Skip to solutionCurrent approach Operational impact 
Big world.
Wind Turbine Predictive Maintenance Systems (ML + Edge AI)
Build predictive maintenance systems for wind turbines using ML and Edge AI. PySquad helps operators reduce downtime, detect faults early, and optimise turbine performance.
Built around your operation
- Wind farm operators managing multiple turbines
- Renewable energy asset owners
- O&M providers supporting wind portfolios
The business case
Lower O&M costs through condition-based servicing
Extended component lifespan
Improved energy production stability
Results depend on scope, integrations and adoption.
The operating context
A clearer view of the whole operation.
Wind turbines operate in harsh, high-variability environments where even minor component failures can cause costly downtime and energy loss. Traditional maintenance approaches rely on scheduled inspections or reactive fixes after faults occur. Modern wind operations require continuous monitoring, anomaly detection, and early fault prediction using real-time sensor data and intelligent models.
Where friction builds
Turbine downtime increases when failures are detected too late.
Operators managing multiple turbines across sites struggle to monitor vibration, temperature, RPM, and environmental data effectively. Manual inspections often miss early warning signs. Large volumes of SCADA and IoT data remain underutilised, and reactive maintenance increases operational expenditure. Without predictive insights, minor component degradation escalates into expensive breakdowns.
- Scheduled inspections without real-time monitoring
- Reactive repairs after component failure
- Manual analysis of limited SCADA data
- No predictive modeling for failure probability
- Unexpected turbine breakdowns
- Higher maintenance and repair costs
- Reduced energy generation
- Limited insight into asset health trends
Inside the solution
The capabilities behind the operation.
Review the functional scope, then discuss the requirements specific to your team.
Real-Time Sensor Data Integration
Ingest vibration, temperature, RPM, acoustic, and weather data.
ML-Based Failure Prediction
Predict gearbox, bearing, blade, and generator faults early.
Edge AI Deployment
Low-latency inference directly on-device or near turbine sites.
Turbine Health Scoring
Continuous performance and risk scoring for each turbine.
Anomaly Detection and Alerts
Automated notifications for abnormal behaviour patterns.
Maintenance Workflow Automation
Trigger service tickets and integrate with O&M systems.
From requirements to implementation
Grounded in the way your team works.
How we work- 01
Integrate SCADA and IoT data pipelines
- 02
Train and validate predictive ML models
- 03
Deploy edge inference for fast detection
- 04
Embed alerts into maintenance workflows
Our approach
We design predictive maintenance systems that combine machine learning models with edge AI deployment. Our approach integrates real-time sensor ingestion, anomaly detection, health scoring, and automated maintenance workflows to reduce downtime and extend turbine life.
Make an informed decision
Is this the right fit?
The right solution starts with the right operating requirements.
Check the fit with usDesigned for
- Wind farm operators managing multiple turbines
- Renewable energy asset owners
- O&M providers supporting wind portfolios
- Energy companies adopting predictive maintenance strategies
May not be suitable for
- Small renewable setups without sensor integration
- Operations relying solely on manual inspections
- Projects without SCADA or IoT data availability
- Teams not pursuing predictive maintenance adoption
Trusted by clients worldwide
See it on your workflows
Discuss your requirementsWalk through the solution with your operation in mind.
Before you decide
Questions worth asking.
Ask something elseWhich turbine data streams do you support?
Vibration, acoustics, temperature, RPM, pitch angle, wind speed, and more.
Do you support on-device (edge) AI inference?
Yes. We deploy lightweight models for fast local analysis.
Can this system integrate with existing SCADA?
Absolutely. We integrate via APIs, OPC-UA, Modbus, and custom gateways.
How accurate are the predictions?
Accuracy improves with data volume and continuous retraining.
Can alerts trigger automated maintenance tasks?
Yes. We integrate with O&M workflows and ticketing systems for seamless automation.
Start with your requirements
Let’s define your next step.
Tell us what needs to work better, the systems you use, and the scope you have in mind.
Discuss your requirementsShare your requirements through our enquiry form.A little closer, wherever you are
Big world.
Close partnership.
Good work travels. We bring product engineering, AI and Odoo ERP to the conversation, and make room for your way of working.
01 / BaseAhmedabadIndia, remote
02 / ApproachOne shared planDiscovery to delivery
03 / ConnectionBuilt around youAgreed meeting rhythm