IIoT Solution for Oil and Gas Industry

This is an IIoT Solution with GE Automation to facilitate the improvement in operational efficiency by allowing the easy flow of data from hardware and sensors to cloud and then to interactive dashboards from there. The entire data is moved to a single platform which then streams live data from different assets using fields and gives real-time monitoring of data. It also helps in data prediction which helps maximize oil production. 

Business Challenge

The client was looking for an IT partner for their automation solution targeted towards Oil & Gas industries. Their automation solution needed data flow from the hardware & sensors to the cloud and then from the cloud to the interactive dashboards for achieving the production Optimization and performing the predictive analytics for business-critical decisions.


Taking care of the challenges on the IT side of the End-to-End solution we implemented the IIoT with our US-based customer and GE Automation in Oil and Gas domain. We moved entire Asset-Monitoring, Alert Module and Reporting Module which includes Oil wells, Gas Pipeline, Oil tanks and compressors to a single platform using GE Predix cloud and GE IIOT field devices. Currently the filed devices are streaming live data with interval of 10 seconds from 8 different assets with 5-6 different data matrix like oil flow, oil level, tank temperature, gas pressure, vibrations, alerts, etc. We have to build a single IIOT app (NodeJS+ AngularJS + Google Polymer) and deployed GE Predix cloud for real-time monitoring, alerts and predictive analysis. Right now, we are implementing Machine learning predictive module to predict tank level, machine failure, and optimized gas injection to maximize oil production. During the project, we have configured field agents to use MQTT to transfer sensor data to Predix Time series database; then we have aggregated the data to calculate actionable information, e.g. based on oil flow rate, the Tank number 4 will be full in 1 hour 39 Minutes, or based on Gas pressure we can predict if gas compressor is going down. ", "Node JS Angular JS GE Predix cloud ",

1.5 Year



Working Hours


Live Date

Applied Technologies

Our Role in Client Success

The end Client were able to improve the operational efficiency by 30% and predict the compressor downtime tine with probability


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