IIoT Predictive Maintenance & Sensor Network Architecture
An end-to-end condition-monitoring pattern using vibration, thermal, and acoustic sensors to catch machine failures early.
Design targets, not measured client results.
The Problem
Why teams need this pattern
Calendar-based maintenance misses real wear. Motors, pumps, and gearboxes fail unexpectedly and halt production lines for days.
Ideal for
- Plants with costly rotating equipment
- Maintenance teams starting condition monitoring
Our Approach
Architectural approach
Wireless tri-axial vibration and temperature sensors on rotating assets, with FFT spectral analysis on edge processors to flag bearing wear and misalignment well ahead of failure.
System Design
Architectural layers & components
How data and control flow from the edge of the system to the people who use it.
- 01
Sensor Layer
Wireless MEMS vibration and IR temperature sensors on rotating assets.
- 02
Edge Processing
Jetson / Raspberry Pi gateways running local FFT analysis.
- 03
Time-Series Ingestion
AWS IoT Core streaming into InfluxDB / Timestream.
- 04
Alerting & Work Orders
Automatic CMMS / SAP PM work orders when thresholds are breached.
Design Targets
What this architecture is built to achieve
Targets we design toward. We confirm them against your own data and workload before you commit to a build.
- Prediction quality improves as failure history accumulates; early alerts are threshold-based.
- Savings depend on current maintenance practice and asset criticality.
What You Get
Artifacts tailored to your environment
The blueprint is a starting point. These are the working documents and code we adapt for you.
Learn about our Industrial Automation & Robotics services- Sensor mounting guidelines
- FFT feature extractors
- Node-RED flows
- Grafana dashboard templates
How We Work
From first call to working prototype
- 130–45 min
Discovery call
We review your constraints, existing systems, and success criteria, and tell you honestly whether this blueprint fits.
- 21–2 weeks
Fit & feasibility workshop
We adapt the reference architecture to your stack, validate the design targets against your real data, and produce a scoped plan.
- 3Scoped per project
Prototype, then build
We ship a working slice first so you can judge the approach before committing to a full build.
Technology Stack
Default tools & infrastructure
We swap components to fit your stack.
- AWS IoT Core
- InfluxDB
- Python SciPy / FFT
- Node-RED
- Grafana
- Docker
FAQ
Common questions
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Want an architecture like this?
Book a call and we'll tell you honestly whether this blueprint fits, and how we'd adapt it to your stack and constraints.