Automated Radio Feed Content Filtering and Customization
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Solution Overview
Problem
Current systems for processing broadcast radio feeds for internet streaming are manual, time-consuming, and costly, resulting in delayed and imperfect digital content, lacking the ability to automatically filter out unwanted content and add customized content in real-time.
Innovation Solution
An automated system that processes data from a radio feed by extracting or removing certain content and inserting customized content, using a server with processing and content units to generate filtered and customized data, which can be distributed through various channels like internet streaming, podcasts, and mobile apps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual processing is used to filter broadcast content for internet streaming, then content can be filtered and customized, but processing time increases significantly and costs increase
Solution Approach 1:
The patent replaces manual mechanical processing with an automated digital processing system that uses computer software and algorithms to filter and customize broadcast content. The system automatically identifies and removes unwanted content (advertisements, local weather, traffic updates) and inserts customized content based on user profiles, eliminating the need for human operators while reducing processing time from several hours to near-real-time.
Solution Approach 2:
The system enables self-service processing where the automated processing unit independently performs content filtering and customization without human intervention. The system automatically compares broadcast content against filter criteria, identifies segments to remove or modify, and generates customized digital content streams tailored to specific user preferences and demographics.
2Ease of manufacture
If manual processing is used to create digital programs, then content filtering is possible, but the process becomes expensive and resource-intensive
Solution Approach 1:
The automated processing system serves multiple functions within a single integrated platform: it filters unwanted content, customizes content based on user profiles, generates multiple customized versions of the same broadcast, and distributes content through various digital channels. This multi-functionality eliminates the need for separate manual processing operations and reduces overall system complexity despite the advanced capabilities.
Solution Approach 2:
The system changes processing parameters dynamically based on user profiles, demographic information, and content type. Rather than using fixed filtering rules, the system adjusts processing parameters such as content selection criteria, customization depth, and output format to optimize ease of manufacture for different scenarios while managing system complexity through automated parameter adjustment.
3Productivity
If manual processing is used to filter radio feeds, then customized digital content can be generated, but the processing is significantly delayed
Solution Approach 1:
The patent replaces manual content analysis with automated digital signal processing and pattern recognition algorithms that operate in near-real-time. The system continuously monitors broadcast streams, automatically identifies content segments based on acoustic patterns, metadata, and predefined criteria, and performs filtering operations without the delays inherent in manual processing while maintaining high accuracy through multiple validation checks.
Solution Approach 2:
The system implements feedback mechanisms where processing results are continuously evaluated and used to refine future processing decisions. The automated system learns from processing outcomes, adjusts filtering thresholds, and optimizes content selection based on user engagement data and playback statistics, thereby improving both processing speed and accuracy over time through iterative feedback loops.
Data Source
AI summary
The embodiments disclosed herein automatically process data from a data source, optionally extract certain content such as advertisements, and optionally insert personalized content in place of the extracted content to generate customized data. The customized data in turn can be distributed to client devices in multiple ways, such as through Internet streaming or podcast downloads.