AI Resource Thresholding for Dynamic Utilization Control
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Solution Overview
Problem
Existing resource utilization management systems are inefficient and time-consuming, often leading to over-utilization errors due to static monitoring metrics that fail to accommodate dynamic user needs and resource availability changes.
Innovation Solution
A system utilizing a network computing device, user computing device, and terminal computing device, with integrated software applications, implements customizable resource utilization thresholds through encryption and authentication, and applies artificial intelligence techniques for enhanced accuracy and categorization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional static monitoring metrics are used to manage resource utilization, then the system is simple to operate, but it leads to over-utilization errors and cannot accommodate dynamic user needs
Solution Approach 1:
The patent implements dynamic resource utilization thresholds that automatically adjust based on real-time conditions, user profiles, and historical data. Instead of fixed static metrics, the system continuously adapts thresholds to match changing resource availability and user needs, preventing over-utilization errors while maintaining operational simplicity through automated adjustment mechanisms
Solution Approach 2:
The system incorporates continuous feedback loops that monitor resource utilization patterns, user behavior, and system performance. This feedback is used to automatically refine and adjust utilization thresholds, ensuring accurate resource management while the automation of this process prevents the system from becoming overly complex for users to manage
2Adaptability or versatility
If flat, static monitoring metrics are applied, then the monitoring process is straightforward, but it fails to accommodate the dynamic needs of individual systems users
Solution Approach 1:
The system performs preliminary actions by pre-configuring multiple user profiles with customized resource utilization thresholds based on historical data and predicted needs. These profiles are automatically applied and adjusted over time, providing personalized adaptation to user needs without requiring users to manually configure complex monitoring parameters
Solution Approach 2:
The monitoring system automatically adapts to individual user needs by analyzing usage patterns and self-adjusting thresholds without requiring manual intervention. The system serves itself by automatically creating and refining customized monitoring profiles for each user, maintaining ease of operation while achieving high adaptability
3Productivity
If resource availability is not frequently monitored, then the monitoring process is less time-consuming, but lapses result in over-utilization errors
Solution Approach 1:
The system implements continuous automated monitoring of resource availability and utilization without requiring manual intervention. The monitoring process runs continuously in the background, automatically detecting and responding to resource threshold violations, thus maintaining both high productivity through automation and high reliability through constant surveillance
Solution Approach 2:
Continuous feedback mechanisms automatically detect resource utilization levels and trigger appropriate responses when thresholds are approached or exceeded. This automated feedback loop ensures reliable resource control while maintaining productivity by eliminating the need for manual monitoring and intervention
Data Source
AI summary
Disclosed are systems and methods for automatically applying resource utilization thresholds. The systems and methods allow resource utilization to be managed effectively, efficiently, and in a secure fashion. The system can utilization artificial intelligence technology to enhance the accuracy and customization of resource utilization thresholds by properly classifying resource utilization demands and applying threshold limitations directed to particular classifications of resource utilizations.


