AI Eye Analysis for Ancestral Information Detection
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Solution Overview
Problem
Existing methods fail to effectively determine ancestral information using artificial intelligence, including identifying unresolved traumas and personality shifts through eye characteristics, which are crucial for self-awareness and improving awareness and self-esteem.
Innovation Solution
A system and method using AI to analyze eye characteristics, such as color, iris patterns, and autonomic nerve wreath, compares these features with historical data to determine ancestral information, identify aberrations, and generate quiz questions for intuitive type determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine ancestral information, then the process is simple, but the accuracy and depth of ancestral information determination is insufficient
Solution Approach 1:
The patent replaces traditional mechanical/manual methods of ancestral research with an AI-based automated system. The AI model analyzes eye characteristics (iris patterns, color, texture) from images to determine ancestral information, substituting human expert analysis with machine learning algorithms that process visual data to extract genetic and ancestral insights.
Solution Approach 2:
The patent introduces eye characteristics as an intermediary medium to bridge the gap between physical appearance and ancestral information. By analyzing specific eye features (iris patterns, color distribution, texture) as intermediate data, the system can infer ancestral origins without direct genetic testing, creating a new pathway for ancestral determination.
2Loss of information
If AI techniques are used to analyze eye characteristics for ancestral information, then the depth of information obtained increases, but the difficulty of detection and measurement increases
Solution Approach 1:
The patent segments the eye into multiple analyzable characteristics including iris patterns, color distribution, texture features, and regional variations. Each segment is analyzed separately by the AI model to extract specific ancestral indicators, allowing comprehensive ancestral determination through multiple independent feature assessments rather than treating the eye as a single unit.
Solution Approach 2:
The patent transforms visual eye characteristics into quantifiable parameters that the AI model can process. Eye color is converted to color space values, iris patterns are converted to texture descriptors, and regional variations are converted to spatial parameters. This parameter transformation enables the AI to measure and compare eye features objectively against training data to determine ancestral information.
3Reliability
If comprehensive ancestral information is determined through AI analysis, then self-awareness and self-esteem improvement are enhanced, but the time required for analysis increases
Solution Approach 1:
The patent performs preliminary actions by pre-training the AI model with extensive datasets of eye characteristics correlated with known ancestral information. The model learns to recognize ancestral patterns during an offline training phase, so that during actual use, it can quickly analyze user-uploaded eye images and provide reliable ancestral determination without requiring extensive processing time for each individual case.
Data Source
AI summary
A system and method for determining ancestral information of a user using an artificial intelligence (AI) technique is disclosed. The method comprises receiving, via the at least one processor, one or more images of eyes of a user from one or more sources; extracting, via the at least one processor, one or more characteristics from the one or more images of the eyes of the user, using an artificial intelligence (AI) model; comparing, via the at least one processor, the extracted one or more characteristics from the one or more images with a historical data, using the AI model; and determining, via the at least one processor, ancestral information of the user based at least on the comparison, using the AI model. The ancestral information corresponds to data and knowledge related to predecessors or originators of the user.