamic and logical rules is achieved. The system can dynamically adjust the logic decision path based on the multi-mode emotional state of the user, and improves the naturalness and situation adaptability of interaction. A dynamic time warping algorithm and a factorization machine are introduced to process a multi-modal feature fusion problem, and the accuracy and robustness of emotional state recognition are improved. The online optimization mechanism enables the model and the rule to be evolved continuously, and reasoning errors are corrected automatically through user feedback, so that error circulation is avoided.

The invention discloses a smart home voice interaction control method and system, and relates to the technical field of smart home. The problems that in the prior art, the intention of a user cannot be accurately understood through non-voice information such as emotion and expression of the user, a control strategy is solidified and lacks individuation, and user requirements and emotion cannot be met in real time are solved. By fusing voice and non-voice information, accurate recognition of user intentions is enhanced, recognition accuracy of voice instructions is improved, emotional states and requirements of users are understood more comprehensively, particularly in a noisy environment or a complex situation, recognition and response effects of the system are obviously improved, and user experience is improved. By utilizing the emotion analysis and context understanding technology of the user, the interaction mode is dynamically adjusted according to the emotion state of the user, the emotion demands of different users can be flexibly adapted, more humanized services are provided, the control strategy is continuously optimized according to the feedback of the user, the user satisfaction is improved, and the user experience is improved. Therefore, the intelligent degree and the user experience of the smart home system are improved.

The invention relates to the technical field of multimedia interaction, in particular to an intelligent interaction control method and system for digital exhibition hall multimedia equipment, and the method comprises the following steps: S1, carrying out the arrangement of a sensor, and carrying out the intelligent sensing and data collection; s2, generating an intelligent interaction strategy; s3, equipment cooperative control and execution; and S4, performing real-time feedback and system optimization. According to the method, user behaviors and environment data are collected in real time through the multi-modal sensor, user requirements are accurately speculated in combination with a deep learning algorithm, the optimal interaction strategy and task priority are generated, individuation and interaction efficiency of user experience are remarkably improved, multi-device cooperation is optimized through distributed task scheduling, and user experience is improved. According to the method, display content and environment parameters are dynamically adjusted, self-optimization of the system is realized by utilizing user feedback, real-time performance, smoothness and reliability of interactive experience of the exhibition hall are ensured, rapid fault response and accurate maintenance demand prediction are realized through anomaly detection and equipment log analysis, and the stability and sustainability of operation of the exhibition hall system are greatly improved.

The invention discloses an art teaching management system and method based on AI. The system comprises an intelligent user management module, a course generation module, a real-time interaction module, an evaluation module, an interaction control module and a data security module. Through a multi-modal deep integration learning algorithm MMDILA and a reinforcement learning algorithm, multi-modal data of a user is analyzed, dynamic generation and adjustment of personalized course content are realized, and real-time learning feedback and personalized suggestions are provided. And a block chain technology and a differential privacy technology are adopted to guarantee the security and privacy of user data. According to the method, the personalized teaching effect and learning efficiency are remarkably improved, the learning time is shortened, the user satisfaction is enhanced, the data security and the privacy protection capability are greatly improved, and the defects in the aspects of personalization, real-time feedback and data security in the prior art are overcome. The method is obviously superior to the prior art in the aspects of personalized teaching and data security, and can meet the requirements of different users.

The invention provides a toy interaction control method and device based on a large language model, a terminal and a medium, and the method comprises the steps: obtaining user side information which comprises one or more of voice, text, image, limb movement or external environment information; performing feature extraction on the user side information to generate feature representation; inputting the feature representation into a large language model, and identifying a user intention; generating a corresponding control instruction according to the identified user intention; and converting the control instruction into a specific control signal, and sending the specific control signal to a control system of the toy so as to execute corresponding control. The large language model is utilized to perceive human language characters, voice emotions, limb actions and the like, human intentions are accurately recognized, then the feedback of the toy is controlled, and intelligent interaction is formed for users.

The invention relates to the technical field of intelligent scene recognition, and discloses an intelligent scene recognition method and equipment for an intelligent interaction control unit, and the method comprises the steps: carrying out the collection and preprocessing of an operation sequence, video content and audio data of the intelligent interaction control unit in a digital set-top box, and obtaining a standard multi-mode data set; inputting the standard multi-modal data set into a multi-branch deep neural network model, and extracting time sequence, visual and audio features through parallel processing to obtain a fusion scene feature vector; carrying out dimensionality reduction and semantic mapping on the fused scene feature vector to obtain a compressed semantic feature vector; performing similarity calculation on the compressed semantic feature vector and a predefined scene query vector to obtain a scene matching score; and based on the scene matching score, integrating the output of the plurality of sub-classifiers to obtain a target scene classification result, and the method can be efficiently operated on the digital set top box with limited resources to realize real-time scene recognition.

The invention relates to a television box intelligent interaction control unit image processing method and device. The method comprises the following steps: carrying out feature analysis on an input video stream of the television box to obtain an enhanced video stream; the method comprises the following steps: collecting visual and voice interaction information of a user based on an intelligent interaction control unit, and inputting the visual and voice interaction information into a double-branch Transform model for multi-modal information fusion to obtain a fusion feature vector; performing conjoint analysis to obtain a user interaction intention and an interaction response strategy; performing local contrast enhancement and motion compensation to obtain a high-quality video frame sequence; and performing scene adaptive color space mapping and dynamic color temperature adjustment on the high-quality video frame sequence according to the environment light information acquired in real time and the pre-stored color characteristics of the display device to obtain an output video stream. According to the implementation of the method, limited computing resources can be fully utilized, efficient video processing and natural man-machine interaction are achieved, and meanwhile the display effect is dynamically optimized according to environmental changes.

The invention provides an intelligent laboratory man-machine interaction control method and system, and relates to the technical field of control, and the method comprises the steps: collecting experimenter and equipment images through a visual collection device, recognizing equipment operation state parameters based on a deep learning model through a processing server, including a switch state, an indicating lamp state, a display screen state and a fault indication state, and transmitting the state parameters to a server; and comparing the identification result with a preset parameter to generate an evaluation result. And the processing server receives the user voice instruction, extracts the content of the control instruction, and determines the target equipment and the control action. And verifying the legality of the instruction and judging whether an execution condition is met by combining an equipment state evaluation result. And a cooperative control strategy is generated according to the control instruction and the evaluation result, the cooperative control strategy comprises a control time sequence, parameters and a data interaction mode, and the control instruction is sent through the field bus network to realize multi-device cooperative control. According to the invention, intelligent management and control of laboratory equipment are realized, and the experiment efficiency and safety are improved.

The invention belongs to the technical field of sound equipment control, and particularly relates to an intelligent sound equipment control method and system and a storage medium, and the method enables the interaction control of the intelligent sound equipment on home equipment to be based on the control effect, and can screen out the interaction control record with the abnormal control effect based on the historical interaction control record. According to the method and the device, the voice control instruction is subjected to abnormal traceability and voice control instruction complexity correlation analysis, so that the targeted adjustment direction of the sound interaction control is obtained, feedback closed-loop adjustment of the sound interaction control is realized, the blank of the existing sound interaction control on feedback control is effectively filled, and the user experience is improved. Continuous optimization and improvement of sound interaction control are accelerated and promoted to a certain extent, so that the user experience is improved continuously, and sustainable development of the intelligent sound is facilitated.

The invention discloses a digital twin interaction control system based on robot vision and tactile fusion, and the system comprises a data collection module which is used for collecting visual image data and tactile sensing data; the preprocessing module is used for preprocessing; the multi-mode perception modeling module is used for executing spatial perception modeling and tactile state modeling; the fusion state vector construction module is used for generating a fusion state vector; the digital twinborn mapping module is used for constructing a digital twinborn body; the simulation interaction control module is used for executing interactive action control and generating a control instruction parameter group; the action execution and feedback module is used for controlling the robot to execute the actual action and updating the fusion state vector; and the dynamic evaluation and self-adaptive adjustment module is used for dynamically optimizing and adjusting the fusion state vector. Visual and touch information of the robot is fused, a digital twinning synchronous control mechanism is constructed, and the interactive optimization method which is fast in operation response, high in execution precision and stable in control process is achieved.

The invention discloses an intelligent household electrical appliance interaction control system based on embedded software. A system operation process specifically comprises the following steps: acquiring a user input signal; analyzing the user input signal based on an embedded software architecture to generate a standardized control instruction; establishing communication connection with a plurality of intelligent household electrical appliances through an Internet of Things protocol, and obtaining real-time environment data and real-time operation states of the intelligent household electrical appliances; performing conjoint analysis on the user historical behavior data and the user input signal; adjusting operation parameters of the intelligent household electrical appliance; and returning interaction response information to the user through at least one mode of a voice feedback module, a touch interface, a gesture recognition interface or a mobile phone APP. The method has the following advantages and effects: multi-mode instructions can be adaptively fused, the equipment capability and the user intention can be dynamically matched, and cross-equipment and cross-protocol efficient and accurate control is realized through standardized instruction generation, real-time load sensing and priority dynamic calculation.

A system, including an analysis server computer, a robot that is configured to participate in interactions with one or more participants; wherein the robot is configured to collect information related to the participants during the interaction, wherein the robot accepts a summary report related to the interaction from a participant or forms a summary report, wherein the robot is configured to forward the summary report to the analysis server for analysis, wherein the analysis server is configured to analyze the summary report and determine if the summary report should pass or fail, when the summary report passes the analysis server is configured to store the summary report in a database; and when the summary report fails the analysis server is configured to provide feedback to the robot with a list of problems for correction in the summary report.

The invention relates to the technical field of data processing of organic displays, in particular to an interaction control method of a double-screen organic display system, which acquires touch control, deformation and ambient light data in real time through a multi-mode sensor array, and realizes cross-screen heterogeneous data space-time alignment by adopting an improved clock synchronization protocol and a sliding window mechanism. And generating a time sequence feature vector set with weight. And based on an LSTM-Transform hybrid model, fusing historical communication delay data, analyzing space-time relevance by using a multi-head attention mechanism, and outputting a cross-screen communication delay probability distribution diagram. And generating a multi-target task allocation strategy in combination with a deep reinforcement learning model, and iteratively calculating a shortest path allocation scheme of a rendering task through an improved ant colony optimization algorithm. The space-time synchronization precision of double-screen interaction is effectively improved, signal misalignment caused by communication delay is reduced, the distribution efficiency of distributed rendering resources is optimized, and the environmental adaptability and operation robustness of a flexible display system are enhanced.

The invention provides a multi-source information fusion automobile light personalized interaction control system and method, and relates to the technical field of automobile intelligent light control. The system comprises a multi-source sensing module, a data preprocessing module, a data analysis processing module and a vehicle lamp driving module. The multi-source sensing module collects multi-source heterogeneous data, after the multi-source heterogeneous data is processed by the data preprocessing module, fusion analysis and intelligent decision are carried out by the data analysis processing module, a control instruction is generated, and finally, the instruction is executed by the vehicle lamp driving module and a state is fed back. According to the invention, the defects of the existing automobile light control technology in the aspects of intelligence, situational and individuation are overcome, the efficient, intelligent and individualized control of the automobile light is realized, and the driving safety, comfort and entertainment are improved.

The invention discloses a WebXR-based digital twinning extension method in a highway scene, and aims to solve the problems of poor interaction adaptability between a three-dimensional twinning model and a Web end XR, high interaction response delay, inflexible resource updating mechanism and the like in an existing system. The method comprises the following steps: constructing a three-dimensional twinborn model based on highway scene structure information, traffic state information and environment monitoring data; formatting the model into an analyzable data structure suitable for a Web end; starting an operation instance through a WebXR session, loading XR equipment capability, collecting and analyzing user space positioning, head posture and control input information, and generating an interaction control instruction; and the incremental resource replacement of the three-dimensional twin model is realized according to the updating instruction of the server side. According to the method, the adaptability, the interactivity and the real-time performance of the Web end XR system in the traffic digital twin environment are improved.

The invention discloses a vehicle-mounted VR back-row entertainment method, and relates to the field of VR, and the method comprises the steps: processing image data transmitted by a controller through a DCT plate negative reflection plate lens, and generating aerial imaging data; reflecting a virtual image corresponding to the aerial imaging data by using a plane mirror to generate real image data; performing voice recognition processing on the input voice of the user to obtain voice control instruction data; acquiring image data of user gestures through an infrared sensor, and performing image recognition to obtain gesture control instruction data; generating interaction control data according to the three-dimensional coordinates in the real image data, the voice control instruction and the gesture control instruction; aiming at low image imaging precision in a vehicle-mounted VR entertainment system in the prior art, high-quality aerial imaging is generated by using a DCT plate negative reflection plate lens and a plane mirror, multi-modal interaction and the like are realized by adopting voice recognition and gesture recognition, and a vivid imaging effect is provided.

The invention relates to a touch all-in-one machine interaction control method and device, computer equipment and a medium, and the method comprises the steps: receiving image data through a preset video stream protocol, and obtaining a corresponding image data stream; acquiring a real-time network bandwidth condition, and then performing adaptive compression processing on the image data stream based on the real-time network bandwidth condition, and dynamically adjusting image transmission parameters; comprehensively analyzing the image data stream by using a deep learning algorithm, extracting operation characteristics of a user, generating an output control instruction based on the operation characteristics, and further controlling and adjusting image display and / or an equipment state; content information is extracted from the image data stream, and content analysis is carried out by adopting a corresponding content analysis strategy according to the content information, so that real-time display and / or storage are / is carried out according to the analyzed content; and obtaining a user interaction behavior, generating a corresponding adjustment feedback instruction based on the user interaction behavior, and performing personalized adjustment on the user interface. The method has the effect of improving the image transmission quality.

The invention discloses an interaction method and device, a medium, electronic equipment and a program product, and relates to the technical field of Internet, and the method comprises the steps: displaying an initial multimedia resource in a display interface; displaying at least one interaction control in the display interface, wherein the at least one interaction control is used for providing a modification suggestion for the initial multimedia resource; in response to a first trigger operation for a target interaction control in the at least one interaction control, determining a target multimedia resource corresponding to the initial multimedia resource according to a modification suggestion provided by the target interaction control; and displaying the target multimedia resource on the display interface. According to the method, a user does not need to actively provide modification suggestions, at least one interaction control is displayed in a display interface, and the at least one interaction control is used for providing the modification suggestions for the initial multimedia resources for the user to select, so that the target multimedia resources corresponding to the initial multimedia resources are obtained through modification; therefore, the content generation requirement of the user is efficiently and flexibly met.

The invention provides an interface interaction control method and device, wearable equipment and a computer readable storage medium. The interface interaction control method comprises the steps that a virtual scene picture is displayed, and the virtual scene picture comprises a cursor interaction interface and a virtual ray of cursor control equipment; based on a current ray interaction point, a cursor of the cursor control equipment is displayed on the cursor interaction interface, and the current ray interaction point is an intersection point between the virtual ray located at the current display position and the cursor interaction interface; and when the cursor control equipment moves, controlling the cursor to move from the current ray interaction point to a target ray interaction point. According to the method, the interface interaction intuition can be improved, and the interface interaction operation efficiency is improved.

The invention discloses an LED cloud screen 3D interaction control system, and relates to the technical field of cloud screen interaction control, and the system comprises a content input module which receives multi-source signal content from the outside and converts the multi-source signal content into an SDS stream; the 3D rendering and processing module performs image generation and effect optimization, and generates a final display image step by step; the display output module converts the final display image into a data frame which can be directly loaded and displayed by the LED cloud screen; the monitoring and maintenance module performs real-time sensing, fault prediction and remote management on the operation state of the LED cloud screen system, and finally outputs system state information and a maintenance response instruction; and the interaction control module analyzes and responds to the control event data in the SDS stream, and converts a structured control event into a standardized system control instruction. The operation stability and the interaction performance quality of the cloud screen system are improved, and the failure rate in the long-term use process is reduced.

The invention belongs to the field of computer control systems, and provides an interaction control method and system based on smart home equipment, and the method comprises the steps: extracting the context information of a current user when there is missing control parameters, the context information comprising time information, a spatial position, an environment state and a user identity; constructing a control context map of the current user; searching a neighborhood user set similar to the behavior portrait characteristics of the current user, and extracting control parameter records of the neighborhood users in the context similar to the current user; performing weighted fusion on the historical control parameter of the current user and the control parameter of the neighborhood user to generate a target control parameter; forming a complete control command, and issuing the complete control command to the target smart home device to execute a control operation; and updating the control context map based on user feedback or a system monitoring result.

The invention provides a control method, which is applied to an artificial intelligence experiment system, at least comprises a robot hardware platform, a controller, a wheeled robot chassis and an industrial mechanical arm, and the method comprises the following steps: starting an operation system and executing hardware self-inspection; loading a large language model service and a traditional AI model, wherein the traditional AI model comprises a speech recognition model, a target detection model and a semantic analysis model; a natural language instruction of a user is received, voice is converted into a structured text through a voice recognition model, an instruction intention is analyzed through a large language model and a semantic analysis model, robot control parameters are generated, and a multi-modal interaction control signal is obtained; based on the multi-mode interaction control signal, a camera is called to collect image data, the position and category of a target object to be grabbed by the robot are recognized through a target detection model, the moving path of the robot and the grabbing track of the mechanical arm are calculated in combination with laser radar data, and the wheeled robot chassis and the industrial mechanical arm are controlled to execute coordinated actions.

The invention discloses a robot visual interaction control method based on an AI large model, and the method comprises the steps: firstly carrying out the audio preprocessing of an audio sampling result, then inputting the processed data into a voice recognition model and the AI large model, enabling the AI large model to carry out the classification and analysis of a text, and obtaining a voice recognition result; whether the voice recognition result is an intelligent control problem or an intelligent interaction problem is judged, control or reply is carried out respectively, a control command is sent to the intelligent terminal equipment, a reply text is input into the voice synthesis model, and a synthesized reply audio is obtained; and inputting the synthesized audio into an AI counterpart model to synthesize a digital human interaction video, and broadcasting reply content by an AI digital human. The large model and the natural language audio data are synthesized into the face action of the digital human, the visual interaction effect of the intelligent interaction control system is greatly improved, meanwhile, better scene landing is achieved by adopting the fine-tuning large model, the generalization ability of the system is improved, the multi-platform intelligent home equipment control method is achieved, and the application range is wide. And the method has extremely high expandability.

The invention relates to the technical field of computers, and discloses an interaction control method of intelligent glasses. The method comprises the following steps: synchronously acquiring multi-modal data such as eye movement, voice, gestures and head postures and environment and application context information; carrying out independent time sequence feature coding on each modal data; generating a modulation vector in combination with the context, and outputting probability distribution of user intentions through a cross-modal attention fusion network; and a unique execution instruction is determined through an instruction arbitration module based on rules and a state machine. The system comprises corresponding function modules. According to the method, the accuracy, robustness and naturalness of interaction are improved through multi-modal synchronous fusion and a context self-adaption mechanism.

The invention discloses a virtual experience interaction control method based on a virtual environment and a related device, and the method comprises the steps: loading a corresponding virtual interaction experience scene to a VR head-mounted display device based on a virtual experience game after an experience user wears the VR head-mounted display device and selects the virtual experience game; associating and generating a three-dimensional virtual character at a specified position of the virtual interaction experience scene based on the three-dimensional character model; acquiring a current motion trend based on capturing the current motion trend of the experiencing user; updating the position and the motion trend of the three-dimensional virtual character in the virtual interaction experience scene based on the current motion trend to obtain an updated position and an updated motion trend of the three-dimensional virtual character; and adjusting interactive experience elements in the virtual interactive experience scene based on the updated motion trend, the updated position and the gaze tracking result. In the embodiment of the invention, seamless connection between the virtual environment and the real action is realized, so that the interactive experience is more natural and smoother.

The invention discloses an interactive travel guide system based on an AR technology, and relates to the field of travel guide. Through the three-dimensional virtual tour guide generation module and the historical scene miniature reduction module, a unique virtual tour guide image is constructed in combination with local cultural characteristics, and a historical scene is presented in a miniature model manner, so that a user can intuitively perceive the original appearance and change of a relics or cultural place, and the manner greatly enriches tour guide contents and improves the tour guide efficiency. According to the method, the cultural cognition depth of tourists is improved, the immersion and interestingness of sightseeing are enhanced, and compared with traditional character labeling or static information superposition, a more vivid and visual historical culture display means is provided. Besides, the data processing and interaction control module is used for dynamically updating the presented virtual tour guide information and the historical scene restoration content, and the personalized interaction mode not only improves the flexibility of tour guide, but also can adjust the display content according to the real-time feedback of the user, thereby meeting the diversified requirements of tourists.

The invention discloses a display equipment intelligent voice interaction method based on a large language model, and the method comprises the steps: constructing a set of display equipment intelligent voice interaction system suitable for a complex scene based on a large language model technical framework through integrating a multi-stage audio processing module, an intelligent voice recognition module, a semantic understanding and intention recognition module and a multi-mode interaction control module; the voice enhancement technology is adopted, high-precision voice instruction capture and noise reduction processing can be achieved in a noisy environment, and geographic space parameters and operation logic implied in user intentions are accurately analyzed in combination with a deep semantic analysis engine; through a multi-mode fusion control mechanism, real-time linkage interaction between a voice instruction and display equipment is supported, natural and smooth voice control experience is provided especially for scenes such as three-dimensional space positioning and topographic data calling in a holographic geographical environment, and the system has strong error recovery capability and good expansibility and is suitable for being popularized and applied. The method is especially suitable for a voice control interaction scene in a holographic environment.

The invention discloses an interaction control method and system for an intelligent agent and a front-end and back-end system, and the method achieves the automatic control of the intelligent agent on the front-end and back-end system through the integration of a large language model. The method comprises the following steps: an intelligent agent performs natural language intention recognition through a large language model, automatically selects a proper tool, extracts parameters required by the tool, converts the intention into a target task, generates a structured control instruction, maintains a complete session history and supports multiple rounds of dialogue interaction; the back end receives a user request, calls an intelligent agent to generate a structured instruction, transmits the structured instruction to the front end, and dynamically adjusts a subsequent instruction according to the received front end feedback; and the front end receives the instruction transmitted by the rear end, automatically identifies an instruction format through a regular expression, performs corresponding operation after parameter verification and feeds back a result. According to the method, unified control of the agent on the front-end UI and the back-end business logic is realized, complex multi-round dialogue and multi-step operation are supported, and the method has a wide application prospect.

The invention provides a game interaction control method and device, a program product and electronic equipment, and relates to the technical field of computers and games. The method comprises the following steps: displaying a first skill control in the graphical user interface; in response to a first trigger instruction for the first skill control, controlling the first virtual character to release a first game skill corresponding to the first skill control; in response to a preset interaction event occurring between the first game skill and a second virtual character in the game scene, switching the first skill control to a second skill control; and in response to a second trigger instruction for the second skill control, controlling the first virtual character to release a second game skill corresponding to the second skill control. According to the method, the occupation of the skill control on the interface space is reduced, the problem of shielding the interface information is improved, the interface display effect is improved, the user operation is simplified, and the user experience is improved.