Hierarchical Protection Verification With AI/ML Policy Updates
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Solution Overview
Problem
Existing methods for verifying the protection of personnel and assets are subjective, limited in scope, and lack adaptability and scalability, making it difficult to objectively assess and dynamically adjust protection strategies.
Innovation Solution
A hierarchical-based weighting process using AI/ML algorithms that apply weighting functions and algorithms across multiple levels, dynamically updating protection strategies based on changes and adjusting resources to ensure adaptable, scalable, and autonomous protection verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If subjective methods are used for protection verification, then ease of operation is improved, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent replaces subjective human judgment with objective computational algorithms and AI/ML models. The system uses automated weighting functions, hierarchical algorithms, and machine learning models to objectively assess protection strategies, eliminating the imprecision of subjective evaluation while maintaining operational ease through automated processing.
Solution Approach 2:
The patent introduces an intermediary computational layer between the protection assets and the verification process. This intermediary system uses standardized weighting functions and algorithms to translate complex protection scenarios into objective assessments, bridging the gap between operational simplicity and measurement precision.
2Device complexity
If protection verification is limited in scope, then device complexity is reduced, but adaptability and versatility deteriorate
Solution Approach 1:
The patent segments the protection verification system into hierarchical levels, where each level handles specific aspects of protection assessment. This segmentation allows the system to manage complexity through modular organization while maintaining adaptability across different protection scenarios through the hierarchical structure.
Solution Approach 2:
The patent creates a universal protection verification framework that can handle multiple types of assets and protection scenarios through standardized weighting functions and algorithms. The system is designed to be multi-functional, accommodating various protection needs without requiring separate specialized systems for each scenario.
3Stability of the object's composition
If static protection strategies are used, then stability is improved, but adaptability deteriorates
Solution Approach 1:
The patent implements dynamic protection strategies that automatically adjust weighting functions and algorithms based on changing conditions. The system uses temporal weighting to adapt protection assessments over time and employs AI/ML algorithms that learn from new data, enabling the system to maintain stability through structured processes while adapting to evolving threats and scenarios.
Solution Approach 2:
The patent incorporates feedback mechanisms where AI/ML algorithms continuously learn from protection assessment outcomes and update their models accordingly. This feedback loop enables the system to maintain stable core functions while adapting its strategies based on accumulated experience and changing conditions, resolving the contradiction between stability and adaptability.
4Ease of operation
If manual protection assessment is used, then ease of operation is improved, but productivity and time efficiency deteriorate
Solution Approach 1:
The patent implements self-service automation where the protection verification system automatically performs assessments without requiring manual intervention for each evaluation. The automated algorithms, weighting functions, and AI/ML models independently process protection scenarios, dramatically improving productivity and time efficiency while maintaining ease of operation through user-friendly interfaces.
Solution Approach 2:
The patent replaces manual protection assessment processes with automated computational systems. The system uses machine learning models and automated algorithms to perform evaluations that would otherwise require significant human time and effort, thereby increasing productivity while preserving operational simplicity through automated processing.
Data Source
AI summary
A method includes obtaining information associated with assets and/or personnel to be protected and executing a set of weighting functions and a set of algorithms for protecting the assets and/or personnel. The weighting functions and algorithms are arranged in multiple levels of a hierarchy. Each level of the hierarchy includes one or more of the weighting functions and one or more of the algorithms. The one or more weighting functions and the one or more algorithms in at least one level of the hierarchy are applied across a timeline. The method also includes applying an artificial intelligence/machine learning (AI/ML) algorithm across the timeline to update results due to one or more changes during one or more operations involving the assets and/or personnel.