Data Center Suggestion Engine for Context-Aware Alert Prioritization

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Solution Overview

Problem

Existing data center management systems lack the ability to provide context-aware, relevant, and efficient suggestions to administrators based on user queries, often overwhelming users with irrelevant information.

Innovation Solution

A suggestion engine integrated into an Information Handling System (IHS) that analyzes user queries, identifies related data center assets with elevated status, and determines relevance based on user context and data center status, providing tailored notifications through a monitoring and management console.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If the system provides comprehensive notifications about all data center assets with elevated status, then the completeness of information is improved, but the user experiences information overload and difficulty in prioritizing actions

Engineering Contradiction:

Improvecompleteness of informationVSAvoiduser experience

Core Design Contradiction:

Loss of informationVSEase of operation

Solution Approach 1:

The system extracts and prioritizes only the most relevant notifications based on user context, query intent, and asset relationships, removing irrelevant information from the notification stream while maintaining completeness of critical information

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The notification system applies different levels of detail and prioritization to different users based on their roles, historical interactions, and current context, providing customized information quality to each user rather than a uniform approach

Inventive Principle:

Principle #3Local quality

2Loss of information

If the system analyzes user context and query intent to filter notifications, then the relevance of suggestions is improved, but the system complexity increases

Engineering Contradiction:

Improverelevance of suggestionsVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system incorporates feedback loops that analyze user queries, historical interactions, and contextual information to dynamically adjust notification relevance, using the user's responses and behavior patterns to refine future suggestion filtering

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system introduces contextual analysis components and query interpretation mechanisms that act as intermediaries between the raw notification data and the user, filtering and prioritizing information based on multiple contextual factors without requiring complete system redesign

Inventive Principle:

Principle #24Intermediary (Mediator)

3Ease of operation

If the system presents fewer notifications to reduce information overload, then the ease of operation is improved, but the completeness of information delivery deteriorates

Engineering Contradiction:

Improveease of operationVSAvoidcompleteness of information

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The system performs preliminary analysis of user context, query intent, and asset relationships before generating notifications, pre-filtering and prioritizing information based on predicted user needs and contextual relevance

Inventive Principle:

Principle #10Preliminary action

4Loss of information

If the system monitors multiple related data center assets, then the comprehensiveness of monitoring is improved, but the quantity of notifications increases

Engineering Contradiction:

Improvecomprehensiveness of monitoringVSAvoidquantity of notifications

Core Design Contradiction:

Loss of informationVSQuantity of substance

Solution Approach 1:

The system merges notifications from multiple related assets into consolidated, prioritized suggestions based on user context and query relevance, combining information from physically or logically related assets while reducing redundant notifications

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS12585659B2Suggestion engine for data center management and monitoring console

Publication Date: 2026.03.24 DELL PROD LP

AI summary

Systems and methods support a console for use in managing data center operations and in suggesting notifications to present to an administrator issuing a query to the console. Upon detecting a user query, the data center administrator that issued the query is identified. A data center asset that is a subject of the query is also identified. One or more data center assets are identified that are related to the asset that is the subject of the query. Any the related data center assets currently operating with an elevated status designation are identified. Suggested notifications are generated regarding the elevated status designations of the related data center assets. Based on the context of the administrator issuing the query and of the data center status, the administrator may be presented with a portion of the suggested notifications regarding the related data center assets currently operating with an elevated status designation.