204 results about "Collaborative interaction" patented technology

The invention relates to the technical field of informatization management systems, and particularly discloses an AI-aid decision-making product full-life-cycle informatization management system which comprises a full-link data sensing module, a digital main line construction module, an AI decision-making center module, a service execution interface module and a man-machine collaborative interaction module. The method comprises the following steps: collecting multi-source heterogeneous data of each stage of a full life cycle of a product through a full-link data sensing module to form a full-amount data sequence with a space-time stamp; and in combination with a data fusion engine, an association graph construction unit and a twinborn model driving unit of the digital main line construction module, data cleaning, alignment, semantic fusion and cross-stage association are realized, a dynamically updated product digital twinborn model is constructed, real-time mapping of a physical entity and a virtual model is achieved, and the real-time mapping of the physical entity and the virtual model is realized. Unified and complete data support is provided for full-link decision making, and the problems of data fragmentation and prominent collaborative barriers of a traditional system are thoroughly solved.

The invention discloses a digital large-screen interaction method and device based on multi-agent cooperation and a medium, and relates to the technical field of digital large-screen interaction.The method comprises the steps that postures, expressions and voice data of a user are collected in real time, the attention weight is calculated in combination with spatial position information, the emotional state change rate is monitored, and the user experience is improved in combination with personal historical browsing preferences; acquiring a main interaction user, an emotional state feature and an emotional change trend; according to the main interaction user, the emotional state features and the emotional change trend, obtaining an initial confidence coefficient of the suspected interested field through a semantic understanding model; and based on the candidate guide images, identifying a user selection intention through a multi-modal fusion processing mechanism, calculating a selection probability, triggering content activation of the main interaction area and content dynamic generation of the auxiliary information area, synchronizing state information, and starting an immersive collaborative interaction process. Through three-level collaborative service configuration, the beneficial effects of improving large screen content organization efficiency and enhancing immersive interaction experience are achieved.

The invention discloses an intelligent fusion analysis and decision support system and method for multi-source heterogeneous data of a spacecraft. The intelligent fusion analysis and decision support system for the multi-source heterogeneous data of the spacecraft and the intelligent fusion analysis and decision support method for the multi-source heterogeneous data of the spacecraft are included. The system comprises a dynamic adaptation access layer, a unified semantic modeling layer, a space-time semantic fusion engine, a digital twin collaborative decision-making center, a knowledge enhancement decision-making auxiliary subsystem, a cross-department collaborative interaction platform and a side cloud collaborative intelligent processing framework. The method comprises the steps of multi-source heterogeneous information dynamic access and semantic modeling, space-time and semantic deep fusion, digital twin driven decision deduction, knowledge enhanced decision assistance, cross-department collaborative decision and interaction, edge cloud collaborative intelligent processing and the like. According to the method, the safety, reliability and decision-making efficiency of spacecraft tasks can be remarkably improved, and the method is suitable for development, testing and on-orbit task stages of various spacecrafts.

The invention discloses an atmosphere lamp control method, electronic equipment and a program product. The method comprises the following steps: acquiring PCM data of an audio signal in real time in the music playing process of a vehicle; performing frequency domain analysis on the PCM data corresponding to each audio frame, and extracting frequency information and loudness information; the method comprises the following steps: calculating frequency information and loudness information of a preset number of continuous audio frames, and respectively calculating a frequency change rate and a loudness change rate within a preset time; respectively comparing the frequency change rate and the loudness change rate with corresponding change rate thresholds; and if at least one of the frequency change rate and the loudness change rate exceeds the corresponding change rate threshold value, a corresponding light updating instruction is sent to the atmosphere lamp control module. The music rhythm function of the automotive interior atmosphere lamp can be enhanced, and the cooperative interaction ability of music and the atmosphere lamp is improved.

The invention discloses a distributed power supply-containing power distribution network coordinated scheduling method, which relates to the field of power distribution network coordination, and comprises the steps of S1, multi-flexibility resource refined modeling and interaction characteristic analysis, S2, power distribution network linear load flow calculation and sensitivity analysis, and after the power distribution network linear load flow calculation and sensitivity analysis in S2 are completed, carrying out power distribution network coordinated scheduling. And S3, generating an uncertainty scene based on the generative adversarial network. According to the coordinated dispatching method for the power distribution network containing the distributed power supply, differences of various resources in control modes, response speeds and adjusting capabilities are analyzed through refined modeling, complementary characteristics of the resources are fully utilized by a collaborative optimization model, an overall optimization effect is achieved, a single type of resources are not optimized in an isolated mode, and the method is suitable for large-scale popularization and application. All adjustable resources such as a distributed power supply, an energy storage system, a reactive power compensation device, a flexible load and an intelligent soft switch are incorporated into a unified modeling and optimizing framework, and deep fusion and collaborative interaction of flexible resources can be realized.

The invention relates to the technical field of power grid energy storage regulation and control, in particular to a power grid energy storage regulation and control method and system considering source-storage-load collaborative interaction. The power transmission node information of the power grid system and the power utilization information of each terminal user are acquired, the power grid system is divided into a plurality of virtual energy storage clusters according to the power transmission node information, and load fluctuation characteristic analysis is performed on the power utilization data of all the terminal users of each virtual energy storage cluster; determining a first importance degree of each load area to the electric energy demand; obtaining a second importance degree of each load area in an abnormal state according to the load power change before and after the power generation fault; and according to the first importance degree and the second importance degree of each load area, correspondingly configuring the electric energy guarantee priority of each load area and supplying power until the power generation fault is repaired. According to the technical scheme, after the power grid system has a power generation fault, cooperative adjustment of the energy storage station, the power supply station and the load end is realized, and the accuracy of electric energy distribution is effectively improved.

The invention discloses a multi-modal remote sensing small target recognition method based on common-differential mode collaborative interactive fusion, and relates to the technical field of image recognition. Performing feature extraction and interactive fusion based on a double-flow backbone feature extraction network in the multi-modal remote sensing small target recognition model to obtain an infrared enhanced fusion feature and a visible light enhanced fusion feature respectively; the infrared enhancement fusion features and the visible light enhancement fusion features output by the corresponding convolution down-sampling module and the output layer in the two backbone feature extraction channels are spliced and then are subjected to neck feature fusion output to obtain a prediction image with a target recognition result. According to the method, infrared and visible light modal features are fully utilized, and common features and difference features of the infrared and visible light modal features are subjected to collaborative modeling and interactive fusion, so that the characterization level of the small target is effectively improved, and recognition of the remote sensing small target is more robust.

The invention relates to the technical field of robots, in particular to a mobile robot remote operation system and method based on mixed reality, and the method comprises an operator end and a robot end, the operator end completes a complex remote operation task based on visual feedback provided by a man-machine cooperation interaction interface, and the robot end completes a remote operation task based on visual feedback provided by the man-machine cooperation interaction interface. The virtual reality controller integrates a motion state and an operation mode of the mobile robot, and the mixed reality server generates visual feedback according to visual information of a remote operation visual angle of the mobile robot; the robot end comprises a mobile robot, a collection device on the mobile robot and a robot server, and after the mobile robot receives a remote control instruction sent by the virtual reality controller to the robot end, posture and button information of the mobile robot are input into the robot server to drive the mobile robot to move. Therefore, the problems of low real-time performance and accuracy of remote control, poor operation efficiency and flexibility and the like caused by limitation of bandwidth and system time delay in related technologies are solved.

The invention relates to the technical field of data processing and artificial intelligence, and particularly discloses a basketball player sport injury risk prediction and rehabilitation training planning system. The system comprises a multi-source data fusion sensing layer, an injury risk dynamic assessment engine, a rehabilitation planning adaptive generator and a man-machine collaborative interaction execution module. Multi-source data of physiology, biomechanics and the like are collected and fused in real time, the damage risk is dynamically evaluated through a depth time sequence diagram neural network, a self-adaptive rehabilitation training prescription is generated based on hierarchical reinforcement learning and a digital twinning model, meanwhile, the execution process is monitored, safety intervention is conducted, and the rehabilitation training accuracy is improved. Personalized dynamic adjustment and safe closed-loop management of the rehabilitation plan are realized, and the rehabilitation effect and safety are improved.

The invention discloses a traffic subject collaborative cognition method based on semantic representation in the technical field of traffic transportation. The method comprises the following steps: S1, collecting original data including state information of a traffic scene and a traffic subject, integrating the original data into perception information through a data fusion technology, and converting the perception information into structured semantic representation information; s2, establishing a multi-mode collaborative interaction architecture for different traffic scenes, dynamically selecting the collaborative interaction architecture according to a real-time traffic state, and performing ordered information interaction according to tasks; and S3, the edge traffic subjects autonomously generate decisions, and the central traffic subject performs overall optimization to realize multi-traffic subject collaborative cognition and behavior consistency. According to the method, semantic mutual understanding among different traffic subjects is realized, and an information barrier is broken; the method realizes the balance between local decision and global optimization, improves the decision efficiency, and has good expandability and adaptability.

The invention relates to the technical field of clean room full-process intelligent management, and discloses a clean project full-life-cycle intelligent management digital twin platform, which comprises a full-cycle data center module, a virtual-real bidirectional interaction engine module, a full-cycle management module and a multi-terminal collaborative interaction module which are connected with one another, the whole life cycle of design, construction, operation and maintenance and decommissioning is covered, whole-course tracing of design-construction-operation-decommissioning is achieved, closed-loop interaction of virtual model rehearsal and entity execution feedback is constructed, and an intelligent decision function is constructed to cover the whole process. Comprising performance rehearsal in a design stage, progress management and control in a construction stage, deep optimization in an operation and maintenance stage and resource evaluation in a decommissioning stage. Through deep fusion of the dynamic BIM model and multi-stage multi-source data, virtual-real two-way interaction and full-period intelligent management, the method is suitable for full-process collaborative management of clean environments such as semiconductors, biological medicines and foods, and full-stage precise management and control from early planning to final decommissioning are realized.

The invention provides a multi-agent collaborative dialogue security control method and system, and relates to the technical field of artificial intelligence, first, a dialogue content set of a current dialogue scene is received, and the dialogue content set comprises an interaction time sequence mark of a dialogue text unit and a participant identity label; scene feature modeling, topic keyword extraction and the like are carried out on the dialogue content set to construct scene feature vectors, and scene categories are divided; and allocating dynamic roles to the plurality of management and control agents based on a classification result, loading corresponding rules and models to identify security risks, and generating a preliminary management and control scheme. And the cooperative interaction agent performs multi-dimensional cooperative verification on the preliminary scheme, and adjusts the confidence coefficient in combination with historical cases to generate a cooperative control decision result. And constructing and executing a final management and control strategy according to a decision result, managing and controlling the dialogue text units with risks, and collecting feedback and risk change data to generate an evaluation report. According to the invention, multi-agent collaboration is realized, different scenes are adapted, and dialogue safety control efficiency is improved.

The invention discloses a teaching content generation method and system based on large model instruction and context knowledge dual drive. The method comprises the following steps: firstly, analyzing, slicing and vectorizing an original knowledge document in the education field through knowledge preprocessing in the education field; then, defining teaching content to generate a prompt word template, and defining a large model instruction, a variable and a context knowledge content block; secondly, arranging teaching content to generate a workflow, and constructing large model instruction driving and context knowledge driving logic; and finally, implementing dual-drive teaching content generation and performing result post-processing. Based on the method, a system corresponding to the method is constructed, and the system comprises an education field knowledge preprocessing module, a teaching content generation prompt word template definition module, a teaching content generation workflow arrangement module, a teaching content generation implementation and result post-processing module and a user man-machine collaborative interaction operation module. According to the method, the teaching content can be generated according with the education rule, the specific teaching scene requirement is met, and the teaching content generation accuracy and applicability are improved.

The invention discloses a multi-terminal cooperative interaction method of an innovative practice teaching experiment platform, and belongs to the technical field of teaching experiment platforms, the innovative practice teaching experiment platform comprises a server, a plurality of terminals and experiment equipment, the terminals comprise a PC terminal, a mobile terminal and an experiment equipment terminal, the method comprises the following steps of terminal access authentication, unified protocol adaptation, resource scheduling and distribution, real-time data cooperative transmission and real-time data cooperative transmission. According to the invention, through the terminal access authentication step, the security of the terminal access platform is ensured, and threats to platform data and resources caused by access of illegal terminals are avoided; meanwhile, an encrypted communication link is established, so that the security of data transmission is ensured; by adopting an adaptive protocol conversion mechanism, uniform adaptation of communication protocols of different terminals is realized, the problem of data transmission caused by non-uniform communication protocols between different terminals in the prior art is solved, and standardization and high efficiency of data transmission are improved.

The invention discloses a multi-modal sensing and edge intelligent decision-making self-adaptive feeding system and method, and relates to the technical field of intelligent logistics equipment, industrial automation and information physical systems, a visual system module is combined with distance measurement, weighing and recognition detection units of a sensor module, multi-modal sensing of the material state and environment is achieved, and intelligent edge decision making is achieved. The edge decision module dynamically optimizes feeding parameters based on reinforcement learning, the edge prediction maintenance module guarantees equipment health, and the system execution module achieves accurate control and cleaning. The feeding method comprises the steps of multi-modal data synchronous acquisition, digital twin model real-time updating, AI multi-target optimization decision making, multi-actuator cooperative action, industrial Internet of Things cooperative interaction and feedback-based iterative optimization, and multi-modal sensing, edge intelligent decision making and accurate execution are fused. Self-sensing, self-decision-making, self-execution and self-optimization in the feeding process are achieved, the feeding efficiency and quality are improved, and accidental shutdown and comprehensive cost are reduced.

The invention relates to the technical field of power systems and energy management, in particular to a source network load storage collaborative interaction optimization system for high-proportion new energy. Comprising a multi-source information sensing data acquisition module used for monitoring various objects and an external environment in real time; the data modeling prediction analysis module is used for constructing a system parameter model and carrying out prediction analysis; the source network load storage collaborative optimization decision-making module is used for realizing multi-time-scale and multi-main-body optimization scheduling; according to the invention, the multi-source information sensing data acquisition module, the data modeling prediction analysis module, the source network load storage collaborative optimization decision module, the execution control instruction issuing module and the like are organically combined, so that the multi-source information sensing data acquisition module, the data modeling prediction analysis module, the source network load storage collaborative optimization decision module and the execution control instruction issuing module are integrated; omnibearing perception and prediction of new energy output, load demand, energy storage operation and power grid state are realized.

The application provides a ConvNeXt model SAR ship classification method based on multi-level feature cooperative interaction. In order to effectively utilize traditional manual features, the method uses a Canny-based edge detection method, captures edge information of objects in an image through multi-level filtering and edge gradient analysis, and inputs the result into a ConvNeXt model for feature extraction. In addition, a multi-level branch structure is expanded in the ConvNeXt model, which is used for deep extraction of feature information at different scales, so as to capture various information of the image at low-level features and high-level features. Finally, cross fusion with traditional manual features is carried out in the multi-scale feature extraction process, so as to improve the classification accuracy of the model.

The invention relates to the technical field of smart community service and real estate data collaboration, in particular to an intelligent and digital driven real estate and community integrated service system. According to the technical scheme, the system comprises an AI intelligent data middle platform, a real estate service intelligent module, a community service digital module, a cross-scene intelligent matching module, a full-process digital operation module, a commercial value increment module, a multi-terminal collaborative interaction module and a safety and compliance management module, all the modules operate collaboratively, and a real estate and community full-service chain is endowed. The business ecology is constructed, the house property and community full-business chain is deeply endowed through intelligent and digital technologies, the problems of insufficient intelligence, data collaboration deficiency, low operation efficiency, weak business value and the like in the prior art are thoroughly solved, and a virtuous circle of technology endowment, business optimization and business value increment is constructed. The method accords with the core appeal of the current capital market for intelligentization, digitization and high growth potential, and has remarkable technical innovation, commercial feasibility and capital attraction.

The invention discloses a city security patrol unmanned aerial vehicle fusing edge agent decision, relates to the crossing field of unmanned aerial vehicle technology and city security technology, and provides the following scheme that the city security patrol unmanned aerial vehicle comprises a vehicle body and further comprises rotor wing assemblies arranged on the periphery of the exterior of the vehicle body in an array mode and used for achieving flight attitude control of the unmanned aerial vehicle; the sensing module is arranged at the top of the machine body. According to the invention, localized processing and decision-making of security and protection data are realized, dependence on a remote control center is not needed, abnormal event identification and processing instruction generation time is shortened to millisecond level, processing lag caused by communication delay is effectively avoided, patrol paths and decision-making strategies can be automatically adjusted according to on-site environments, waiting for remote instructions is not needed, and operation is simple and convenient. The method is suitable for complex and changeable urban security protection scenes, the edge computing power of the unmanned aerial vehicle is fully utilized through cooperative interaction between the edge intelligent agents, idle equipment resources are avoided, the algorithm precision is continuously optimized through an autonomous learning function, and the long-term security protection patrol effect is improved.

The application belongs to the technical field of virtual reality, and particularly relates to a sound-driven VR serious game interaction control method for semi-blind people. The method comprises the following steps: constructing a 3D sound scene space and a motion guide field, and converting a motion path into a sound change rule; collecting and fusing user pose and physiological feedback signals in real time; dynamically adjusting sound source parameters and tactile feedback according to pose deviation to realize non-visual orientation guidance; performing boundary verification and area determination through ray projection to ensure interaction safety; synchronously processing collision by using a bounding box model and quaternion interpolation; and establishing a mapping model of emotional parameters and sound characteristics to synthesize exciting sound effects. Through multi-modal collaborative interaction, the application significantly improves the perception accuracy and safety of semi-blind users in a virtual space, realizes the cooperation of psychological intervention and motion rehabilitation, and has excellent real-time response capability.

The invention mainly discloses a quality detection cooperative interaction suite group, which is used for performing defect detection on a continuous material conveyed by a roll-to-roll mechanism. Particularly, the quality detection cooperative interaction suite set further provides the following functions: (1) intuitively displaying the position of the detected flaw on the continuous material; (2) when the flaw detection result is misjudged, a user (a quality inspector) operates a tablet computer provided by the quality detection collaborative interaction suite group to delete the misjudged flaw detection result online; (3) when a flaw category identification error occurs in a flaw detection result, the user operates the tablet computer to correct the flaw category identified by the error online; and (4) when missing detection occurs, the user operates the tablet computer to add one or more images containing flaws into the database.

The invention provides a hand-eye collaborative interaction system based on eye movement tracking and a pressure ring, which is characterized in that two different modal inputs are subjected to a coarse positioning-fine operation interaction framework with complementary advantages, and specifically, large-range coarse glancing and positioning are completed by using natural and rapid characteristics of eye movement tracking; small-range fine pointing and confirmation are completed by means of the stable and controllable characteristics of the ring pressure sensing device, and the cooperative workflow of'coarse positioning-fine operation 'combining the advantages of rapidness and coarse-grained positioning of eye movement tracking with continuous and high-precision manual control provided by the finger-wearing device is adopted. On the premise that physiological and cognitive burdens of a user are not obviously increased, rapid and stable selection and control of long-distance and high-density virtual objects in the head-mounted display device can be achieved, and coordinate-level precision can be achieved.

The invention discloses a geographic information acquisition and processing device, which comprises a multi-mode driving module, a multi-mode sensing module, a data processing module and a data processing module, wherein the multi-mode driving module enables the device to adapt to flexible movement of different complex terrains on the basis of a multi-mode driving structure; the multi-mode sensing module is used for synchronously acquiring positioning and attitude determination data, three-dimensional terrain data and environment parameter data and performing time-space calibration of multi-source data; the adaptive control module dynamically adjusts acquisition parameters of each sensor based on environment parameters acquired in real time, and the edge calculation module performs real-time compression, target identification and quality evaluation on original data based on a parallel calculation low-power-consumption embedded GPU and an ARM processor. The cloud collaborative interaction module is used for executing collaborative calculation of edge preprocessing and cloud precision processing; through synchronous triggering and space-time calibration, millimeter-level space-time consistency of positioning, terrain and environment parameters is achieved, the data fusion precision is improved, sensor parameters can be dynamically adjusted through the self-adaptive control module, and the problems of signal shielding, illumination change and the like are solved.

The invention provides a voice anti-cheating method and system based on double interactive query, and relates to the technical field of voice recognition. The invention provides an audio understanding model based on double interactive query, aiming at the technical problem that the performance and the efficiency of deep counterfeit voice detection cannot be well considered in the prior art. According to the model, a local mode branch in a double-branch processing module based on cross attention is used for extracting local acoustic artifacts in forged voice, a global context branch is used for capturing global context anomalies, and meanwhile, cross attention mechanisms in the global context branch and the local mode branch are symmetrical layer by layer by using a symmetric collaborative interaction mechanism, so that the local acoustic artifacts in the forged voice are extracted. The two heterogeneous branches are subjected to deep interactive fusion, and global and local representations can be mutually complemented and jointly optimized in the whole network, so that more comprehensive feature representation for forged voice is formed, and the detection precision for known and unknown spoofing attacks is improved while the complexity of the model is remarkably reduced.

This invention discloses a robot-assisted navigation method, comprising the steps of: acquiring the robot's speed and assistance information, and constructing its assisted motion model; performing path planning for the robot, collecting the robot's heading angle and speed information during path execution, constructing its active traction motion model, and controlling the robot's movement in conjunction with the presence or absence of obstacles and the aforementioned assisted motion model. This invention constructs both an assisted motion model and an active traction motion model for the robot, and selects and controls them according to actual conditions, flexibly combining the robot's assisted motion and active traction motion. It is simple and quick to operate, responds rapidly, and allows for efficient collaborative interaction with assistant doctors, effectively reducing the doctor's additional workload.

The application provides an augmented reality-based cooperative interaction method and device and related equipment, and relates to the technical field of augmented reality. The technical scheme provided by the application obtains a cooperative task in an augmented reality environment and identifies key task nodes therein. When a user reaches a key task node, the operation behavior information and voice information of the user are obtained in a timely manner, the operation intention information of the user is obtained through multi-modal information recognition, the operation intention information is converted into intuitive visual information, and the visual information is displayed in the augmented reality environment of other users. Through the accurate collection, understanding and visual communication of the operation intention at the key task node, the cooperative intention is accurately communicated at the key node of the cooperative task, so that the completion efficiency of the cooperative task can be improved.

The invention discloses an equipment fault early warning method and device, equipment, a medium and a product. The method comprises the following steps: carrying out collaborative interaction analysis on a virtual sensing point location of an integrated three-dimensional model of target equipment; correcting the virtual sensing point location according to a collaborative interaction analysis result; deploying a corresponding target sensor at a position corresponding to the target equipment according to the corrected virtual sensing point location; acquiring stress wave data and vibration waveform data of the target equipment according to the target sensor; and performing fault analysis on the target equipment according to the stress wave data and the vibration waveform data, and performing fault early warning on the target equipment according to a fault analysis result. By presetting the virtual sensing point on the three-dimensional model to optimize the sensor deployment of the actual equipment and introducing the stress wave sensing technology, the problems of fault early warning lagging, high sensor deployment cost and the like in the traditional equipment management can be solved, and the early warning of the equipment fault is realized to improve the equipment maintenance efficiency and safety.

The invention discloses a multi-modal man-machine cooperative interaction method for exercise rehabilitation and cognitive evaluation of the elderly, and the method comprises the following steps: S1, extracting voice features from collected voice signals, and predicting the probability distribution of each voice feature; s2, decoding the extracted voice features of each frame, performing semantic reconstruction and intention reasoning on the decoded text to generate a corresponding execution action, and feeding back an operation result to a user through voice broadcast and a screen; s3, a reentrant multi-mode evaluation process control model based on a finite-state machine; s4, generating a comprehensive compliance score according to the degree of the task, adjusting the difficulty or reminding strategy of the task according to the compliance score, and predicting the compliance trend of the old in the future; and S6, combining the deep learning model with the knowledge graph to recommend personalized intervention measures for the user.

The invention relates to the technical field of network security, and discloses a social robot collaborative group detection method based on a multi-order collaborative knowledge graph. According to the method, user data in a Chinese social platform is collected through a crawler, a multi-order collaborative interaction graph is constructed based on the interaction relation of users of the social platform and then input into a graph encoder module, node feature vectors are obtained and input into a time perception module and a graph perception module respectively, and a time sequence prediction task and a side link prediction task are executed. Meanwhile, the model is constructed based on a time-graph semantic consistency perception module of a self-attention mechanism. And finally, inputting a node feature vector obtained by training under the guidance of double tasks into a group detection module constructed based on a Gaussian mixture model and a K-means clustering method for detection. According to the method, the complex interaction relationship among the users in the social robot group and the abnormal mode in the time sequence activity can be effectively captured, and efficient detection of the social robot collaborative group in the social network platform is realized.

This invention discloses a personalized patient care information management system, comprising a server and medical staff, caregiver, and family member terminals connected to the server. The server is configured with: an information recording module for recording basic patient care information and temporarily added information; a permission management module for assigning corresponding operation permissions; a collaborative interaction module for real-time synchronization of care information among the medical staff, caregiver, and family member terminals; and an approval module that receives care plans submitted by the caregiver terminal and pushes approval requests to the family member terminal, synchronizing the approval results to both the caregiver and medical staff terminals after the family member terminal provides feedback. If the care plan is modified midway, a second approval request is pushed, and the modified care plan can only be implemented after approval by the family member terminal. Its beneficial effects are: this invention enables multi-dimensional information recording, real-time sharing of multi-party collaboration, and care plan approval management, improving care efficiency and accuracy.