Efficient rendering optimization system and method for mass GIS point data in unmanned aerial vehicle ground control station

Abstract

The invention discloses an efficient rendering optimization system and method for mass GIS point data in an unmanned aerial vehicle ground control station, belongs to the technical field of geographic information processing of unmanned aerial vehicle ground control, and aims to load and render a large amount of GIS point data on the premise of not reducing data transmission quantity, and improve the rendering efficiency of the GIS point data under the condition that the data is frequently updated. The system only rerenders the GIS points needing to be updated, so that the consumption of computing resources is remarkably reduced, the performance burden caused by global redrawing is avoided, the quick response of a user interface is ensured, and the stable operation of the system in a high-load environment is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of geographic information processing for ground control of unmanned aerial vehicles, and in particular relates to an efficient rendering optimization system and method for massive GIS point data in a ground control station of an unmanned aerial vehicle. Background Art

[0002] With the increasing popularity of drone technology, the application scenarios based on geographic information systems (GIS) are constantly expanding, especially in drone ground control stations, where the demand for efficient processing and visualization of real-time data is becoming more urgent. The rendering of massive GIS point data has become a key link in achieving efficient monitoring and decision support.

[0003] In current GIS applications, users often need to process data from multiple drones, which are usually presented in the form of a large number of points. As the amount of data increases, traditional rendering methods face performance bottlenecks, often resulting in slow interface response and poor user experience, especially on the browser side, where users need to view and interact with a large amount of dynamically updated data in real time, which places higher requirements on rendering technology. For example, the patent with publication number CN114218215A discloses a large-scale GIS data optimization rendering method that significantly improves the initial rendering efficiency through data preprocessing and layered rendering technology, effectively solving the problem of computational complexity in large-scale data rendering; however, when processing frequently updated data, layered rendering may cause delays in the user interface, affecting the overall experience. For another example, the patent with publication number CN109388680A discloses a method and device for improving the rendering efficiency of GIS point data on the browser side that reduces the amount of data transmission and improves the rendering speed through data compression and intelligent loading technology, but in scenarios that require real-time updates, it may still face the problem of data acquisition delay, limiting its application in dynamic environments. Therefore, there are still some technical problems that need to be solved in the prior art in the process of high-frequency data updates and large-scale data rendering. Summary of the invention

[0004] The present invention provides an efficient rendering optimization system and method for massive GIS point data in an unmanned aerial vehicle ground control station, which can effectively solve the performance bottleneck problem occurring during the dynamic update process, and achieve faster rendering speed and smoother user interaction experience.

[0005] To achieve the above objectives, the present invention adopts the following technical solutions:

[0006] An efficient rendering optimization method for massive GIS point data in a UAV ground control station includes the following steps:

[0007] Dynamic z-index management is used to ensure that the drawn markers are displayed correctly according to the visual hierarchy and avoid marker overlap.

[0008] Introduced a custom icon generation and cache mechanism, prioritized cache searches, and improved the efficiency of drawing large amounts of similar point data;

[0009] A graphics rendering-based algorithm is used to ensure that the markers can be rendered quickly. At the same time, the drawing order is dynamically adjusted according to the z-index, and a minimized drawing strategy is adopted when the marker is updated to avoid unnecessary redrawing.

[0010] In the above steps, in dynamic z-index management, when a marker changes, the system automatically updates its z-index value and allows the user to register an event callback function to respond to the marker's state change.

[0011] The custom icon generation and caching mechanism is as follows: using the Canvas tag, an icon is generated according to the waypoint number and status, and it is converted into an image URL and stored in the cache object data. When drawing a new marker, the system first searches the cache. If the corresponding icon is found, it is used directly; if not found, a new icon is generated and added to the cache.

[0012] The efficient rendering optimization system for massive GIS point data in the UAV ground control station used in the above method includes:

[0013] Data acquisition module: responsible for obtaining point data from the GIS database, including identification ID, status and spatial coordinates;

[0014] Cache management module: realizes the generation and caching of custom icons, and is responsible for the storage and retrieval of icons;

[0015] Event handling module: registers event handlers for each tag to allow users to interact;

[0016] Rendering engine module: responsible for drawing markers based on the acquired point data, z-index value and icon information;

[0017] Dynamic update module: responsible for monitoring the changes in point data, re-acquiring data and updating marks when changes occur;

[0018] The data acquisition module interacts directly with the data layer to provide real-time data support; the cache management module cooperates with the rendering engine module to ensure efficient icon use; the rendering engine module coordinates with the event processing module to provide user interaction experience; the dynamic update module relies on the data acquisition module and the rendering engine module to ensure real-time data update and visualization.

[0019] Beneficial effects: The present invention provides an efficient rendering optimization system and method for massive GIS point data in a UAV ground control station, which has the following advantages over the prior art:

[0020] 1. The present invention introduces dynamic z-index management to effectively solve the problem of mark overlap, ensuring that the visual hierarchical relationship of drawn marks is clear, so that users can intuitively identify the status and importance of each point when viewing a large number of marks, significantly improving the system's usability and user experience, and avoiding information transmission barriers caused by mark confusion.

[0021] 2. The present invention adopts a custom icon generation and caching mechanism to greatly improve the efficiency of drawing similar point data. By precisely controlling the generation and caching of icons, the time required for repeated icon generation is reduced, ensuring the system's response speed when processing large amounts of dynamic data. It not only improves the overall drawing speed, but also reduces the system load, and performs particularly well in high-concurrency scenarios.

[0022] 3. The implementation of the efficient drawing algorithm of the present invention ensures the fast rendering of markers and dynamically adjusts the drawing order, effectively avoiding unnecessary redrawing and performance degradation, directly solving the performance bottleneck that may occur when drawing large amounts of data, and ensuring the stability and fluency of the system when processing complex data sets.

[0023] 4. The present invention adopts a rich event processing mechanism to provide users with flexible interaction options, so that users can customize personalized interaction logic according to their needs, support users to generate custom icons, so that points in specific states can be identified by intuitive visual elements, and improve the readability of information and user experience; at the same time, users can flexibly set the display level of icons according to the importance of the point or business logic, to ensure that key information can be displayed first, optimize user operation process and visual experience, and allow users to bind custom event handlers to each mark, enhance the user's interaction ability with the system, in the dynamic data update scenario, users can quickly obtain the required information and perform personalized operations, improve the response speed and flexibility of the system, enhance the interactivity between users and maps, improve user operational satisfaction, encourage users to explore and use GIS data more deeply, this customizable interaction method also improves the system's recognition and ease of use, and adapts to the usage scenarios of different users.

[0024] 5. The present invention's measures of throttling z-index updates and timely clearing useless records effectively prevent memory leaks and performance losses, which not only improves the stability of the system but also enhances its scalability, making it easier to integrate new functions or cope with larger-scale data processing needs in the future.

[0025] 6. The present invention ensures the smooth operation of the system under high-load environment through a series of performance optimization measures. It loads and renders a large amount of GIS point data without reducing the amount of data transmission, meeting the requirements of modern applications for real-time and high efficiency. In the case of frequent data updates, the system only re-renders the GIS points that need to be updated, thereby significantly reducing the consumption of computing resources, avoiding the performance burden caused by global redrawing, and ensuring the rapid response of the user interface. Compared with the existing technology, it shows obvious advantages, not only providing users with a smoother operating experience, but also providing users with a more efficient solution when processing massive GIS data, and promoting the further development of drone-related applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a rendering schematic diagram in an embodiment of the present invention;

[0027] Figure 2 The figure is a flowchart of a rendering optimization method in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments:

[0029] like Figure 2 As shown in the figure, an efficient rendering optimization method for massive GIS point data in a UAV ground control station is provided. The specific steps are as follows:

[0030] Step 1: Obtain GIS point data

[0031] Obtain point data from the GIS database, including the identification ID, status (such as green, yellow, light yellow, gray) and spatial geographic coordinates (latitude and longitude information) of each point;

[0032] Step 2: Find the Custom Icon Cache

[0033] According to the identification ID and status of the point, query the custom icon cache to check whether the corresponding icon already exists. If the corresponding icon does not exist in the cache, the system will enter step 3; if it exists, the icon in the cache is directly used.

[0034] Step 3: Draw and cache icons

[0035] If the corresponding icon does not exist in the cache, the system generates a new custom icon using the Canvas tag based on the identification ID and status, converts the generated icon into an image URL, and stores it in the icon cache. At this time, the icon generation process is designed accordingly according to the status of the point (such as color) to ensure that users can intuitively identify the point status.

[0036] Step 4: Set the z-index

[0037] According to the importance or hierarchical relationship of the points, the system sets a corresponding z-index value for each point. The setting of the z-index value can be based on business logic or user settings to ensure that the display order of the markers on the map is correct and avoid overlap and visual confusion. The layering process is specifically divided into the following steps:

[0038] Define hierarchical rules: Define hierarchical rules for each point according to business needs. For example, the current waypoint of the current aircraft belongs to the first level, and other waypoints of the current route of the current aircraft belong to the second level; all waypoints of the route to be flown by the current aircraft belong to the third level, all waypoints of the current route of non-current aircraft belong to the fourth level, and all waypoints of other routes of the current aircraft or non-current aircraft belong to the fifth level;

[0039] Calculate z-index value: Calculate z-index value for each point, usually based on its importance, status and location and other factors for comprehensive evaluation, you can set a benchmark value, important marks z-index higher than ordinary marks; according to the aircraft to which the waypoint belongs, the display level of the waypoint is set, the large level is displayed at the top of the canvas, the small level is displayed at the bottom of the canvas, in this embodiment, the z-index setting specification is: sort the waypoints, to facilitate the drawing of the level problem, the level is divided into 1-6, a total of 6 levels, specifically:

[0040] 1. Current aircraft, current route, current waypoint: Level 6,

[0041] 2. Current aircraft, current route, 2 waypoints before and after the current waypoint: Level 5,

[0042] 3. Current aircraft, current route, other waypoints except the current waypoint and the two points before and after it: Level 4,

[0043] 4. Current aircraft, route to be flown: Level 3,

[0044] 5. Non-current aircraft, current route: Level 2,

[0045] 6. Other routes except the current route and the route to be flown, regardless of whether it is the current aircraft: Level 1;

[0046] Sorting: Sort the z-index values ​​of all markers to ensure that markers with higher z-index values ​​are displayed first when drawing. You can use an array or list structure to store and sort these values;

[0047] Rendering: Draw the markers one by one according to the sorting results, and put the markers with higher priority in front, to ensure that users can intuitively identify the hierarchical relationship between markers when viewing, and avoid overlap and confusion.

[0048] Step 5: Draw the Markers

[0049] Combining spatial geographic coordinate data, z-index value and custom icon, the system draws markers in the map's canvas container. According to the high and low z-index values, the markers are drawn one by one according to the hierarchical relationship to ensure that the markers are displayed in the correct order on the map.

[0050] Step 6: Register event handler

[0051] Register corresponding event handlers for each drawn marker to support user interaction. Users can set custom responses to events such as clicks and hovers for markers, allowing users to implement personalized interaction logic to enhance user experience.

[0052] Common event types include: marker added (triggered when a new marker is added to the map), marker moved (triggered when the position of a marker changes), marker deleted (triggered when a marker is removed), marker state updated (triggered when the state of a marker (such as color, shape, etc.) changes), click / double-click (triggered when a marker is clicked / double-clicked).

[0053] Step 7: Dynamically Update Markup

[0054] During use, if the data of a certain point changes (such as status update), the system will automatically re-acquire the data of the point, repeat steps 2 to 5, search, draw and update the icon according to the latest data, and update the corresponding event handler; in the case of mark state changes, the event callback function can be used to respond to these changes and adjust the z-index accordingly. Specifically, when the user marks the state change, the event callback function can perform the following operations:

[0055] Update marker state: When the user triggers an event (such as clicking a marker), the callback function can update the state of the marker (for example, from "inactive" to "active")

[0056] Reassign z-index: After the state changes, the callback function can recalculate and set the z-index value of the tag based on the new state or the priority set by the user. For example, when a tag is activated, the system can automatically increase its z-index to display it above other tags, so that users can intuitively identify important tags.

[0057] Step 8: Cleaning and Maintenance

[0058] When a tag is no longer needed, the system promptly clears the tag's z-index record and event binding to prevent memory leaks and maintain system stability.

[0059] Through the implementation of the above steps, efficient drawing and management of massive GIS point data is achieved, ensuring that users can quickly and accurately obtain the required information and conduct effective interaction. The test results are as follows:

[0060] In terms of loading and rendering time, three data sets of different sizes were tested, including 10,000 points, 50,000 points, and 100,000 points. The results show that the traditional rendering method takes 2.5 seconds to render when processing 10,000 points, while the method of the present invention only takes 0.8 seconds, with a performance improvement of 68%. When the amount of data increases to 50,000 points, the rendering time of the traditional method is 8.3 seconds, while the rendering time of the present invention is shortened to 2.1 seconds, with a performance improvement of 75%. When processing 100,000 points, the rendering time of the traditional method is 18.6 seconds, while the rendering time of the method of the present invention is 4.5 seconds, and the performance improvement is also 76%. These results show that the above method significantly improves rendering efficiency under high load conditions.

[0061] In terms of system resource usage, the CPU usage and memory occupancy of the traditional rendering method are significantly higher than those of the method of the present invention. Taking the processing of 10,000 points as an example, the CPU usage of the traditional method is 85%, while that of the method of the present invention is only 40%; the memory usage drops from 250MB to 120MB. When processing 50,000 points, the CPU usage of the traditional method rises to 92%, and the memory usage is 450MB, while that of the present invention is reduced to 50% and 220MB, respectively. When processing 100,000 points, the CPU usage of the traditional method reaches 95%, and the memory usage is 800MB, while the method of the present invention controls the CPU usage at 60%, and the memory usage drops to 400MB. This shows that the present invention has higher efficiency and lower load in resource management.

[0062] In the dynamic update test, when updating 100 points per second, the average response time of the traditional method is 500 milliseconds, while the method of the present invention is only 120 milliseconds, an improvement of 76%. When updating 500 points per second, the average response time of the traditional method is 800 milliseconds, while the method of the present invention is 200 milliseconds, and the performance improvement also reaches 75%. These results all illustrate the advantages of the present invention in processing high-frequency data updates, ensuring that users can obtain a smoother interactive experience.

[0063] The above comparison between the traditional rendering method and the method of the present invention loads the same amount of GIS point data under the same hardware and network environment, measures the rendering time, user interface response time, and system CPU and memory usage. The experimental results show that the rendering speed of the present invention is significantly improved, and the system load is lower.

[0064] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An efficient rendering optimization method for massive GIS point data in an unmanned aerial vehicle ground control station, characterized in that: The following steps are involved: Dynamic z-index management is used to ensure that the drawn markers are displayed correctly according to the visual hierarchy; Introduced a custom icon generation and caching mechanism, giving priority to cache searches; A graphics rendering-based algorithm is used to ensure fast marker rendering. The drawing order is dynamically adjusted according to the z-index, and a minimal drawing strategy is adopted when the marker is updated.

2. The efficient rendering optimization method for massive GIS point data in the UAV ground control station according to claim 1 is characterized in that: The process of layering in a hierarchical relationship includes the following steps: Define hierarchical rules: define hierarchical rules for each point according to business requirements; Calculate z-index value: Calculate z-index value for each point; Sorting: Sort the z-index values ​​of all markers to ensure that markers with higher z-index values ​​are displayed first when drawing; Rendering: Draw the markers one by one according to the sorting results, and put the markers with higher priority in front, so as to ensure that users can intuitively identify the hierarchical relationship between markers when viewing, and avoid overlap and confusion.

3. The efficient rendering optimization method for massive GIS point data in the UAV ground control station according to claim 2 is characterized in that: The base value is set in calculating the z-index value. The z-index of important markers is higher than that of ordinary markers.

4. The method for efficiently rendering and optimizing massive GIS point data in a UAV ground control station according to claim 2, characterized in that: Use an array or list structure to store and sort the z-index values.

5. The efficient rendering optimization method for massive GIS point data in the UAV ground control station according to claim 1 or 2, characterized in that: In dynamic z-index management, when a marker changes, the system automatically updates its z-index value and allows users to register event callback functions to respond to marker state changes.

6. The method for efficiently rendering and optimizing massive GIS point data in a UAV ground control station according to claim 5, characterized in that: When the marker state changes, the event callback function does the following: Update the mark status: When the user triggers an event, the callback function updates the mark status; Reassign z-index: After the state changes, the callback function recalculates and sets the z-index value of the marker according to the new state or the priority set by the user.

7. The efficient rendering optimization method for massive GIS point data in the UAV ground control station according to claim 1 is characterized in that: The custom icon generation and caching mechanism is as follows: using the Canvas tag, an icon is generated according to the waypoint number and status, and it is converted into an image URL and stored in the cache object data. When drawing a new marker, the system first searches the cache. If the corresponding icon is found, it is used directly; if not found, a new icon is generated and added to the cache.

8. The method for efficiently rendering and optimizing massive GIS point data in a UAV ground control station according to claim 5, characterized in that: Combining spatial geographic coordinate data, z-index value and custom icon, the system draws markers in the map's canvas container. According to the high and low z-index values, the markers are drawn one by one according to the hierarchical relationship to ensure that the markers are displayed in the correct order on the map.

9. The method for efficiently rendering and optimizing massive GIS point data in a UAV ground control station according to claim 8, characterized in that: When a tag is no longer needed, the system promptly clears the z-index record and event binding of the tag.

10. The efficient rendering optimization system for massive GIS point data in the UAV ground control station used in the method according to any one of claims 1 to 9, characterized in that: include: Data acquisition module: responsible for obtaining point data from the GIS database; Cache management module: realizes the generation and caching of custom icons, and is responsible for the storage and retrieval of icons; Event handling module: registers event handlers for each tag to allow users to interact; Rendering engine module: responsible for drawing markers based on the acquired point data, z-index value and icon information; Dynamic update module: responsible for monitoring the changes in point data, re-acquiring data and updating marks when changes occur; Among them, the data acquisition module interacts directly with the data layer to provide real-time data support; the cache management module cooperates with the rendering engine module to ensure efficient icon use; the rendering engine module and the event processing module coordinate with each other to provide user interaction experience; the dynamic update module relies on the data acquisition module and the rendering engine module to ensure real-time data update and visualization.

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