693 results about "Point location" patented technology

The invention relates to the technical field of computer vision and industrial automation, in particular to a shoe sole three-dimensional gluing contour extraction system and method based on vision single-line laser, and aims to solve the problems that virtual calibration target spots cannot be accurately generated based on shoe sole geometry, the positions and sizes of the target spots are difficult to determine by combining curvature extreme values and principal component analysis in the prior art, and the production cost is low. The problem that a double-branch deep learning model cannot be adopted to fuse feature prediction transformation, and the re-projection error is increased is solved; a virtual calibration target spot is automatically generated based on sole geometry through a feature fusion calibration module, a grid is generated through point cloud processing and Poisson reconstruction, the position and size of the target spot are determined by combining a curvature extreme value and principal component analysis, a corresponding relation is established by utilizing two-dimensional and three-dimensional feature matching, initial alignment is realized through ICP and re-projection error optimization, and the target spot position and size are determined. A double-branch deep learning model is adopted to be fused with feature prediction transformation, iterative optimization is carried out through space consistency errors, and re-projection errors are reduced.

The invention discloses an automatic river network grading and river topological relation identification method based on a graph theory, and relates to the technical field of hydrological geographic information. The method comprises the following steps: acquiring and cleaning a vector river network, a key point location and DEM data of a target drainage basin; constructing an initial river network graph model based on the line element connection relationship; integrating DEM topographic evidence and graph theory connection features, constructing and solving a global potential energy field equation containing topographic driving and boundary constraint, and calculating flow potential energy attributes of nodes of the whole network to determine a flow relationship; based on the flow direction relation, identifying topology abnormal structures such as strong connectivity components in the network, and performing ring breaking processing by using direction confidence to generate a ring-free directed network structure; and performing river grade division based on a topology transfer rule, and associating the key point location to a river network skeleton. According to the method, through global potential energy field solving and topological optimization, the problems that the flow direction of the plain micro-geomorphic area is difficult to recognize and complex loops cannot be graded are solved, and automatic construction of the river network topology is achieved.

The invention provides a reinforcing steel bar binding point detection method based on improved YOLOv8, and the method comprises the following steps: obtaining a construction site image, carrying out the preprocessing, inputting a to-be-detected image into an improved target detection model, sequentially carrying out the local space attention calculation, depth separable convolution and channel attention weighting operation, and carrying out the detection of the to-be-detected image. Detail feature expression of reinforcing steel bar intersection points is enhanced; performing dynamic weight fusion on the top-down first feature path and the bottom-up second feature path, and embedding a lightweight residual unit in a fusion node; a classification task and a regression task are respectively processed by adopting a classification branch and a regression branch, the classification branch outputs category confidence, and the regression branch outputs coordinate positioning through depth separable convolution and a probability distribution prediction layer; and decoding output data of the target detection model, and generating a detection result containing the position and the category of the binding point. According to the method, the requirement of real-time detection can be met while the accuracy of steel bar binding point detection is improved.

The invention discloses an abnormal detection method and system for a splayed anti-loosening line of a rail train, and relates to the technical field of rail traffic detection, and the method comprises the steps: image collection and processing: shooting an image of a fixed point region containing the anti-loosening line, and preprocessing the image to obtain a target image; line integrity judgment: extracting a bolt, a bolt marking line and an anti-loosening line through an analysis model to form a target area graph, and judging whether the anti-loosening line is complete or not according to line segment continuity and form; performing line deformation depth analysis, and synchronously obtaining the position of an anti-loosening line intersection point and deformation data through the model in combination with the loosening angle of the bolt marking line when the line deformation is complete; performing line deformation safety judgment, setting a safety threshold group based on historical data, and comparing deformation data to output a signal; after line deformation abnormity judgment and comparison signal receiving, actual data are compared with theoretical data output by the mechanical model, and abnormal or normal signals are output. The anti-loose line full-dimension high-precision detection is achieved, automation and real-time performance are improved, and train operation safety is guaranteed.

The invention discloses a multi-protocol hardware communication adaptation module based on an energy storage system and a configuration method, the module comprises a protocol template library, an intelligent mapping engine and a model generator, and the method comprises the following steps: storing structured protocol point location information through the protocol template library; an intelligent mapping engine is used for shielding the isomerism of Modbus, MQTT, IEC104 and other underlying protocols, and a unified data interface is provided; intelligent matching among different protocol terms is realized by adopting a natural language processing technology through a semantic level mapping unit; and finally, generating a target data model by a model generator through one key. The method effectively solves the problems that when the energy storage system integrates multi-manufacturer equipment, protocol configuration depends on manpower, efficiency is low, errors are prone to occurring, and expansibility is poor.

The invention discloses a path planning method and system for corner optimization. The method and system are used for cutter radius compensation and machining instruction smooth transition of a three-dimensional path of a numerical control machine tool. The method comprises the steps that a machining instruction is pre-read, and a path point location is analyzed; calculating a path direction vector and a normal vector, and determining a path plane equation; calculating a plane included angle and an intersection direction vector through a normal vector; generating a compensation curve by translating along the perpendicular direction of the intersecting line by taking the radius of the cutter as a constraint; and generating a smooth control instruction through curve subdivision and inserting the instruction into an instruction queue. The problem that three-dimensional path corner transition is not smooth is solved, the machining precision and efficiency are remarkably improved, and the method is suitable for a numerical control machine tool for complex curved surface machining.

The invention relates to the technical field of building engineering, and provides a building construction progress digital monitoring method and system. The method comprises the following steps: collecting three-dimensional point location data of a construction area, and comparing the three-dimensional point location data with a BIM model to extract a progress deviation; associating the construction log to a BIM component node and setting a first evaluation index; associating the material records to BIM component nodes, and setting second evaluation indexes; drawing up a resource map of construction process logic in combination with the deviation and the two indexes; and based on the atlas, according to a weight attenuation coefficient, multi-scale assessment of cumulative influence is carried out by taking efficiency as a feature, and resource compensation reminding is carried out in combination with dynamic threshold adjustment. The technical problem that progress deviation is difficult to accurately recognize due to data updating lagging and construction process logic disjunction in traditional building construction progress monitoring is solved, real-time accurate analysis of the construction progress is achieved through intelligent comparison of multi-source data fusion and the BIM model, resource allocation is dynamically optimized in combination with multi-dimensional evaluation indexes, and the construction progress monitoring efficiency is improved. And the construction management efficiency is improved.

The invention provides a path planning method, electronic equipment and a computer program product. The intelligent agent realizes path planning based on a pulse neural network of width, and the path planning method comprises the steps that a target area is divided based on environment information of the target area and an optimization target, a rasterized map composed of different sub-areas is determined, the optimization target comprises calculation efficiency and environment adaptability of the intelligent agent, and the rasterized map is determined based on the calculation efficiency and the environment adaptability of the intelligent agent. Each sub-region corresponds to one pulse neural network sub-node, and the rasterized map comprises a starting point position, an ending point position and obstacle information; based on the environment feature vectors of the sub-regions of the rasterized map and the position information of the intelligent agent, the current state of the intelligent agent is determined, and the current state is determined based on the Markov decision process; and based on the current state of the intelligent agent and a path planning algorithm, performing path planning on the rasterized map, and determining a planned path.

The invention discloses a method for automatically calculating the waviness of an aircraft profile in an MATLAB environment, and the method comprises the steps: 1, obtaining the plane section point location data of the waviness of the aircraft profile based on the reverse point cloud data of the aircraft profile; and step 2, automatically calculating the airplane profile waviness in the MATLAB environment, including plane classification of point location data, three-dimensional coordinate system conversion, two-dimensional wave crest and wave trough point location calculation, wave crest and wave trough point coordinate system reverse conversion, waviness calculation and form report output on the point location data of the plane cross section obtained in the step 1 through a program in the MATLAB environment. Therefore, automatic calculation of the airplane appearance waviness is completed. According to the invention, the problem that the existing detection mode for the airplane profile corrugation is difficult to have convenient operability, detection precision and detection efficiency at the same time is solved.

The invention relates to a cluster scheduling method and system for multi-unmanned aerial vehicle cooperative detection of hoisting equipment, and the method comprises the steps: obtaining detection object information from a detection request when the detection request of a user side is received; calling a preset equipment three-dimensional model based on the detection object information, and generating a detection task based on the equipment three-dimensional model; performing demand analysis on the detection task, and outputting task demand information; a cooperative detection strategy is generated based on the task demand to generate a cooperative flight route, the unmanned aerial vehicles of the corresponding model and number are called, and the multiple unmanned aerial vehicles are controlled to cooperatively execute the flight task according to the generated cooperative flight route; and based on a preset communication link, receiving detection data acquired by the unmanned aerial vehicle, mapping the detection data to a corresponding detection point location in the equipment three-dimensional model, and sending the detection data to a user side. The method and the device have the effect of improving the efficiency and the accuracy of large-scale equipment detection.

The invention relates to a path planning method and device based on hierarchical reinforcement learning, equipment and a medium, and the method comprises the steps: converting any planar map into rasterization, taking the shortest path between a starting point position and an end point position as an optimization target under the constraint of avoiding the collision of an obstacle, and starting from the starting point position, selecting a plurality of sub-target positions, the method comprises the following steps of: establishing a path planning problem between a starting point position and an end point position until the end point position is reached, converting the path planning problem between the starting point position and the end point position into a plurality of local sub-path planning problems, constructing a learning heuristic network by adopting an artificial neural network as a heuristic function in an A * algorithm, and training the learning heuristic network by utilizing reinforcement learning to obtain a learning heuristic network; and solving each local sub-path planning problem by using the trained learning heuristic network to obtain an optimal solution of each local sub-path, and then obtaining a bounded suboptimal path planning result. By adopting the method, path planning can be efficiently carried out on any plane map.

The invention relates to the technical field of capacitive touch, and discloses a capacitive touch signal self-adaptive compensation method and device. The method comprises the following steps: collecting original capacitance signal grid data in an initial contact stage, and constructing a dynamic contact quadtree; on the basis of the quadtree, a first point position prediction algorithm of contact dynamics perception is operated, and stable coordinate prediction mapping with confidence is constructed; and executing multi-mode first point decision and touch event generation based on the mapping, outputting a touch event and feeding back the touch event to an operating system. According to the method, initial contact signal features are captured through the dynamic contact quadtree, stable coordinate prediction mapping and multi-modal decision are combined, the problem of jumping coordinates in the initial touch stage of an existing system is solved, the touch accuracy of scenes such as vehicle-mounted center control and industrial HMI is improved, the operation risk is reduced, and the application value of the capacitive touch technology is expanded.

The invention relates to the technical field of intelligent traffic, in particular to a training method and system for a vehicle track frame filling model, and the method comprises the steps: training a pre-trained Transform network based on a plurality of pieces of sheltered historical track data, and obtaining a trained vehicle track frame filling model; the training process comprises the following steps: obtaining a prediction result corresponding to each shielded time step; obtaining map constraint loss based on prediction results of all shielded time steps and a preset tunnel center point position matrix; obtaining position loss, speed loss and course angle loss based on the time step data of the prediction result corresponding to all the shielded time steps and the time step data in the historical trajectory data; based on the map constraint loss, the position loss, the speed loss and the course angle loss, model parameters are adjusted, and a vehicle track frame compensation model is obtained. The method has the beneficial effect that the frame supplementing track of the vehicle is more reasonable, smoother and smoother.

The invention discloses a double-target automatic tracking shooting method and an automatic tracking shooting device, and the method comprises the steps: determining two to-be-tracked targets in a real-time shooting image; obtaining respective feature vector queues of two to-be-tracked targets through a human body feature algorithm, and obtaining respective reference target frame serial numbers of the two to-be-tracked targets through a target detection algorithm; based on the feature vector queue and a reference target frame serial number, matching a target frame in each frame in a subsequent real-time shot picture; if matching succeeds or partial matching succeeds, determining the position of a tracking point according to the position of the successfully matched target frame; if matching fails, the position of the fixed tracking point is the center of the current picture; and when the matching of the continuous preset frames fails, adjusting the focal length to expand the field of view of the real-time shot picture. According to the dual-target cooperative tracking mechanism, dual-target equivalent tracking is realized through parallel feature vector queues and dynamic weight distribution.

The present invention provides a method for extracting features of the nearshore wave breaking process based on time series video images; wherein, the method comprises: setting at least one pixel sampling area in a plane geographic coordinate system, collecting time series video images of ocean nearshore waves, quickly converting them into plane geographic coordinate images through a coordinate model, and then stacking cross-shore pixel values ​​of several pixel sampling areas within a set time to generate a cross-shore pixel value and time relationship sequence diagram, mining the time-varying signal of the wave propagating toward the shore, combining the geometric relationship between the camera angle of view and the plane projection of the wave breaking, and calculating key wave breaking features such as the wave breaking point position, wave breaking water depth, and wave breaking height; the method can continuously monitor the nearshore wave breaking features efficiently, automatically, and stably, effectively making up for the shortcomings of traditional monitoring and analysis methods, and providing strong technical support for the refined research and management of nearshore beach dynamic landforms.

The invention relates to the technical field of three-dimensional reconstruction, and discloses a three-dimensional reconstruction method and terminal equipment, and the method comprises the steps: carrying out the unmanned plane route planning and ground end scanning planning of a scanning region; acquiring an aerial image and a ground image; performing air model reconstruction according to the air image to obtain an air sparse point cloud and first pose information, and performing ground model reconstruction according to the ground image to obtain a ground sparse point cloud and second pose information; matching a target aerial image and a target ground image with an overlapping region in the aerial image and the ground image to obtain relative pose information between the target aerial image and the target ground image; and according to the first pose information, the second pose information and the relative pose information, utilizing global binding with control point constraint to adjust and optimize pose information and sparse point positions of each image in the target aerial image and the target ground image with the overlapping region, and obtaining a fusion model. According to the invention, the space-ground coordinate alignment precision of three-dimensional reconstruction is improved.

The invention discloses an OHT track node automatic identification and path planning method and system, and relates to the technical field of OHT tracks, and the method comprises the following steps: identifying track node positions based on vehicle motion track feature analysis, point cloud geometric clustering processing and a multi-mode verification method combining visual and magnetic features; performing semantic recognition according to the node positions to obtain node types, and constructing a track topological graph according to the node types; a candidate path set is generated through the track topological graph, and local optimization is conducted on the task execution sequence of the candidate path set and the vehicle matching relation; based on a local optimization result, performing synchronous adjustment on path selection and task allocation, and outputting an integrated scheduling scheme; according to the method, high-precision node positioning, semantic classification, structured track topology construction and integrated optimization of multi-vehicle path and task scheduling can be realized, and the operation efficiency, the scheduling reliability and the resource utilization rate of an OHT system are remarkably improved.

The invention provides a water leakage point positioning method and device based on resistance gradient calculation, and the method comprises the steps: obtaining a total resistance value and a tail end resistance value of a water leakage induction rope, and reading a preset resistivity parameter per unit length; calculating the distance of a water leakage point based on the total resistance value, the tail end resistance value and the resistivity parameter per unit length; according to the mapping relation between the length of the induction rope and the physical position established in the installation and debugging stage, the distance of the water leakage point is converted into the physical position described by corresponding 3D coordinates or characters; the physical position information is combined with real-time monitoring data to generate alarm prompt information containing a specific water leakage point location, and the alarm prompt information is output to a monitoring interface, so that accurate positioning of the water leakage point can be realized, the fault response time is remarkably shortened, and through a multi-thread data acquisition and dynamic alarm judgment mechanism, the real-time performance and the alarm accuracy of the system are improved; and the false alarm and repeated alarm frequency is reduced.

The invention relates to the technical field of point location labeling, in particular to a self-adaptive load balancing point location labeling method and system based on image processing, and the method comprises the following steps: obtaining an image source division region, extracting an edge pixel number texture direction number color channel standard deviation, generating region detail redundant structure distribution information, and monitoring node state data. The method comprises the following steps: constructing a node resource load state mapping set, matching according to a regional detail redundancy ratio and a node state, establishing a task allocation relationship, extracting a boundary gray derivative, screening a boundary stable candidate point location set, calling point location coordinates, sending the point location coordinates to corresponding nodes, executing target verification, writing in an image frame, and generating a labeling result. Quantitative extraction is performed on distribution among image region edge pixels, texture directions and color channels, and task assignment is accurately paired in combination with image structure complexity and node states, so that resource mismatching and processing retardation are avoided, and task distribution accuracy is improved.

The invention discloses a practical training platform three-dimensional scene mass data loading optimization method, and relates to the technical field of computer graphics and three-dimensional visualization. Passive response of data loading is converted into active pre-judgment through an orbit prediction model and prospective visible area calculation, and the real-time performance of data loading is improved. The rendering lag caused by the rapid change of the satellite track is obviously reduced; the combination of the predicted position and the camera vision cone ensures that the point location is scheduled before the vision field is switched; secondly, GPU resource utilization is optimized through dynamic attribute increment updating and a dirty marking mechanism; static and dynamic attribute buffer areas are separated, only change data are updated, the CPU-GPU communication overhead is reduced, the frame rate fluctuation problem caused by batch updating is solved, and the system is still kept smooth under ten-thousand-level point location dynamic updating; in addition, the collaborative design with terrain rendering eliminates point location dislocation during terrain detail level switching through monitoring and double-buffer correction, and improves visual consistency.

The invention discloses a focus depth determination method and a related device, and relates to the technical field of rendering, and the method comprises the steps: collecting eye movement data of a user according to a preset eye movement sampling rate in a process that the user watches a three-dimensional scene, so as to obtain multi-frame eye movement data collected in a target duration, and determining a focus depth of the user according to the multi-frame eye movement data, determining a fixation point position of the sight line of the user in the target three-dimensional model, generating a sphere with the radius as a target value by taking the fixation point position as a sphere center, obtaining a target vertex set in the sphere in the target three-dimensional model, and performing vertex density analysis on the target vertex set to obtain a focus depth for rendering the three-dimensional scene. According to the method, the focus depth dynamically adjusted along with the sight line of the user can be generated, the detail resolution capability of the user on the fixation point is improved, and the watching experience of the user on the three-dimensional scene is further improved.

Example methods, apparatuses, and computer-readable media are provided. Example methods include generating a virtual environment including a first shape and a second shape in a virtual viewpoint, the first shape in front of the second shape. The second shape adjusts as the virtual viewpoint adjusts, and is offset from the first shape along a test axis. The first shape is affixed to the virtual viewpoint. The virtual viewpoint is configured to adjust in response to movement of a HMD. The method includes moving a position of the virtual viewpoint with respect to the second shape in response to the movement. The method includes recording reference data associated with moving of the position of the virtual viewpoint. The method includes generating a positional displacement vector by comparing reference data of the second shape with reference data of the first shape, and determining a HMD movement tracking error based on the vector.

The invention discloses a building structure safety monitoring method and system based on a digital twin model, and the method comprises the steps: obtaining target environment parameters and target monitoring point parameters of a building structure, and inputting the target environment parameters and the target monitoring point parameters into a damage feature prediction model to obtain damage rate distribution feature coefficients of the building structure in different time periods; carrying out nonlinear combination on a damage distribution characteristic mode of the building structure and the coefficient to generate a target damage rate distribution matrix; obtaining a first performance index distribution matrix of the building structure obtained in the previous monitoring period, and calculating a second performance index distribution matrix of the current time period in combination with the target damage rate distribution matrix; judging whether the value of the position of any monitoring point exceeds the structural failure threshold value of the position, and if so, marking the monitoring point as an abnormal monitoring point and triggering multi-stage early warning; and the damage type of the abnormal monitoring point is diagnosed to match a corresponding repair strategy. According to the method, refined simulation and accurate prediction of the building structure damage evolution process are realized, and a reliable basis is provided for performance evaluation and matching of a repair strategy.

The invention belongs to the technical field of computer vision, and particularly discloses a monocular 3D object detection method for realizing depth enhancement based on a visual basic model, electronic equipment and a readable storage medium, and the method comprises the steps: S1, building a data set: employing a monocular camera to collect a pavement scene, and obtaining an RGB image in the pavement scene; s2, image preprocessing: preprocessing the RGB image for subsequent feature extraction and depth estimation; s3, performing feature extraction by adopting a dual-backbone network: performing visual semantic feature extraction on the preprocessed RGB image by using DINOv2; performing depth feature extraction on the preprocessed RGB image by using a DPT head; s4, generation of depth perception query points: inputting the visual semantic features and the depth features into a DETR network to generate the depth perception query points; and S5, target detection output: using an MLP-based detection head to obtain information of the category, the size, the center point position, the depth, the 3D size and the direction of the object.

The invention discloses a high-precision adaptive numerical simulation method and system for solving a nonlinear integral-differential equation, and relates to the technical field of computer simulation and numerical calculation. Comprising the steps of setting simulation conditions; constructing a grid space based on the computational domain; constructing a global cubic spline interpolation function based on the solutions on the grid points; if the updated grid point location exists, calculating a right-end integral item by using an adaptive numerical simulation integral algorithm; calculating a heuristic solution and an error estimation value; dynamically adjusting the tentative step length and updating the time according to the estimated value and the ODE tolerance; checking gradient and curvature distribution of solutions, encrypting grids for areas with violent solution changes, and sparse grids for areas with smooth solution changes; using a global cubic spline interpolation function to demap the old grid space to the adjusted new grid space; and iteratively executing the steps, and outputting an integral solution in the computational domain. And finally, collaborative improvement of integral simulation calculation in precision, efficiency and stability is realized.

The invention discloses a fully mechanized coal mining face multi-protocol equipment simulation linkage control system and a working method. The control system comprises a presentation layer, a business logic layer and a data layer. The working method comprises the following steps: S1, selecting equipment needing to be simulated and issuing the equipment to the business logic layer; s2, an equipment simulation module obtains point location information of the selected equipment, and a linkage rule read-write module obtains equipment linkage control rule information; s3, the device simulation module calls a point location read-write module of a corresponding protocol according to the read device point location information, and point location change monitoring during device operation is achieved; s4, the rule simulation module completes point location read-write module calling across the devices according to the analyzed rules, and therefore linkage simulation between the devices is achieved; s5, the point location read-write module receives the calling command, scans the read point location and feeds back a scanning result to the business logic layer; and S6, the service logic layer transmits a feedback result to a simulation monitoring module for simulation effect display.

The invention provides a scenic spot navigation method, system and device based on location services and a medium, and belongs to the technical field of scenic spot navigation, the method comprises the following steps: developing a scenic spot navigation light application based on a host application, and presetting location data of each scenic spot and a dynamic distance trigger threshold configuration rule for judging the location of a user; starting a scenic spot navigation light application, and obtaining a user position and a current positioning precision parameter through a real-time position interface of a host application; executing a dynamic distance trigger threshold configuration rule, and dynamically calculating a distance trigger threshold of each scenic spot according to the scenic spot distribution density and the current positioning precision parameter; when the distance between the position of the user and a certain scenic spot is smaller than the corresponding distance triggering threshold value, staying timing is started, and corresponding voice explanation is triggered after the duration condition is met. The intelligent level and the user experience of the scenic area guide system are improved by dynamically adjusting the trigger threshold value and comprehensively considering the judgment of multi-dimensional factors such as the positioning precision, the scenic spot distribution density and the residence time.

The invention relates to a laser radar point-to-line weighted matching method based on edge point quality evaluation, and belongs to the technical field of measurement. The method solves the problems that in traditional point-to-line matching, due to the fact that the quality of edge points is not evaluated, the pose estimation precision is low, and the robustness of an unstructured scene is poor. According to the technical scheme, a preprocessing module screens candidate edge points through projection point cloud, target segmentation and roughness calculation; the position judgment module classifies the candidate points as middle, left or right edge points according to the category consistency of the adjacent points; the direction consistency judgment module calculates a direction standard deviation and screens effective edge points; and the dynamic weighting module allocates weights according to an exponential attenuation function, and optimizes the pose through weighting residual errors. The method has the advantages that the pose estimation precision is remarkably improved, the weak structure environment adaptability is enhanced, the calculation efficiency is optimized, and redundant iteration is avoided.

The invention provides a three-dimensional geologic body rendering method and system which are used in the field of geospatial information visualization, and the method comprises the steps: obtaining a three-dimensional geologic body model; simplifying the three-dimensional geologic body model by a half folding algorithm based on secondary error measurement; blocking the simplified geologic body model through a planar quadtree, and constructing a spatial index tree according to the blocks to generate a geologic body blocking model of an LOD level; obtaining a viewpoint position and a vision field range of a user, calculating a screen space error, switching a geologic body partitioning model corresponding to an LOD level, and preferentially loading a high-precision close-range tile; the calculation shader based on the WebGPU performs parallel rendering on the geologic body block model tiles; and after the tiles of the geologic body block model are compressed through a Draco compression algorithm, the geologic body block model data stream is sent to the client. According to the scheme, the processing efficiency of the geologic body model in the links of loading, rendering, transmission and the like is improved, and the rendering efficiency of the geologic body model under mass requirements can be effectively guaranteed.

The invention provides a smart city data processing method and device, a node and a storage medium, relates to the technical field of computers, and is used for effectively meeting data processing requirements in a smart city scene. The method comprises the following steps: receiving point location data from a sensor; the point location data is data acquired by the sensor at a deployment position in a city; obtaining a task type and a task priority of a calculation task corresponding to the point location data, and a calculation capability of each distributed calculation node in the plurality of distributed calculation nodes; calling an intelligent contract to process the task type, the task priority and the computing power of each distributed computing node, and determining the task allocation weight of each distributed computing node; based on the task allocation weight of each distributed computing node, allocating the computing task to a target computing node; the probability that the distributed computing node is determined as the target computing node is positively correlated with the task allocation weight of the distributed computing node.