293 results about "Visual interaction" patented technology

The invention discloses a network security situation awareness and analysis platform based on AI, and relates to the technical field of network security situation awareness and analysis, and the platform comprises a multi-source data collection module which integrates flow, logs, assets and threat intelligence data, and carries out encryption transmission and standardization; the data preprocessing module purifies and optimizes data, and guarantees data quality and sensitive information security; the AI situation awareness analysis module extracts features through a deep learning model, dynamically evaluates the situation and identifies threats; the threat early warning and decision-making module triggers graded early warning and generates a targeted emergency response scheme; the visual display and interaction module displays information in multiple dimensions and supports query and report generation; and the data storage and tracing module adopts a mixed storage architecture, so that the data security and traceability are ensured. The platform integrates multi-source data and realizes situation accurate perception and intelligent decision by means of an AI technology; the early warning is accurate, the visual interaction is convenient, and the intelligent and efficient level of network security protection is comprehensively improved.

The invention relates to the technical field of data processing, discloses a digital twin adaptive decision platform for TBM tunneling and a control method, and aims to solve the problems of single sensing dimension, mutual separation of physical and data models, disjunction of early warning and control links and low man-machine interaction efficiency in the prior art. According to the scheme, the method mainly comprises the steps that multi-source real-time data is collected through a hardware sensing layer, after the multi-source real-time data is processed through a data management and fusion layer, a digital twin model layer constructs a physical-data fusion model and completes risk assessment, finally risk visualization is achieved through an augmented reality interaction layer, and an intelligent control decision-making layer generates a control instruction and outputs the control instruction to a TBM main control system. According to the integrated intelligent decision-making platform and the control method, multi-source perception deep fusion, physical and data model online coupling, risk assessment and equipment control second-level closed loop can be realized, and visual interaction can be realized through augmented reality.

The invention discloses a sewage treatment information intelligent management method, system and equipment based on the Internet of Things, and relates to the technical field of sewage treatment information management, and the method comprises the steps: 1, collecting multi-source water quality data, initializing sensor equipment, and carrying out the primary processing and caching of the data; step 2, carrying out edge intelligent prediction on pollutant concentration and pollution load sudden increase; step 3, establishing a prediction and control response model, introducing a control strategy generation mechanism based on a rule engine and priority tradeoff, and calculating a dosing dynamic sensitivity value; 4, adjusting frequency conversion of a fan, a dosing module and a reflux pump, and feeding back, collecting and uploading in real time; and step 5, performing artificial intelligence strategy center verification and a digital twinborn simulation strategy, analyzing multi-plant load scheduling and implementing optimization measures, and performing visual interaction in real time. The problem of energy and medicament waste caused by lack of a feed-forward pre-judgment mechanism is solved.

The invention provides a vision-based cross-network interaction method and system, and relates to the technical field of intelligent interaction, and the method comprises the steps: obtaining a visual interaction sequence, constructing multi-modal feature representation, achieving cross-domain semantic alignment, deconstructing visual information into a hierarchical control instruction set, and transmitting the hierarchical control instruction set to a target network environment for execution after security classification. And a bidirectional mapping relation graph is constructed to realize incremental optimization. According to the method, semantic bridging between heterogeneous networks can be established, the cross-domain control precision is improved, and meanwhile safe interaction in a network isolation environment is guaranteed.

The invention relates to the technical field of industrial carbon emission monitoring, and particularly discloses an industrial carbon emission visual monitoring method and system based on digital twinning, and the method comprises the following steps: S1, carrying out the collaborative collection and preprocessing of carbon emission data; s2, dynamically updating the hierarchical digital twin model; s3, intelligent early warning and accurate tracing are carried out; and S4, virtual-real linkage visual interaction is carried out. According to the invention, by establishing a multi-factor driven hierarchical iteration mechanism, hierarchical updating and closed-loop verification of parameters-structures are realized, by establishing a space-time correlation-process coupling-mode matching three-dimensional fusion early warning rule, the false alarm rate and the missing report rate are reduced, a visual interaction system of virtual-real linkage is built, the decision-making efficiency is improved, and the decision-making efficiency is improved. And an accurate and efficient carbon emission control technical support is provided for multi-process industrial scenes such as metallurgy and chemical engineering.

The invention discloses a mineral resource metallogenic law simulation and target prediction system based on big data, and relates to the technical field of geological exploration. The multi-source data acquisition and standardization module supports acquisition of five types of data, and the data are preprocessed and then transmitted to the distributed database; mining key elements by using an improved Apriori algorithm, and constructing a correlation graph; building a model based on Unity 3D, and integrating three types of dynamic simulation; performing three-level prediction by using a CNN-LSTM model; three-dimensional rendering and multifunctional display are supported; and automatically updating data, models and rules to form an optimized closed loop. According to the method, multi-source data is integrated to improve ore-forming element recognition comprehensiveness, dynamic simulation fits geological reality, AI prediction is accurate, uncertainty analysis is included, visual interaction is practical, iterative optimization continuously improves efficiency, invalid exploration cost is reduced, and mineral exploration is efficiently guided.

The invention relates to the technical field of hydropower station intelligent operation and maintenance, in particular to a hydropower station equipment operation and maintenance management system with a fault self-diagnosis function, which comprises a data acquisition module, a fault diagnosis module, a decision optimization module and a visual interaction module which are connected in sequence, the data acquisition module comprises a hydraulic parameter acquisition unit, a mechanical vibration acquisition unit and an electrical parameter acquisition unit; the fault diagnosis module comprises a hydropower station feature extraction unit, a multi-physics field coupling analysis unit and a dynamic threshold adjustment unit; the decision optimization module comprises a fault influence tree unit and a maintenance decision optimization unit; the visual interaction module comprises a three-dimensional equipment twinning unit and an early warning traceability unit. Through the fault influence tree and maintenance decision optimization, the remaining service life of the equipment can be effectively predicted, the maintenance time is reasonably arranged, and stable operation of the hydropower station is ensured.

The invention relates to the technical field of heat meter performance test and operation and maintenance management, in particular to a heat supply working condition multi-source parameter real-time acquisition heat meter performance intelligent analysis system, which comprises a working condition simulation subsystem, a multi-source parameter real-time acquisition module, an intelligent analysis engine and data management and visual interaction interface, and a digital twinning virtual calibration module. Multi-dimensional variable working conditions are constructed through the working condition simulation subsystem, the acquisition module realizes high-precision synchronous acquisition, the intelligent analysis engine integrates multiple algorithms to complete data fusion, performance prediction, health degree evaluation and fault early warning, and the data management module realizes whole-process closed-loop management. The heat meter test accuracy and the working condition coverage are improved, intelligent analysis and accurate calibration are achieved, the operation and maintenance cost is reduced, and stable and efficient operation of a heat supply system is guaranteed.

The invention discloses a point cloud three-dimensional reconstruction method and system based on multiple view angles. The data processing flow of the point cloud three-dimensional reconstruction method based on the multiple view angles comprises the steps of time-space synchronization, multi-source registration based on transformation loss and rotation consistency, Li-CoFiNet neural reconstruction, dynamic consistency optimization guided by optical flow and full-flow visual interaction. The method has the advantages of high-precision dynamic reconstruction, stable layout, precise fusion, strong dynamic processing capability, and traceable and interactive results.

The invention relates to the technical field of complex industrial equipment monitoring and digital twinning, and discloses a gas turbine data visualization and intelligent interaction system which comprises a sensor array, a computing unit, a force feedback device, an eye tracker and a display terminal. The system constructs a three-dimensional physical field and corrects a velocity vector by using Kriging interpolation and Euler equation momentum balance, and generates a variable radius flow tube reflecting the compressibility of fluid; calculating mass, momentum and energy conservation residual errors to construct a generalized potential energy field, and generating gradient guide force and self-adaptive damping force by driving force feedback equipment; and dynamically adjusting solving precision and rendering parameters through sight tracking. According to the method, the flow field is reconstructed through physical constraint, multi-modal feedback is introduced, the problem that discrete data feature distortion and single visual interaction are difficult to perceive physical consistency is solved, and high-fidelity reduction of the gas turbine flow field and visual touch synchronous accurate diagnosis of fault types are achieved.

The invention belongs to the technical field of intelligent control, and discloses a robot visual interaction control method and device, electronic equipment and a storage medium, when the electronic equipment is started, an ROS2 communication environment is initialized, and a Qt graphical user interface is loaded; whenever any user interface subpage on the Qt graphical user interface is detected to be switched from the hidden state to the display state, adding one to the count value; when any user interface sub-page is detected to be switched from the display state to the hidden state, subtracting one from the count value; when the count value is changed from 0 to 1, starting ROS2 topic subscription; when the count value is changed from 1 to 0, the ROS2 topic subscription is canceled; by introducing a dynamic binding mechanism of the interface visibility and the ROS2 subscription state, the data subscription is automatically cancelled when the interface component is hidden, so that the continuous receiving and processing of background invalid data streams can be avoided, the CPU resource occupancy rate and communication resources are effectively reduced, the communication load and processing overhead are further reduced, and the operation fluency and response speed are improved.

The invention provides a power distribution network low-carbon operation mode obtaining method, and the method comprises the steps: extracting power quality disturbance and load fluctuation characteristic parameters based on PCA dimension reduction and fuzzy C-means clustering; constructing a three-level evaluation index system, and calculating a comprehensive energy efficiency index through an entropy weight-TOPSIS method; establishing an electrical-information coupling model based on a digital twinborn technology, and injecting a photovoltaic fluctuation and load sudden change scene to simulate and verify a low-carbon operation scheme; solving the multi-objective optimization model through an NSGA-II algorithm, generating a Pareto leading edge, obtaining a low-carbon operation mode, and achieving the global optimization of low-carbon operation through a three-stage evaluation system and multi-objective optimization; visual interaction and automatic calibration are supported, and efficient decision support is provided for low-carbon transformation of the power distribution network.

The invention provides a vehicle remote control driving system and method integrating AR virtual path projection, and relates to the technical field of vehicle remote control. The system constructs a high-precision three-dimensional environment model through cooperative work of an environment sensing module and a data processing and decision module; the AR path generation unit generates a collision-free virtual path and a vehicle dynamic rehearsal picture, and the collision-free virtual path and the vehicle dynamic rehearsal picture are visually presented in an augmented reality mode through the remote control terminal outside the vehicle, so that a driver can obtain comprehensive situation awareness beyond a physical visual field outside the vehicle; and after the virtual path is confirmed or adjusted in combination with the interaction control, the vehicle control strategy unit automatically generates a cooperative control command adapting to the road condition, and an execution mechanism is driven to perform accurate execution. According to the system, the safety and operation confidence of remote control driving are improved, the blind area collision risk is effectively avoided, the trafficability of the vehicle in a complex environment is enhanced, meanwhile, the operation difficulty is greatly reduced through AR visual interaction, and intelligent and user-friendly vehicle exterior remote control driving experience is achieved.

The invention discloses a multi-dimensional network space security intelligent analysis and early warning platform, which relates to the technical field of network security intelligent analysis and early warning, and comprises the following steps: a multi-source network data acquisition module acquires multi-level data and encrypts and gathers an association identifier; the data preprocessing and standardization module filters invalid data to unify a format, and encrypts sensitive information to generate a verification abstract; the multi-dimensional feature extraction module extracts multiple types of features and maps the features to the same vector space; the intelligent security analysis module analyzes threats in combination with a deep learning model and a rule engine; the grading early warning and response module triggers early warning according to grades; the distributed data storage and traceability module adopts a hybrid architecture to ensure that data cannot be tampered and traced; and the visual interaction and management module presents the state in multiple dimensions. According to the platform, multi-source data are integrated to realize multi-dimensional collaborative analysis, and an early warning threshold is dynamically adjusted to avoid false alarm and missing alarm; strategy dynamic optimization, compliance adaptation and full-process tracing are realized, and the network security protection capability is comprehensively enhanced.

The invention relates to the technical field of data management and information systems, in particular to an experimental data management system conforming to GLP specifications, which comprises a data acquisition and standardization unit, a data storage and version management unit, a natural language query and interaction unit, a data quality and compliance verification unit and an audit tracking and authority management unit. According to the method, professional terms and query intentions are accurately analyzed by means of a field-specific language model, intelligent recognition and visual interaction of image data are realized by the multi-modal interaction module, dialogue continuity is maintained by the context dialogue management module, and an association analysis scheme is actively pushed by the intelligent recommendation module. Intelligent retrieval and analysis requirements of animal experiment data are efficiently supported, the compliance and quality of the experiment data are guaranteed, and data risks are effectively identified and handled.

The invention provides a water conservancy model parallel scheduling calculation method, system and equipment, which are applied to a water conservancy model parallel computing scheduling system, the water conservancy model parallel computing scheduling system comprises a computing engine, a visual interaction module, a GIS map and a user interaction interface, and the water conservancy model parallel computing scheduling method comprises the following steps: obtaining a control instruction, the control instruction is sent to the calculation engine; controlling the calculation engine to interact with the visual interaction module based on the control instruction, and obtaining an interaction result; and rendering the interaction result into the GIS map. According to the method, the whole process of the computing power resources is visually displayed, the integration of an algorithm is concerned in a water conservancy model platform, construction in the computing power resources is concerned at the same time, and the computing nodes, the computing unit states, the computing process grouping information and the like are visually displayed in the computing process, so that the computing power resource construction application is assisted to be optimized and improved.

The invention also provides a fusion casting deep well casting intrinsic safety informatization management and control system and a fusion casting deep well casting intrinsic safety informatization management and control method. The system comprises an equipment sensing layer, a region control layer, a data convergence layer, a data center layer and an application layer, the equipment sensing layer is provided with multiple types of industrial Internet of Things sensors; the area control layer adopts a distributed PLC control mode and undertakes production area equipment operation control and collected data preliminary preprocessing. The data aggregation layer realizes protocol conversion, sampling period configuration and data exception filtering and compression through a data acquisition gateway module; the data center layer adopts a remote storage architecture, and deploys a database based on a hyper-converged server; the application layer constructs a safety early warning rule base and a visual interaction interface. By applying the technical scheme, key safety parameter monitoring, risk early warning, intelligent control and visual management are realized, and an industry safety management mode is promoted to be upgraded to intelligentization and refinement.

The invention relates to the technical field of data analysis, discloses an artificial intelligence-based index data attribution analysis method and system, and aims to solve the problems of poor accuracy, timeliness, dynamic adaptability and interpretability of an existing method. The scheme mainly comprises the following steps: accessing a target index, an association index, dimension data and a domain knowledge graph; cleaning and screening the data, and constructing a causal attribution graph structure with indexes and dimensions as nodes and association relationships as edges; using a graph attention network model to identify a core influence factor causing the target index abnormity from the graph under the business rule constraint of the knowledge graph, and calculating the contribution degree weight of the core influence factor; locally updating the graph structure and the model through an incremental learning mechanism; and finally, converting a causal path output by the model into a visual interaction map and a structured report. According to the method, accurate, real-time, self-adaptive and interpretable automatic index attribution is realized, and the method is particularly suitable for risk management and control and business optimization of enterprises.

The invention discloses a man-machine collaborative robot teleoperation method and system based on visual interaction, and belongs to the technical field of robot control and interaction. In order to solve the problems that a traditional teleoperation instruction is not clear, execution is not verified and dependence on a network is high, the method comprises the steps that a robot video stream is displayed on a client; determining a target two-dimensional coordinate in response to a click operation of a user on the video picture; and the coordinates and the three-dimensional environment data space are mapped, and the execution pose of the robot is calculated and verified. The system allows a user to visually specify a target through frame selection / click selection, and a background automatically converts two-dimensional interaction information into an accurate three-dimensional robot instruction subjected to feasibility verification. According to the method, the coordinate precision is guaranteed by introducing the static reference image, batch planning and submission are supported through the task queue to reduce network dependence, and safe, accurate and high-robustness man-machine collaborative operation is realized.

The invention discloses a power transmission and transformation equipment maintenance and overhaul decision generation system, method, product and equipment, and relates to the technical field of power equipment state monitoring and operation and maintenance management, the system comprises a sensing layer, an intelligent brain layer and an application layer, the sensing layer collects multi-source heterogeneous monitoring data; the intelligent brain layer extracts feature indexes through data fusion, constructs a digital twin model fused with a multi-physical field mechanism, adopts an AI algorithm to realize fault prediction and health assessment, and generates a maintenance strategy based on multi-objective optimization; and the application layer provides a panoramic cockpit for visual interaction. Through a technical chain of multi-source data fusion, digital twinning, AI prediction and multi-objective optimization, the limitation of data islands, early warning lag and decision isolation in traditional operation and maintenance is broken through, normal form transformation from passive response to active prediction and from local optimization to global optimization is realized, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. The accuracy, the safety and the economical efficiency of operation and maintenance of the power transmission and transformation equipment are remarkably improved, and the method has wide engineering application value.

The invention provides a CT machine intelligent console system and a control method thereof, and relates to the technical field of CT machines and intelligent consoles. The system comprises a key module, an identity recognition module, an MCU module, a think tank module, a visual interaction module and a voice interaction module, the key module, the identity recognition module, the visual interaction module and the voice interaction module are in communication connection with the MCU module, the MCU module is in communication connection with the think tank module, and the think tank module is in communication connection with an external diagnosis and treatment network; the key module comprises a plurality of CT function operation keys and a plurality of movable key function indication labels, the think tank module comprises a CT equipment control computer additionally provided with an intelligent algorithm library, and the intelligent algorithm library comprises a CT equipment fault solution guide algorithm library. On the basis, the problem that an existing CT machine system is limited in the aspects of information input, fault processing and operation efficiency is solved.

The invention belongs to the technical field of image processing and privacy protection, and particularly relates to a deep face anonymization standardization processing and evaluation system. The system comprises a data preprocessing module, a multi-technology integration anonymization module, a cross-scene test set module, a multi-dimensional evaluation module and a visual interaction module. The data preprocessing module realizes face data standardization processing by unifying image size, resolution and color depth standards and combining Dlib face detection and feature point positioning; the multi-technology integration anonymization module packages mainstream anonymization technologies such as FIT, G2Face, DeepPrivacy and the like, and provides an extensible interface; the cross-scene test set module covers face samples of different illumination, postures and ages; the multi-dimensional evaluation module constructs an evaluation system from privacy protection intensity (re-recognition rate, cosine similarity and the like), image quality (FID, SSIM and the like), attribute maintenance (difference measurement of expressions, hairstyles and the like) and processing efficiency (time / memory consumption); and the visual interaction module supports data uploading, technology selection, result viewing and automatic report generation. According to the method, the problems of no unified architecture and evaluation fragmentation in the prior art are solved, standardized processing and fair evaluation of a face anonymization technology are realized, and a privacy protection technology is promoted to be applied to the ground.

The invention discloses an intelligent computing center-oriented multi-type hardware equipment energy efficiency evaluation system, which realizes dynamic and accurate evaluation of individual and overall collaborative energy efficiency by collecting full-dimensional data of multi-type hardware in an intelligent computing center, and further quantifies the influence of resource interaction on the energy efficiency by establishing a cross-equipment collaborative relation model, thereby improving the energy efficiency evaluation efficiency. A targeted optimization strategy is generated, and a closed-loop management mechanism integrating energy efficiency evaluation, intelligent decision, instruction execution and data traceability is finally formed, so that continuous optimization and improvement of the energy efficiency of the intelligent calculation center are comprehensively driven; the system comprises a multi-type hardware data acquisition module, a dynamic load feature extraction module, a multi-dimensional energy efficiency evaluation module, a cross-device collaborative modeling module, a dynamic optimization decision module, a visual interaction module and a data storage and traceability module.

This application relates to a motorcycle, which includes: a main body, wheels, a suspension system, a power system, a control system, a headlight system, and an interactive device. The interactive device includes a control module and a visual interaction module. The visual interaction module includes a printed circuit board, an LED module, a light-blocking plate, and a diffuser. The aforementioned motorcycle, by incorporating an additional interactive device and employing a combination of dot-matrix LED modules, light-blocking grids, and diffusers, achieves a pixel-block style appearance. This solves the problems of uneven light emission, bright spots, and glare associated with single LED modules, resulting in higher display brightness, more vibrant color display, increased visual interest, and enhanced user interaction.

The invention discloses a complex man-machine cooperation station operation compliance sequential logic verification method and system based on a multi-modal video, and the method comprises the steps: obtaining a standard operation instruction (SOP), analyzing the SOP, and converting the SOP into a formal model with sequential logic constraints; synchronously acquiring a video data stream, an audio data stream and an equipment data stream of the station; performing real-time analysis on the video data stream by using a human-object interaction (HOI) deep learning model to generate structured visual event metadata; taking the visual event metadata as input, and driving the formalized model to carry out state evolution so as to judge the compliance of an operation process; and performing fusion cross validation on the audio data stream and the equipment data stream at a preset key verification node by taking the time window of the occurrence of the visual event as a reference. By fusing fine-grained visual interaction recognition, strict sequential logical reasoning and multi-modal cross validation, high-reliability closed-loop verification can be carried out on operational process compliance and physical result authenticity.

The invention relates to the technical field of intelligent robot behavior control, and discloses a cleaning robot task self-learning control method, which comprises the following steps that a user sends a task instruction to a cleaning robot, the robot generates a task process after analyzing the instruction, and the robot acquires working environment data in real time and performs task learning on the cleaning robot. A cleaning task model is established through a deep reinforcement learning algorithm DQN, cleaning control parameters are generated, cleaning work is carried out, task execution data are collected, the cleaning control parameters are dynamically adjusted according to the task execution data in the working process, after the cleaning work is completed, a user can submit user feedback information, and user experience is improved. And finally, task execution data and user feedback are uploaded to a cloud server, and a user personalized model is established. Through multi-modal data fusion, the behavior evaluation model and visual interaction, the dynamic adjustment and self-learning ability of the cleaning robot in a complex environment is realized, and the cleaning effect, the cleaning efficiency and the user experience are remarkably improved.

The invention discloses a Pandas expression generation system based on visual interaction, and belongs to the technical field of data processing. The front-end interaction layer is used for providing a graphical interface; the logic processing layer is used for converting a Pandas expression character string; and the expression storage layer is used for storing the generated expression in a JSON format. According to the method, a user can intuitively configure a data set, a screening condition, a grouping dimension and a calculation type through a graphical interface, and a system automatically converts configuration into a Pandas expression and stores the Pandas expression; according to the scheme, the problem that a traditional data processing tool depends on the programming capability is solved, the efficiency and autonomy of data processing are improved, and the method is suitable for scenes such as data analysis and business reports.

The invention relates to the technical field of education big data analysis and visualization, in particular to an education data visualization teaching quality evaluation method. Comprising the following steps: acquiring knowledge point structure data based on a standard outline, and constructing a standard knowledge point directed acyclic graph comprising a plurality of nodes and directed edges; collecting multi-modal behavior data of the student in the learning process, wherein the multi-modal behavior data at least comprises homework interaction data, examination result data and classroom interaction data; generating a cognitive impedance thermodynamic diagram reflecting node numerical value distribution by utilizing an individual cognitive impedance network and combining the flow residual error and a cognitive impedance value, and identifying nodes with abnormal numerical values as knowledge chain blockage points; and presetting an impedance evaluation reference, generating a dredging intervention strategy for the knowledge chain blockage point based on the teaching quality evaluation result, and feeding back the dredging intervention strategy to the visual interaction terminal. The method disclosed by the invention reveals a structural reason causing a poor learning effect, and provides a deep diagnosis basis conforming to cognitive logic for teaching quality evaluation.

The invention discloses a simulated hot-air balloon experience system which comprises a hot-air balloon taking cabin and MR visual interaction intelligent glasses. The MR visual interaction intelligent glasses are internally provided with a display device with a display function and a taking cabin real scene storage module storing a fire balloon taking cabin real scene. The control unit is used for controlling interaction between the riding cabin live-action storage module and the outdoor live-action storage module and displaying the riding cabin live-action and the outdoor live-action in the display device, and the display device, the riding cabin live-action storage module and the outdoor live-action storage module are all in signal communication with the control unit. And the riding cabin live-action storage module is in signal communication with the outdoor live-action storage module. According to the simulated hot-air balloon experience system and the method for realizing the system, the effect of hot-air balloon travel can be experienced in a common environment, and the requirement that the hot-air balloon travel can be experienced without going outdoors is met.

The application relates to the field of device control and discloses a control method and device of an air supply device, electronic equipment and a storage medium, which comprises the following steps: generating a target air supply area based on a closed figure drawn by a user in a panoramic view of an operation interface, the panoramic view being a panoramic view of an environment in which the air supply device is required to provide air supply; setting an air supply route and an air supply speed for the target air supply area; and controlling the air supply device to perform an air supply operation according to the air supply route and the air supply speed. The application introduces panoramic view visual interaction, and a user directly circles or selects an area to be air supplied on a panoramic view of a mobile phone or a tablet computer or the like operation interface by using a finger. The user does not need to repeatedly adjust an air supply angle, and the operation object is the physical space itself to which air is finally to be supplied, so that the control threshold is greatly reduced, and the control becomes more intuitive and accurate.