Condition Evaluation Engine with Automated-to-Expert Escalation
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Solution Overview
Problem
Existing technologies face challenges in efficiently and accurately evaluating the existence of conditions, particularly in adapting to changing circumstances, ensuring consistency and quality control, and scaling evaluations as the number increases, while dealing with subjective inputs and resource overheads.
Innovation Solution
A system and method utilizing a condition profile server, coordination server, and network to apply multiple evaluation tiers, including peer and non-peer evaluations, artificial neural networks, and distributed ledger technology for scalable and accurate condition evaluation, with mechanisms for reputation management and load simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple evaluation tiers are applied to ensure accuracy and quality control, then measurement precision is improved, but device complexity and time consumption increase
Solution Approach 1:
The evaluation system is divided into multiple evaluation tiers (first evaluation tier, second evaluation tier, third evaluation tier) with different levels of scrutiny. Each tier processes specific portions of the evaluation workload, allowing the system to segment complex evaluation tasks into manageable stages that progressively refine accuracy while controlling overall system complexity through modular architecture.
Solution Approach 2:
The patent introduces a hierarchical dimension to the evaluation process by organizing evaluation tiers in sequence rather than simultaneously. This dimensional arrangement allows the system to manage complexity through temporal and hierarchical organization, where lower-tier evaluations are processed first and feed into higher-tier validations, effectively managing system complexity while maintaining high measurement precision.
2Productivity
If automated evaluations are used to increase productivity, then productivity is improved, but reliability decreases due to subjective input vulnerability
Solution Approach 1:
The evaluation process is segmented into automated first evaluation tier and human review tiers. The automated system handles high-volume initial screenings to maintain productivity, while human evaluators are deployed to review specific cases requiring judgment, ensuring reliability. This segmentation allows each component to operate in its optimal performance zone.
Solution Approach 2:
The system introduces an intermediary layer of human evaluation that mediates between automated evaluation and final decision-making. Human evaluators serve as intermediaries who review automated assessments, providing subjectivity and judgment where needed, thus maintaining reliability while allowing automated systems to handle the bulk of productivity-intensive tasks.
3Productivity
If evaluation scale is increased to handle more conditions, then productivity is improved, but device complexity and resource overhead increase
Solution Approach 1:
The evaluation workload is segmented across multiple tiers and distributed to different processing units. The first evaluation tier handles the bulk of evaluations independently, while the second and third tiers process subsets requiring additional scrutiny. This segmentation enables the system to scale productivity by distributing work rather than monolithically processing all evaluations, reducing the complexity burden on any single component.
Solution Approach 2:
The patent manages scalability by adding a temporal and hierarchical dimension to processing. Instead of increasing the complexity of a single evaluation process, the system scales by adding more evaluation tiers and processing capacity across time and hierarchy levels, allowing linear or near-linear scaling of productivity without proportional increases in per-evaluation complexity.
4Measurement precision
If human input is used to improve measurement precision, then measurement precision is improved, but loss of time increases due to subjective evaluation requirements
Solution Approach 1:
The evaluation process segments time-consuming human review tasks from high-volume automated processing. Human evaluators are assigned to specific tiers that handle only the most critical or ambiguous cases, minimizing their time investment while maximizing precision where needed. The automated tiers handle the majority of evaluations quickly, reducing overall time loss while maintaining precision through targeted human review.
Solution Approach 2:
The system applies partial human action only where necessary rather than requiring full human review for all evaluations. By applying human evaluation selectively to specific tiers and cases rather than universally, the system achieves the required measurement precision for critical decisions while minimizing time consumption on routine evaluations that can be handled by automated systems.
Data Source
AI summary
Disclosed is a method, a device, a system and/or a manufacture of scalable evaluation of existence of one or more conditions based on application of one or more evaluation tiers. In one embodiment, a system includes a network, a coordination server, and a condition profile server storing an evaluation criteria data for determining existence of one or more conditions. An evaluation request agent receives a condition data indicating the existence of the conditions. A condition evaluation engine for coordinating evaluation of the conditions may include a tier allocation routine that selects a first evaluation tier, generates an evaluation query, and upon receipt of a determination value, selects a second evaluation tier for re-evaluation and/or performs one or more response actions. The evaluation tiers may include, for example, an automated evaluation, an artificial neural network evaluation, a peer evaluation, a panel evaluation, and/or a non-peer (e.g., expert) evaluation.