Progress display method and system based on data-driven particle dynamic reconstruction identification

Abstract

The invention relates to the technical field of image data processing, and provides a progress display method and system based on data-driven particle dynamic reconstruction identification. The method comprises the steps of segmenting a data packet into data blocks and generating a meta-information file to establish a mapping relation between a data block index and an anchor point by presetting an anchor point coordinate set and a particle coordinate range of a target identifier, determining an initial position of a particle based on meta-information, and driving the particle to dynamically converge to the anchor point according to a transmission progress until the target identifier is aggregated. According to the method, deep binding of data and vision, multi-dimension of progress perception, self-adaptive compatibility and fusion of visual information spreading value and user experience are realized, and the technical bottleneck that a traditional progress display mode is boring and lacks interactivity and brand relevance is effectively solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image data processing, and more particularly, to a progress display method and system based on data-driven particle dynamic reconstruction identification. BACKGROUND

[0002] The progress display in the current software upgrade package download process mainly relies on traditional progress bars, percentage numbers or simple animations (such as rotating icons) and other basic visualization forms. Such traditional techniques have three core limitations: first, the visual presentation form is single, and users are prone to boredom and anxiety during the waiting process; second, the progress display content and the data itself lack substantive correlation, and only the task completion degree can be mechanically reflected, and the technical characteristics in the data transmission process cannot be transmitted; finally, the interactive dimension is missing, and users cannot perceive real-time state parameters such as transmission rate and stability through visual elements. This one-way display method cannot meet the needs of modern users for interactive experience and information transparency.

[0003] In view of the deficiencies of traditional techniques, some improvement schemes attempt to use preset animations to simulate progress changes (such as graphic filling effects). However, such animation content is still disconnected from the actual transmission data, and its essence belongs to pre-generated standardized visual effects. Since the dynamic mapping relationship between data parameters and visual elements has not been established, the improvement scheme only achieves superficial visual beautification and does not break through the technical bottleneck of "data-visual" duality. This technical limitation makes it difficult to truly reflect the micro-dynamics of data transmission, and there are obvious deficiencies in technical expressiveness and information transmission efficiency.

[0004] Under the background of rapid development of industrial internet and smart devices, especially in the context of vehicle OTA upgrade, the traditional progress display technology has exposed serious adaptability deficiencies. Two-dimensional plane display technology cannot support the presentation needs of device running state space topology, and existing three-dimensional visualization schemes have technical bottlenecks such as low model loading efficiency and high interaction delay. The industry urgently needs a new progress display scheme that can convert data flow into three-dimensional visual expression in real time and has dynamic interaction capability. SUMMARY

[0005] The present application provides a progress display method and system based on data-driven particle dynamic reconstruction identification to break through the one-way display mode of traditional techniques and realize the deep coupling of data characteristics and visual presentation, providing key technical support for cutting-edge scenarios such as intelligent manufacturing and digital twin.

[0006] According to a first aspect of the present application, a progress display method based on data-driven particle dynamic reconstruction identification is provided, comprising: Anchors coordinate set of a preset target identifier, and a preset particle coordinate range; The data packet is divided into a plurality of data blocks according to a preset rule, and a meta-information file is generated based on data block feature information, wherein the data block index has a mapping relationship with the anchor point coordinates of the target identifier; Based on the meta-information file and the particle coordinate range, the initial position of each data block corresponding to the particle is determined in sequence according to the data block index; The real-time position of the corresponding particle is updated according to the transmission progress of the data block until all particles reach the anchor point coordinates to aggregate into the target identifier.

[0007] On the basis of the above technical solutions, the application can also be improved as follows.

[0008] Optionally, the preset anchor point coordinate set of the target identifier comprises: The three-dimensional anchor point coordinate set of the target identifier is pre-stored, and the three-dimensional anchor point coordinate set has N anchors, each anchor has a unique index number and a fixed three-dimensional coordinate (X n , Y n , Z n ), wherein N is a positive integer, n∈[0, N-1].

[0009] Optionally, the preset particle coordinate range comprises: The size of the display unit for displaying the target identifier is determined, and each anchor point coordinate of the target identifier is mapped to the coordinate system of the display unit according to the size ratio of the target identifier and the display unit to determine the particle coordinate range.

[0010] Optionally, the data packet is divided into a plurality of data blocks according to a preset rule, and a meta-information file is generated based on data block feature information, comprising: According to the preset number of anchors N, the data packet is divided into N data blocks, and each data block is assigned a unique index number m, the index number m∈[0, N-1]; For each data block, its data content feature is extracted, and corresponding three-dimensional space offset parameters are generated based on the feature; The index number, size and three-dimensional space offset parameters of each data block are recorded to form a meta-information file; The corresponding mapping relationship between the data block and the anchor point coordinate is established through the index number, realizing one-to-one correspondence between the data block index and the anchor index.

[0011] Optionally, the data block feature is extracted for each data block, and the corresponding three-dimensional space offset parameters are generated based on the feature, comprising: The data content of the data block is converted into a digital sequence, and the bit width w of the digital sequence is determined; The digital sequence is evenly divided into three sub-segments, each sub-segment corresponding to a coordinate axis in three-dimensional space; For each sub-segment, convert it to a decimal value as the original offset value; Each original offset value is normalized and mapped to a preset coordinate range to generate the final three-dimensional spatial offset parameters.

[0012] Optionally, for any coordinate axis in three-dimensional space, the normalization process uses the following formula: Offset parameter = Minimum coordinate value + (Original offset value / Maximum possible value) × (Maximum coordinate value - Minimum coordinate value), The maximum possible value is calculated based on the bit width (w / 3) of the sub-segment.

[0013] Optionally, determining the initial particle position corresponding to each data block according to the index order of each data block based on the metadata file and the particle coordinate range includes: Parse the data block index number, size, and three-dimensional spatial offset parameters recorded in the metadata file; The correspondence between data blocks and preset anchor point coordinates established based on index numbers ensures that anchor points and data blocks with the same index number are bound to each other. Based on the three-dimensional spatial offset parameters and the coordinate values ​​of the corresponding anchor points, the initial spatial coordinates of the particles are determined through spatial vector operations. The initial positions of all particles are generated sequentially according to the data block index order, forming the initial particle spatial distribution.

[0014] Optionally, updating the real-time positions of the corresponding particles according to the transmission progress of the data blocks until all particles reach the anchor point coordinates to aggregate into the target identifier includes: For each data block, a convergence coefficient representing its transmission progress is calculated in real time. The convergence coefficient is the ratio of the amount of data transmitted to the total amount of data. Based on the convergence coefficient, the real-time position of the particle is dynamically updated, so that the particle moves from the initial spatial coordinates along a straight spatial path to the corresponding anchor point coordinates. When the convergence coefficient of the data block reaches 1, the real-time position of the particle coincides with the coordinates of the anchor point. Traverse all data blocks to ensure that the real-time positions of all particles coincide with the corresponding anchor point coordinates, and aggregate them into a complete target identifier.

[0015] Optionally, the real-time position of the particle is updated through interpolation calculation, where the interpolation formula is: Real-time coordinates = Initial spatial coordinates + (Anchor point coordinates - Initial spatial coordinates) × Convergence coefficient.

[0016] According to a second aspect of the present invention, a progress display system based on data-driven particle dynamic reconstruction identifiers is provided, comprising: The anchor point management module is used to preset the anchor point coordinate set of the target identifier and configure the spatial coordinate range of particle motion; The data processing module, connected to the anchor point management module, is used to divide the data packet to be processed into multiple data blocks and generate a metadata file based on the data block feature information; The particle initialization module is connected to the anchor point management module and the data processing module respectively, and is used to determine the initial spatial position of the particle corresponding to each data block according to the data block index order in the metadata file. The dynamic convergence control module, connected to the particle initialization module, is used to update the particle spatial position in real time according to the data block transmission progress status, and drive the particle to converge towards the corresponding anchor point coordinates. The rendering and display module, connected to the dynamic convergence control module, is used to render the particle motion trajectory in real time and present the dynamic reconstruction process of the target identifier on the display interface.

[0017] According to a third aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein the processor is configured to implement the steps of the above-described progress display method based on data-driven particle dynamic reconstruction identifier when executing a computer management program stored in the memory.

[0018] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer management program is stored, wherein when the computer management program is executed by a processor, the steps of the above-described progress display method based on data-driven particle dynamic reconstruction identifier are implemented.

[0019] This invention provides a progress display method, system, electronic device, and storage medium based on data-driven particle dynamic reconstruction of identifiers. Through two main mechanisms—data-driven and dynamic convergence—it transforms traditional linear progress display into a three-dimensional visualization process with the reconstruction meaning of a target identifier (e.g., a brand identifier). Specifically, first, a geometric framework (anchor point coordinate set) of the target identifier is preset. Then, the transmitted data packet is divided into data blocks corresponding to the number of anchor points. Spatial offset parameters are generated by extracting features from the data blocks, thereby determining the initial distribution of particles. As the data transmission progresses, the particle positions are dynamically updated based on a convergence algorithm, causing them to gradually converge from the data-driven initial state towards the preset anchor points, ultimately completely reconstructing the target identifier when the progress is complete.

[0020] This invention employs a data-driven mechanism, segmenting data packets and extracting features to generate particle parameters. This achieves deep integration of progress visualization and data content, ensuring the uniqueness and authenticity of each display process and overcoming the limitations of traditional progress bars being disconnected from data. Secondly, through a particle dynamic convergence algorithm, linear progress indicators are transformed into a multi-dimensional visual experience, allowing users to intuitively perceive real-time statuses such as transmission speed and stability, enhancing the richness and interactivity of progress perception. Finally, particles are aggregated to form preset identifiers with special meanings, such as brand logos, transforming functional progress display into a visual information dissemination process. This not only optimizes the tedium of the waiting process but also enhances the visual information dissemination effect, achieving a fusion of technical functionality and commercial value. Attached Figure Description

[0021] Figure 1 A flowchart of a progress display method based on data-driven particle dynamic reconstruction identifier provided by the present invention; Figure 2 A block diagram of a progress display system based on data-driven particle dynamic reconstruction identifiers provided by the present invention; Figure 3 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention; Figure 4 This is a schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. Detailed Implementation

[0022] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0023] Figure 1 A flowchart of a progress display method based on data-driven particle dynamic reconstruction identifier provided by the present invention is shown below. Figure 1 As shown, the method includes steps S1 to S4: S1 is a preset set of anchor point coordinates for the target identifier, and a preset range of particle coordinates.

[0024] This step is the foundational stage for building the visualization framework. By predefining the geometric structure of the target identifier (such as a brand logo) and the boundaries of particle movement, it provides spatial constraints for subsequent data-driven operations. For example, the anchor point coordinate set uses a three-dimensional coordinate system, containing N anchor points with unique indices. Each anchor point corresponds to a key location point of the identifier, forming the "skeleton" of the target identifier. The particle coordinate range is dynamically set according to the physical size and scale of the display terminal. For example, a coordinate range from -F to +F is defined based on the size of the vehicle's central control screen, ensuring that particle movement is always within the visible range and proportionally consistent. This step transforms the abstract identifier into a quantifiable spatial parameter system, providing a geometric benchmark for particle initialization.

[0025] S2, the data packet is divided into multiple data blocks according to preset rules, and a metadata file is generated based on the data block feature information, wherein the data block index and the anchor point coordinates of the target identifier have a mapping relationship.

[0026] This step, which transforms data into visual parameters, is the core of the data-driven mechanism of this invention. For example, firstly, the data packet is intelligently divided into N data blocks based on the number of anchor points N. Each data block is assigned a unique index number to ensure alignment between the number of data units and visual units. Then, the digital features (such as binary sequences) of each data block are extracted and transformed into three-dimensional spatial offset parameters using a segmented mapping algorithm. For example, the data content is evenly divided into three segments and mapped to X / Y / Z axis offsets. Finally, a metadata file is generated to record the index, size, and offset parameters, and a one-to-one mapping relationship is established between the data block index and the anchor point index, forming a binding chain of "data block m → particle m → anchor point m," providing the data source and target point for particle motion.

[0027] S3. Based on the metadata file and the particle coordinate range, determine the initial position of the particle corresponding to each data block according to the index order of each data block.

[0028] This step completes the initial configuration of the particle system, transforming data features into spatial positions by parsing the metadata file. For example, the system sequentially reads the index number and 3D offset parameters of each data block, combines them with the reference coordinates of the corresponding anchor points, and determines the initial positions of the particles through spatial vector addition. This step strictly follows the data block index order to ensure that the particle distribution retains both data features (the offset parameters reflect differences in data content) and spatial regularities (based on the anchor points). The initialized particle swarm forms a scattered distribution in 3D space, uniquely determined by the data, providing an initial state for dynamic convergence.

[0029] S4, update the real-time position of the corresponding particles according to the transmission progress of the data block until all particles reach the anchor point coordinates to aggregate into the target identifier.

[0030] This step achieves dynamic construction of visual results through progress-driven real-time control. For example, a convergence coefficient K (K = amount of data transmitted / total amount of data) representing the data transmission progress is calculated for each data block. This coefficient K is then substituted into the interpolation formula to dynamically update the particle positions, causing the particles to move gradually along a straight path from their initial positions towards the anchor point. As the transmission progresses, the value of K increases linearly from 0 to 1, and the particle positions continuously approach the anchor point. When all data blocks have been transmitted, K = 1, and the particles completely overlap with the anchor point, aggregating into a complete target identifier on the display interface. In this step, progress data is transformed into visual animation, allowing users to intuitively perceive the complete process of "data flow constructing identifiers."

[0031] Understandably, given the deficiencies in the background technology, this invention proposes a progress display method based on data-driven particle dynamic reconstruction of identifiers. This method transforms traditional linear progress display into a three-dimensional visualization process with the reconstruction significance of a target identifier (e.g., a brand identifier) ​​through two main mechanisms: data-driven and dynamic convergence. Specifically, firstly, a geometric framework (anchor point coordinate set) of the target identifier is preset. Then, the transmitted data packet is divided into data blocks corresponding to the number of anchor points. Spatial offset parameters are generated by extracting features from the data blocks, thereby determining the initial distribution of particles. As the data transmission progresses, the particle positions are dynamically updated based on a convergence algorithm, causing them to gradually converge from the data-driven initial state towards the preset anchor points, ultimately completely reconstructing the target identifier when the progress is complete.

[0032] This embodiment employs a data-driven mechanism, segmenting data packets and extracting features to generate particle parameters. This achieves deep integration of progress visualization and data content, ensuring the uniqueness and authenticity of each display process and overcoming the limitations of traditional progress bars being disconnected from data. Secondly, through a particle dynamic convergence algorithm, linear progress indicators are transformed into a multi-dimensional visual experience, allowing users to intuitively perceive real-time status such as transmission speed and stability, enhancing the richness and interactivity of progress perception. Finally, particles are aggregated to form preset identifiers with special meanings, such as brand logos, transforming functional progress display into a visual information dissemination process. This not only optimizes the tedium of the waiting process but also enhances the visual information dissemination effect, achieving the integration of technical functionality and commercial value.

[0033] Based on the above technical solutions, the embodiments of the present invention can be further improved as follows. To provide a more intuitive explanation of the embodiments of the present invention, the following examples illustrate the application scenario of a vehicle downloading an upgrade data package from the cloud.

[0034] In one possible embodiment, in step S1, the set of anchor point coordinates of the preset target identifier includes: A pre-stored set of three-dimensional anchor point coordinates for target identifiers, wherein the set of three-dimensional anchor point coordinates has N anchor points, each anchor point having a unique index number and fixed three-dimensional coordinates (X, G). n Y n Z n ), where N is a positive integer, n∈[0, N-1].

[0035] For example, using a car manufacturer's 3D logo as the target identifier, 1000 key contour points (N=1000) are extracted using 3D modeling software to construct an anchor point coordinate set. Each point is assigned a unique index number n∈[0,999] and its normalized 3D coordinates are recorded (e.g., index 0 corresponds to coordinates (0.12,0.45,0.78), and index 999 corresponds to (0.88,0.92,0.65)). These preset anchor points not only precisely define the spatial structure of the brand identifier but also provide a geometric reference for subsequent data block mapping: when the upgrade data package is divided into 1000 data blocks, each data block is bound to a specific anchor point through an index number, ultimately driving particle convergence to reconstruct the complete 3D logo, achieving a dynamic brand identifier construction effect and improving the visual information dissemination effect.

[0036] In one possible embodiment, in step S1, the preset particle coordinate range includes: Determine the size of the display unit used to display the target identifier. Based on the size ratio between the target identifier and the display unit, map the coordinates of each anchor point of the target identifier to the coordinate system of the display unit to determine the particle coordinate range.

[0037] For example, in this embodiment, the vehicle's central control screen (1280×720 pixels resolution) is used as the display unit to display the target identifier reconstruction process. First, the normalized coordinate range of the particles is set to [-F, F], where -F is the minimum value of the target range and +F is the maximum value of the target range. This coordinate range is determined according to the size and coordinate ratio of the central control screen, and should not exceed the display range of the central control screen. For example, if F=1.0 is set, then [-F, F] is [-1.0, +1.0].

[0038] Next, the original 3D anchor point coordinates of the target logo (a brand logo) (e.g., the original value of an anchor point (2.5, 1.8, 0.6)) are converted into actual coordinates in the screen coordinate system using a scaling algorithm (X-axis: 2.5 / 5.0×1280=640 pixels, Y-axis: 1.8 / 3.6×720=360 pixels, Z-axis retains the relative depth value of 0.6). Here, parameters 5.0 and 3.6 are scaling factors for the X and Y axes during the coordinate normalization process, used to map the original 3D model coordinates to a preset normalized coordinate range [-1.0, +1.0] (i.e., F=1.0), and then further converted into screen pixel coordinates.

[0039] This embodiment uses a dynamic mapping mechanism based on the display unit size to ensure visual consistency of the markings on devices with different resolutions, while also achieving the technical effect of setting the coordinate range according to the size of the central control screen.

[0040] In one possible embodiment, step S2 includes sub-steps S201 to S204.

[0041] S201, according to the preset number of anchor points N, the data packet is divided into N data blocks, and a unique index number m is assigned to each data block, wherein the index number m∈[0, N-1].

[0042] For example, the cloud divides the upcoming upgrade data packet into N data blocks according to preset rules. The operation process is as follows: When the preset number of anchor points N=1000 (corresponding to the 1000 anchor points of the aforementioned brand logo) and the total size of the upgrade data package is 8.5MB (8500KB), the basic data block size B=8500÷1000=8.5KB is first calculated. Since the total size is divisible by N, the system directly divides the upgrade package into 1000 8.5KB data blocks evenly, and assigns a unique index number m∈[0,999] to each data block sequentially (e.g., the first block m=0, the last block m=999).

[0043] If the total size of the upgrade data package is 8503KB, which is not divisible, then the first 999 data blocks are 8KB each, and the last data block (m=999) contains the remaining 503KB.

[0044] This adaptive segmentation mechanism based on the number of anchor points ensures a one-to-one correspondence between data blocks and anchor points, while also implementing dynamic data block segmentation and anchor point binding rules to adapt to target upgrade packages of different sizes.

[0045] S202, for each data block, extract its data content features, and generate corresponding three-dimensional spatial offset parameters based on the features. Specifically, this includes: The data content of the data block is converted into a digital sequence, and the bit width w of the digital sequence is determined; The number sequence is evenly divided into three sub-segments, each with a bit width of w / 3, and each sub-segment corresponds to a coordinate axis in three-dimensional space; For each sub-segment, convert it to a decimal value as the original offset value; Each original offset value is normalized and mapped to a preset coordinate range to generate the final three-dimensional spatial offset parameters.

[0046] For example, suppose a data block has a 24-bit binary sequence (w=24), specifically "11001010001111010101010". The system first divides it evenly into three 8-bit segments (i.e., each segment has a bit width w / 3=8 bits), including: the X-axis segment "11001010", the Y-axis segment "00111101", and the Z-axis segment "01101010".

[0047] Then, each segment is converted into a decimal raw offset value, such as X-axis: 202, Y-axis: 61, Z-axis: 106.

[0048] Finally, a normalization formula is used for processing. The normalization formula for each axis is: Offset parameter = Minimum coordinate value + (Original offset value / Maximum possible value) × (Maximum coordinate value - Minimum coordinate value). In this normalization formula, the maximum possible value is... The coordinate range is set to [-1.0, 1.0]. The calculated X-axis offset parameter is -1.0 + (202 / 255) × 2 ≈ 0.58, the Y-axis offset parameter is approximately -0.52, and the Z-axis offset parameter is approximately -0.17, thus generating the final three-dimensional spatial offset parameters (0.58, -0.52, -0.17).

[0049] Step S202 fully implements the data-driven mechanism that maps binary data segments to three-dimensional coordinate offsets.

[0050] S203, record the index number, size and three-dimensional spatial offset parameters of each data block, and form a metadata file in the cloud so that the vehicle's OTA Master controller can obtain the metadata file before downloading the data packet.

[0051] Understandably, after the system completes the calculation of the three-dimensional spatial offset parameters for 1000 data blocks, it generates a structured metadata file. This file fully records the index number of each data block (e.g., m=0,1,2...999), the data block size (e.g., the base block is 8.5KB, the last block is 503KB), and the three-dimensional offset parameters (e.g., the offset for index 0 is (0.12,-0.05,0.33), and the offset for index 1 is (0.08,0.21,-0.17)). This metadata file can preferably use JSON format to organize the data, forming a structure such as containing "total_blocks":1000, "blocks":[{"index":0, "size":8704, "offset_x":0.12, "offset_y":-0.05, The complete data structure of “offset_z”:0.33},...], this metadata file, as the core part of data-driven visualization, not only fulfills the technical requirement of recording block size and offset through the metadata file, but also provides accurate parameter basis for subsequent particle initialization.

[0052] S204 establishes a mapping relationship between data blocks and anchor point coordinates through index numbers, realizing a one-to-one correspondence between data block indexes and anchor point indexes.

[0053] Before downloading the upgrade data package, the vehicle's OTA Master controller obtains the aforementioned metadata file and, based on the data block index in the metadata file, maps each data block in the cloud to the vehicle's preset anchor point.

[0054] For example, after the system completes the recording of metadata for 1000 data blocks, a strict mapping relationship is established through index numbers. That is, the data block index m∈[0,999] and the anchor point index n∈[0,999] form a completely corresponding binding relationship (e.g., data block 0→anchor point 0, data block 1→anchor point 1, ..., data block 999→anchor point 999). The dual-index binding mechanism of this embodiment ensures that the particles driven during the download of each data block have a uniquely determined target anchor point. This achieves both the precise mapping of "data block m→particle m→anchor point m" and resolves the technical contradiction between dynamic data generation and fixed identification results through index consistency, providing a reliable path foundation for the subsequent particle convergence motion.

[0055] In one possible embodiment, step S3 includes sub-steps S301 to S304.

[0056] S301, parse the data block index number, size, and three-dimensional spatial offset parameters recorded in the metadata file.

[0057] In this step, the vehicle-side OTA Master controller first loads the aforementioned metadata file and parses the recorded data block index numbers (e.g., index m=0 corresponds to data block 0, m=1 corresponds to data block 1, and so on up to m=N-1), the size of each data block, and the three-dimensional spatial offset parameters (generated by the binary feature mapping of the data blocks, such as the offset parameters of index 0 being 0.12 on the X-axis, -0.05 on the Y-axis, and 0.33 on the Z-axis). The metadata file parsing process can be implemented through file reading and field extraction algorithms to ensure that the index, size, and offset parameters are accurately loaded into memory, providing data support for subsequent particle initial position calculations.

[0058] S302, based on the correspondence between the data block and the preset anchor point coordinates established by the index number, ensure that anchor points and data blocks with the same index number are bound to each other.

[0059] S303, the vehicle-side OTA Master controller determines the initial spatial coordinates of the particles through spatial vector operations based on the three-dimensional spatial offset parameters and the coordinate values ​​of the corresponding anchor points.

[0060] For example, assuming the anchor point coordinates corresponding to the data block with index number m=0 are (X0, Y0, Z0) = (0.5, 0.3, 0.2), the three-dimensional spatial offset parameters of this data block are calculated as (Δx, Δy, Δz) = (0.1, -0.05, 0.03) through step S202. The system calculates the initial position of the particle using the spatial vector addition formula "initial coordinates = anchor point coordinates + offset parameters", that is: Initial X-axis coordinate = 0.5 + 0.1 = 0.6 Initial Y-axis coordinate = 0.3 + (-0.05) = 0.25 Initial Z-axis coordinate = 0.2 + 0.03 = 0.23 The initial spatial coordinates of the particle were finally obtained as (0.6, 0.25, 0.23).

[0061] The vector operation process in this step is performed block by block, ensuring that the initial position of each particle retains the data characteristics reflected by the offset parameter and follows the spatial distribution law based on the anchor point. This achieves the effect that the initial characteristics of the particles are completely determined by the data transmitted in real time.

[0062] S304: Generate the initial positions of all particles sequentially according to the data block index order to form the initial particle spatial distribution.

[0063] For example, after the vehicle-side OTA Master controller completes the initial particle position calculation for a single data block, it iterates through each data block in the order of index m=0,1,2,...,999: First, for the data block with index 0, the initial coordinates of particle 0 (0.6, 0.25, 0.23) are obtained through spatial vector operation using S303. Then, for the data block with index 1, the initial coordinates of particle 1 (0.55, 0.32, 0.19) are calculated, and so on, until the data block with index 999 generates the initial coordinates of particle 999 (0.72, 0.41, 0.28), ultimately forming an initial spatial distribution of 1000 particles in three-dimensional space. This sequential generation mechanism ensures that the particle distribution strictly corresponds to the data block index, fulfilling the requirement of generating particles in index order. This ordered spatial distribution lays a visual foundation for the subsequent dynamic convergence process.

[0064] The OTA Master controller sends the initial coordinates of all generated particles to the vehicle system via the CAN network, and the vehicle system displays the initial positions of the particles on the central control screen.

[0065] In one possible embodiment, step S4 includes: For each data block, the OTA Master controller calculates a convergence coefficient K in real time, which represents the progress of data block transmission. The convergence coefficient K is the ratio of the amount of data transmitted in a single data block to the total amount of data. K = Size of downloaded data block files / Total size of data block files; Based on the convergence coefficient K, the real-time position of the particle is dynamically updated, causing the particle to move from its initial spatial coordinates along a straight spatial path to the corresponding anchor point coordinates; wherein, the update of the particle's real-time position is achieved through interpolation calculation, and the interpolation formula is: Real-time coordinates = Initial spatial coordinates + (Anchor point coordinates - Initial spatial coordinates) × Convergence coefficient K; When the convergence coefficient of the data block reaches 1, the real-time position of the particle coincides with the coordinates of the anchor point. Traverse all data blocks to ensure that the real-time positions of all particles coincide with the corresponding anchor point coordinates, and aggregate them into a complete target identifier.

[0066] For example, assuming the total size of the data block with index m=0 is 8KB, when the amount of data transmitted reaches 4KB, the system calculates the convergence coefficient K=4 / 8=0.5 in real time. Based on the initial particle coordinates (0.6, 0.25, 0.23) and anchor point coordinates (0.5, 0.3, 0.2) corresponding to this data block, the real-time coordinates of the three axes are calculated using interpolation formulas. Real-time X-axis coordinate = 0.6 + (0.5 - 0.6) × 0.5 = 0.55 Real-time Y-axis coordinate = 0.25 + (0.3 - 0.25) × 0.5 = 0.275 Z-axis real-time coordinate = 0.23 + (0.2 - 0.23) × 0.5 = 0.215 As the transmission progresses, when the data block is fully downloaded, the convergence coefficient K=1, and the particle coordinates and anchor point coordinates completely coincide at (0.5, 0.3, 0.2). This process can be executed in parallel for all 1000 data blocks, or it can be traversed sequentially according to the index order. When the K value for all data blocks reaches 1, all particles aggregate into a complete brand logo in three-dimensional space, achieving the effect of displaying progress in multiple dimensions through particle convergence.

[0067] Figure 2 A structural diagram of a progress display system based on data-driven particle dynamic reconstruction identifiers is provided in an embodiment of the present invention, as shown below. Figure 2 As shown, a progress display system based on data-driven particle dynamic reconstruction identifiers includes an anchor point management module, a data processing module, a particle initialization module, a dynamic convergence control module, and a rendering and display module, wherein: The anchor point management module is used to preset the anchor point coordinate set of the target identifier and configure the spatial coordinate range of particle motion; The data processing module, connected to the anchor point management module, is used to divide the data packet to be processed into multiple data blocks and generate a metadata file based on the data block feature information; The particle initialization module is connected to the anchor point management module and the data processing module respectively, and is used to determine the initial spatial position of the particle corresponding to each data block according to the data block index order in the metadata file. The dynamic convergence control module, connected to the particle initialization module, is used to update the particle spatial position in real time according to the data block transmission progress status, and drive the particle to converge towards the corresponding anchor point coordinates. The rendering and display module, connected to the dynamic convergence control module, is used to render the particle motion trajectory in real time and present the dynamic reconstruction process of the target identifier on the display interface.

[0068] It is understood that the progress display system based on data-driven particle dynamic reconstruction identifier provided by the present invention corresponds to the progress display method based on data-driven particle dynamic reconstruction identifier provided in the foregoing embodiments. The relevant technical features of the progress display system based on data-driven particle dynamic reconstruction identifier can be referred to the relevant technical features of the progress display method based on data-driven particle dynamic reconstruction identifier, and will not be repeated here.

[0069] Please see Figure 3 , Figure 3 This is a schematic diagram illustrating an embodiment of the electronic device provided in this invention. For example... Figure 3 As shown, this embodiment of the invention provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, it performs the following steps: S1, preset the anchor point coordinate set of the target identifier, and preset the particle coordinate range; S2, the data packet is divided into multiple data blocks according to preset rules, and a metadata file is generated based on the data block feature information, wherein the data block index and the anchor point coordinates of the target identifier have a mapping relationship; S3. Based on the metadata file and the particle coordinate range, determine the initial position of the particle corresponding to each data block according to the index order of each data block. S4, update the real-time position of the corresponding particles according to the transmission progress of the data block until all particles reach the anchor point coordinates to aggregate into the target identifier.

[0070] Please see Figure 4 , Figure 4 This is a schematic diagram illustrating an embodiment of a computer-readable storage medium provided by the present invention. (See diagram below.) Figure 4As shown, this embodiment provides a computer-readable storage medium 400 on which a computer program 311 is stored. When the computer program 311 is executed by a processor, it performs the following steps: S1, preset the anchor point coordinate set of the target identifier, and preset the particle coordinate range; S2, the data packet is divided into multiple data blocks according to preset rules, and a metadata file is generated based on the data block feature information, wherein the data block index and the anchor point coordinates of the target identifier have a mapping relationship; S3. Based on the metadata file and the particle coordinate range, determine the initial position of the particle corresponding to each data block according to the index order of each data block. S4, update the real-time position of the corresponding particles according to the transmission progress of the data block until all particles reach the anchor point coordinates to aggregate into the target identifier.

[0071] This invention provides a progress display method, system, and storage medium based on data-driven particle dynamic reconstruction of identifiers. First, a set of three-dimensional anchor point coordinates of the target identifier is preset as the geometric framework for visual construction. Then, the data packet is divided into data blocks according to the number of anchor points. Three-dimensional spatial offset parameters are generated by extracting data features and an index mapping between data blocks and anchor points is established. Next, the initial position of the particles is determined based on meta-information to form a data-driven spatial distribution. Finally, the convergence coefficient is calculated in real time according to the transmission progress, driving the particles to dynamically converge towards the anchor points until they are aggregated into a complete identifier.

[0072] This invention achieves breakthrough technical effects on multiple levels through a data-driven particle dynamic reconstruction mechanism: 1. At the level of data and visual integration, binary data streams are converted into particle motion parameters in real time, which completely solves the technical pain point of data and visual disconnect in traditional progress display, ensuring that each progress visualization is unique and authentic; 2. At the progress perception level, a multi-dimensional progress perception system is constructed by synchronously presenting particle convergence degree, motion trajectory stability and progress value, enabling users to intuitively judge changes in transmission status; 3. In terms of system compatibility, the adaptive mechanism of fixed anchor point number and dynamic data segmentation enables intelligent adaptation to data packets of different sizes, significantly improving the universality of the technical solution; 4. In terms of user experience and visual information dissemination, the functional progress display is transformed into a dynamic construction ritual of visual information dissemination symbols. This not only optimizes the tedium of the waiting process but also enhances the effect of visual information dissemination, such as strengthening brand memorability and improving brand value.

[0073] The multiple technical effects of this invention together constitute a complete solution that integrates technological innovation, practical value, and commercial value, breaking through the limitations of traditional progress display technology.

[0074] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0075] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0076] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0077] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0078] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0079] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0080] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A progress display method based on data-driven particle dynamic reconstruction identification, characterized in that, The method comprises the following steps: S1, presetting anchor point coordinate set of target identification, and presetting particle coordinate range; S2, dividing data packet into multiple data blocks according to preset rule, and generating meta-information file based on data block characteristic information, wherein data block index and anchor point coordinate of target identification have mapping relationship; S3, determining initial position of each data block corresponding particle based on meta-information file and particle coordinate range according to index sequence of each data block; S4, updating real-time position of corresponding particle according to transmission progress of data block until all particles reach anchor point coordinate to aggregate into target identification.

2. The progress display method based on data-driven particle dynamic reconstruction identification according to claim 1, characterized in that, The preset anchor point coordinate set of target identification comprises: A three-dimensional anchor point coordinate set of a pre-stored target identifier, the three-dimensional anchor point coordinate set having N anchor points, each anchor point having a unique index number and fixed three-dimensional coordinates (X n , Y n , Z n ), wherein N is a positive integer, n∈[0, N-1].

3. The progress display method based on data-driven particle dynamic reconstruction identification according to claim 1, characterized in that, The preset particle coordinate range comprises: Determining size of display unit for displaying target identification, mapping each anchor point coordinate of target identification to coordinate system of display unit according to size ratio of target identification and display unit to determine particle coordinate range.

4. The progress display method based on data-driven particle dynamic reconstruction identification according to any one of claims 1-3, characterized in that, The method of dividing data packet into multiple data blocks according to preset rule and generating meta-information file based on data block characteristic information comprises: According to preset anchor point number N, data packet is divided into N data blocks, and each data block is assigned a unique index number m, wherein m ∈ [0, N-1]; For each data block, its data content characteristic is extracted, and corresponding three-dimensional space offset parameter is generated based on the characteristic; Index number, size and three-dimensional space offset parameter of each data block are recorded to form meta-information file; Corresponding mapping relationship between data block and anchor point coordinate is established through index number to realize one-to-one correspondence between data block index and anchor point index.

5. The progress display method based on data-driven particle dynamic reconstruction identification according to claim 4, characterized in that, The method of extracting data content characteristic of each data block and generating corresponding three-dimensional space offset parameter based on the characteristic comprises: Data content of data block is converted into digital sequence, and bit width w of the digital sequence is determined; The digital sequence is uniformly divided into three sub-segments, and each sub-segment corresponds to a coordinate axis of three-dimensional space; For each sub-segment, it is converted into decimal value as original offset value; Each original offset value is normalized to map it into preset coordinate range to generate final three-dimensional space offset parameter.

6. The progress display method based on data-driven particle dynamic reconstruction identification according to claim 5, characterized in that, For any coordinate axis of three-dimensional space, normalization processing adopts the following formula: Offset parameter = coordinate minimum value + (original offset value / maximum possible value) × (coordinate maximum value - coordinate minimum value), Wherein, the maximum possible value is calculated based on bit width (w / 3) of the sub-segment.

7. The progress display method based on data-driven particle dynamic reconstruction identification according to claim 5 or 6, characterized in that, The method of determining initial position of each data block corresponding particle based on meta-information file and particle coordinate range according to index sequence of each data block comprises: Analyzing data block index number, size and three-dimensional space offset parameter recorded in meta-information file; According to corresponding relationship between data block and preset anchor point coordinate established by index number, ensuring that anchor point and data block with same index number are bound to each other; Based on three-dimensional space offset parameter and coordinate value of corresponding anchor point, initial space coordinate of particle is determined through space vector operation; Initial position of all particles is generated in sequence according to index sequence of data block to form initial particle space distribution.

8. The progress display method based on data-driven particle dynamic reconstruction identification according to claim 7, characterized in that, The real-time position of the corresponding particle is updated according to the transmission progress of the data block until all particles reach the anchor point coordinates to aggregate into the target identifier, comprising: For each data block, a convergence coefficient representing the transmission progress thereof is calculated in real time, the convergence coefficient being the ratio of the amount of transmitted data to the total amount of data; Based on the convergence coefficient, the real-time position of the particle is dynamically updated, so that the particle moves from the initial spatial coordinates to the corresponding anchor point coordinates along a straight path in space; When the convergence coefficient of the data block reaches 1, the real-time position of the particle coincides with the anchor point coordinates; All particles are traversed so that their real-time positions coincide with the corresponding anchor point coordinates to aggregate into a complete target identifier.

9. The progress display method based on data-driven particle dynamic reconstruction identification according to claim 8, characterized in that, The update of the real-time position of the particle is realized by interpolation calculation, wherein the interpolation formula is: Real-time coordinates = initial spatial coordinates + (anchor point coordinates - initial spatial coordinates) x convergence coefficient.

10. A progress display system based on data-driven particle dynamic reconstruction identification, characterized in that, Comprising: An anchor point management module for presetting anchor point coordinate sets of a target identifier and configuring a spatial coordinate range of particle motion; A data processing module connected with the anchor point management module for splitting a data packet to be processed into multiple data blocks and generating a meta-information file based on data block feature information; A particle initialization module connected with the anchor point management module and the data processing module respectively for determining the initial spatial position of each data block corresponding particle according to the data block index sequence in the meta-information file; A dynamic convergence control module connected with the particle initialization module for updating the spatial position of the particle in real time according to the transmission progress state of the data block to drive the particle to converge and move towards the corresponding anchor point coordinates; A rendering display module connected with the dynamic convergence control module for rendering the particle motion trajectory in real time and presenting the dynamic reconstruction process of the target identifier on the display interface.

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