Our system throws hundreds of alarms a day, and the crew stopped pa…

What We'll Build

• An intelligent alarm management layer that filters nuisance alarms using configurable suppression rules and statistical baselines — reducing alarm flood by 60–80% in typical deployments.
• A correlation engine that groups related alarms into single incidents (e.g., low lube oil pressure + high bearing temp + RPM deviation = one propulsion alert), reducing cognitive overload for crew.
• A prioritised dashboard showing only actionable alarms with context: affected system, severity, recommended action, and time-to-respond.

How It Works

• Data ingested from existing alarm management systems via Modbus, OPC-UA, or NMEA 2000 — no rip-and-replace required.
• Edge processing on board applies real-time suppression and correlation rules; only ranked incidents are transmitted to shore via MQTT over VSAT or LTE.
• Rule sets are tuned per vessel class using historical alarm logs — the system learns what is genuinely noise vs. a precursor to failure.

Next Step

Share a sample alarm log export (even a week's worth) and your current system's data interface spec — we'll scope a proof of concept in the project workspace and show you what filtered output looks like on real data.