The increased pressure to meet environmental compliance teamed with the high costs associated with accurate reporting and the higher-still costs in the event of fuel leaks has led to a growing demand for trustworthy leak detection.

18 Sep 2018 By Russell Dupuy

Data Science Collaboration in Retail Petroleum

Environmental Monitoring Solutions Pty Ltd (EMS) and the Royal Melbourne Institute of Technology (RMIT University) have entered into a twelve-month research project that aims to unlock predictive analytics for the benefit of Petroleum Retailers and consumers globally.

Headed by Dr. Roshan Kumar and Dr Li Chick of the EMS research team and Jeffrey Chan PhD Senior Lecturer, School of Science (Computer Science and Software Engineering) faculty head at RMIT, the collaboration affords wider and deeper reach for the EMS R&D team.

So what does this mean for the typical Petroleum Retailer or consumer?

  • Unlocking predictive analytics to detect over and/or under dispenser fuel hoses/nozzles in real-time: a win-win for retailer and consumer
  • Through the application of machine and deep learning, predict why a fuel hose and/or nozzle is not delivering to the consumer at the expected flow rate: a win-win for retailer and consumer
  • Solve the age-old problem of fuel delivery variance i.e what happens to the fuel mass/volume: from leaving the terminal-depot, to its arrival at the retail site through geo-fencing tanker fuel movements in transit: a win-win for the fuel supplier and fuel retailer

These are a few examples of the problems that our collaboration aims to solve through rigorous research. For more information please contact EMS via [email protected] or alternatively, get in touch with us here.