AI Intelligent Alert Engine
Traditional monitoring relies on fixed threshold alarms, producing high false-alarm rates and alert storms. The platform embeds an AI time-series analysis model that learns each device's historical operating patterns, detects slow drift and hidden anomalies, auto-merges duplicate alerts, and routes graded alerts to ensure O&M staff focus on real risks.
Fixed thresholds: only trigger when limits are crossed — slow degradation goes unnoticed. One fault floods the screen with dozens of alerts.
Dual threshold + trend logic: each device establishes a normal baseline. Duplicate alerts merged within time windows, graded as urgent/normal and routed per person.
- Three rule types coexist: threshold, rate-of-change, and trend drift alerts
- Same-device same-type alerts auto-merged within time windows to eliminate alert storms
- Delayed confirmation filters transient interference like door openings and start/stop events
- Alert grading, per-person, per-shift routing with auto-escalation on timeout
- Alert acknowledgment and clearing actions fully logged for process traceability
Scope: AI conclusions serve as O&M reference signals — they do not replace on-site detection instruments, protection devices, or legally mandated periodic inspections.