IoT Driven Predictive Analytics & Equipment Failure Monitoring For Oil & Gas Industry

Project Overview

The client was seeking a solution to help them achieve their main objective, which was to provide upstream oil industry expertise to prevent equipment failure. The goal is to develop a cloud-based, online, mobile, scalable, flexible, modular, and secure end-to-end IoT-driven predictive analytics and equipment failure monitoring software suite.

About Client

The client, an oil and gas consulting firm, leverages IoT-driven analytics to assist O&G companies in enhancing and optimizing their operations.

Business Requirements

The reason Indium was selected was due to its track record of accomplishment in the Big Data Analytics field, particularly when dealing with IoT data. One of the most important things to take into account was Indium’s significant experience handling the massive volumes of data that IoT devices produce at a high rate. The following elements were included in the software package:

  • Sensor data (IoT) ingestion from a time-series database to a NoSQL database.
  • Statistical model for predicting Time to Failure (TTF) of devices/equipment using near real-time data.
  • Automated system to send mobile push notifications to all stakeholders regarding predicted failure events.
  • User Interface (UI) for monitoring and managing the entire process.