Vehicle-Based Geophysical Anomaly Mapping with AI Sensor Fusion
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Solution Overview
Problem
Current methods for detecting unexploded ordnance (UXO) and landmines are inefficient, costly, and pose risks due to reliance on single remote sensing techniques and land-based systems that are limited by terrain and vegetation, often yielding false flags and being cumbersome to deploy.
Innovation Solution
A vehicle-based system using a combination of environmental and geophysical sensors, integrated with machine learning algorithms, to generate anomaly maps by optimizing sensor data fusion and processing, enabling accurate detection of subsurface anomalies like UXO and other geophysical features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If single remote sensing methods are used for landmine detection, then deployment simplicity is improved, but detection reliability deteriorates due to false flags
Solution Approach 1:
The patent combines multiple remote sensing methods (magnetometer, GPR, electromagnetic conductor detector, optical camera, thermal camera) into an integrated aerial detection system. This merging of sensors allows the system to maintain deployment simplicity while improving detection reliability by cross-validating anomalies across multiple sensor types, thereby reducing false flags.
2Reliability
If land-based multi-sensor systems are used, then detection reliability is improved, but adaptability to diverse terrain deteriorates due to terrain and vegetation limitations
Solution Approach 1:
The patent inverts the traditional land-based approach by using aerial vehicles (UAVs) to conduct detection operations from the air. This inversion allows the system to maintain high detection reliability through multi-sensor integration while dramatically improving adaptability to diverse terrain and vegetation conditions, as the aerial platform is not constrained by ground obstacles.
3Difficulty of detecting and measuring
If victim detonated ordnance detection is attempted using surface-based methods, then detection capability is improved, but safety deteriorates due to triggering events
Solution Approach 1:
The patent introduces an aerial vehicle as an intermediary platform between the detection system and the UXO targets. This intermediary approach allows the system to maintain detection capability while eliminating safety risks, as the sensors detect anomalies from a safe aerial distance without requiring physical contact or proximity that could trigger victim-detonated ordnance.
4Measurement precision
If comprehensive multi-sensor systems are deployed, then detection precision is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal aerial detection platform that integrates multiple sensor types (magnetometer, GPR, electromagnetic conductor detector, optical camera, thermal camera) into a single multi-functional system. This universal platform maintains detection precision through comprehensive sensing while managing device complexity by consolidating multiple functions into one integrated aerial vehicle system.
Data Source
AI summary
Geophysical anomalies in an area or region can be detected, characterized, or otherwise mapped using a combination of environmental and geophysical sensor data acquired using a vehicle, which may be a remotely operated or autonomously controlled unmanned vehicle. Anomalies are detected by processing the environmental sensor data and geophysical sensor data using artificial intelligence algorithms, programs, or models. As an example, the artificial intelligence algorithms, programs, or models can include machine learning algorithms, programs, or models. The environmental sensor data are processed to generate control parameters for controlling the acquisition and/or processing of the geophysical sensor data optimized for environmental conditions in the area.