—— How SSOLAS Works
Different physics.
Better detection.
SSOLAS deploys sensors, processes data in near real time, and learns from every site it surveys — so each deployment is faster and more reliable than the last.
SSOLAS field demonstration setup for testing at Texas A&M’s Bush Combat Development Complex. Sensors deployed in sand, data acquisition running in real time. Buried targets detected in controlled conditions across three soil types.
The ground has a signal. SSOLAS hears it.
SSOLAS Sensing
Other methods look.
SSOLAS listens.
SSOLAS measures how soil responds to sound energy — detecting buried objects by the changes they cause in that response.
Conventional tools — metal detectors, magnetometers, ground-penetrating radar, even chemical vapor sensors — each fail in different conditions. No single technology reliably detects the full range of buried threats across varying soils, depths, and casings.
SSOLAS uses different physics entirely: it measures how soil transmits sound energy, a signal that is unaffected by metal content, soil conductivity, or electromagnetic interference.
Using commercial off-the-shelf instrumentation, we measure how soil responds to sound energy — meter by meter, in actual field conditions. Field experiments across three locations and four soil types produced consistent, measurable changes in soil response when targets were present.
Deployment & Data Acquisition
Volumes, not strip by strip.
SSOLAS sensors are deployed by uncrewed vehicles in an evolving array, with each sensor contributing to the search volume immediately. The control system adapts spacing in real time — closer where detection demands it, wider where conditions permit.
A single source/sensor combination can search hundreds of cubic meters in favorable conditions. Conventional methods search in ribbons along the surface, requiring sequential passes that slow clearance dramatically. Seismic sensing searches in volumes, not ribbons.
SSOLAS’ overlapping coverage from neighboring sensors is complementary, not duplicative. Because the system measures signal loss in near real time, detectable object size is known at each location rather than assumed from reference data.
Based on Gorin et al., “Hyperlocal Seismic Soil Characteristic Measurements for Unexploded Ordnance Detection,” EarthArXiv preprint, April 2026.
Survey Coverage — Conventional vs. SSOLAS
VS
From Field to Cloud
Every site surveyed makes the next one more effective.
SSOLAS processes data in near real time, allowing the automated system to continuously adapt its search as conditions change. Field data flows to the cloud, where each site’s measurements contribute to a growing worldwide dataset of seismic soil characteristics and detection outcomes.
1
Real-Time Processing
Data is processed as it is collected — not after the fact. The automated system continuously adapts sensor spacing and search parameters as conditions change across the survey area.
2
Global Soil Knowledge Base
Each deployment contributes to a growing worldwide dataset of seismic soil characteristics and detection outcomes. The knowledge compounds across every site, every soil type, every threat environment.
3
AI-Assisted Pattern Recognition
AI analysis across the accumulated dataset identifies patterns of threat types and soil signatures — so every new deployment benefits from every previous one. The system learns. The knowledge compounds.
