Predictive Center is the predictive maintenance software module of BuildOT One, the MachineSens IoT cloud platform. It analyses asset and system data, detects anomalies, tracks asset health and flags likely failures early, so teams can fix problems before they stop equipment or upset occupants.
| Key fact | Detail |
|---|---|
| Module | Predictive Center |
| Part of | BuildOT One |
| What it monitors | Asset performance, anomalies, faults and asset health across a portfolio |
| Data sources | IoT telemetry and asset-level data, AirBMS monitoring data, energy and utility analytics, fault detection engines |
| Integrations | Automation Hub rules, FM360 work orders, BuildOT Copilot explanations |
| Typical users | Maintenance engineers, facilities managers, asset managers, operations directors |
| Sensors | BACnet, Modbus and MQTT systems plus wireless vibration, differential pressure and contact sensors |
What Predictive Center does
- Spots abnormal behaviour. It compares current readings with real-time and historical patterns to find anomalies.
- Scores asset health. Health scores and condition indicators show which equipment needs attention first.
- Finds the likely cause. Root cause analysis and fault detection and diagnostics (FDD) link a problem to system behaviour.
- Ranks the risk. Issues are prioritised by severity, impact and operational risk.
- Moves from alert to action. A predictive alert can become a work order or trigger an automation rule.
Predictive maintenance software features
- Anomaly detection on real-time and historical data
- Predictive alerts and issues with severity and context
- Asset health monitoring across the portfolio
- Fault detection and diagnostics
- Failure pattern recognition for recurring issues
- Risk prioritisation
- Recommendation engine for maintenance and corrective action
- Rule management for predictive thresholds
- Overview dashboard of active rules, anomalies and asset health
- Alerts and issues view with severity, context and insight
- Asset health view of condition and performance trends
- Insights passed to BuildOT Copilot for explanation and decision support
How Predictive Center works
- Collect. Telemetry, AirBMS data and energy analytics feed the module.
- Detect. It compares live readings with historical patterns to flag anomalies and degradation.
- Rank. Issues are prioritised by severity, impact and operational risk.
- Act. An alert becomes a work order, an automation rule or another operational action.
Who uses it
Maintenance and engineering teams use Predictive Center to move from fixed schedules to condition-based work. Asset managers use it to see where risk sits across buildings. In hot Gulf climates, where cooling plant runs hard, early warning on chillers and air handlers matters.
Works with
- FM360 turns predictive alerts into work orders
- Automation Hub runs automated responses to predictive conditions
- AirBMS supplies HVAC and system monitoring data
- Energy and Utilities adds consumption analytics
- BuildOT Copilot explains alerts in plain language
- Gateways bring device data into the platform
- Solution page: Building performance management
Frequently asked questions
What is predictive maintenance in a building?
It means using live equipment data to find signs of wear or faults early, then fixing the asset before it fails. It replaces fixed schedules with condition-based work.
What data does Predictive Center need?
It uses IoT telemetry, AirBMS monitoring data, energy analytics and fault detection outputs. Better sensor coverage gives better results.
Does it create work orders by itself?
It can send predictive alerts into FM360 as work orders, or into Automation Hub to trigger a rule.
How much history does it need before it is useful?
It starts flagging anomalies as soon as live data flows. A typical building goes live on BuildOT One in about 30 days, and results improve as history builds.
Explore all BuildOT One modules
Ask us how Predictive Center would work on your plant and equipment. Request a demo
