IoT & analytics · Energy
From manual checks to automated oil-field monitoring
Sensor outages across North American oil fields tracked automatically, with site-level dashboards to troubleshoot and predict breakdowns
The challenge
IoT sensors across oil fields went offline without anyone knowing until a manual check. Troubleshooting was slow, and there was no history to predict which sites would fail next.
How we approached it
- IoT sensor APIA custom API that pings sensors, fetches readings and stores them in MongoDB
- Data transformationsPython and Pandas to clean, aggregate and structure readings for analysis
- Performance monitoringA Python Dash dashboard with site-level, time-sensitive views down to each sensor
What was delivered
An automated monitoring pipeline and dashboard that shows sensor health across every site in near real time.
Impact
Real timeOutage tracking and troubleshooting
Proactive failure prediction reduces downtime risk, and operators get granular, site-level insight instead of manual checks.
More work
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