Sustainability Data Visualization Using AI Summarization Pipelines

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Solution Overview

Problem

Entities face challenges in efficiently managing, summarizing, and visualizing large volumes of complex sustainability data, making it difficult to track and analyze their sustainability performance effectively.

Innovation Solution

A sustainability generation system that retrieves data from various sources, extracts relevant information using computer vision and OCR, splits and summarizes the data using AI models, and generates visualized reports based on user inputs or templates, enabling efficient data management and visualization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual methods are used to collect and summarize sustainability data, then users have control over the process, but the time required and labor intensity increase significantly

Engineering Contradiction:

Improvedata summarization speedVSAvoidtime required for data collection and summarization

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system enables self-service through automated data collection, extraction, and summarization processes. The AI model automatically retrieves sustainability data from multiple sources, extracts relevant information, and generates summaries without requiring manual intervention, thereby significantly reducing the time and labor intensity associated with traditional manual methods

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical processes with automated AI-based systems. Instead of manually collecting and summarizing data, the system uses AI models to automatically process information from diverse sources, extract key insights, and generate reports, thereby eliminating the time-consuming manual operations

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If comprehensive sustainability data is collected from multiple sources, then the completeness and accuracy of sustainability information improve, but the complexity of data management increases

Engineering Contradiction:

Improvecompleteness of sustainability dataVSAvoiddata management complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system segments the data management process into distinct automated modules: data collection from multiple sources, data extraction using AI models, data summarization, and report generation. This segmentation allows each component to handle specific tasks independently, reducing the overall complexity of managing comprehensive sustainability data while maintaining completeness

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The AI model serves as an intermediary that bridges the gap between diverse data sources and the final sustainability report. It automatically processes, extracts, and summarizes information from multiple sources, thereby managing the complexity of comprehensive data collection and presentation in a unified manner

Inventive Principle:

Principle #24Intermediary (Mediator)

3Ease of operation

If sustainability data is manually analyzed and visualized, then users can customize the analysis, but the efficiency and timeliness of insights decrease

Engineering Contradiction:

Improveuser control over analysisVSAvoidinsight generation efficiency

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system provides self-service through automated analysis and visualization generation. The AI model automatically analyzes sustainability data, identifies key insights, and creates visualizations without requiring manual analysis, thereby maintaining ease of operation while significantly improving efficiency and timeliness of insights

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary automated analysis and visualization generation before user review. The AI model pre-processes the data, extracts insights, and creates initial visualizations that can be quickly reviewed and customized by users, thereby maintaining user control while dramatically improving the efficiency of the overall process

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20260004058A1Systems and methods for sustainability data integration and visualization

Publication Date: 2026.01.01 SCHLUMBERGER TECH CORP

AI summary

A tangible, non-transitory, computer-readable medium includes instructions that, when executed by processing circuitry, are configured to cause the processing circuitry to transmit a set of sustainability data to a computer vision model for extraction into a textualized set of sustainability data, divide the textualized set of sustainability data into one or more subsets of textualized sustainability data, transmit the one or more subsets of textualized sustainability data to an artificial intelligence (AI) model, transmit at least one instruction to the AI model to elicit summarization the one or more subsets of textualized sustainability data into a summarized dataset, and generate a visualized sustainability report by the AI model as a graphical user interface on a display utilizing the summarized dataset, wherein the visualized sustainability report comprises at least one metric selected from the summarized dataset.