Multilingual Transport Video Streaming for Low-Latency Live Updates
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Solution Overview
Problem
Existing transportation information systems struggle to provide timely, visually appealing, and interactive updates across diverse platforms, failing to meet the growing demands of a global audience, particularly in busy travel hubs.
Innovation Solution
A system and method for real-time video streaming of transportation information using a multi-lingual, AI-driven approach that integrates data acquisition, processing, and streaming modules to deliver personalized, low-latency video streams across various devices, supporting multiple languages and formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If real-time video streaming is implemented for transportation information, then information timeliness and user engagement are improved, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent introduces a streaming server as an intermediary component that receives transportation information from multiple sources, processes it through template-based formatting, and distributes it to various client devices. This mediator architecture simplifies the overall system by centralizing the complex real-time processing and streaming logic, while clients only need standard video playback capabilities.
Solution Approach 2:
The system segments the information delivery process into distinct modules: data acquisition from transportation sources, template-based content generation, video encoding and streaming, and client-side playback. This segmentation allows each component to be optimized independently and facilitates parallel processing, reducing overall system complexity while maintaining real-time performance.
2Adaptability or versatility
If multiple languages and personalized content are provided, then user accessibility and satisfaction are improved, but data processing complexity and computational requirements increase
Solution Approach 1:
The system uses template parameters that can be dynamically changed based on user preferences. Language, content format, and information type are implemented as configurable parameters in the templates, allowing the same base template to generate personalized multi-language content without requiring separate processing logic for each language or user type.
Solution Approach 2:
The template-based system serves multiple functions: it formats information for different languages, adapts content for various user preferences, and structures data for diverse transportation modes all through a single unified mechanism. This universal template approach eliminates the need for separate processing systems for each language or content type.
3Speed
If low-latency streaming protocols are used, then real-time update capability is improved, but network bandwidth consumption and energy usage increase
Solution Approach 1:
The system implements periodic updates where transportation information is streamed at optimized intervals rather than continuously. The streaming server pushes updates to clients only when new information is available, using time-based and event-based triggering mechanisms. This periodic approach maintains real-time responsiveness while significantly reducing unnecessary network traffic and energy consumption compared to continuous streaming.
Data Source
AI summary
Disclosed is a system (100) and method (200) for real-time video streaming information relating to transportation that comprises a user device (127) that allows users to access live updates. Users input queries, specifying a preferred location and language, through typed-text or voice-commands, with the system automatically detecting the language via a multi-lingual module (106). The data acquisition module (101) retrieves raw transportation data, including schedules, delays, and hub assignments, from service provider servers, storing it in a real-time database (102). The data processing module (104), aided by the multi-lingual module (106), processes and translates the data into the user's preferred language. The content generation module (108) produces visual schedules, 3D overlays, and voiceovers, which the screen capturing module (114) transforms into low-latency streams. The multi-platform streaming module (122) broadcasts these streams to digital platforms in a news-feed format, delivering culturally relevant, real-time updates within a 6-hour window, displayed on the user device (127) for seamless access across various platforms.