Graphical Data Management System for Automated Broadcasting Visualization
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Solution Overview
Problem
Current graphical data management systems for broadcasting are complex and expensive, requiring skilled specialists to automate real-time text and graphics overlays on live video, which is not feasible for amateur broadcasters like Twitch streamers and high school sportscasters who need an affordable and user-friendly solution to connect multiple data services and display dynamic information.
Innovation Solution
A graphical data management system comprising a Service Handler, Scheduler, Template Library, Template Finder, Play List, Editor, Render Engine, and Playback Engine that automates the connection of disparate data services to pre-built templates, allowing users to easily select, customize, and schedule data visualization without programming, using a standardized protocol for data processing and rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional broadcasting systems are used to achieve real-time text and graphics overlays, then the quality and reliability of data visualization is improved, but the device complexity and cost increase significantly
Solution Approach 1:
The system divides the broadcasting functionality into separate modular components: a graphics system that retrieves and processes data, a rendering engine that generates visual overlays, and a playback system that composites graphics with video. This segmentation allows each component to be optimized independently while reducing overall system complexity.
Solution Approach 2:
The graphics system is designed to work with multiple data sources (APIs, databases, files) and support various output formats, making it universally applicable to different broadcasting scenarios. This multi-functionality reduces the need for specialized equipment while maintaining reliability.
2Productivity
If specialized broadcasting equipment and skilled specialists are used, then the automation and productivity of graphics generation is improved, but the ease of operation and accessibility deteriorates
Solution Approach 1:
The system includes automated data retrieval and processing capabilities that operate without constant human intervention. The graphics system automatically fetches data from configured sources, processes it through templates, and generates overlays, enabling users to maintain professional broadcasts with minimal technical expertise.
Solution Approach 2:
The system provides pre-configured templates and data source connections that are prepared in advance. Users can select from pre-built graphic templates and configure data sources before broadcasting, which automates the setup process and reduces the need for specialized knowledge during live operations.
3Adaptability or versatility
If comprehensive data management and automation features are implemented, then the adaptability and versatility of the system is improved, but the device complexity increases
Solution Approach 1:
The system employs a universal data access layer that can connect to multiple types of data sources (REST APIs, databases, flat files) through standardized interfaces. This allows the system to adapt to various data sources without requiring separate specialized components for each source type.
Solution Approach 2:
The graphics system acts as an intermediary layer between diverse data sources and the video output. It provides a standardized interface that mediates between different data formats and protocols, simplifying connections while maintaining versatility in supporting multiple data sources simultaneously.
Data Source
AI summary
Embodiments of the invention relate to an automated, intelligent visualization of data through text and graphics for connecting a wide range of data sources to graphics visualization software and automating its presentation, including building on a standard template driven system for generating graphics from data. Some of these building mechanisms include: Service Handlers, which are plugin components with their own process for converting the data into something uniform, Input Behaviors, which define actions and data to deliver from a service, a system for matching templates to input behaviors by the set of variables in each and the rules for matching them, a Schedule Request mechanism, which connects the data from the service, via the input behavior mechanism, to the correct titles, and handles the assignment of data and then conducts the appropriate actions, and the use of handler defined queues for managing the order of things in parallel.