Develop an analytics system that processes IoT sensor data to predict industrial equipment failures. The platform will enhance maintenance planning and reduce downtime through predictive maintenance models.
Collect IoT sensor datasets.
Clean and preprocess time-series data.
Identify patterns indicating equipment degradation.
Implement predictive models such as LSTM.
Evaluate prediction accuracy.
Visualize equipment health metrics.
Create alert mechanisms for failures.
Optimize real-time data processing.
Conduct system testing.
Document predictive maintenance insights.
