Asset Portfolio Dashboard Automation via AI Analytics
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Solution Overview
Problem
Traditional data analytics and digital transformation of asset data require significant human interaction, making it difficult to efficiently identify and resolve issues in large portfolios of assets, as they often involve manual configuration of dashboards and inefficient use of computing resources.
Innovation Solution
A system that generates dashboard visualizations for asset portfolios using asset descriptors, aggregating data, determining contextual information based on asset relationships, and providing prioritized actions, allowing for remote monitoring and management of assets through an IoT platform that integrates disparate systems and provides real-time insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration and human interaction are used for data analytics and dashboard generation, then customization and flexibility are improved, but productivity and efficiency deteriorate due to the large portfolio of assets requiring management
Solution Approach 1:
The system enables automated self-service through AI-driven analytics that automatically generate insights, prioritize actions, and create dashboard visualizations without requiring manual human configuration. The asset management system performs self-analysis of aggregated data and automatically determines contextual relationships and prioritized actions, eliminating the need for specialized workers to manually analyze each asset while maintaining adaptive customization capabilities.
2Measurement precision
If specialized workers manually manage large portfolios of assets, then detailed analysis capability is improved, but loss of time increases due to the sheer volume of assets that must be monitored
Solution Approach 1:
The patent replaces the mechanical human analysis process with automated AI-driven computational systems. The system uses machine learning models to automatically analyze aggregated asset data, determine contextual relationships, and identify issues with high precision across large portfolios. This substitution eliminates manual time consumption while maintaining or enhancing analysis detail through automated pattern recognition and anomaly detection capabilities.
Solution Approach 2:
The system performs preliminary automated analysis of asset data continuously in the background, pre-identifying potential issues and prioritizing actions before human intervention is needed. By pre-processing and pre-analyzing data across the entire asset portfolio, the system prepares actionable insights in advance, significantly reducing the time required for specialists to identify and address issues when they arise.
3Power
If computing resources are traditionally allocated for manual data analytics, then processing capability is improved, but efficiency deteriorates due to limited time spent on data modeling and analysis
Solution Approach 1:
The system implements continuous automated data processing and analysis operations that continuously aggregate asset data, update contextual relationships, and generate prioritized actions without interruption. Unlike traditional manual processes where analysis is performed intermittently when specialists are available, this system maintains continuous computational analysis of all assets, maximizing the utilization of computing resources and significantly improving analytics productivity through uninterrupted processing.
Data Source
AI summary
Various embodiments described herein relate to remote monitoring and management of assets from a portfolio of assets based on an asset model. In this regard, a request to generate a dashboard visualization associated with a portfolio of assets is received. The request includes an asset descriptor that describes one or more assets in the portfolio of assets. In response to the request, aggregated data associated with the portfolio of assets is obtained based on the asset descriptor. Contextual data is also determined for the portfolio of assets based on asset relationship data for the aggregated data. Based on the contextual data, prioritized actions for the portfolio of assets are determined. Furthermore, the dashboard visualization is provided to an electronic interface of a computing device, the dashboard visualization comprising the prioritized actions for the portfolio of assets.