1167 results about "Interaction technology" patented technology

The invention relates to the technical field of building data interaction, in particular to a building engineering interaction method and system based on a BIM model and a medium. The method comprises the following steps: collecting construction site environment parameters and structure response data by using a distributed sensor network; preprocessing the data by an edge computing node; generating standardized environment data and key structure indexes; comparing environment threshold values to identify abnormal events; the method comprises the following steps of: displaying spatial positioning and risk levels through a visual interface, receiving a regulation and control instruction input by a user, dynamically adjusting construction parameters of a BIM model, generating an optimized construction progress scheme, comparing the optimized scheme with an original model to identify a construction conflict area, and generating a conflict resolution report. Through the advanced monitoring technology and construction management technology, the response speed and decision-making efficiency of the building engineering project are improved, and the safety guarantee and resource utilization efficiency in the construction process are improved.

The invention provides a dynamic order making method and device based on multiple rounds of dialogues and electronic equipment, and belongs to the technical field of intelligent interaction. The method comprises the steps of guiding a user to gradually fill in a form through a multi-round dialogue mechanism, generating a question based on a business logic dependency relationship, and mapping a natural language answer of the user into a structured field value in combination with semantic analysis and field dependency management; integrating a business rule engine in a multi-round dialogue mechanism process, executing field-level, logic-level and process-level multi-dimensional verification in real time in a user input process, and dynamically adjusting a verification strategy based on context; constructing and adaptively adjusting a form structure in real time based on a dynamic form generation engine, multi-round dialogue contents and business rules; based on a low-code configuration development platform, in combination with a preset intelligent interaction component and a visual tool, an intelligent filling system supporting natural language interaction is constructed. And the intelligence, flexibility and accuracy of form filling are obviously improved.

The invention discloses a multi-screen voice interaction system and method applied in an automobile cabin, and relates to the technical field of vehicle-mounted intelligent interaction, and the system comprises a voice collection unit which is used for carrying out sound source positioning and collection, carrying out the noise reduction processing of a collected voice signal, extracting features from the processed voice signal, and generating a voice feature vector; the multi-modal sensing unit is used for collecting behavior information and physiological state data of a driver and passengers through multi-sensor fusion, so as to extract multi-modal information; the man-machine interaction unit is used for carrying out space-time modeling on the multi-modal information to generate a scene state vector; and the cooperative scheduling unit is used for realizing multi-screen intelligent distribution and cooperative control. According to the invention, voice instructions of a driver and passengers can be accurately identified, the safety and experience of the driver are improved, changes in different driving environments are dynamically adapted, the operation efficiency and user experience of a vehicle-mounted system are improved, and the intelligence and adaptability of the system are improved.

The invention discloses a multi-mode interaction method for an accompanying robot, and relates to the technical field of robot interaction.The multi-mode interaction method comprises the steps that voice, visual and tactile signals are converted into quantum states through multi-mode quantum state coding, emotion weights are dynamically fused, and unified quantum representation is constructed; the dynamic quantum decision engine analyzes environmental noise and user emotion intensity in real time based on a quantum measurement theory, generates an adaptive strategy through dynamic modal weight distribution, and solves a multi-modal instruction conflict; holographic reinforcement learning optimization is combined with quantum acceleration calculation and classical reinforcement learning, the reward function weight is dynamically adjusted, cross-modal knowledge migration is achieved through the quantum tunneling effect, and the system strategy is continuously optimized. The problems that a traditional multi-mode interaction system is rigid in mode switching, high in emotion recognition error rate, lack of self-adaptive optimization of a feedback strategy and the like are solved, and the interaction efficiency and the user experience are improved.

The invention relates to the technical field of voice interaction, particularly discloses an AI intelligent robot voice interaction method and system, and aims to solve the problems of low voice interaction accuracy, insufficient reliability and lack of authority control in a complex noise environment. A dynamic noise feature library containing steady-state noise, impact noise and human voice interference features and a pre-stored gesture instruction library are constructed, audio signals are collected in real time, low-frequency-band, middle-frequency-band and high-frequency-band differential noise reduction is executed, Mel-frequency cepstral coefficient features are extracted, noise scenes are matched, corresponding voice recognition models are switched, and voice recognition is achieved. And calculating a confidence value of the voice instruction, outputting multi-modal verification data in combination with a dynamic confidence threshold, and outputting an authority control signal through voiceprint matching, authority verification and instruction consistency judgment. Through multi-modal fusion, dynamic adaptation and authority control, the voice recognition accuracy and interaction safety in a complex noise environment are remarkably improved, and the method is suitable for scenes such as factory intelligent inspection.

The invention relates to the technical field of computer vision and human-computer interaction, and discloses an AI digital human intelligent interaction method, system and equipment based on multiple modalities, and the method comprises the steps: pre-awakening a digital human when a human face is detected, and further thoroughly awakening the digital human based on recognized preset voice information or preset gesture information; voice and video information of a user in the interaction process is obtained, a keyword extraction result, a gesture recognition result and an emotional state tag are generated, a pre-constructed knowledge base is utilized to retrieve related information, a big language generation model module is combined to generate an answer text, and the answer text is input into a preset voice synthesis model to generate emotional voice output. And based on the current emotional state label of the user, driving the digital human animation to be output in an emotional manner. According to the method and the system, the digital human for understanding the emotion of the user, generating personalized answers, providing voices with rich emotions and displaying natural expressions and actions can be created, better interaction with the user can be realized, and more humanized and effective services can be provided.

The invention discloses a database interaction method, device and equipment based on multi-agent cooperation and a medium, and relates to the technical field of database interaction. The method comprises the steps of obtaining a query request, performing semantic partitioning and vectorization, and obtaining a retrieval vector set; and selecting a search source and searching to obtain an information block. And obtaining candidate knowledge through knowledge base retrieval. And integrating the information blocks and the candidate knowledge to obtain a candidate information set. And constructing a dynamic demand understanding model according to the query request and the candidate information set, and obtaining a task state matrix and a tool calling task. And calling a corresponding auxiliary tool and operating, updating the task state matrix according to an operation result and returning the task state matrix to the task planning agent to update the tool calling task until the tool calling task is no longer output, and obtaining a task result. And when the database interaction module is called, generating a chart according to an output result of the database interaction module, and outputting the chart and a task result together. Otherwise, directly outputting a task result.

The invention, which relates to the technical field of intelligent interaction, discloses an AI-based adaptive scene intelligent interaction system comprising a multi-modal data acquisition module, a modal preprocessing module, a multi-modal embedded coding module, an intention fusion and representation module, a service scene matching module and a service execution and reinforcement learning module. The method comprises the following steps: acquiring multi-modal original data in a user interaction process, including voice signals, text input and user behavior tracks, and synchronously recording an acquisition timestamp; according to the method, through a multi-modal unified embedding and dynamic weighting mechanism, the problem of characteristic dimension imbalance is effectively solved, and the user intention recognition accuracy is improved; meanwhile, reinforcement learning and a multi-factor scoring model are combined, personalized scene matching and dynamic response are achieved, the adaptive capacity and service accuracy of the system in a complex environment are improved, and therefore the stability and user experience of the intelligent interaction system are remarkably optimized.

The invention discloses a voice interaction system and method based on an artificial intelligence technology, and relates to the technical field of voice interaction, and the method comprises the steps: employing the double-layer cooperative recognition of a main channel Transform model and an auxiliary channel CTC-Attention mixed architecture, obtaining a text with a multi-dimensional feature label, carrying out the scene classification and dependency syntactic analysis through a bidirectional recurrent neural network, and obtaining a multi-dimensional feature label text; retrieving associated entities in real time and generating structured intention data in combination with a dynamic knowledge graph, executing three-dimensional analysis through an interpretability engine and generating a multi-dimensional traceability report, and triggering an intelligent decision fusion engine through a confidence threshold to generate structured enhanced interaction data; according to the method, scene classification and dependency syntactic analysis are carried out through the bidirectional recurrent neural network, the associated entities are retrieved in real time in combination with the dynamic knowledge graph, and the structured intention data are generated, so that the intention of the user is accurately understood, and personalized interaction services are provided.

The invention relates to a multi-modal fusion real-time digital human driving method based on unified behavior vector mapping, and belongs to the technical field of human-computer interaction. The method comprises the following steps of: 1) extracting multi-modal features of voice, action and vision, and generating input features by adopting language feature-emotion decoupling, staged action modeling and macroscopic-micro expression flow analysis; (2) cross-modal collaborative alignment and conflict correction are carried out, and high-precision fusion is realized through knowledge graph constraint time sequence decomposition, particle-by-particle interactive fusion and a situation-driven modal dominant strategy; and 3) constructing a three-dimensional behavior vector space, mapping the multi-modal features to a unified coordinate by utilizing honeycomb grid projection, and driving the digital human to output in combination with a coordinate-action mapping table. According to the method, the problems of difficulty in multi-modal time sequence alignment, feature isomerism and out-of-control conflict are solved, real-time interaction of naturalization, emotional and scenarized is realized, and the expressive force and adaptability of the digital human are remarkably improved.

The invention relates to the technical field of man-machine collaborative interaction, and discloses a resource allocation method and system in a man-machine collaborative decision-making scene, and the method comprises the steps: generating corresponding task features based on the three dimension indexes of task complexity, knowledge density and intelligent adaptation degree of a to-be-processed task; initializing initial weight coefficients of the three-dimensional indexes, and dynamically optimizing the weight coefficients corresponding to the three-dimensional indexes by using a preset strategy network according to the task characteristics and the real-time system resource state; performing weighted normalization on the three-dimensional indexes according to the weight coefficient to generate a task comprehensive score; task priorities are divided according to the task comprehensive scores, and the tasks are dynamically allocated to manual and / or intelligent systems to execute the tasks according to the priorities, so that the flexibility of artificial experience and the high efficiency of the intelligent systems can be brought into full play, man-machine labor division is flexibly adjusted according to task characteristics, and the universality of cross-task scenes is improved. And the dynamic adaptability, decision reliability and task execution efficiency of the man-machine cooperation system are improved.

The invention relates to the technical field of man-machine interaction, and discloses a touch screen control method and device and electronic equipment. The method comprises the steps that S1, it is detected that a user generates a touch starting event in a screen edge area, touch track data are collected, and the track data comprise touch position coordinates, pressure values and corresponding timestamps; s2, constructing the touch track data into a track function with continuous time, and obtaining speed information, acceleration information and track steering change characteristics of a track; and S3, according to the speed information, the acceleration information and the track steering change characteristics, calculating a group of track dynamic characteristic indexes representing track naturalness. By adopting a combined judgment technology of track naturalness and structural complexity, the naturalness and the complexity of the touch track can be accurately recognized, and a high-precision gesture recognition effect is achieved. Compared with the scheme depending on the touch position and speed in the prior art, the method can effectively distinguish mistaken touch and effective touch, and the problem of frequent misoperation is solved.

The invention discloses an intelligent interaction system based on a large language model and a knowledge graph, and relates to the technical field of artificial intelligence and intelligent interaction. According to the system, data processed by a data acquisition and preprocessing module is stored in a local knowledge warehouse in a three-layer nested structure; the multi-modal semantic understanding module constructs a knowledge system in which a triple knowledge graph and a vector database are complementary by optimizing a BERT model and performing dual-channel analysis; the intelligent interaction module realizes natural language interaction and business task automatic triggering based on an RAG technology and a dialogue memory mechanism; the information change identification and analysis module generates a personnel change risk report and performs early warning; and the summary report automatic generation module outputs a structured report. According to the method, the problems of data splitting, complex interaction and slow response in traditional enterprise management are solved, the functions of system intelligent question answering, personnel change risk analysis, structured report automatic generation and the like are realized, and the management efficiency and the information consistency are improved.

The invention discloses a water ecological environment decision response intelligent interaction system based on AI natural language processing, and the system carries out the data collection and preprocessing, and forms a training set. In combination with the training set, data annotation and feature engineering are carried out, and AI model training including data segmentation, a training method and transfer learning is further carried out; on the basis, continuously collecting monitoring data, and inputting the monitoring data into the trained AI model for real-time prediction; data analysis and decision support are carried out; and once an abnormal trend is detected, an early warning mechanism is triggered. Through an AI large model technology in the vertical field, big data and an artificial intelligence algorithm are utilized to simulate and improve intelligence, convenience and precision of water ecological environment supervision, through combination of an AI large model and an intelligent voice interaction technology, based on analysis and processing capability of the AI large model, deep analysis is performed on water ecological environment data, and a water ecological environment monitoring result is obtained. And managers are helped to quickly make scientific decisions.

The invention discloses an Android system user interface interaction method and device based on a large language model, and relates to the technical field of intelligent man-machine interaction, and the method comprises the steps: receiving a natural language instruction of a user, and synchronously capturing a real-time interface state of a current Android screen to generate a structured context containing semantic information of interactive elements; inputting the instruction and the context into a large language model, and generating a hierarchical task plan formed by a plurality of atomic operations with a logic dependency relationship; based on a dynamic adaptation mechanism, converting the atomic operation sequence into an operation instruction which can be executed by the Android system; receiving interface change information after instruction execution, and feeding back the interface change information as a new round of context to the large language model to determine a task execution state; and finally generating natural language feedback information to the user according to the execution state. By means of the mode, complex cross-application tasks can be understood and executed, and interaction intelligence of the Android system is remarkably improved through real-time interface perception and dynamic planning adjustment.

The invention provides a passenger cabin service intelligent auxiliary system based on a multi-modal interaction technology. The passenger cabin service intelligent auxiliary system comprises a multi-modal information acquisition module, a passenger intention identification module, an intelligent service scheduling module, a multi-modal feedback module and a data management and self-learning module. According to the passenger cabin service intelligent auxiliary system based on the multi-modal interaction technology, the demand identification accuracy is high, the emergency response speed is extremely high, the workload of a steward is greatly reduced, and the service efficiency is greatly improved; health monitoring and early warning accuracy is extremely high, block chain evidence storage guarantees data integrity and traceability, and safety is enhanced; the federated learning-driven recommendation system greatly improves the satisfaction degree of passengers, the holographic projection interaction naturalness score is high, the personalized experience is optimized, various complex scenes such as day and night, bumping and strong light are supported, the system availability is extremely high, and the environmental adaptability is good; and multi-modal deep fusion is realized, and high-precision interaction is still kept under environmental interference.

The invention relates to the technical field of robot control and somatosensory interaction, and particularly discloses a knee joint exoskeleton robot control system based on somatosensory interaction. The system comprises a somatosensory signal acquisition and fusion module, a personalized dynamic model construction module, an adaptive intention decision module, a variable impedance compliance control module and a rehabilitation process evaluation and parameter self-tuning module. Through cooperative work of the modules, precise recognition of the motion intention of a wearer, online construction of an individualized biomechanical model and flexible and adaptive motion control are achieved, control parameters can be automatically adjusted according to the rehabilitation process, and therefore the flexibility and individuation level of man-machine interaction and the effectiveness of rehabilitation training are improved.

The invention relates to the technical field of man-machine interaction, in particular to a dialogue Agent interaction method based on multi-modal intention understanding, which comprises the following steps: S1, collecting multi-modal data in a user interaction process in real time, and calculating a time synchronization deviation value of each modal data source; s2, constructing a space-time fusion feature vector; s3, analyzing a dominant action instruction and a recessive behavior clue in the space-time fusion feature vector; s4, generating a multi-level intention analysis tree; s5, when the corrected confidence coefficient of any node in the intention analysis tree is lower than a set threshold value, activating a targeted sensor to complementarily collect data; and S6, analyzing a tree drive response decision according to the finally confirmed intention. According to the method, high-precision identification and response control of the dialogue Agent on the user intention in a complex scene are realized by constructing a multi-modal interaction method with space-time consistency fusion capability, an explicit and implicit intention analysis mechanism and an adaptive modal clarification strategy.

The invention provides a low-altitude typical scene-oriented aircraft cockpit simulation method, system and device and a storage medium, and the method comprises the steps: constructing a dynamic extensible low-altitude scene library through fusing mixed reality (MR) and a high-precision digital twin model; in combination with a man-machine in-the-loop multimode interaction technology (eye movement-gesture-voice cooperation), the operation naturalness is improved; and an intelligent optimization algorithm driven by reinforcement learning is introduced, adaptive adjustment of flight control parameters is realized, and finally a'perception-decision-evaluation 'closed-loop training system is formed. According to the invention, digital twinning, mixed reality (MR), multi-modal sensing and adaptive control technologies are fused, pilot low-altitude flight skill training, man-machine work efficiency evaluation and intelligent aircraft control system verification are carried out, and the method can be expanded to UAM operator training and unmanned aircraft simulation testing. The technical barrier of low-altitude flight skill training at present is solved, and the technical blank of low-altitude dynamic scene simulation is filled up.

The invention relates to the technical field of intelligent equipment interaction, in particular to an intelligent equipment intention rapid insight and intelligent response method, which comprises the following steps: acquiring multi-modal interaction data input into intelligent equipment by a user, and generating a standardized intention input vector; performing hierarchical feature extraction on the standardized intention input vector, and outputting a fusion intention feature matrix; inputting the fused intention feature matrix into an intention classifier to obtain initial intention probability distribution data of the user; dynamically correcting the initial intention probability distribution data based on the historical intention record to generate a final intention judgment label; the optimal response action set is matched from the intention response strategy library on the basis of the final intention judgment label, the characteristic representation capacity is improved through multi-modal fusion, intention continuity understanding is enhanced through dynamic context perception, response self-adaptive optimization is achieved through reinforcement learning, and therefore the intention recognition accuracy can be improved in the noise environment, and the intention recognition accuracy is improved. And response delay is reduced.

The invention discloses an Internet of Vehicles vehicle information interaction system based on a YTS engine, and relates to the technical field of vehicle information interaction, a data acquisition module fuses multi-source sensing data, and an AI computing power optimization module adopts a dynamic computing power scheduling strategy; the 3D modeling and physical simulation module ensures the real-time performance of modeling based on an AI-driven 3D environment reconstruction and physical simulation technology; the cloud cooperative computing module processes multi-vehicle data in a distributed manner by using a cloud computing architecture of a YTS engine, optimizes a local model and improves the accuracy of an automatic driving decision; and the intelligent interaction module adaptively adjusts a modal man-machine interaction mode according to the dynamic change of the automatic driving decision, so that the driving experience is improved. The technical bottlenecks of information interaction delay, insufficient 3D modeling precision, poor decision stability and the like of the existing vehicle networking system in a high-speed dynamic environment are broken through; efficient energy consumption management, intelligent cloud optimization and accurate interaction are realized, and the safety and reliability of automatic driving are improved.

The invention belongs to the technical field of man-machine interaction, and discloses a diagnosis and treatment auxiliary system and method based on a voice gesture interaction technology, and the system comprises a voice recognition module which is used for collecting voice information; converting the voice information into text information; inputting the text information into the large language model to obtain a voice system instruction, and sending the voice system instruction to the data processing and interaction module; the gesture recognition module is used for collecting diagnosis and treatment scene information; identifying a preset operation gesture in the diagnosis and treatment scene information; mapping a preset operation gesture into a gesture system instruction and sending the gesture system instruction to the data processing and interaction module; the data processing and interaction module is used for receiving and executing a voice system instruction or a gesture system instruction; generating a calling instruction according to the voice system instruction or the gesture system instruction and sending the calling instruction to the network communication module; converting the received medical record data into diagnosis and treatment data in a display format; the network communication module is connected with a hospital information system; the calling module is used for calling medical record data after receiving a calling instruction of the data processing and interaction module and sending the medical record data to the data processing and interaction module; the display module is used for displaying the diagnosis and treatment data. The problem that a doctor cannot conveniently operate a computer to check patient data due to the sterility principle in the diagnosis and treatment process is solved, the diagnosis and treatment efficiency is improved, infection control is facilitated, and the sterility principle is met.

The invention provides a multi-intention processing method and device for a smart home, electronic equipment and a storage medium, and relates to the technical field of man-machine interaction. The smart home system can first judge whether intention conflicts exist among the different intentions, and if the intention conflicts exist, the smart home system can first calculate a first priority score corresponding to the intention map and a second priority score corresponding to the secondary intention; the method comprises the following steps: acquiring a first priority score and a second priority score, then performing strategy selection according to the first priority score and the second priority score, determining a conflict resolution strategy for the deliberate map and the secondary intention, and then executing a control instruction corresponding to the conflict resolution strategy, thereby improving intention understanding accuracy and response efficiency, and improving intention understanding experience. And the capability and decision of the system on complex intention conflicts are improved, the timeliness and flexibility of control instruction response are guaranteed, and the accuracy of system response is improved.

The invention relates to the technical field of man-machine interaction, and discloses an intelligent man-machine interaction system based on meta-universe, which is used for solving the problem of lagging caused by the fact that each virtual module possibly initiates response at the same time during man-machine interaction, and comprises the following steps: constructing a meta-universe scene, collecting multi-modal behavior information of a user in the meta-universe scene, and displaying the multi-modal behavior information of the user in the meta-universe scene. Performing unified formatting processing on the multi-modal behavior information to obtain formatted multi-modal behavior information, and performing joint reasoning on the formatted multi-modal behavior information by adopting a natural language processing engine and a multi-modal fusion model to obtain structured command data; the method comprises the following steps: obtaining a virtual module in a meta universe scene needing to make a response action according to structured command data, recording the virtual module as a driven module, obtaining priority information of all the driven modules, evaluating to obtain a priority index, and driving the modules to make the response action according to the priority index, thereby effectively improving the interaction response efficiency and the user experience continuity.

The invention discloses an e-commerce virtual scene generation method and system based on digital twinning and visual interaction, and belongs to the technical field of computer interaction. According to the method, the basic data set of the e-commerce scene is acquired, and then scene modeling is performed by using digital twinning, so that the initial virtual scene model containing the three-dimensional space layout of the commodity and the visual features of the environmental elements can be generated; performing visual interaction feature analysis on the initial model, and innovatively mining user interaction attention region features and interaction operation preference features as key bases for optimizing the virtual scene; and on the basis of the characteristics, interaction optimization adjustment is performed on the initial model, and finally the e-commerce virtual scene supporting dynamic visual interaction is generated, so that the user interaction experience of the e-commerce scene is comprehensively improved, the crossing from the traditional static display to the dynamic and intelligent interaction experience is realized, and the immersive interactive e-commerce virtual scene construction is realized.

The invention relates to the technical field of engineering drawing interaction, and provides a CAD instruction optimization method and system combined with user behavior analysis. The method comprises the following steps: identifying a CAD operation task which is performed by a user and performing scene analysis to generate a CAD task scene; on the basis of a CAD task scene, instruction personalized configuration based on the operation frequency and the operation path is executed, primary optimization of an instruction toolbar is completed, and real-time operation characteristics of a user are continuously monitored; instruction continuity prediction based on the CAD base file is performed based on the real-time operational features to predict a continuity instruction to complete quadratic optimization of the instruction toolbar. According to the method and the device, the technical problems that the adaptability of the instruction toolbar is poor and intelligent optimization is difficult to perform according to operation habits of different users in the use process of a user in an existing CAD system are solved, and the technical effects of realizing personalized configuration and continuous optimization of the instruction toolbar through user behavior analysis, improving CAD operation efficiency and enhancing user experience are realized.

The invention discloses a duplex-screen intelligent cabin interaction method and system, and relates to the technical field of intelligent cabin interaction, and the method comprises the steps: collecting user operation behavior data, vehicle state data and environment perception data in real time through a vehicle-mounted sensor group, a man-machine interaction interface and a vehicle bus; establishing a multi-dimensional user data model containing an interaction feature vector, a driving mode matrix and a preference configuration tree; the method comprises the following steps: analyzing user historical interaction data based on an adaptive weighting algorithm, and calculating use frequency weight coefficients of different functional modules; according to the duplex-screen intelligent cockpit interaction method and system provided by the invention, the precision of a user portrait is remarkably improved by constructing a multi-dimensional user data model, personalized interaction experience is realized, and the interface layout and interaction logic can be dynamically adjusted according to a real-time driving scene by adopting a self-adaptive weighting algorithm and a random forest classifier, so that the user experience is improved. The real-time performance and the adaptability of the system are enhanced, and the interaction experience is optimized.

The invention provides a medical aid decision-making method and device, relates to the field of intelligent medical treatment, and adopts three models with different capabilities to cover different plates of a whole inquiry process, thereby effectively reducing common illusion problems of a large model. The triage route is responsible for a special medical logic reasoning model, and it is ensured that the patient is accurately guided to the needed medical service. The multi-modal model is responsible for collecting the complaint information of the patient through an efficient voice interaction technology, meanwhile, effective communication and recording are carried out, and detailed data support is provided for follow-up diagnosis. The medical expert model realizes semantic alignment on medical data through special training, can deeply understand slight differences in expression of patients, and further improves the accuracy and efficiency of diagnosis and treatment.

The invention relates to the technical field of man-machine interaction, and discloses a multi-modal task interaction assisting method and system and computer equipment, and the method comprises the steps: collecting multi-modal interaction data of a user executing a multi-dimensional interaction task; determining a user behavior feature vector based on the multi-modal interaction data, and constructing a task completion quantitative model; determining the weight of each operation step by adopting a dynamic weight distribution strategy based on the multi-dimensional interaction task completion degree quantification model, and dynamically adjusting a preset adaptive coefficient by adopting a preset adjustment mechanism based on the multi-modal interaction data and the weight of each operation step; generating a dynamic task guiding strategy by adopting a dynamic path planning algorithm based on the weight of each operation step and a dynamically adjusted preset adaptive coefficient; and executing the dynamic task guiding strategy to obtain a multi-modal execution result. According to the method, a complete closed-loop process is formed from data acquisition, analysis, decision making to execution, intelligent services can be provided for middle-aged and elderly users, and the user experience and the task execution efficiency are improved.

The invention relates to the technical field of ceramic teaching, in particular to a handmade ceramic teaching system applying a visual sensor and a use method thereof, and the system comprises a visual perception module, a data processing module, an interaction guidance module, a process knowledge base and terminal equipment integrating the above modules. The method is suitable for scenes such as ceramic technology teaching, ceramic art training and non-inheritance, and aims to improve understanding and operation normalization of learners on the handmade ceramic manufacturing process through intelligent perception and interaction technologies.