Digital Agent for Automated Media Rights Management
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Solution Overview
Problem
Users face significant challenges in identifying and managing the usage of their digital media, such as images and documents, as they are often posted online without proper attribution or can be plagiarized, leading to time-consuming searches and requests for corrective actions.
Innovation Solution
A digital agent system that compares media content to a user profile, assigns an identification confidence level, and contacts the media host to request licensing, identification, or removal based on user-defined criteria, utilizing facial recognition, voice recognition, and other characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually search networks to find their media and contact hosts for corrective actions, then they can identify and manage unauthorized use of their content, but it requires a significant amount of time and effort
Solution Approach 1:
The system enables self-service by automatically monitoring networks for unauthorized use of user media and initiating correction requests without user intervention. The digital agent autonomously performs the functions of searching, identifying, and contacting hosts, allowing the system to serve itself rather than requiring manual user effort.
Solution Approach 2:
A digital agent acts as an intermediary between users and media hosts. The agent automatically detects unauthorized use of user media across networks and communicates with hosts to request corrective actions, eliminating the need for users to directly search and contact each host manually.
2Ease of operation
If media is posted online without identification or attribution, then accessibility and sharing are improved, but digital rights and ownership cannot be protected
Solution Approach 1:
The system implements feedback by continuously monitoring networks for posts containing user media and automatically responding to detected violations. When unauthorized use is detected, the digital agent sends notifications to hosts requesting attribution or removal, creating a closed-loop feedback system that protects digital rights while maintaining online sharing capabilities.
Solution Approach 2:
Users perform preliminary actions by registering their media with the system before posting online. The system pre-processes this media to create identifiable signatures and establishes protection parameters in advance, enabling automatic detection and response to unauthorized use without requiring manual intervention when violations occur.
3Productivity
If a digital agent automatically monitors and contacts hosts about unauthorized media use, then time and effort are reduced, but system complexity increases
Solution Approach 1:
The system segments the complex task of protecting digital rights into distinct functional modules: media registration and signature creation, network monitoring and detection, host identification, and automated communication. Each module handles a specific aspect of the process, making the overall complex system manageable through functional decomposition.
Solution Approach 2:
The digital agent is designed as a universal system that can handle multiple types of media (images, documents, videos), monitor various network platforms, and communicate with different hosts through standardized protocols. This multi-functionality allows a single system to address diverse unauthorized use scenarios without requiring separate specialized tools for each case.
Data Source
AI summary
A method for digital rights management includes a digital agent for contacting a media host. Media content is compared to a user profile and an identification confidence level is assigned to the media based on the comparison. A digital agent contacts a host of the media based on the identification confidence level, the type of media, and the context of the media. The digital agent requests one or more actions of a media host based on user designations concerning information related to the media. The identification confidence level is generated based on a plurality of user characteristic confidence levels which are generated based on media being analyzed.