2922 results about "Human–robot interaction" patented technology

The invention discloses a mechanical equipment state monitoring method and system based on multiple sensors, and the method comprises the five core steps: multi-modal data collection and preprocessing, dynamic feature fusion, adaptive threshold diagnosis, digital twin fault tracing and predictive maintenance decision. All-domain coverage of equipment is realized through a three-layer sensor network architecture, the problems of data synchronization and interference resistance are solved by utilizing a temperature and vibration integrated sensor, deep fusion and anomaly detection of multi-source data are realized in combination with an attention mechanism, a Gaussian mixture model, a three-dimensional convolutional neural network and the like, and finally a precise maintenance strategy is generated through digital twinning and reinforcement learning. The multi-sensor-based mechanical equipment state monitoring system comprises a sensor network layer, an edge computing layer, a cloud platform layer and a man-machine interaction layer, supports federated learning to protect data privacy, improves real-time diagnosis capability through edge-cloud collaboration, and enhances a reality interface to realize intelligent operation and maintenance interaction.

The invention relates to the technical field of unmanned aerial vehicle cluster control, and particularly discloses an intelligent cooperative flight path planning method and system for an unmanned aerial vehicle cluster system, and the method comprises the steps: firstly constructing a dynamic environment perception model, collecting data through all unmanned aerial vehicle sensors, and carrying out the preprocessing, attention feature extraction and federal learning fusion, and generating a global environment situation map; planning and screening a candidate track set by adopting a particle swarm-genetic hybrid optimization algorithm for adaptive weight adjustment on the basis of the image; a global optimal track consensus is achieved through an improved consensus algorithm and conflict resolution through a distributed collaborative negotiation mechanism and no human-computer interaction evaluation indexes; and finally, monitoring the environment in real time during execution, triggering dynamic re-planning when the environment is abnormal, and ensuring track adaptation through multi-level threshold and incremental planning. According to the method, the unmanned aerial vehicle cluster can quickly respond to the environment change and adjust the flight path, so that the task execution efficiency and success rate of the unmanned aerial vehicle cluster in the complex dynamic environment are improved.

The invention relates to the technical field of medical rehabilitation, and discloses a lower limb weight-bearing gait rehabilitation training system which comprises a data acquisition module, a data processing and analysis module, a patient individualized modeling module, an intelligent decision and control module, a rehabilitation execution module and a man-machine interaction and medical information interface module which are in communication connection through a network. The data acquisition module is used for acquiring multi-modal data of a patient in real time, and the multi-modal data comprises static sign data, dynamic physiological parameters, kinematics and dynamics parameters and non-motion physiological and psychological state data; and the data processing and analysis module is used for carrying out preprocessing, feature extraction and deep analysis on the original data, and outputting a structured patient individualized feature vector and an evaluation result. According to the invention, a patient three-dimensional skeletal muscle digital twinborn model is constructed through the patient individualized modeling module, and in combination with a continuous learning intelligent model library, body sign differences of different patients can be accurately adapted.

The embodiment of the invention provides an excavator handle control system for remote operation, a handle control method based on a Hall sensor is adopted, non-contact rocker data sensing is achieved, the influence of contact and movement abrasion on the service life of a handle is reduced, and the excavator handle control system has the advantages of being high in sensitivity and good in performance; the handle mechanism is more flexible to operate, and the service life of the handle is prolonged; a two-hand cooperative control mode is adopted, and two three-degree-of-freedom handles are used for simulating the driving environment of a real excavator, so that a good remote control effect is achieved, and the feeling of presence of an operator in the remote operation process is improved; the operation habits of a driver are fully considered, the walking and working of the excavator are respectively controlled through combination of different degrees of freedom of the left hand handle and the right hand handle, an operating lever of the real excavator is simulated in the aspects of structure, motion degree of freedom and working range, and the man-machine interaction environment of excavator driving is restored.

The invention relates to the technical field of medical rehabilitation, and particularly discloses an anorectal postoperative rehabilitation nursing evaluation method and system based on a sensor. According to the scheme, the system comprises a multi-source physiological information sensing module, a data preprocessing and feature extraction module, a multi-modal data fusion analysis module, a dynamic risk assessment and early warning module and a man-machine interaction and decision support module, multi-dimensional physiological signals are continuously collected, a rehabilitation state index is generated through fusion, the complication risk is assessed in real time, and the rehabilitation effect is improved. Early warning and accurate nursing decision support are realized, and comprehensiveness and timeliness of rehabilitation evaluation are improved.

The invention relates to the technical field of multi-modal posture recognition, and relates to a multi-modal posture recognition system based on Transform fusion, which fully excavates the complementary advantages of visual information in spatial detail representation and inertial information in time sequence dynamic capture through space-time alignment of multi-modal data and deep fusion based on an attention mechanism. The accuracy and the stability of attitude estimation under the conditions of visual occlusion, rapid movement and complex illumination are obviously improved; posture optimization is carried out by introducing physical constraints such as bone length constancy and joint movement range limitation, and time domain smoothing and contact state correction are applied, so that the precision of the generated three-dimensional posture sequence is ensured, a solid technical foundation is laid for improving the naturalness, safety and intelligent level of man-machine interaction, and the method is suitable for popularization and application. And meanwhile, reliable application and deep development of the intelligent robot in key fields of service robots, virtual reality, remote cooperation and the like are powerfully promoted.

The invention provides a multichannel gas ultrasonic flowmeter, which relates to the technical field of flow measurement and comprises a hardware layer and a software layer, the hardware layer comprises a pipeline, a connecting mechanism, a multichannel ultrasonic transducer, a pressure sensor, a temperature sensor, a wiring terminal box and a control box with an LCD display screen; the software layer comprises a data acquisition module, a preprocessing module, a multichannel speed measurement module, a data fusion module, a dynamic parameter compensation module, a flow calculation module, a man-machine interaction module, a communication module and a storage module. Pipeline section flow velocity information is collected through a multichannel ultrasonic transducer array, and a complex flow state is fitted in combination with a weighted fusion algorithm; the flow is dynamically compensated and corrected based on pressure and temperature; reliable operation of the system is guaranteed by means of hardware redundancy and a software verification diagnosis mechanism, the problems that a traditional flowmeter is low in measurement precision and poor in working condition adaptability are solved, and high-precision and stable gas flow measurement is achieved.

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 discloses a heterogeneous robot control method and system based on an extensible command library, electronic equipment and a storage medium, and the method comprises the steps: dividing a plurality of different types of commands from the angle of robot commands, and defining a unique code for the commands; constructing a hardware-independent command library on the to-be-executed command queue according to the unique code of each command; constructing a command mapping table according to the code of each command under the to-be-executed command queue, and expanding according to the command codes based on the commands to form a command library related to the robot; based on man-machine interaction of a large model, a specific command to be executed by a user is recognized through semantic understanding and command recognition, and then the recognized command is sent to a to-be-executed command queue from a hardware-independent command library through command execution management; and monitoring a to-be-executed command independent of the robot in real time, mapping a command irrelevant to hardware into a specific command of the robot through a robot related command library, and executing the specific command of the robot at the same time.

The invention discloses a surgical operation system with a training or auxiliary function, particularly relates to the field of intelligent surgical operation systems, and cooperatively works through five modules including multi-modal sensing, layered AI decision making, dynamic feedback, closed-loop learning and an expansion interface. MEMS pressure sensing and biological signal fusion sensing are adopted, strategic layer three-dimensional navigation and execution layer magneto-rheological damping control are combined, and an operation whole-process optimization system is constructed; a multi-source data persistent evolution model is integrated through federal learning, and precise man-machine interaction is realized by matching eye movement tracking AR and a variable stiffness touch glove. According to the system, the intraoperative risk identification accuracy is improved, the operation efficiency is improved, third-party equipment extension and doctor skill quantitative evaluation are supported, and the operation safety and the training standardization level are remarkably improved.

The invention provides a robot social adaptive navigation knowledge learning and migration method and system, and relates to the field of mobile robot navigation. Aiming at the problems that an existing path planner lacks time sequence memory and neglects pedestrian social intent, a man-machine co-fusion scene is constructed, a training set containing an expert demonstration path is made, and a recursive generation model is input; designing a recurrent neural network embedded RRT, generating an RNN-RRT planner, and fusing historical information and pedestrian convergence probability in training; new scene loading training parameters are finely adjusted to realize knowledge migration, loss convergence or output RNN final parameters after reaching a preset round number. According to the method, the path anthropomorphism and generalization ability are improved, and the method is suitable for complex human-computer interaction scenes.

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 present invention relates to the field of robotic arm teleoperation technology, and specifically to a construction method and system for real-time teleoperation of a dual arm and hand robot based on vision guidance, which includes setting up a first experimental platform, acquiring pose information of the dual arm and hand robot and a homogeneous transformation matrix of an end joint and transforming a first coordinate system; setting up a second experimental platform; performing calibration by a plurality of cameras and transforming a second coordinate system; obtaining spatial transformation pose information of the end joint of the robotic arm under a tracking state, reading finger pose data, and performing real-time following. The real-time teleoperation system of the present disclosure includes a control system host, an operation glove, an optical locator, a positioning coordinate plate, a marker ball tool, and a dual arm and hand robot. The present disclosure introduces a method of identifying the marker ball tool by the optical locator into the teleoperation control of the dual arm and hand robot, which is more accurate and faster. Meanwhile, the method of remotely controlling the robotic arm by an operator wearing the operation gloves can provide better human-machine interaction function.

The invention discloses a human-computer interaction method and system based on a vision-language-action model, and belongs to the field of human-computer interaction. According to the method, an anchoring ring strategy is adopted to collect human teaching data to finely adjust the VLA model, and then the trained model is applied to an actual human-computer interaction scene. In the data acquisition stage, a first operator guides a master robot to execute task actions, and a slave robot synchronously moves and interacts with a second operator, and returns to a predefined initial position after each interaction; a teaching sample is formed by recording a robot state, an environment image and an instruction text, and a high-quality data set is generated through data enhancement. In the application stage, the real-time robot state, the environment image and the instruction text serve as input, an action instruction is generated through the VLA model, and the robot is driven to complete a cooperation task. According to the method, the data utilization efficiency and the model generalization ability are remarkably improved, the difference between simulation and the real environment is effectively overcome, and efficient, safe and natural man-machine cooperation is achieved.

The invention discloses a large-span truss hoisting and splitting system and method based on digital twinning, and belongs to the technical field of building construction, and the system comprises a physical entity unit, a data acquisition and transmission unit, a digital twinning model unit, a function service and data analysis unit and an application and interaction unit. According to the invention, through real-time sensing of a physical entity state, multi-source data fusion transmission, high-precision digital twinning modeling, intelligent simulation analysis and decision optimization, and fusion of multi-modal man-machine interaction, a virtual control system which is in whole-course synchronous mapping and bidirectional interaction with a physical entity is constructed; according to the method, real-time visual monitoring, trend prediction and risk early warning of the hoisting and splitting process can be achieved, scheme preview and dynamic optimization are supported, virtual-real fusion operation guidance is achieved through the AR technology, and the safety, precision and efficiency of hoisting and splitting operation of the large-span truss are improved.

The invention provides a man-machine interaction method, device, system and equipment and a medium, and relates to the technical field of artificial intelligence, in particular to the technical field of large language models, intelligent assistants and the like. According to the implementation scheme, in response to a received user instruction, an operation instruction generation request is obtained based on the user instruction and function description information of multiple functions; an operation instruction generation request is sent to the server, and the operation instruction generation request is used for triggering the server to apply the cloud large model so as to select at least one function from the multiple functions based on the user instruction and the function description information, and an operation instruction used for completing the user instruction is generated based on the at least one function; and in response to a received operation instruction sent by the server, executing a calling operation for each function in the at least one function based on the operation instruction so as to obtain an execution result of the user instruction.

The invention discloses a method, a system and equipment for voice interaction inside and outside a vehicle and a storage medium, and relates to the technical field of intelligent cabins and human-computer interaction. Identifying an interaction trigger type (in-vehicle active request, out-of-vehicle passive request, or system active trigger) based on the perceived data and / or the vehicle event; determining a corresponding response permission strategy according to the trigger type, and determining whether to allow the system to respond based on the response permission strategy; and if so, calling a large language model to generate a voice text, synthesizing voice by combining external perception characteristics, and broadcasting the voice through a loudspeaker outside the vehicle or a sound box in the vehicle. According to the scheme, three types of interaction intentions including the in-vehicle active request, the out-vehicle passive request or the system active triggering are recognized, the large language model is called to generate the scene-adaptive voice text, and personalized voice synthesis and broadcasting are performed in combination with the external perception characteristics, so that the response efficiency, the expression naturalness and the object adaptability of the in-vehicle and out-vehicle voice interaction are improved.

The invention relates to a leather material cutting robot and a cutting method thereof, and belongs to the technical field of material cutting, the leather material cutting robot comprises a human-computer interaction interface, a CAD / CAM system, a multi-mode visual perception unit, a central processing system, a dynamic compensation cutting unit and a quality closed-loop system, and the multi-mode visual perception unit comprises a high-resolution multispectral imaging module and a 3D scanning module. According to the method, the problems that a traditional leather material cutting robot visual recognition system cannot recognize leather thickness changes, material waste is easily caused by subcutaneous defects, natural curling deformation of leather is difficult to adapt, and the edge precision error is large are solved, the rejection rate can be further reduced through multispectral and 3D defect recognition, and the production efficiency is improved. Three-dimensional dynamic compensation enables edge errors to be further reduced, and real-time force control further reduces the occurrence rate of crush damage.

The invention relates to the technical field of man-machine cooperation, and aims to solve the problems that the traditional man-machine cooperation process mainly depends on a preset flow and timing rhythm control, and is difficult to dynamically capture personnel misoperation, machine response delay or cooperation rhythm imbalance, so that response strategy lagging and low regulation and control efficiency are caused in the face of complex and variable man-machine interaction situations. According to the enterprise intelligent man-machine cooperation method and system, through comprehensive analysis with behavior response offset, cooperation rhythm consistency and a personnel fatigue state as core indexes, a set of intelligent man-machine cooperation process which is distinct in hierarchy, logic closed-loop and sustainable iterative optimization is constructed; the real-time response capability of man-machine cooperation and the production takt time stability are improved, the cooperation efficiency fluctuation can be dynamically monitored, the precise regulation and control strategy is output in time, quantitative evaluation and actual improvement of man-machine cooperation efficiency are achieved, and efficient production of a production line and the quality level of products are guaranteed.

The invention discloses a personalized semantic understanding system for assisting an autonomous mobile platform, and the system comprises a user personalized word meaning library which is used for recording the mapping relation between the user habit expression and the corresponding operation; the fuzzy semantic analysis module is used for identifying fuzzy expression in a natural language instruction of a user and generating a plurality of candidate targets or operation options of semantic generalization; the multi-round context modeling module is used for establishing a semantic context based on session history and performing disambiguation and complementation on current semantics; and the intention generation module is used for converting the processed semantic information into a structured instruction. The personalized semantic understanding system is reasonable in structural design, all the modules cooperate with one another, the effect that 1 + 1 is larger than 2 can be achieved, fuzzy semantic understanding and multi-round context modeling can be conducted, the personalized requirement of a user can be met, semantic understanding precision is high, user adaptability is good, and the personalized semantic understanding system is suitable for man-machine interaction of an autonomous mobile platform.

The invention particularly relates to an atomic business intelligent arrangement device and method. The atomic business intelligent arrangement device comprises an atomic business relation graph intelligent construction module, an atomic business fine management module, a business intelligent arrangement and visual arrangement module and a man-machine interaction module. According to the atomic service intelligent arrangement device and method, full-chain intelligentization from user demand identification, service scene analysis to process automatic arrangement is realized, the service handling efficiency and the service quality are improved, manual correction is supported, the error rate is reduced, the reusability of atomic services is improved, policy scenes can be helped to rapidly fall into the ground, and the service quality is improved. And diversified operation requirements of the user are met, so that the user satisfaction is improved.

The invention belongs to the technical field of voice processing, and discloses an intelligent cockpit multi-mode voice interaction system and method, and the system comprises a voice triggering unit which collects the environment audio and video information in a cockpit, judges whether to enter a voice interaction mode or not through combining with the environment perception parameters in a vehicle, and sends the voice interaction mode to the vehicle; when the voice interaction triggering condition is satisfied, generating a voice interaction input signal matched with the current environment; the mouth shape analysis unit is used for carrying out acoustic feature extraction on the voice interaction input signal, synchronously analyzing the lip motion trail of the driver in the video information, establishing a corresponding relation between voice phonemes and mouth shape motion, and forming a joint analysis feature; the candidate generation unit is used for carrying out segmented alignment on the joint analysis features and constructing a continuous multi-modal fragment sequence; performing time synchronization on the multi-modal fragment sequence, and projecting the multi-modal fragment sequence to a predefined intention space to obtain a candidate intention set containing different candidate intentions; and the man-machine interaction experience of the intelligent cabin is improved.

The invention relates to the technical field of chronic kidney disease screening, and discloses an intelligent chronic kidney disease early screening instrument which comprises a physiological parameter detection module configured to synchronously collect multi-dimensional bio-electricity signals, optical characteristic parameters and body fluid biochemical parameters of a subject and output original signals; the multi-modal data processing module is in communication connection with the physiological parameter detection module and is configured to receive original signals, perform time domain and frequency domain conjoint analysis and construct a parameter incidence matrix; the wireless communication module is configured to realize encrypted interaction between the screening data and the cloud server and block chain evidence storage; and the man-machine interaction module is configured to display the risk level map in real time. According to the method, holographic dynamic correlation modeling of kidney function related micro-electrophysiological fluctuation and optical metabolism characteristics is realized, and a specific cross-modal pathological correlation mode of early renal injury can be effectively identified based on a time-frequency domain combined characteristic extraction and dynamic coupling algorithm.

The invention belongs to the technical field of analog simulation, and particularly discloses an intelligent agent-based dynamic confrontation simulation system, which comprises a data acquisition module, an intelligent analysis module, a decision generation module, an intelligent agent behavior self-adaption module, a training evaluation module and a multi-mode man-machine interaction module, physiological, action, voice and eye movement data of trainees are collected in real time through a multi-modal sensor, and a tactical intention is recognized and a dynamic three-dimensional battlefield situation thermodynamic diagram is generated in combination with virtual battlefield environment parameters; an agent coping strategy is generated based on reinforcement learning and a decision tree, and an agent is driven to carry out real-time confrontation; and performing multi-dimensional quantitative evaluation on the whole training process through a training evaluation module, and performing closed-loop optimization on an agent decision and strategy library based on an evaluation result. The method supports various natural interaction modes such as voice, gestures and eye movement, remarkably improves the fidelity, intelligence and training efficiency of simulation training, and is suitable for the field of military training and tactical drilling.

The invention relates to the technical field of textile machinery, and discloses a covering yarn machine spindle speed and twist control system which comprises a data acquisition module, a global control module, an individual diagnosis module, a power execution module and a man-machine interaction module. The actual average speed of the whole machine is calculated by collecting the speed of each spindle in real time, and PID closed-loop control is carried out on the actual average speed and a set value, so that the systematic speed deviation of the whole machine is accurately corrected. Meanwhile, the individual diagnosis module calculates spindle difference signals of the speeds of the spindles and the average speed of the whole machine in parallel, time domain and frequency domain analysis is carried out on the signals, and hidden faults such as steady-state deviation, periodic fluctuation and transient impact existing in a single spindle are accurately recognized. And finally, the system carries out visual early warning through a human-computer interaction interface and provides a predictive maintenance instruction. According to the method, high-precision control of the twist and high consistency of products are achieved, an effective predictive maintenance mechanism is established, and the production quality and the intelligent level are remarkably improved.

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 relates to the technical field of power station operation and maintenance, and discloses a power station multi-robot collaborative inspection and task optimization scheduling system, which comprises a digital twinborn modeling module used for establishing a digital twinborn model of a power station environment, equipment and multi-type inspection robots, and realizing real-time mapping of a power station physical space and a virtual space through state synchronization; a task modeling and decomposition module; a task and capability matching scheduling module; a dynamic rescheduling module; a cloud edge cooperative control module; a data acquisition and feedback module; and a man-machine interaction and visualization module. Through integration of task node graph construction, robot capability vector modeling, local hot start rescheduling and a digital twin closed-loop self-learning mechanism, distribution continuity can be maintained when tasks change or robot states are updated, and parameters are continuously corrected based on operation data. And cooperative improvement of inspection task execution efficiency, scheduling response speed and system stability is realized.

The invention discloses a machine control system and method based on large language model structured data output, and relates to the technical field of artificial intelligence and robot control. Voice information and image information are acquired through a multi-mode acquisition module, and based on a Gemma 3 large model, a text instruction and a coding image are combined, so that a multi-mode model is obtained; a decision output module generates a structured instruction conforming to predefined JSON Schema, the structured instruction is analyzed by an execution control module to drive a mechanical arm, a memory feedback module is utilized to store interaction data and execute feedback, dynamic switching between a dialogue mode and an action mode is supported, and the mechanical arm is controlled to operate. On the basis of large language model structured output and a multi-module cooperation mechanism, the ambiguity and unreliability of natural language control are effectively solved, and the man-machine interaction precision, the execution reliability and the complex scene adaptation intelligence level are improved.

The invention relates to the technical field of geological engineering, discloses an agent-based three-dimensional geological model auxiliary construction method and device, and aims to solve the problems of low efficiency and accuracy, slow rendering response and few interaction functions of an existing method. The scheme mainly comprises the following steps: generating a three-dimensional generalized model base based on an AI model; performing verification and correction by using a graph neural network to obtain a three-dimensional compliance model base; an optimized geological parameter field is obtained based on Fourier feature mapping and a GeoFormer-PT model; embedding the optimized geological parameter field into three-dimensional software to realize dynamic visualization of a three-dimensional geological model; carrying out visual enhancement on the three-dimensional geologic model; an interactive operation platform is introduced into three-dimensional software. According to the invention, the construction efficiency, accuracy and rendering response speed of the three-dimensional geologic model are improved, and a man-machine interaction function is added.

The invention provides a PID-based clean room intelligent regulation and control system and method. The system comprises a multi-parameter sensing module used for monitoring real-time environment data in a clean room in real time; the data processing module is used for preprocessing the real-time environment data to obtain monitoring data; the PID control module is used for determining the deviation between the monitoring data and a preset target parameter value, and determining an environment control signal based on the deviation; the environment regulation and control execution module is used for regulating the operation state of corresponding environment regulation equipment in the clean room according to the environment control signal; the multi-factor coupling prediction model is used for predicting a change trend of cleanliness according to the real-time environment data and historical environment data in the clean room, and optimizing control parameters of the PID control module based on the change trend; and the human-computer interaction interface is used for displaying real-time environment data, an operation state and a change trend, so that high-precision and high-stability dynamic cooperative control and intelligent prediction of various environment parameters in the clean room are realized.