Low-altitude intelligent networking video service simulation method and device, equipment and storage medium

Abstract

The application provides a low-altitude intelligent networking video service simulation method and device, equipment and storage medium, and relates to the technical field of information processing. The method comprises the following steps: acquiring scene information, generating an application scene comprising a plurality of unmanned aerial vehicles according to the plurality of unmanned aerial vehicles indicated by the scene information; simulating the application scene to obtain scene data of the application scene, and storing the scene data in a cloud service platform; wherein the unmanned aerial vehicles are used for collecting field data, and the scene data is obtained according to the field data of the plurality of unmanned aerial vehicles; when a service request indicating a video service is acquired, the scene data is called from the cloud service platform, and video data used for replying to the service request is obtained according to the scene data. The method of the application solves the problem of how to efficiently and quickly realize video service simulation.

Description

Technical Field

[0001] This application relates to the field of information processing technology, and in particular to a low-altitude intelligent network video service simulation method, apparatus, equipment and storage medium. Background Technology

[0002] With the development of drone technology, drones are being increasingly widely used in people's production and daily lives, such as surveying and monitoring. In many fields, drones transmit footage captured during flight to cloud service platforms, where the videos can then be viewed.

[0003] However, video files are typically large, and the processing time during transmission is significant, severely impacting video playback. Furthermore, most commercially available drone video services utilize standalone simulation systems, which cannot integrate local area networks with the simulation system, hindering real-time acquisition and processing of video data.

[0004] How to efficiently and quickly implement video service simulation is a problem that this invention urgently needs to solve. Summary of the Invention

[0005] This application provides a method, apparatus, device, and storage medium for simulating low-altitude intelligent network video services, in order to solve the problem of how to efficiently and quickly realize video service simulation.

[0006] Firstly, this application provides a method for simulating low-altitude intelligent network video services, the method comprising:

[0007] Acquire scene information, and generate an application scenario that includes multiple drones based on the multiple drones indicated by the scene information;

[0008] The application scenario is simulated to obtain scenario data, which is then stored on a cloud service platform. The scenario data is obtained from the on-site data collected by multiple drones.

[0009] When a business request for video services is received, scene data is retrieved from the cloud service platform, and video data for responding to the business request is obtained based on the scene data.

[0010] In one possible design, scene information is obtained, including:

[0011] Obtain the scenario networking planning file; the scenario networking planning file includes the number of multiple drones and the number of each drone;

[0012] Based on the scenario networking planning document, the scenario information is obtained.

[0013] In one possible design, the site data includes site photos;

[0014] The application scenario is simulated to obtain scenario data, including:

[0015] Simulations were performed on the on-site images, motion mode data, and shooting time data of multiple drones to obtain scene data for the application scenario; among which, motion mode data includes the real-time motion status and real-time motion data of the drones.

[0016] In one possible design, upon receiving a service request indicating a video service, scene data is retrieved from the cloud service platform, including:

[0017] Parse the service request to obtain the packet header information; the packet header information is used to indicate the type of service request; the type of service request includes video service or data service;

[0018] When the Baotou information indicates the type of business request, and it is a video service, multiple drones' respective on-site images are retrieved from the cloud service platform.

[0019] In one possible design, based on scenario data, video data for responding to business requests is obtained, including:

[0020] By integrating the on-site images from multiple drones, on-site videos of each drone can be obtained;

[0021] Based on multiple live videos, video data was obtained to respond to business requests.

[0022] In one possible design, when parsing the business request, call parameters are also obtained; the call parameters are used to indicate the display of video data from at least one target drone; the target drone is one of multiple drones.

[0023] By integrating the on-site images from multiple drones, on-site videos of each drone are obtained, including:

[0024] Based on the call parameters, filter out the on-site images of each target drone;

[0025] By integrating the on-site images of each target drone, an on-site video of each target drone can be obtained.

[0026] In one possible design, upon receiving a business request indicating data service, the method further includes:

[0027] The system retrieves motion mode data and shooting time data from multiple drones from the cloud service platform.

[0028] Based on the motion pattern data and shooting time data of each drone, text data for responding to business requests is obtained.

[0029] Secondly, this application provides a low-altitude intelligent network video service simulation device, comprising:

[0030] The scene generation module is used to acquire scene information and generate an application scene that includes multiple drones based on the multiple drones indicated by the scene information.

[0031] The data processing module is used to simulate application scenarios, obtain scenario data, and store the scenario data to the cloud service platform; among them, drones are used to collect on-site data, and the scenario data is obtained based on the on-site data of multiple drones.

[0032] The video generation module is used to retrieve scene data from the cloud service platform when a business request indicating video service is received, and to obtain video data to respond to the business request based on the scene data.

[0033] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0034] The memory stores instructions that the computer executes;

[0035] The processor executes computer execution instructions stored in memory to implement a low-altitude intelligent network video service simulation method according to the first aspect of the invention.

[0036] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement a low-altitude intelligent network video service simulation method according to the first aspect of the invention.

[0037] Fifthly, this application provides a computer program product, comprising: a computer program, which, when executed by a processor, is used to implement a low-altitude intelligent network video service simulation method according to the first aspect of the invention.

[0038] This application provides a low-altitude intelligent network video service simulation method, apparatus, equipment, and storage medium. It acquires scene information, generates an application scenario involving multiple drones based on the scene information indicating multiple drones, simulates the application scenario to obtain scene data, and stores the scene data on a cloud service platform. The drones are used to collect field data, and the scene data is obtained based on the field data of each drone. When a service request indicating a video service is received, the scene data is retrieved from the cloud service platform, and video data for responding to the service request is obtained based on the scene data. The following technical effects are achieved: By designing a simulation system to generate application scenarios, the flight and motion states of drones can be simulated, avoiding the problem of high testing costs due to the large amount of manpower, resources, and equipment required for real-world testing; combined with a local area network, drone data can be acquired, and application scenario data can be obtained based on the data simulation, solving the problem of video service simulation and facilitating rapid verification of video service functions and processes; through service requests, image data can be quickly retrieved, and video can be generated based on the image data, avoiding the problem of lengthy video transmission times, effectively reducing costs and latency, and improving verification efficiency. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 A schematic diagram of the system architecture of the low-altitude intelligent network video service simulation method provided in the embodiments of this application;

[0041] Figure 2 Application scenario framework diagram of the low-altitude intelligent network video service simulation method provided in the embodiments of this application;

[0042] Figure 3 A flowchart illustrating the low-altitude intelligent network video service simulation method provided in this application embodiment. Figure 1 ;

[0043] Figure 4 A flowchart illustrating the low-altitude intelligent network video service simulation method provided in this application embodiment. Figure 2 ;

[0044] Figure 5 Video service interaction diagram of the low-altitude intelligent network video service simulation method provided in the embodiments of this application;

[0045] Figure 6A schematic diagram of the structure of the low-altitude intelligent network video service simulation device provided in the embodiments of this application;

[0046] Figure 7 This is a schematic diagram of the structure of the electronic device hardware provided in the embodiments of this application.

[0047] Figure label:

[0048] 100 - Low-altitude intelligent network video service simulation system; 110 - Access network simulation server; 120 - Central server; 130 - Database; 140 - Client; 150 - Gateway;

[0049] 111-Scene Generation Module; 112-Data Generation Module; 113-First Communication Module; 121-Database Module; 122-Main Service Module; 123-Second Communication Module; 131-Data Management Module; 132-Storage Module; 133-Read Module; 141-Display Module; 142-Client Processing Module; 143-Third Communication Module;

[0050] 210 - Unmanned Aerial Vehicle (UAV);

[0051] 600 - Low-altitude intelligent network video service simulation device; 610 - Scene generation module; 620 - Data processing module; 630 - Video generation module;

[0052] 700 - Electronic device; 710 - Processor; 720 - Memory; 730 - Communication component; 740 - Bus. Detailed Implementation

[0053] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0054] In the embodiments of this application, the terms "first" and "second" are used to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, nor do they necessarily imply difference. It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner. In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more.

[0055] It should be noted that the phrase "at...time" in the embodiments of this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; the embodiments of this application do not specifically limit this. Furthermore, the low-altitude intelligent network video service simulation method provided in the embodiments of this application is only an example, and the low-altitude intelligent network video service simulation method may include more or less content.

[0056] To facilitate a clear description of the technical solutions in the embodiments of this application, some terms and technologies involved in the embodiments of this application will be briefly introduced below:

[0057] Low-altitude intelligent network: The low-altitude intelligent network refers to a comprehensive network system built using advanced communication, navigation, surveillance, and data processing technologies to support the efficient and safe operation of low-altitude aircraft (such as drones). This network not only includes interconnection between low-altitude aircraft but also covers connections between low-altitude aircraft and other facilities such as ground stations and satellites, aiming to achieve intelligent management and application in the low-altitude domain.

[0058] Gateway: A gateway is a device that connects different types of networks and enables them to communicate with each other. A gateway can not only forward data packets between two different networks, but also convert data formats as needed to suit the requirements of the target network.

[0059] Cloud service platform: A cloud service platform refers to a platform that provides computing resources and services via the Internet. These resources and services may include servers, storage, databases, networks, software, analysis tools, etc., and users can choose appropriate services according to their needs. In this application, it can be understood as an implementation method of drone video services, and does not refer to a single server in this application, but rather to a system with the same functions as multiple servers in this application, which can be used to implement video service simulation.

[0060] Intelligent terminal devices: Intelligent terminal devices refer to those devices with built-in computing power and intelligent operating systems, which can interact with users or other devices through the Internet or other communication networks. These devices are typically highly portable and easy to use, capable of performing a variety of functions, from simple information retrieval to complex task processing.

[0061] Unreal Engine: Unreal Engine is a software platform widely used in simulation development. It can be used for simulation software in various scenarios.

[0062] Satellite Tool Kit (STK): STK is a high-performance spacecraft simulation software primarily used for spacecraft orbit design, satellite communication analysis, radar coverage analysis, missile trajectory simulation, and Earth observation mission planning. In this application, a UAV node can be added to enable video service verification.

[0063] Packet Header: This usually refers to the header portion of a data packet, which contains various control information and metadata about the packet.

[0064] Low-altitude intelligent networking (LAC) is a communication technology based on cloud service platforms and intelligent terminal devices, providing a comprehensive network system for drones to support efficient and safe operation. Drones are widely used in various fields, and their terminals can send data to cloud servers for unified management, with video service verification being particularly important.

[0065] In existing technologies, verification of video services mostly relies on Unreal Engine or STK to generate low-altitude terminal scenarios and verify video services.

[0066] While this method can verify video services, it still has some technical issues:

[0067] Firstly, video files are usually large and take a lot of time to transmit. Using virtual software cannot avoid the problem of extended video file transmission.

[0068] Secondly, this type of method only achieves virtual scene generation, but does not achieve interconnection with the local area communication network, and cannot quickly realize the verification of video services.

[0069] Video file processing involves large volumes and high costs, so functional and process verification must be performed through a simulation verification system before building a real system.

[0070] Therefore, how to efficiently and quickly realize video service simulation is a problem that this invention urgently needs to solve.

[0071] Based on this, embodiments of this application provide a low-altitude intelligent network video service simulation method, apparatus, device, and storage medium, which can be used in the field of information processing technology and aims to solve the above-mentioned technical problems of the prior art.

[0072] Figure 1 This is a schematic diagram of the system architecture for the low-altitude intelligent network video service simulation method provided in this application embodiment. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this application, in order to help those skilled in the art understand the technical content of this application, but do not mean that the embodiments of this application cannot be used in other devices, systems, environments or scenarios.

[0073] like Figure 1 As shown, the system architecture of the low-altitude intelligent network video service simulation method includes: low-altitude intelligent network video service simulation system 100.

[0074] In this embodiment of the application, the low-altitude intelligent network video service simulation system 100 can be equipped with a variety of software or systems that provide service support, including: access network simulation server 110, central server 120, database 130, client 140 and gateway 150.

[0075] The access network simulator 110 includes three modules: a scenario generation module 111, a data generation module 112, and a first communication module 113. The scenario generation module 111 generates a corresponding number of drones based on the acquired scenario information, i.e., generates an application scenario, and sends the corresponding numbers of multiple drones to the data generation module. The data generation module 112 generates the motion trajectory of each drone and the data of the drone at each moment based on the multiple drones and the application scenario generated, and stores this data. The first communication module 113 is responsible for receiving and sending data and signaling.

[0076] The central server 120 comprises three modules: a database module 121, a main service module 122, and a second communication module 123. The database module 121 stores and retrieves data sent by the first communication module 113, including user image and video information, and interacts with the database 130. The main service module 122 identifies various service requests, instructs the database module 121 to perform data operations for those requests (i.e., parses the service request, determines its type, retrieves the corresponding service data from the database module 121, and pushes it to the second communication module 123). The second communication module 123 is responsible for receiving and sending data or signaling.

[0077] Database 130 comprises three modules: a data management module 131, a storage module 132, and a retrieval module 133. The data management module 131 is used to classify and store various types of business data, and can interact with and access the storage module 132 and retrieval module 133. The storage module 132 stores data from database module 121 of the central server 120 into the data management module 131. The retrieval module 133 retrieves data from the data management module 131.

[0078] The client 140 comprises three modules: a display module 141, a client processing module 142, and a third communication module 143. The display module 141 is used to play videos, with data sourced from the client processing module 142. The client processing module 142 is used to generate videos from received image data, with data sourced from the second communication module 123 of the central server 120. The third communication module 143 is responsible for communication with the server, as well as sending and receiving data and signaling.

[0079] Gateway 150 is used to connect the access network simulation server 110, central server 120, database 130 and client 140 for communication.

[0080] Figure 2 This is an application scenario framework diagram for the low-altitude intelligent network video service simulation method provided in the embodiments of this application. The application scenario architecture diagram can be used for various application scenarios described below, as well as other application scenarios not specified. It should be noted that... Figure 2 The illustrations shown are merely examples of application scenarios that can be applied to the embodiments of this application, in order to help those skilled in the art understand the technical content of this application, but do not mean that the embodiments of this application cannot be used in other devices, systems, environments or scenarios.

[0081] like Figure 2 As shown, the drone 210 captures images during its flight and transmits them to the low-altitude intelligent network video service simulation system 100 via a communication network.

[0082] After acquiring image data and other data, the low-altitude intelligent network video service simulation system 100 generates application scenarios through the access network simulation server 110 and processes service requests through the central server 120. Based on the service requests, it calls data stored in the database 130 and transmits the data to the client 140. The client 140 processes the image data and generates the video captured by the drone 210, which is played on the client at a certain frame rate to facilitate rapid verification of the video service.

[0083] The video data from the UAV 210 can be transmitted to the Low-Altitude Intelligent Network Video Service Simulation System 100 for video playback, or the UAV data uploaded by the user 220 can be transmitted to the Low-Altitude Intelligent Network Video Service Simulation System 100 for video playback.

[0084] Figure 3 A flowchart illustrating the low-altitude intelligent network video service simulation method provided in this application embodiment. Figure 1 .like Figure 3 As shown, the method includes:

[0085] S301. Obtain scene information and generate an application scene including multiple drones based on the multiple drones indicated by the scene information.

[0086] Specifically, scenario information refers to the application scenario information extracted from the scenario networking planning document. Scenario information includes multiple drones and their respective corresponding numbers.

[0087] Read the scenario networking planning file provided by the user, obtain the scenario information, and generate application scenarios for a corresponding number of drone terminals based on the scenario information.

[0088] S302. Simulate the application scenario to obtain scenario data, and store the scenario data to the cloud service platform.

[0089] Among them, drones are used to collect on-site data, and the scene data is obtained based on the on-site data of multiple drones.

[0090] Specifically, the system simulates multiple application scenarios for drones, generates the motion trajectory of each drone, acquires the data corresponding to each drone at each moment, and stores the data in a database.

[0091] In this application, the on-site data corresponding to each of the multiple drones can be either data captured by drones connected to the system in real time, or data uploaded by the user from their own drones.

[0092] S303. When a business request for video services is received, scene data is retrieved from the cloud service platform, and video data for responding to the business request is obtained based on the scene data.

[0093] Specifically, the scene data includes on-site images, motion mode data, and shooting time data.

[0094] When a user's video service request is received, the system retrieves the scene images from the drone's scene data corresponding to the request from the database and generates a video from the scene images to display the video captured by the drone corresponding to the request.

[0095] In addition, when the business request is a data service, the motion mode data and shooting time data of the drone scene data corresponding to the business request are retrieved from the database and displayed on the client.

[0096] This application provides a low-altitude intelligent network video service simulation method. It acquires scene information, generates an application scenario involving multiple drones based on the scene information indicating multiple drones, simulates the application scenario to obtain scene data, and stores the scene data on a cloud service platform. Since the drones are used to collect on-site data, the scene data is obtained from the on-site data of each drone. When a service request indicating a video service is received, the scene data is retrieved from the cloud service platform, and video data for responding to the service request is obtained based on the scene data. This achieves the following technical effects: By designing a simulation system to generate application scenarios, the flight and motion states of drones can be simulated, avoiding the problem of high testing costs due to the large amount of manpower, resources, and equipment required for real-world testing; combined with a local area network, drone data can be acquired, and application scenario data can be obtained through data simulation, solving the problem of video service simulation and facilitating rapid verification of video service functions and processes; through service requests, image data can be quickly retrieved, and video can be generated based on the image data, avoiding the problem of lengthy video transmission times, effectively reducing costs and latency, and improving verification efficiency.

[0097] Figure 4 A flowchart illustrating the low-altitude intelligent network video service simulation method provided in this application embodiment. Figure 2 This embodiment is in Figure 3 Based on the embodiments, the specific steps of the low-altitude intelligent network video service simulation method are described in detail, such as... Figure 4 As shown in the figure, this embodiment provides a low-altitude intelligent network video service simulation method, including:

[0098] S401. Obtain the scenario networking planning file.

[0099] The scenario networking planning document includes the number of drones and the number of each drone.

[0100] Specifically, it involves acquiring scene information. The scene networking planning file is a planning file uploaded by the user, which includes multiple drones and the corresponding number information for each drone.

[0101] S402. Obtain scene information based on the scene network planning document.

[0102] Specifically, based on the scenario networking planning document, the number of drones present in the desired application scenario is obtained.

[0103] S403. Based on the scene information indicating multiple drones, generate an application scene that includes multiple drones.

[0104] Specifically, based on the multiple drones provided in the scenario information, an application scenario is generated. The application scenario includes multiple drones. The scenario generation module of the access network simulation server generates the application scenario.

[0105] S404. Simulate the scene data of the application scenario by analyzing the on-site images, motion mode data, and shooting time data of multiple drones.

[0106] The motion mode data includes the drone's real-time motion status and real-time motion data. The on-site data includes on-site images.

[0107] Specifically, the application scenario is simulated to obtain scenario data. Simulations are performed on application scenarios using multiple drones to obtain scenario data. Scenario data includes on-site images captured by each drone, motion pattern data for each drone, and shooting time data for each drone. The data generation module of the access network simulation server generates the motion trajectory of each drone after generating the application scenario.

[0108] S405. Store the scene data to the cloud service platform.

[0109] Among them, drones are used to collect on-site data, and the scene data is obtained based on the on-site data of multiple drones.

[0110] Specifically, the scenario data generated from the simulated application scenarios is stored on a cloud service platform.

[0111] The data generation module of the access network simulation server stores the data at each moment into the database.

[0112] S406. Parse the business request to obtain the packet header information.

[0113] The header information is used to indicate the type of business request.

[0114] Specifically, the business request is obtained, parsed, and the packet header information is obtained.

[0115] The main service module of the central server identifies various types of business requests, that is, it parses the received business requests, obtains the packet header information, and determines what type of business request it is.

[0116] When the Baotou information indicates that the service request type is video service, execute step S409; when the Baotou information indicates that the service request type is data service, execute step S407.

[0117] S407. From the cloud service platform, retrieve the motion mode data and shooting time data of multiple drones.

[0118] Specifically, the system retrieves motion mode data and shooting time data for multiple drones from the cloud service platform. In other words, when the central server's database module receives data from the main service module's business request, it retrieves the corresponding motion mode data and shooting time for each drone from the database.

[0119] After S407 is executed, S408 is executed.

[0120] S408. Based on the motion mode data and shooting time data of each drone, obtain text data for responding to business requests.

[0121] Specifically, the motion mode data and shooting time data of each drone retrieved from the database are transmitted to the client via the communication module and displayed so that users can view the data.

[0122] S409. When the type of service request indicated by the Baotou information is video service, retrieve the on-site images from multiple drones from the cloud service platform.

[0123] Specifically, when a business request indicating a video service is received, scene data is retrieved from the cloud service platform. If the header information indicates that the business request type is a video service, multiple on-site images taken by drones corresponding to the business request are retrieved from the cloud service platform.

[0124] After executing S409, execute S410.

[0125] S410: Based on the call parameters, filter out the on-site images of each target drone.

[0126] When parsing the business request, the call parameters were also obtained; the call parameters are used to indicate the display of video data of at least one target drone; the target drone is one of multiple drones.

[0127] Specifically, the parameters to be invoked refer to the video data corresponding to the target drone selected by the user.

[0128] S411. Integrate the on-site images of each target drone to obtain the on-site video of each target drone.

[0129] Specifically, based on the scene data, video data is obtained to respond to business requests. The on-site images from multiple drones are integrated to obtain the on-site video from each drone.

[0130] S412. Based on multiple on-site videos, obtain video data for responding to business requests.

[0131] Specifically, based on multiple on-site videos, video data of the target drone corresponding to the business request is obtained.

[0132] The technical effects of the low-altitude intelligent network video service simulation method provided in this application are as follows: based on the service request, the video footage corresponding to the target drone can be filtered out, which helps users to conveniently select the desired drone footage; by calling on on-site images, the computation time extension of video transmission is avoided, so as to quickly verify the functions and processes of the video service.

[0133] To explain this application in detail, a specific embodiment is introduced herein: this embodiment is merely an example of a video service.

[0134] Figure 5 The video service interaction diagram is provided for the low-altitude intelligent network video service simulation method in the embodiments of this application.

[0135] S501, the access network simulation server generates application scenarios and obtains scenario data.

[0136] The access network simulation server receives the scenario networking planning file. The scenario generation module acquires the scenario information, generates a corresponding number of drone terminals based on the scenario information, and sends the corresponding number of each drone to the data generation module. The data generation module is then used to generate data for the terminal drones, such as location and motion information. That is, after the scenario generates the drones, the data generation module generates the motion trajectory of each drone, thus obtaining the scenario data.

[0137] S502, the access network simulation server transmits the scenario data to the gateway.

[0138] The access network simulation server sends the scenario data to the gateway through the first communication module.

[0139] S503, the gateway transmits scene data to the central server.

[0140] S504, the central server transmits scene data to the database.

[0141] The central server's database module sends scene data to the database via the second communication module.

[0142] S505, the database stores the scene data.

[0143] The database storage module stores the scene data in the data management module.

[0144] S506: The client sends a video service request to the gateway.

[0145] S507, the gateway transmits video service requests to the central server.

[0146] The main service module of the central server has identified the request as a video service request based on the header information of the service request.

[0147] S508: The central server retrieves the corresponding data from the database based on the video service request.

[0148] The central server's database module retrieves the corresponding data from the database.

[0149] S509. The database sends the corresponding data to the central server.

[0150] The database reading module reads the corresponding data from the data management module and sends it to the central server.

[0151] S510, the central server forwards the corresponding data to the gateway.

[0152] S511, the gateway sends the corresponding data to the client.

[0153] S512: The client integrates the corresponding data and generates a video.

[0154] The client's third communication module receives the corresponding data, and the client processing module generates a video from the received image data, which is then displayed on the display module. Users can select and play videos captured by the target drone according to their requirements.

[0155] This application provides a low-altitude intelligent network video service simulation method. The system is combined with a local area communication network and is not limited to stand-alone simulation software, which effectively improves the efficiency of video service functional verification. By combining virtual low-altitude scenarios and local area communication networks, the verification cost and latency are effectively reduced, and the verification efficiency of video services is improved.

[0156] This application embodiment can divide an electronic device or main control device into functional modules according to the above method examples. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0157] Figure 6 This is a schematic diagram of the structure of the low-altitude intelligent network video service simulation device provided in an embodiment of this application. Figure 6As shown, the low-altitude intelligent network video service simulation device 600 includes: a scene generation module 610, a data processing module 620, and a video generation module 630.

[0158] The scene generation module 610 is used to acquire scene information and generate an application scene including multiple drones based on the multiple drones indicated by the scene information.

[0159] The data processing module 620 is used to simulate the application scenario, obtain the scenario data, and store the scenario data to the cloud service platform; wherein, the drone is used to collect field data, and the scenario data is obtained based on the field data of multiple drones.

[0160] The video generation module 630 is used to retrieve scene data from the cloud service platform when it receives a business request indicating video service, and to obtain video data to respond to the business request based on the scene data.

[0161] In one possible design, the scene generation module 610 includes:

[0162] The file acquisition module is used to acquire the scene networking planning file; the scene networking planning file includes the number of multiple drones and the number of each drone.

[0163] The scene information module is used to obtain scene information based on the scene networking planning file.

[0164] In one possible design, the site data includes site photos;

[0165] Data processing module 620 includes:

[0166] The scene data module is used to simulate the scene data of the application scenario by analyzing the on-site images, motion mode data and shooting time data of multiple drones. Among them, the motion mode data includes the real-time motion status and real-time motion data of the drones.

[0167] In one possible design, the video generation module 630 includes:

[0168] The parsing module is used to parse business requests and obtain packet header information; the packet header information indicates the type of business request; the type of business request includes video service or data service;

[0169] The calling module is used to indicate the type of business request in the packet header information. When it is a video service, it calls the on-site images of multiple drones from the cloud service platform.

[0170] In one possible design, the video generation module 630 includes:

[0171] The integration module is used to combine the on-site images from multiple drones to obtain the on-site video of each drone.

[0172] The video display module is used to obtain video data for responding to business requests based on multiple live videos.

[0173] In one possible design, when parsing the business request, call parameters are also obtained; the call parameters are used to indicate the display of video data from at least one target drone; the target drone is one of multiple drones.

[0174] The integration module includes:

[0175] The filtering module is used to filter out on-site images of each target drone based on the calling parameters;

[0176] The video processing module is used to integrate the on-site images of each target drone to obtain the on-site video of each target drone.

[0177] In one possible design, the low-altitude intelligent network video service simulation device 600 also includes:

[0178] The data module is used to retrieve motion mode data and shooting time data of multiple drones from the cloud service platform.

[0179] The data display module is used to generate text data for responding to business requests based on the motion mode data and shooting time data of each drone.

[0180] This embodiment provides a low-altitude intelligent network video service simulation device, which can execute the low-altitude intelligent network video service simulation method of the above embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0181] In the specific implementation of the aforementioned low-altitude intelligent network video service simulation method, each module can be implemented as a processor. The processor can execute computer execution instructions stored in the memory, thereby enabling the processor to execute the aforementioned low-altitude intelligent network video service simulation method.

[0182] Figure 7 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application. For example... Figure 7 As shown, the electronic device 700 includes at least one processor 710 and a memory 720. The electronic device 700 also includes a communication component 730. The processor 710, memory 720, and communication component 730 are connected via a bus 740.

[0183] In the specific implementation process, at least one processor 710 executes computer execution instructions stored in memory 720, causing at least one processor 710 to execute a low-altitude intelligent network video service simulation method as executed on the electronic device side.

[0184] The specific implementation process of processor 710 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0185] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0186] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage.

[0187] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0188] The above description addresses the functions implemented by electronic devices and main control devices, and introduces the solutions provided in the embodiments of this application. It is understood that, in order to achieve the above functions, the electronic device or main control device includes hardware structures and / or software modules corresponding to the execution of each function. By combining the units and algorithm steps of the various examples described in the embodiments disclosed in this application, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solutions of the embodiments of this application.

[0189] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the above-described low-altitude intelligent network video service simulation method.

[0190] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof.

[0191] Examples of readable storage media include Static Random Access Memory (SRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disks, or optical disks. Readable storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0192] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in an electronic device or a host device.

[0193] This application also provides a computer program product, which includes: a computer program stored in a readable storage medium, at least one processor of an electronic device being able to read the computer program from the readable storage medium, and when the computer program is executed by the processor, it is used to implement the above-mentioned low-altitude intelligent network video service simulation method.

[0194] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disk, or optical disk. The technical solutions of this application have been described above in conjunction with the preferred embodiments shown in the accompanying drawings. However, those skilled in the art will readily understand that the scope of protection of this application is obviously not limited to these specific embodiments. The above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A low-altitude intelligent networking video service simulation method, characterized in that, The method comprises: acquiring scene information, generating an application scene comprising a plurality of unmanned aerial vehicles indicated by the scene information according to the plurality of unmanned aerial vehicles; the unmanned aerial vehicles are used for collecting live data; the live data comprises live pictures; the live pictures, motion mode data and shooting time data of the plurality of unmanned aerial vehicles are simulated to obtain scene data of the application scene; wherein the motion mode data comprises real-time motion state and real-time motion data of the unmanned aerial vehicles, and the scene data is stored to a cloud service platform; parsing a service request to obtain header information; wherein the header information is used for indicating a type of the service request; the type of the service request comprises a video service or a data service; when the header information indicates that the type of the service request is the video service, live pictures of the plurality of unmanned aerial vehicles are called from the cloud service platform; when the service request is parsed, calling parameters are also obtained; the calling parameters are used for indicating video data of at least one target unmanned aerial vehicle; the target unmanned aerial vehicle is one of the plurality of unmanned aerial vehicles; live pictures of each target unmanned aerial vehicle are screened according to the calling parameters; live videos of each target unmanned aerial vehicle are obtained by integrating the live pictures of each target unmanned aerial vehicle; and video data used for replying to the service request is obtained according to a plurality of live videos.

2. The method of claim 1, wherein, The acquisition of the scene information comprises: acquiring a scene networking planning file; wherein the scene networking planning file comprises a number of the plurality of unmanned aerial vehicles and a number of each unmanned aerial vehicle; the scene information is obtained according to the scene networking planning file.

3. The method of claim 1, wherein, When a service request indicating a data service is acquired, the method further comprises: motion mode data and shooting time data of the plurality of unmanned aerial vehicles are called from the cloud service platform; text data used for replying to the service request is obtained according to the motion mode data and the shooting time data of each unmanned aerial vehicle.

4. A low-altitude intelligent networking video service simulation device, characterized in that, It comprises: a scene generation module, configured to acquire scene information, generate an application scene comprising a plurality of unmanned aerial vehicles indicated by the scene information according to the plurality of unmanned aerial vehicles; a data processing module, configured to simulate the application scene to obtain scene data of the application scene, and store the scene data to a cloud service platform; wherein the unmanned aerial vehicles are used for collecting live data; the live data comprises live pictures; a video generation module, configured to call the scene data from the cloud service platform when a service request indicating a video service is acquired, and obtain video data used for replying to the service request according to the scene data; the data processing module comprises: a scene data module, configured to simulate live pictures, motion mode data and shooting time data of the plurality of unmanned aerial vehicles to obtain scene data of the application scene; wherein the motion mode data comprises real-time motion state and real-time motion data of the unmanned aerial vehicles; the video generation module comprises: An analyzing module is configured to analyze the service request to obtain header information, wherein the header information is used to indicate the type of the service request, and the type of the service request includes a video service or a data service; A calling module is configured to call live pictures of the plurality of unmanned aerial vehicles from the cloud service platform when the header information indicates that the type of the service request is the video service; An integrating module is configured to integrate the live pictures of the plurality of unmanned aerial vehicles to obtain live videos of each of the unmanned aerial vehicles; A video displaying module is configured to obtain video data for replying to the service request according to the live videos; When analyzing the service request, a calling parameter is also obtained, wherein the calling parameter is used to indicate video data of at least one target unmanned aerial vehicle, and the target unmanned aerial vehicle is one of the plurality of unmanned aerial vehicles; The integrating module includes: A screening module is configured to screen live pictures of each of the target unmanned aerial vehicles according to the calling parameter; A video processing module is configured to integrate the live pictures of each of the target unmanned aerial vehicles to obtain live videos of each of the target unmanned aerial vehicles.

5. An electronic device, comprising: It includes: A processor and a memory connected with the processor in communication; The memory stores computer execution instructions; When the processor executes the computer execution instructions stored in the memory, it is used to implement the low-altitude intelligent networking video service simulation method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer execution instructions, and when the processor executes the computer execution instructions, it is used to implement the low-altitude intelligent networking video service simulation method according to any one of claims 1 to 3.

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