Crowd Source Media Engine for Digital Content Compilation
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Solution Overview
Problem
Users face frustration and inefficiency when trying to find specific or relevant portions of media files, as they must manually navigate through entire files using fast forward, skip, and rewind, wasting time and effort.
Innovation Solution
The implementation of crowd sourced processing of media files, which involves condensing media files into condensed versions, stitching sections from multiple files into compilation files, and supplementing with additional content, using a network of devices and a crowd source media engine to create modified and compilation files tailored to user characteristics and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually navigate through entire media files using fast forward, skip, and rewind controls, then they can find pertinent sections, but they spend a considerable amount of time and effort which causes frustration and inconvenience
Solution Approach 1:
The system performs preliminary actions by pre-processing media files to identify and tag pertinent sections before the user arrives. The crowd source media engine analyzes media files, divides them into sections, and tags sections containing pertinent information based on crowd source input, so when users search for content, the system can quickly locate and present relevant sections without requiring manual navigation through entire files
Solution Approach 2:
The patent introduces an intermediary system (the crowd source media engine and its components) that mediates between the user's information needs and the raw media files. This intermediary automatically processes media files, identifies pertinent sections using crowd source input, and presents filtered content to users, eliminating the need for users to manually search through entire media files
2Productivity
If the system processes and condenses media files using crowd sourced input to create modified versions, then users can access pertinent content quickly, but the system complexity increases
Solution Approach 1:
The system segments the complex task of media file processing into distinct functional modules: a crowd source media engine that receives and processes crowd source input, a media identification module that identifies pertinent sections, a media division module that divides files into sections, and a compilation module that assembles modified files. This segmentation distributes complexity across multiple specialized components rather than requiring a single complex system
Solution Approach 2:
The system enables self-service by using crowd source input from users to automatically tag and identify pertinent sections in media files. The crowd source media engine processes user input and automatically modifies media files based on aggregated crowd source data, eliminating the need for manual professional editing while maintaining high productivity in content delivery
Data Source
AI summary
Through use of crowd sourced information, media files may be transformed into or used to create product files that are derived from the media files. A product file may be generated using feedback from the crowd sourced information received from an electronic device. The crowd sourced information may indicate one or more portions of the media file to exclude from the product file to create a consolidated product file. In some embodiments, the crowd sourced information may indicate supplemental material and/or portions of other media files that may be included in the product file.