Video Stream Ingestion Automation via Access Token Exchange
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video streaming methods across web platforms lack automation and efficiency in ingesting and analyzing video streams, often requiring manual intervention and lacking robust content analysis capabilities.
Innovation Solution
A system and method that utilizes machine learning, computer vision, and natural language processing to ingest video streams by receiving web addresses, identifying user contact details, generating automated messages for access tokens, and enabling debugging processes, while storing content and rules in a video library database for future analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual intervention is used for video stream ingestion, then system complexity is reduced, but productivity and efficiency deteriorate
Solution Approach 1:
The system automatically performs video stream ingestion, analysis, and processing without requiring manual intervention. The automated message generation and access token distribution enable the system to serve itself in coordinating with users, significantly improving productivity while managing complexity through automation.
Solution Approach 2:
The system performs preliminary analysis of video streams using machine learning and computer vision techniques before full processing. Contact details are identified and automated messages are prepared in advance, allowing the system to pre-process information and reduce subsequent manual work requirements.
2Measurement precision
If advanced machine learning and computer vision techniques are implemented, then content analysis capability is improved, but device complexity increases
Solution Approach 1:
The video analysis function is divided into separate modules: machine learning techniques for one type of analysis, computer vision techniques for another, and natural language processing for text-based content. This segmentation allows each technique to be optimized independently while managing overall system complexity.
Solution Approach 2:
The system employs multiple analysis techniques (machine learning, computer vision, natural language processing) that can handle different types of video content universally. This multi-functionality approach allows a single system to accurately analyze various content types without requiring separate specialized systems for each.
3Ease of operation
If automated message generation and access token distribution are implemented, then ease of operation is improved, but reliability may deteriorate due to automation errors
Solution Approach 1:
The system includes mechanisms to receive feedback from users regarding the automated messages and access tokens. This feedback loop allows the system to monitor the effectiveness of automated operations and make adjustments to improve reliability while maintaining ease of operation.
Solution Approach 2:
The system prepares automated messages and access tokens in advance with built-in error handling and validation. By anticipating potential issues and preparing compensatory measures beforehand, the system cushions against automation errors and maintains reliability while providing easy user access.
Data Source
AI summary
System and method to ingest one or more video streams across a web platform are disclosed. The system an input module configured to receive at least one web address associated of the corresponding video streams across the web platform, a video analysis module configured to analyse content of the video streams, a token receiving module configured to identify contact detail associated to the user on receiving a prompt from the contact detail; to generate an automated message to transfer contact detail of the user and to receive an access token from the user, a video exception module configured to enable the user to debug a video retrieving process if a prompt is not generated from the contact detail and to create at least one of a set of rules, a set of logic or a combination thereof, to analyse the content of the video streams.