Media asset combined putting system and method

Abstract

The invention discloses a media asset combined delivery system, which comprises a terminal, a media asset delivery cloud, a content docking platform and a media asset delivery background, and is characterized in that the content docking platform and the media asset delivery background call a cloud interface of the media asset delivery cloud in a feed form to obtain data; the terminal calls a cloud interface of a media asset putting cloud through the Https request to obtain data; the content docking platform is docked with a media asset content generation AI large model. The system further comprises a MySQL database used for storing a metadata table, a content configuration table and a content resource table. The invention further discloses a media asset combined putting method. The configuration process of the intelligent television media asset putting system is simplified, manual operation of operation is reduced, unnecessary iteration of the system is reduced, the operation cost of the system is lower, and maintenance and expansion are easier.

Description

Technical Field

[0001] The present invention relates to the field of smart television technology, and in particular to a media resource combination delivery system and method. Background Art

[0002] In smart TV systems, a large number of application scenarios involve the delivery of cloud-based media resources. TV terminals need to request some pre-configured media resources (hereinafter referred to as media resources) from the cloud. Common media resource types include video resources: including streaming media resources and static video resources in various formats; image resources: including static images and dynamic images; audio resources: streaming audio resources and audio resources in various formats; text type resources: short sentences, article excerpts or long articles.

[0003] At present, the common practice is that the operator configures various types of resources corresponding to specific scenarios of smart TV terminals in advance. Common scenario locations include the data container of the launcher system. Common data containers from large to small include mode, section, component and component layout (that is, content, corresponding to one or more media assets actually to be displayed to users), etc. The TV terminal initiates a request to obtain the corresponding resources for playback and display. When the number of media assets issued is particularly large, this process involves a lot of operational work, which requires manual configuration, inspection and review operations. If the corresponding media assets are not configured or configured incorrectly, the terminal may not be able to obtain the corresponding resources, which will cause playback abnormalities. At the same time, conventional operations also have the problem of rigid and inflexible configuration. Once the type of media assets, combination arrangement, parameter constraints and quantity constraints need to be changed, in many cases the software system needs to be iteratively updated to achieve it. In summary, the common practice has the problem of large amount of manual operation and inflexible configuration for smart TV media asset configuration and delivery. Summary of the Invention

[0004] In order to solve the problems existing in the prior art, the purpose of the present invention is to provide a media resource combination delivery system and method. The present invention realizes the smart TV media resource delivery system, simplifies the configuration process, reduces manual operations, reduces unnecessary system iterations, lowers the system operating cost, and is easier to maintain and expand.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a media asset combination delivery system, including a terminal, a media asset delivery cloud, a content docking platform and a media asset delivery backend. The content docking platform and the media asset delivery backend call the cloud interface of the media asset delivery cloud in the form of feign to obtain data, and the terminal calls the cloud interface of the media asset delivery cloud through Https request to obtain data; the content docking platform is connected to a media asset content generation AI large model, and the system also includes a MySQL database for storing metadata tables, content configuration tables and content resource tables.

[0006] The present invention also provides a method for media asset combination delivery, which is implemented using the above-mentioned media asset combination delivery system, and the method includes the following steps:

[0007] Step 1: Configure the AI ​​model for media content generation and the effectiveness of meta-field data for content of different media asset types, and configure constraint rules based on media asset types.

[0008] Step 2: Upload the corresponding media asset files according to the media asset type and synchronize them to the content docking platform through the interface;

[0009] Step 3: The content docking platform configures and connects to different content generation platforms. Based on the media asset parameters and prompt words, it generates corresponding resources, returns them to the content docking platform, and uploads them to the CDN server to obtain the resource address.

[0010] Step 4: The terminal and the content docking platform obtain metadata configured for the content through the interface. The terminal uses the metadata to verify the content, and the content docking platform judges the metadata and performs manual review.

[0011] Step 5: Once the media content is configured correctly and the review is effective, the application pulls and configures it through the media resource acquisition interface.

[0012] Step 6: The terminal requests data from the cloud based on the metadata information of different content locations. It matches the sent media asset type or unique ID of the media asset content with the data returned from the media asset data list, and obtains the constraint parameters of each media asset content. If the match is successful, the correct media asset content is obtained.

[0013] Step 7: After the media resource is successfully delivered, the terminal verifies it according to the metadata definition. If the verification is successful, the media resource is displayed.

[0014] As a further improvement of the present invention, in step 1, the media content generation AI large model includes GPT and Doubao.

[0015] As a further improvement of the present invention, in step 1, the media asset types include static media assets and streaming media assets, and the constraint rules include supported formats of video, picture and audio, resolution and size of the media assets, and playback information of the media assets.

[0016] As a further improvement of the present invention, the playback information of the media asset includes playback volume, playback duration, daily playback frequency, and early exit duration.

[0017] As a further improvement of the present invention, in step 2, if it is static media, the corresponding media file is uploaded according to the metadata configuration, uploaded to the OBS server and then returned; if it is streaming media, the corresponding resource address is directly configured; if it is AI-generated content, the basic file requirements and corresponding prompt words are configured, and the prompt words and metadata are synchronized to the content docking platform through the interface.

[0018] As a further improvement of the present invention, in step 4, metadata of the content bits are shared through an interface, and other modules query corresponding metadata information through an ID.

[0019] As a further improvement of the present invention, in step 4, when it is detected that the resource is an AI-generated type, the metadata and prompt words are processed and then forwarded to the corresponding AI content generation platform. After successful generation, the returned file is uploaded to OBS, and after obtaining the resource address, the resource address is written into the data table for manual review.

[0020] As a further improvement of the present invention, in step 5, media resource acquisition is provided through a pull-down interface and is divided into three levels of data: media resource type, media resource specific type, and media resource content ID.

[0021] As a further improvement of the present invention, in step 7, when the terminal displays the media asset, it first uses the playback control parameters sent by the cloud. If the cloud does not return the playback control parameters, it uses the default parameters for playback.

[0022] The beneficial effects of the present invention are:

[0023] The present invention supports free format configuration, free quantity and type combination of different media resources, and supports a media resource delivery system that automatically generates content to a certain extent by configuring the AI ​​content platform. After the terminal is developed and adapted in advance, it can achieve very flexible media content distribution through a single interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 2 is a system block diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0026] Example 1

[0027] A media asset combination delivery system and method, comprising:

[0028] 1. Build the nacos registration center to provide configuration management and service registration discovery for the cloud, backend, and content docking platforms. The backend projects are all deployed in a distributed manner and forwarded through ELB to solve high-performance concurrency issues.

[0029] 2. Build a MySQL database and create the data tables required for the back-end project. The core data tables include the metadata table (meta_data), the content configuration table (content_configuration), and the content resource table (content_resources).

[0030] 3. Build the backend project, including the cloud, background and content docking platform, using the springboot+springcloud architecture. The cloud service uses feign to define the interface. This system only needs two core interfaces, the content configuration interface (geContentConfig) and the content delivery interface (getContentResources). Other modules call the cloud interface in the form of feign to obtain data, and the terminal directly calls the cloud interface through Https request to obtain data. The framework of this system is as follows Figure 1 shown.

[0031] 4. The operator configures the content docking platform in the background to generate AI big models for media content. For example, GPT and Doubao are currently supported, and more content generation AI big models can be expanded. It only requires iterative upgrades of the content docking platform.

[0032] 5. The operator configures the effectiveness of the meta-field data of different types of content in the background, configures constraint rules based on the type, such as film and television type content, supports video, pictures, and audio, specifies whether the media type is static or streaming media, enables file format verification, such as video supports MP4 and ts formats, audio supports mp3 and aac formats, pictures support jpeg, png, gif and webp formats, etc., enables resolution verification, specifies 4K resolution, 2K resolution or 1080P resolution, etc., specifies file size, such as video files do not exceed 10M, picture files do not exceed 2M, these configurations are shared to the terminal and content docking platform through the interface. At the same time, the operator can also choose to configure the playback information of a specific media resource according to needs, including playback volume, playback duration, daily playback frequency, early exit time, etc.

[0033] 6. Operations are configured in the background. For static media assets, upload the corresponding media files according to the metadata configuration, and return them after uploading to the OBS server. For streaming media assets, directly configure the corresponding resource address. For AI-generated content, configure basic file requirements and corresponding prompt words. Prompt words can be divided into multiple groups. Prompt words and metadata are synchronized to the content docking platform through the interface.

[0034] 7. The content docking platform is configured to connect to different content generation platforms. Using specific media parameters and prompt words, it generates corresponding resources, returns them to the content docking platform, and simultaneously uploads them to the CDN server to obtain the resource address. Different content generation platforms can be switched, and multiple can be configured and used according to priority.

[0035] 8. The terminal and content docking platform obtain metadata configured for the content through an interface. The terminal uses this data to verify the content, and the content docking platform determines the data. If it detects an AI-generated resource, it processes the metadata and prompt words and forwards it to the corresponding AI content generation platform. After successful generation, the returned file is uploaded to OBS, and the resource address is obtained and written to the data table for manual review. If the generation fails, the failure information is also recorded for verification and review by operations personnel.

[0036] 9. The metadata configuration information of the content bit is shared through the interface, and other modules can query the corresponding metadata information through the ID.

[0037] 10. Whether it is a media file uploaded manually or generated by AI, it needs to be uniformly reviewed and approved by the operation department before it takes effect.

[0038] 11. Once media content is correctly configured and approved, it can be pulled and configured by other applications through the media resource acquisition interface. This is provided through a drop-down interface, with three levels of data: the media type (video, image, audio, text, etc.), the specific media type (optional; otherwise, only typeless media content can be configured), and the media content ID. In any application backend, such as the launcher system of the core application of a smart TV, when configuring content, simply select the corresponding content type or content ID. Once configured and approved, the corresponding media content and constraints take effect immediately. If you need to configure more refined operations, such as selecting multiple content groups, the same configuration operations can be used.

[0039] 12. The terminal requests data from the cloud based on the metadata information of different content locations. The corresponding content information must exist and pass the operation review before it can be successfully delivered.

[0040] 13. The terminal application matches the media type or media content unique ID issued by the system with the data returned by the media data list, and obtains the constraint parameters of each media content. After a successful match, the correct media content is obtained.

[0041] 14. After the media resources are successfully delivered, the terminal verifies them according to the metadata definition. If the verification is successful, the media resources are displayed.

[0042] 15. When the terminal plays media resources, it will give priority to the playback control parameters sent by the cloud. If the cloud does not return the parameters, the default parameters will be used for playback.

[0043] Example 2

[0044] A media asset combination delivery system and method, comprising:

[0045] 1. This system is mainly divided into four modules: one terminal module, namely the smart TV terminal media resource acquisition module, and three cloud modules, including the media resource delivery cloud module, the media resource configuration backend module, and the AI ​​media resource content docking platform module, hereinafter referred to as the terminal, cloud, backend, and content docking platform respectively.

[0046] 2. The smart TV terminal and the cloud agree in advance on the basic fields supported by the media data delivery format, whether a field is valid, and the specific data definition, collectively referred to as metadata meta_data. The terminal calls the cloud interface to obtain the definition and validity status of the metadata fields.

[0047] 3. The data granularity supported by this system is as small as the content bit, which represents a collection of media content at a fixed location and can display different media content as needed.

[0048] 4. In the background, media assets support type configuration, but it is not mandatory. That is, content locations can be configured by category, or by specifying a unique ID. Configuring only the type may match multiple media assets, which is usually designed for refined operations or special needs. If both are configured at the same time, the unique ID configuration takes precedence over the type configuration.

[0049] 5. Data exchanged between the terminal and the cloud is generally divided into two groups. The first group is a list of media resource data, including various possible media types (video, image, audio, text, etc.). The second group contains the specific configuration definitions for each media resource type. Content location configuration is achieved by matching media resource types or unique IDs, enabling compatibility with various smart TV terminal applications. Actual media resources are retrieved by matching media resource types or content IDs in the media resource data acquisition list, thus supporting different data containers.

[0050] 6. The content docking platform is configured to connect to different content generation platforms. Using specific media parameters and prompts, it generates corresponding resources, returns them to the content docking platform, and simultaneously uploads them to the OBS server to obtain the resource address. Different content generation platforms can be switched, and multiple can be configured, with each platform being used according to its priority.

[0051] 7. All services are deployed as containerized microservices to facilitate elastic expansion and subsequent maintenance.

[0052] 8. The operator configures the media resources corresponding to different terminals and applications in the background. First, configure the metadata. Metadata represents the most basic settings of media resources in this system, including the type of resources, the support of multiple types and formats for the same content, the configuration of different quantities for each resource type, specifying different formats, specifying different specifications and data size and resolution, etc.

[0053] 9. The metadata configuration information of the content is shared through the interface, and other modules can query the corresponding metadata information through the ID

[0054] 10. Based on metadata definitions, each content slot can be configured with a content selection switch to specify static content, AI-generated content, and streaming resources. Streaming resources are configured with a playback address. Static resources are manually uploaded to the OBS server, where different media assets for each content slot are returned. AI-generated content can also be configured with a prompt. If a prompt is configured, the cloud will forward it, along with all metadata for that content slot, to the content docking platform. Expanding and upgrading the content docking platform can support more large AI models without affecting the normal operation of other modules of the system.

[0055] 11. After the media assets are correctly configured and take effect, they are provided to external systems through a drop-down interface. Other applications can directly configure content positions in the minimum data body by matching types and unique IDs as needed, without having to upload the corresponding media assets one by one.

[0056] 12. The media resources of the content position are configured with specific operating parameters according to the metadata definition: the number of each media type (passed in array form), the format of each group of media elements, the parameters corresponding to the resource, resolution, size, bit rate, etc., and the corresponding playback control parameters, including playback time, early exit time, etc.

[0057] 13. The content docking platform performs parameter verification. If the verification is passed, the prompt words and metadata are forwarded to the third-party AI generation platform in text form. The generated media content is returned to the backend and, like manually uploaded content, is manually reviewed and takes effect only after passing the review.

[0058] 14. The terminal requests data from the cloud based on the metadata information of different content locations. The corresponding content information must exist and pass the operation review before it can be successfully delivered.

[0059] 15. The cloud consists of three parts: interface definition project, interface project and gateway project. The gateway system performs security verification, load balancing and log printing. The interface definition project defines a unified media resource delivery interface, and the interface project implements it. Other projects in the same system can call the media resource delivery interface in the form of feign.

[0060] 16. The terminal requests the media configuration data and media resource data corresponding to different content positions. If all configurations are correct and the security check is successfully passed, the data is sent and the terminal applies it in the launcher position or

[0061] 17. Media asset files uploaded to OBS are distributed to terminals through CDN. After the media assets are successfully delivered, the terminals verify them according to the metadata definition. If the verification is successful, the media assets are displayed.

[0062] 18. In the launcher system, for each section or component in multiple modes, you can configure the content as needed without having to configure the content one by one. You only need to configure the type of content bit or fill in the content bit ID.

[0063] 19. When the terminal plays media resources, it will give priority to the playback control parameters sent by the cloud. If the cloud does not return the parameters, the default parameters will be used for playback.

[0064] 20. Through the collaborative work of the above four modules, combined with manual configuration of operations and AI content generation assistance, flexible configuration of smart TV media resource combinations and delivery effects is achieved. With the addition of AI content generation, the content needs of some simple scenarios can reduce manual participation and save operating costs.

[0065] The above-described embodiments merely represent specific implementations of the present invention. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, and all such variations and improvements fall within the scope of protection of the present invention.

Claims

1. A media asset combination delivery system, characterized in that: It includes a terminal, a media asset delivery cloud, a content docking platform and a media asset delivery backend. The content docking platform and the media asset delivery backend call the cloud interface of the media asset delivery cloud in the form of feign to obtain data, and the terminal calls the cloud interface of the media asset delivery cloud through Https request to obtain data; the content docking platform is connected to a large AI model for generating media asset content. The system also includes a MySQL database for storing metadata tables, content configuration tables and content resource tables.

2. A method for media asset combination delivery, characterized in that: The method is implemented using the media asset combination delivery system according to claim 1, wherein the method comprises the following steps: Step 1: Configure the AI ​​model for media content generation and the effectiveness of meta-field data for content of different media asset types, and configure constraint rules based on media asset types. Step 2: Upload the corresponding media asset files according to the media asset type and synchronize them to the content docking platform through the interface; Step 3: The content docking platform configures and connects to different content generation platforms. Based on the media asset parameters and prompt words, it generates corresponding resources, returns them to the content docking platform, and uploads them to the CDN server to obtain the resource address. Step 4: The terminal and the content docking platform obtain metadata configured for the content through the interface. The terminal uses the metadata to verify the content, and the content docking platform judges the metadata and performs manual review. Step 5: Once the media content is configured correctly and the review is effective, the application pulls and configures it through the media resource acquisition interface. Step 6: The terminal requests data from the cloud based on the metadata information of different content locations. It matches the sent media asset type or unique ID of the media asset content with the data returned from the media asset data list, and obtains the constraint parameters of each media asset content. If the match is successful, the correct media asset content is obtained. Step 7: After the media resource is successfully delivered, the terminal verifies it according to the metadata definition. If the verification is successful, the media resource is displayed.

3. The media asset combination delivery method according to claim 2, characterized in that: In step 1, the media content generation AI model includes GPT and Doubao.

4. The media asset combination delivery method according to claim 2, characterized in that: In step 1, media asset types include static media assets and streaming media assets, and constraint rules include supported formats of video, image, and audio, resolution and size of media assets, and playback information of media assets.

5. The media asset combination delivery method according to claim 4, characterized in that: The playback information of media resources includes playback volume, playback duration, daily playback frequency, and early exit time.

6. The media asset combination delivery method according to claim 4, characterized in that: In step 2, if the media resource is static, the corresponding media file is uploaded according to the metadata configuration and returned after being uploaded to the OBS server. If the media resource is streaming, the corresponding resource address is directly configured. If the content is AI-generated, the basic file requirements and corresponding prompt words are configured. The prompt words and metadata are synchronized to the content docking platform through the interface.

7. The media asset combination delivery method according to claim 2, characterized in that: In step 4, the metadata of the content bit is shared through the interface, and other modules query the corresponding metadata information through the ID.

8. The media asset combination delivery method according to claim 2, characterized in that: In step 4, when an AI-generated resource is detected, the metadata and prompt words are processed and then forwarded to the corresponding AI content generation platform. After successful generation, the returned file is uploaded to OBS. After obtaining the resource address, the resource address is written to the data table for manual review.

9. The media asset combination delivery method according to claim 2, characterized in that: In step 5, media resource acquisition is provided through a drop-down interface and is divided into three levels of data: media resource type, media resource specific type, and media resource content ID.

10. The media asset combination delivery method according to claim 2, characterized in that: In step 7, when the terminal displays the media resource, it first uses the playback control parameters sent by the cloud. If the cloud does not return the playback control parameters, it uses the default parameters for playback.

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