50results about How to "Realize dynamic" patented technology

The invention relates to the technical field of logistics transportation, in particular to a logistics transportation route optimization method and system based on digital twinning. The method comprises the following steps: constructing a digital twin logistics base through multi-source heterogeneous data fusion and dynamic logistics network modeling; carrying out regional logistics distribution feature extraction and dynamic time sequence prediction based on a digital twinborn substrate to obtain a predicted regional transportation demand; performing real-time state evaluation on the line, generating a dynamic line performance matrix, and performing vehicle resource allocation in combination with the order task priority; and carrying out multi-objective solution and dynamic adjustment on the transportation scheduling scheme to finally obtain an optimal transportation scheduling scheme. And performing iterative optimization on the digital twin model through real-time deviation analysis and a feedback mechanism, and dynamically adjusting a transportation plan to form a closed-loop optimization process. Through the logistics transportation route optimization technology, the logistics transportation efficiency is remarkably improved, the cost is reduced, and the toughness of the system is enhanced.

The invention discloses an interrupt scheduling method, device and equipment and a computer readable storage medium, and is applied to the technical field of non-uniform memory access, and the method comprises the following steps: obtaining system load prediction data corresponding to a non-uniform memory access system; dynamically adjusting the interrupt scheduling strategy based on the system load prediction data to obtain a target interrupt scheduling strategy; and determining a target interrupt processing device corresponding to each interrupt based on the target interrupt scheduling strategy, and processing each interrupt based on the target interrupt processing device. Compared with a traditional method for scheduling the interrupt based on a static scheduling strategy, the method has the advantages that the target interrupt scheduling strategy is obtained by obtaining the system load prediction data and dynamically adjusting the interrupt scheduling strategy based on the system load prediction data, so that the interrupt is scheduled based on the adjusted interrupt scheduling strategy; intelligent and dynamic interrupt scheduling is realized, and the accuracy of interrupt scheduling is improved.

The invention discloses an Internet of Things access control system and method based on an intelligent contract and trust evaluation. The system comprises IoT equipment, a resource data memory RDS, an attribute authority AA and a block chain network, the method comprises the steps of initiating a resource access request, searching and responding attributes, evaluating and calculating trust values, deciding access authorization, sending access authorization and tokens, verifying access tokens, judging strategy violation, and sending and accessing resource data. According to the method, trust evaluation is introduced as the basis of authorization decision, and the comprehensive trust value is dynamically evaluated to realize fine-grained and self-adaptive access authorization; and meanwhile, safe and credible access control of the Internet of Things is realized by utilizing the characteristics of traceability and non-tampering of the block chain and adopting an intelligent contract mode. In addition, the sensitive attribute information is separated from other access control data in a main chain and side chain mode, and privacy protection of the sensitive attribute information in the access control process of the Internet of Things is achieved.

The invention relates to the technical field of visual health management, in particular to a ciliary muscle adjustment training system and method based on eye movement tracking, and the method comprises the steps: collecting eye movement data of a fixation point track, an adjustment amplitude change rate and pupil response time in real time, and combining personalized parameters such as the age of a user, diopter and a training target; inputting a ciliary muscle training dynamic planning algorithm module, dynamically generating a stage scheme containing a training action type, a single-group duration, a stimulation interval and a focal length adjustment strategy, and adaptively adjusting the strategy according to real-time adjustment stability and a historical ability curve; through multi-dimensional matching analysis of a pre-stored standard eye movement template, a training specification score is calculated from the track goodness of fit, speed uniformity, amplitude standard-reaching rate and binocular coordination, visual fatigue parameters are obtained based on continuous training duration, pupil fluctuation and retina reflex change, a scoring result is dynamically corrected, and a visual fatigue evaluation result is obtained. Personalized, self-adaptive and quantitative safety control of the training process is realized.

The invention discloses a respiratory disease oxygen precise conveying system based on a sensor, and relates to the technical field of medical equipment, and the system comprises a sensing module which integrates multiple sensors to collect and process airway and physiological data of a patient; the disease matching module identifies disease types through database comparison; the dynamic adaptation module calculates exclusive oxygen concentration based on a multi-mode fusion initial algorithm; the conveying module executes adjustment; the closed-loop feedback module continuously fine-tunes the oxygen concentration through a closed-loop stepped fine-tuning algorithm to form a closed-loop link, so that accurate dynamic control of oxygen delivery is realized; according to the invention, multi-sensor collaborative acquisition and disease precise matching are combined with a dynamic algorithm and closed-loop feedback, so that individuation and dynamic oxygen delivery are realized, the system avoids misjudgment by relying on a standardized database, and the oxygen concentration, flow and pressure are ensured to be adjusted in real time along with physiological indexes of a patient through multi-parameter collaborative adjustment and stepped fine adjustment; the treatment comfort, the effectiveness and the long-term adaptability are improved.

The invention belongs to the field of wireless communication, and discloses a power wireless local area network information security transmission method and a related device, and the method comprises the steps: obtaining a current physical layer leader sequence and a physical layer header, and carrying out the processing of to-be-transmitted data on the basis of the current physical layer leader sequence and the physical layer header, thereby achieving the dynamic operation of the physical layer leader sequence and the physical layer header. Meanwhile, when data to be transmitted are modulated by adopting an orthogonal frequency division multiplexing technology, a positive value random quantity is introduced to modify a cyclic prefix selection area and length and modify subcarrier parameters, so that the randomness and unpredictability of signal transmission are further improved, and the hiding of physical layer waveform parameters is realized. By dynamically switching the waveform factors of the physical layer, an attacker is difficult to capture and identify the characteristic information of the wireless signal due to the dynamic change, so that the anti-reconnaissance and anti-interception capabilities of the system are greatly improved. A parameter dynamic change rule can be self-formulated for the power wireless local area network, so that the powerful supervision capability of the power industry on the wireless local area network technology can be realized.

The invention provides a user interface updating method and device, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining a target domain specific language which indicates the characteristics of a target user interface; converting the target domain specific language into a user interface model; and calling a server interface to send the user interface model to a target client, so that the target client performs user interface updating through the user interface model. The dynamic user interface is realized by converting the target domain specific language into the target interface model, so that updating does not need to be performed depending on an installation package, and meanwhile, the user interface model is sent to the target client by calling the server interface; therefore, pushing of user interface updating can be efficiently achieved on the basis that packaging is not needed, and waste of resources is reduced.

This invention proposes an ESG-based comprehensive governance assessment method, electronic device, storage medium, and product for shipbuilding enterprises. The method includes: collecting multi-source ESG data and operational data from the shipbuilding enterprise during the assessment period; calculating state baseline parameters based on the operational data according to preset time slices; converting the multi-source ESG data into standard evaluation units and forming ESG vector data corresponding to the preset time slices; matching corresponding ESG assessment parameters from a preset ESG assessment parameter library based on the enterprise size, ship type, or production organization method; if no match is found, adaptively calibrating the ESG assessment parameters to obtain calibrated ESG assessment parameters; calculating governance efficiency indicators for each time slice based on the ESG vector data, state baseline parameters, and ESG assessment parameters; calculating a comprehensive ESG governance efficiency coefficient based on the governance efficiency indicators for each time slice; and obtaining the ESG governance assessment result based on the comprehensive ESG governance efficiency coefficient.

The invention provides a displacement vector dynamic space model modeling method based on a GNSS platform. The displacement vector dynamic space model modeling method comprises the following steps that S1, initial point position coordinates X1 of all observation stations are obtained and stored through GNSS satellite navigation signal receiving equipment; s2, after a data acquisition period T0, obtaining and storing a new observation station coordinate X2; s3, defining the direction of the Cartesian coordinate system; s4, obtaining a spatial trend structure function based on the displacement vector data of each observation station and the initial observation station coordinate X1; s5, performing detrending processing on the displacement vector data, and calculating a spatial autocorrelation function of the data; s6, establishing a displacement vector space distribution model in x, y and z directions, and obtaining displacement vectors of each non-direct measurement point in the x, y and z directions in the space; s7, calculating a total displacement vector of each non-direct measurement point; and S8: updating the initial point position coordinate of each observation station as X2, taking X2 as a new initial point position coordinate X1, and repeating the steps S2 to S7. According to the invention, dynamic and high-precision spatial modeling of the displacement vector is realized.

The invention discloses a dynamic evaluation and intelligent compensation system and method for contact rigidity of a machine tool joint part. The system comprises a digital twin and multi-source data interface module, a contact interface multi-scale morphology acquisition and characterization module, a joint part contact mechanical state online simulation module, a contact rigidity dynamic calculation model library, a performance evaluation and intelligent compensation decision-making unit and a compensation strategy execution and feedback module. According to the method, dynamic and high-precision contact stiffness analysis is achieved, the problem that a traditional static model is insufficient in precision is solved by deeply fusing microstructure measured data, a macrostructure model and a dynamic working condition load, and the time-varying characteristic of the joint part under the complex working condition can be reflected more truly. A perception-evaluation-compensation active control closed loop is constructed, and the digitization level of machine tool design and operation is improved. According to the method, the contact state of the joint part is actively optimized, so that the dynamic and static performance and machining quality of the machine tool are improved.

The invention discloses an auxiliary evaluation system for future scene guidance. The auxiliary evaluation system comprises an evaluation management module, an evaluation control module and an evaluation process module, the evaluation management module is used for defining an evaluation stage, an evaluation standard and a risk probability calculation method; the method comprises the following execution steps: defining an evaluated session scene, evaluation content and an evaluation stage; determining an evaluation standard and a scoring dimension, and determining a method for calculating a risk probability according to the evaluation standard; setting an evaluation plan according to the risk probability; the evaluation control module is used for executing the evaluation plan and initiating an evaluation event to the evaluation process module; the evaluation process module is used for responding to the evaluation event, providing evaluation content for the user side according to the evaluation stage, calculating the risk probability of the evaluation stage according to the feedback result of the user side, and generating an evaluation result and an evaluation plan. According to the technical scheme, assessment obstacles caused by high frequency and multi-mode characteristics in the future scene guidance psychological assessment process can be effectively solved, and the assessment process is dynamic and procedural.

The invention is applicable to the field of games, and discloses a game difficulty adjusting method, system and device and a medium, the method comprises the following steps: acquiring first meteorological data of the current position of a player, and adjusting the movement track of the player according to the first meteorological data; acquiring second meteorological data of the current position of the player, and adjusting the moving speed and physical exhaustion speed of the player in combination with character attribute data of the player; and acquiring third meteorological data and a scene model of the current position of the player, and adjusting the communication quality of the player according to the third meteorological data and the scene model. According to the method, different meteorological data of the current position of a player are obtained, and the moving track, the moving speed, the physical exhaustion speed and the communication quality of the player are adjusted respectively. The adjustment basis comprises the role attribute data of the player and the game scene model, so that the game difficulty is personalized and dynamic, and the game experience and interactivity are improved.

The application belongs to the technical field of payment security, and provides an import and export cross-border payment chain supervision method based on a dynamic graph, comprising: payment knowledge graph construction, payment node portrait construction, initial graph risk data acquisition, influence diffusion processing, FinBERT model identification, decision generation and execution; the application upgrades the risk monitoring of cross-border payment from single node monitoring to risk tracking of the whole link and correlation by building a cross-border payment exclusive knowledge graph, adding an influence diffusion processing mechanism and combining a large language model; and the application realizes dynamic and scenario-based grading of cross-border payment risks by calculating the risk value and risk level interval boundary of the node and the payment chain, so that the grading can accurately adapt to the dynamic risk changes of cross-border payment and fit the scenario differences of different nodes and payment chains.

The present invention discloses a soil water balance simulation calculation method based on climate, including: S1, constructing a complementary relationship model of actual evapotranspiration about climate, and determining the actual evapotranspiration under different climate modes; S2, calculating the crop water requirement of the area to be studied based on the actual evapotranspiration; S3, constructing a soil water balance model based on the water cycle law and crop water requirement of the area to be studied, and then determining the soil water balance change. The present invention fully considers the impact of climate on soil water, constructs a complementary relationship model of actual evapotranspiration about climate, obtains actual evapotranspiration based on the model, determines the actual water requirement of the study area, and constructs a soil water balance model in combination with other influencing parameters, thereby realizing the simulation calculation of soil water balance and realizing real-time monitoring of multi-layer soil moisture content, which is conducive to strengthening regional water resources management, rationally utilizing precipitation resources and soil water resources, and alleviating water resource scarcity.

The present invention relates to the field of deep learning artificial intelligence technology, and in particular to a post-disaster restorative maintenance decision-making method based on deep reinforcement learning. A post-disaster restorative maintenance decision-making method based on deep reinforcement learning provides an efficient and intelligent solution for post-disaster restoration of large-scale distributed cluster systems through the combination of complex network models and deep reinforcement learning algorithms. After an extreme event, the method can dynamically adjust the repair strategies of multiple maintenance teams to minimize the elasticity loss in the system recovery process, thereby achieving rapid and efficient recovery of the system and ensuring that the cluster system can resume normal operation as soon as possible after a disaster.

The invention provides a ship lock operation scheduling system and method based on big data analysis, and relates to the technical field of ship lock operation scheduling. By integrating big data analysis of historical operation data, ship priority evaluation, real-time navigation state monitoring and intelligent prediction, refinement, dynamics and intelligence of ship lock scheduling are achieved, the overall traffic efficiency is remarkably improved, and congestion of a lock area is effectively relieved. Low-efficiency links are identified through clustering analysis, congestion points are captured in real time in combination with a space thermodynamic diagram, and a declaration time period and interval time are dynamically adjusted, so that the adaptive capacity of the system to abnormal conditions such as load change, severe weather and equipment faults is enhanced; differentiated services and green channel support of high-priority ships are realized, and key transportation requirements are guaranteed; and upstream and downstream ship lock linkage scheduling is realized through a network cloud platform, and a neural network model is utilized to generate an optimization scheme containing a lockage sequence, suggested arrival time and a coordination instruction to improve watershed navigation collaboration.

The present invention belongs to the technical field of coal flow monitoring, analysis and processing, and specifically discloses a coal flow dynamic real-time monitoring, analysis and processing system based on image recognition, including a coal flow image sampling module, an environmental information detection module, a coal image detection module, a coal flow template generation module and a coal flow template update module. The present invention effectively solves the problem that the influence of the external environment on image detection is not considered during the current coal flow monitoring, reduces the tediousness of subsequent coal flow determination, and provides a strong guarantee for the subsequent accurate determination of coal flow. At the same time, by generating the current coal flow laser line template and updating the coal flow laser line template, the dynamic and real-time update of the coal flow laser line template is realized, which can better deal with the coal flow accuracy error caused by belt offset and belt up and down floating, ensure the consistency and representativeness of the coal flow measurement results, and thus provide a reliable foundation for the determination of coal flow.

The present invention discloses an intelligent curtain control method based on control pyramid and multimodal interaction, including: collecting real-time ambient light intensity, real-time multi-point temperature and humidity to generate first-level curtain control features; capturing on-site environmental sound features, separating voice commands from environmental noise in real time, and generating second-level curtain control features; regularly requesting control instructions from user terminal devices, analyzing and converting the control instructions, and generating third-level curtain control features; correlating and analyzing the first, second, and third-level curtain control features based on a multimodal fusion algorithm to form a curtain control pyramid; learning, converting, filling, and bidirectionally extracting the curtain control pyramid to determine the control intent, and inputting it into a curtain control model to control the opening and closing state; real-time monitoring of the motion state of the curtain, and feeding back the monitoring information to the curtain control model for dynamic adjustment. The present invention improves the intelligent level, accuracy, and adaptability of curtain control.

The present invention discloses a dynamically adjusted warehouse equipment operation management method and system, which belongs to the field of warehouse management, wherein the method includes: collecting parameters of multiple stackers; obtaining multiple stability parameters according to the parameters of multiple stackers; obtaining the predetermined stacking positions of multiple stored items, formulating multiple stacking planning information, and obtaining value information and vulnerability information of multiple stored items; obtaining busyness information of multiple target devices; constructing a stacking task function for stacking task management, optimizing the stacking scheme, and obtaining the optimal stacking scheme; using the optimal stacking scheme to perform operation management on multiple target devices. The present application solves the technical problem that the prior art lacks refined management of warehouse equipment operation, resulting in low safety and efficiency of warehouse equipment operation, and achieves the technical effect of improving the safety and efficiency of warehouse equipment operation by combining the equipment operation status with the actual needs of stored items.

The application discloses a kind of carbon emissions determination methods of energy storage system, belong to energy storage management technical field.It includes: obtaining energy storage regulating parameters including energy storage load power, released power space and alternative power output;According to the load absorption constraint between energy storage load power and grid new energy consumption limited power, determine the direct consumption of new energy power and account the first carbon emission reduction;According to the space replacement constraint between the released power space and the limited power, determine the indirect consumption of new energy power and account the second carbon emission reduction;Based on the third carbon emission reduction of alternative power output, the third carbon emission reduction of conventional power direct carbon emission is accounted;The total carbon emission reduction is determined by summarizing the three. The application subdivides three scenarios of direct consumption, indirect space replacement and alternative output, introduces dynamic constraint to realize accurate quantification of emission reduction based on real-time consumption boundary of power grid, solves the problem of static accounting distortion and missing calculation.

The invention relates to the technical field of electric power computing power scheduling, and discloses an electric power cross-domain computing power elastic scaling scheduling system supporting a creative GPU (Graphics Processing Unit). The system receives a power cross-domain computing power scheduling request, and searches a matched historical computing power use record set from a historical computing power database according to the request. And carrying out load category division on the historical record set to generate historical computing power record subsets of a plurality of load categories. Computing power feature core calculation is performed on the subsets to obtain a plurality of computing power feature core points and associated time intervals; and using the associated time intervals as the time range of a plurality of scheduling analysis layers, performing multi-scale scheduling feature analysis on the computing power monitoring data sequence of the current power cross-domain within the specified time range through the plurality of set scheduling analysis layers, and outputting a plurality of computing power scheduling feature sets. And carrying out cross-scale fusion calculation on the feature sets to obtain a fusion computing power scheduling feature set.

The application discloses an intelligent carbon metering device and a carbon emission calculation method thereof, and the method comprises the following steps: pre-processing multi-source data; using a deep learning model to identify the working conditions of each device, and simultaneously considering device aging correction to improve identification accuracy; establishing a bottom-up calculation model of carbon emission driven by energy consumption and a top-down calculation model based on emission concentration for concentration inversion; and obtaining the final carbon emission result through adaptive Kalman filtering fusion. The application identifies the device state in real time through AI, dynamically matches the emission factor, and adopts adaptive Kalman filtering to fuse the energy consumption and concentration double models, thereby significantly improving the accuracy and robustness of carbon metering. The method can effectively solve the problems of hysteresis, singleness and error accumulation in the traditional carbon metering method, realize real-time, accurate and traceable carbon emission calculation from the device level to the regional level, and realize the digitization, dynamicization and intelligentization of carbon metering.

The invention relates to the field of intelligent wearable devices, and discloses a dimmable dice wearable device which comprises a dice shell, a main control circuit board is arranged in an inner cavity of the dice shell, and a central processing unit, an LED dot matrix module, a near-field induction unit, a wireless communication unit, an audio conversion unit and an electric power storage unit are integrated on the main control circuit board; the central processing unit is connected with the LED dot matrix module, the near-field induction unit, the wireless communication unit, the audio conversion unit and the power storage unit through an electrical loop. Through cooperation of the integrated LED display module and the light guide composite material shell, dynamic and digital adjustment of the wearable device is realized, and the wearable device integrates LED, audio playing, communication and user interaction functions. Different LED colors can be switched and corresponding audios can be played according to the emotion of a user, and meanwhile, emotion data can be transmitted and received through wireless communication.

The invention relates to the field of agricultural credit approval, and discloses an agricultural production process data generation method, which comprises the steps of receiving credit application data of a target farmer through a farmer terminal; querying a user file according to the peasant household attribute information to obtain a peasant household integrity score, a planting type, an Internet of Things crop monitoring equipment identifier and a key evidence chain storage file; if the integrity score does not meet the preset condition, verifying the authenticity of the asset ownership proof file through the key evidence chain storage file; after the authenticity verification is passed, acquiring corresponding agricultural production process data according to the planting type, forming agricultural production process display data, pushing the agricultural production process display data to an intelligent terminal for visual presentation, initiating interactive inquiry, and acquiring supplementary description information of the farmer; and receiving the supplementary description information and carrying out associative storage on the supplementary description information and agricultural production process data to generate an agricultural production process data evidence material. Therefore, the authenticity, the integrity and the verifiability of the data are improved.

An implementation method of intelligent agricultural planting decision support based on big data analysis, including: equipping with diversified sensor equipment and remote sensing technology, monitoring various indicators of farmland environment, integrating external relevant information; using the entropy-based weighted principal component analysis (PCA) method to clean data, and introducing the construction of spatiotemporal sequence features under the geographic space coordinate system; applying statistical big data analysis technology to construct an environment-crop response model and resource demand prediction model based on big data analysis; using the particle swarm optimization algorithm (PSO) based on adaptive learning weights and multimodal search to perform global optimization search and formulate planting decision strategies. The implementation method of intelligent agricultural planting decision support based on big data analysis realizes the intelligence of the entire process from data collection, processing, analysis to decision generation, and provides scientific, accurate, and real-time planting decision support for agricultural producers, with significant application value and broad market prospects.

The invention discloses a dynamic field retrieval method and system based on an extensible retrieval processor mechanism. The method comprises the steps that multiple retrieval types are defined, and corresponding retrieval processors are configured; constructing a dynamic mapping template based on regular expression matching, and automatically distributing data types for dynamic fields; configuring a search field pool which can be dynamically loaded, and defining a retrieval attribute and an interaction mode of a field; receiving and analyzing a dynamic retrieval request generated by a front end according to the field pool, and obtaining a retrieval parameter of each field; according to a retrieval type in the parameters, dynamically scheduling a corresponding retrieval processor through a processor factory; query conditions are automatically constructed by the processor based on the parameters and integrated into the primary query. Full-link configuration driving from field definition, type mapping, interface generation to query execution is achieved, non-intrusive expansion of retrieval logic is supported, and the flexibility, maintainability and development efficiency of a system facing business changes are remarkably improved.

The application discloses a kind of based on multidimensional data's teacher interdisciplinary accomplishment dynamic evaluation method and system, wherein method includes: based on teacher subject background, teaching age, teaching period of study constructs evaluation standard library, and different accomplishment evaluation weight is assigned to each dimension;Build multidimensional data acquisition terminal, interface existing teaching research system, input teacher basic information and automatically match exclusive evaluation standard and weight;Real-time collection and multidimensional data of the interdisciplinary accomplishment of the teacher to be evaluated;The multidimensional data collected are preprocessed, and time series feature dataset is constructed;Based on the time series feature data, dynamic evaluation and trend prediction of teacher accomplishment are carried out, and the evaluation result of the interdisciplinary accomplishment of teacher is output in combination with the weight matched and current window dynamic threshold value.The significant effect is: evaluation accuracy is greatly improved, adapts to different scenes and teacher type, realizes the deep fusion of evaluation and improvement, and can help teachers to rapidly improve interdisciplinary accomplishment.

The application discloses a low-cost high-accuracy e-commerce goods-carrying video analysis method and system, and belongs to the technical field of data processing, and comprises the following steps: performing multidimensional availability checking on a to-be-analyzed goods-carrying video, then demultiplexing the video into a video audio stream and a video picture stream; performing streaming voice transcription on the video audio stream to generate a text semantic sequence, performing dynamic analysis on the video picture stream to extract a motion intensity coefficient, dynamically dividing video clips based on the two, and generating picture frame sets corresponding to each semantic segment, and simultaneously performing cross-segment summary aggregation to generate a video overall summary; performing parallel reasoning analysis on the picture frame sets of each segment, the audio text and the overall summary, generating multidimensional text analysis results, structurally processing each dimension analysis result, and integrating and concatenating in time sequence to generate a complete video structured description document, so that low-cost, high-accuracy e-commerce goods-carrying video automatic analysis is realized.

The invention discloses an urban landscaping ecological benefit intelligent evaluation method based on digital twinning, and particularly relates to the technical field of smart city and ecological information crossing, which comprises the following steps: collecting vegetation multispectral images, canopy three-dimensional point cloud, soil temperature and humidity and atmospheric microclimate parameters in real time, and combining a landscaping geometric model and a plant physiological parameter library to evaluate the ecological benefit of urban landscaping. The method comprises the following steps: constructing a high-fidelity and time-space synchronous urban landscaping digital twinborn body, dynamically extracting a multi-dimensional characteristic index, inputting an ecological process dynamic coupling model, outputting an ecological benefit comprehensive evaluation index and a time-space distribution map thereof, and supporting virtual scene deduction and multi-objective optimization by a system. Greening configuration and maintenance decision suggestions considering ecological benefits and cost benefits are generated, and dynamic display and closed-loop intelligent evaluation are realized through a visual interaction platform. According to the invention, real-time, accurate and systematic evaluation and intelligent management of urban landscaping ecological benefits are realized.

This application provides a pointing remote controller, a display device, and a cursor positioning method. The pointing remote controller can acquire ultra-wideband data measured by a first ultra-wideband device and a second ultra-wideband device, as well as motion data of the pointing remote controller measured by an inertial measurement unit. Based on the ultra-wideband data and motion data, target parameters are calculated. Based on the motion data, the motion state of the pointing remote controller is determined. Based on the anchor point update mode corresponding to the motion state, the anchor point parameters corresponding to the target parameters are updated so that the anchor point parameters approach the target parameters. Based on the updated anchor point parameters, the cursor position is calculated and sent to the display device so that the display device moves the cursor according to the cursor position. By combining ultra-wideband data and motion data, and based on the anchor point update algorithm, a fast and smooth cursor response effect is achieved while ensuring tracking accuracy.