Drone Gas Leak Imaging With AI Segmentation and Standardized Reporting

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Solution Overview

Problem

Existing gas leak detection and reporting methods are time-consuming, lack precision, and suffer from inconsistent reporting due to reliance on subjective human observation, leading to inefficient response efforts.

Innovation Solution

A drone-based system equipped with onboard computing resources, infrared imaging, and AI/ML algorithms for automated gas leak detection, annotation, and reporting, which selectively offloads computational tasks to remote resources, ensuring standardized and efficient reporting.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual observation and reporting methods are used, then human judgment and flexibility are maintained, but time consumption increases and reporting consistency deteriorates

Engineering Contradiction:

Improvereporting efficiencyVSAvoidtime consumption

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system enables automated self-service through AI/ML algorithms that automatically detect gas leaks, segment video footage, generate annotations, and create standardized reports without human intervention, eliminating manual observation and reporting processes

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical observation and reporting processes with automated computational systems including AI/ML algorithms, automated video segmentation, and standardized report generation systems that process and analyze data automatically

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If manual observation methods are used, then operational simplicity is maintained, but measurement precision and detection accuracy deteriorate

Engineering Contradiction:

Improvedetection accuracyVSAvoidoperational simplicity

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system introduces an intermediary automated analysis layer between raw video capture and final reporting, using AI/ML algorithms to objectively detect and analyze gas leaks, removing subjective human observation while maintaining operational simplicity through automated workflows

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If comprehensive video analysis is performed manually, then detailed inspection is achieved, but time consumption and processing duration increase

Engineering Contradiction:

Improveanalysis precisionVSAvoidprocessing duration

Core Design Contradiction:

Measurement precisionVSDuration of action of moving object

Solution Approach 1:

The system implements periodic automated analysis cycles where video footage is continuously processed through AI/ML algorithms at optimized intervals, enabling comprehensive analysis without manual processing delays through systematic automated review cycles

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The patent replaces manual video analysis mechanics with automated computational processing using AI/ML algorithms that can analyze video footage rapidly and consistently without human time constraints

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Stability of the object's composition

If automated AI/ML processing is implemented, then reporting consistency and data standardization improve, but computational resource requirements and system complexity increase

Engineering Contradiction:

Improvedata consistencyVSAvoidsystem complexity

Core Design Contradiction:

Stability of the object's compositionVSDevice complexity

Solution Approach 1:

The system segments the complex automated processing task into distinct modular components including video segmentation, AI/ML-based leak detection, automated annotation generation, and standardized report creation, allowing each function to be optimized independently while maintaining overall system consistency

Inventive Principle:

Principle #1Segmentation

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The system provides accurate, efficient, and standardized gas leak detection and reporting, minimizing human error and enhancing data consistency, facilitating seamless integration with LDAR workflows.

Implementation Method 1

an infrared imaging sensor configured to capture a video feed of the area under inspection

Methodology Applied

Scientific EffectInfrared radiation detection: Infrared Radiation

Data Source

PatentUS20250251298A1Drone-based gas leak imaging and reporting with automatic segmentation, annotation, and normalization

Publication Date: 2025.08.07 AERIALOGI LLC

AI summary

According to various embodiments, a drone is configured with a camera and is in communication with onboard control systems and/or control systems in remote devices to detect and report gas leaks during flights. The control subsystems enable uniform incident reporting and imaging using specialized optical sensors and color schemes. The presently described systems and methods enable efficient detection, annotation, and reporting of gas leaks utilizing a unique combination and configuration of drone technology, video capture, artificial intelligence (AI), and data integration.