Six integrated capabilities that turn raw machine data into maintenance decisions your team can act on — before failures happen.
Industrial machines communicate failure through vibration — long before any visible sign appears. SnellIoT captures vibration data at up to 25.6 kHz sampling rate, processes it through FFT spectrum analysis, and identifies the precise fault signatures of bearing defects, imbalance, misalignment, and mechanical looseness.
Overheating is the root cause of 30% of motor failures and 25% of electrical failures in industrial plants. SnellIoT continuously monitors motor windings, bearings, electrical panels, and drive units — providing trend analysis that identifies abnormal heat buildup before insulation breakdown or thermal runaway occurs.
The Machine Health Score (MHS) synthesizes vibration, temperature, current, operating hours, and historical failure patterns into a single 0–100 score — updated every 10 seconds. It gives your maintenance team an instant, unified view of every machine's condition without needing to interpret raw sensor data.
SnellIoT's AI engine uses machine learning models trained on millions of industrial failure events. It analyzes degradation patterns across all sensor channels and calculates a probabilistic failure timeline — giving your team a specific window to act, not just a vague warning.
The AI continuously compares your machine's sensor readings against its learned baseline and known failure signatures. As degradation accelerates, the failure probability curve steepens — triggering maintenance alerts with enough lead time to plan without emergency shutdowns.
The SnellIoT dashboard gives every role — from operator to CEO — the right information at the right level of detail. Fully responsive, works on desktop, tablet, and mobile.
Operators see machine status. Technicians see fault details and work orders. Managers see KPIs and trend summaries. Each role gets exactly what they need.
Full-featured mobile app for iOS and Android. Maintenance engineers can check machine status, acknowledge alerts, and log work orders from anywhere on the factory floor.
Scheduled PDF reports — daily shift summary, weekly machine health report, monthly executive summary — delivered automatically to the right stakeholders.
Compare any parameter across any time range. View vibration trends over 6 months, temperature spikes after major maintenance events, or health score degradation curves.
Visualize your plant as an interactive floor map with machine health color-coding. Click any machine to drill into its sensor data, alerts, and maintenance history.
Automatic OEE calculation, downtime event logging, and MTBF/MTTR metrics — giving you the data needed to benchmark performance and justify maintenance investments.
SnellIoT's alert system is built around one principle: no alert fatigue. Alerts are intelligently tiered, routed to the correct person, and suppressed during known maintenance windows — so your team responds to real problems, not noise.
Book a live demo tailored to your machine types and industry. We'll show you exactly what SnellIoT would monitor, detect, and predict in your specific environment.