Anomaly Detection
Flagging observations or patterns that fall outside normal operating behavior, without needing every fault type labeled in advance.
Industrial IoT & Analytics
Turning plant data into decisions you can act on.
Industrial IoT connects sensors, machines, and control systems into a continuous stream of operating data. Depending on the problem, that data feeds anomaly detection, pattern search, process optimization, or predictive maintenance — the most widely used of these, but far from the only one.
Connect
sensors, SCADA, historians, and IoT connectors capture continuous plant data
Analyze
anomaly detection, pattern search, and signal analysis turn raw data into insight
Act
dashboards, alerts, and models translate analysis into a decision
Applications
Where IIoT analytics gets used.
IIoT data supports several distinct kinds of analysis, each suited to a different problem. Predictive maintenance tends to get the most attention because it's the most widely deployed, but it's one application among several.
Pattern Search
Finding recurring or hidden structure in time-series data, using methods such as matrix profile analysis.
Predictive Maintenance
The most widely used IIoT application: reading sensor trends to catch a developing equipment fault before it causes downtime.
Batch & Process Anomalies
Real-time anomaly detection within batch processes, catching issues early enough to prevent a failed batch.
OT Pattern Detection
Spotting abnormal patterns in operational technology data collected from plant systems.
Decision Support
Turning validated data into dashboards, alerts, and workflows that support energy, process, and operating decisions.
Techniques
How the data is captured and read.
Each application above draws on a smaller set of underlying techniques for capturing a signal and turning it into features a model or a person can use.
Flow
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Pressure
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Temperature
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Vibration
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Motor Current
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Tank Level
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Frequency Spectrum
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Health Radar
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Pattern Clusters
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- IIoT Sensing & Integration Sensors, SCADA, historians, and IoT connectors stream operating data from existing plant systems.
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Vibration Analysis
Accelerometers capture machine vibration; time-domain, frequency-domain, and envelope features reveal imbalance, misalignment, and bearing wear.
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Motor Current / Electrical Signature Analysis
Current and voltage signals, captured non-intrusively at the motor control center, assess motors, drives, pumps, and compressors.
- Signal & Time-Series Processing Statistical, spectral, and pattern-based features turn a raw signal into inputs a model can actually use.
Apps & Tools
Try it yourself.
Interactive apps and reference material for each application area above. Free apps may take a few seconds to wake up if they've been idle.
Anomaly Detection & Pattern Search
Predictive Maintenance, Vibration & MCSA
ML Playground
Contact
Have a question about IIoT or industrial analytics?
Share the problem you're trying to solve — the asset or process, the data you have, and what decision it needs to support. Submitting opens it in your email app, ready to send.