AI Sentry™ — DAS/DVS False Alarm Reduction
Inject in-house AI pattern recognition into existing DAS/DVS systems — cutting false alarms without replacing hardware.
What is AI Sentry™?
AI Sentry™ is an AI upgrade that injects in-house trained pattern recognition into existing DAS/DVS systems, cutting false alarms without replacing hardware. Instead of discarding a working fiber sensing installation because its alarm logic is too noisy, operators keep the installed interrogators, fibers and field infrastructure and add a classification layer on top: the raw DAS or DVS signals are re-interpreted by AI models trained on real field event signatures, so genuine threats are distinguished from environmental and operational noise. For DAS-based systems recognition accuracy reaches ≥95%, and for DVS-based systems ≥90%, measured under field evaluation conditions.
- DAS recognition accuracy ≥95%, DVS recognition accuracy ≥90% (field evaluation)
- Zero hardware replacement — existing interrogators and fiber stay in service
- In-house models trained on field-recorded event signatures, not generic libraries
- Alarm-level output — classified events and threat levels, not raw traces
- Works across operators' mixed installed bases — the upgrade layer sits above the sensing hardware
| DAS recognition accuracy | ≥95% |
|---|---|
| DVS recognition accuracy | ≥90% |
| Hardware change | None required |
Applications
Existing DAS retrofit
Reduce false alarms on deployed DAS systems.
Existing DVS retrofit
Upgrade legacy DVS with AI recognition.
Petrochemical
Improve intrusion detection accuracy.
Power & energy
Enhance perimeter monitoring.
Retrofit with AI Sentry™ vs. replacing the sensing system
| Aspect | Replacing with a new sensing system | AI Sentry™ retrofit |
|---|---|---|
| Installed hardware | Full replacement — interrogators, cabling and commissioning repeated | Kept in service, untouched |
| Impact on live monitoring | Detection coverage interrupted during changeover | Existing protection continues while the AI layer is added |
| False-alarm reduction | Not guaranteed — new hardware alone does not fix event classification | AI classification targets the alarm logic itself (DAS ≥95% / DVS ≥90%) |
| Alarm output | Vendor-specific re-integration | Classified events and threat levels for the control room |
Comparison is generic and based on typical upgrade paths for installed DAS/DVS systems; actual project scope is confirmed per site.
How an AI Sentry™ retrofit works
The retrofit path is deliberately short — the value of an upgrade is that most of the system is already built.
- Installed-system assessment. Engineers review the existing DAS/DVS installation — hardware type, fiber routing, alarm behavior and the noise sources behind current false alarms.
- Signal access and data audit. Raw or processed signal access is established, and historical alarm recordings are collected to understand what the models must learn.
- Site-specific model adaptation. In-house recognition models are adapted using the site's own event signatures — real machinery, traffic and environmental noise from the actual route.
- Parallel validation. The AI layer runs alongside the existing alarm logic so its decisions can be compared against live events before it takes control.
- Go-live and continuous refinement. The AI classification takes over alarm output, and operator feedback keeps the models aligned with site conditions.
Where AI Sentry™ fits — and where it does not
AI Sentry™ is the right answer when the sensing hardware works but the alarms do not — high false-alarm rates that waste patrol dispatches and erode operator trust.
- Good fit: petrochemical plants, power & energy corridors and pipelines where installed DAS/DVS systems generate noise-driven alarms.
- Good fit: sites where recognition accuracy must be validated — Landsub Global quotes field-evaluated figures (≥95% DAS / ≥90% DVS) rather than unsubstantiated claims.
- Boundary: AI Sentry™ upgrades the classification layer; it does not repair damaged fibers, extend optical range or replace failed interrogators — those are hardware projects.
- Not a fit: installations with no usable signal output, or assets that have no existing DAS/DVS system (a new Landsub Global DAS project is the starting point there).
Frequently asked questions
How AI classification cuts false alarms
Most DAS/DVS false alarms share the same root cause: threshold-based alarm logic cannot tell the difference between a threat signature and an everyday vibration source — a tractor in the next field, rain on the right-of-way, pumps inside a plant. AI Sentry™ replaces that decision boundary with pattern recognition: models trained in-house on field-recorded event signatures read the incoming signal stream and output a classified event with a threat level, so the control room sees what is happening, not just that something moved.
- Event classes, not raw triggers: mechanical excavation, manual digging, vehicle movement and ambient noise are separated before an alarm is raised.
- Site-adapted models: training data comes from the operator's own route, so the models learn the specific machinery, traffic and terrain of that site.
- Field-evaluated accuracy: ≥95% recognition on DAS systems and ≥90% on DVS systems, evaluated under field conditions rather than laboratory clips.
- Transparent operation: the AI layer runs in parallel first, so its decisions can be reviewed against real events before it takes over alarm output.
The operational effect is measured in what does not happen: fewer dispatches to nothing, fewer alarm-fatigued operators silencing alerts, and a monitoring system the response team actually trusts — with the existing hardware investment preserved instead of written off.
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Last updated: September 2026