AI-Powered Predictive Maintenance


MARS uses real-time SCADA sensor data and machine learning to detect anomalies, predict equipment failures, and protect critical assets across oil & gas operations.

Capabilities

Intelligent Asset Reliability

MARS transforms raw sensor signals into actionable intelligence, keeping your critical infrastructure running at peak performance.

Predictive Maintenance

Machine learning models trained on historical sensor data and maintenance logs to forecast equipment failures before they occur — reducing unplanned downtime by up to 40%.

Anomaly Detection

Real-time monitoring of vibration, temperature, pressure, and flow data to detect abnormal patterns in critical rotating equipment across your operations.

SCADA Integration

Seamless ingestion from existing SCADA systems and control room infrastructure. MARS plugs into your Real-Time Operations Center with zero disruption.

Powered By
Google Cloud
TFTensorFlow
PyPython
BQBigQuery
Kubernetes
📡IoT Core
📊Grafana
KApache Kafka
Google Cloud
TFTensorFlow
PyPython
BQBigQuery
Kubernetes
📡IoT Core
📊Grafana
KApache Kafka
How It Works

The MARS Pipeline

From raw sensor signals to predictive intelligence — three stages that keep your operations running.

01

Ingest

Data Acquisition

Real-time sensor streams from SCADA systems — vibration, temperature, pressure, and flow data from critical rotating equipment.

02

Analyze

Model Training

ML models trained on historical sensor data and maintenance logs to identify degradation patterns and predict failures with precision.

03

Protect

Dashboard Integration

Actionable alerts and predictive insights delivered directly to your control room dashboards for immediate operational response.

Get Started

See MARS in Action

Discover how MARS can reduce unplanned downtime and cut operational costs across your oil & gas assets.

mars_demo.sh