Student Resources

09 Jun 2020 By Sumi

Machine learning techniques for fuel loss detection at service stations

Coupling industry expertise and university research to develop effective data analytic and machine learning techniques for identifying and quantifying the different sources of fuel losses from underground petroleum storage systems (UPSSs) at service stations. EMS & RMIT SECURES ARC GRANT TO DESIGN THE NEXT GENERATION OF WETSTOCK MANAGEMENT Australian Research Council (ARC) has announced that RMIT researchers in collaboration with industry ...

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26 Aug 2019

Why Your Business Needs Wetstock Management

Why Your business needs wetstock management Proper and comprehensive wetstock management can offer fuel retailers real-time, accurate and actionable insights to help them manage their network of products. ...

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23 Aug 2019

How Does Wetstock Management Work?

How Does Wetstock Management Work? Wetstock management systems can utilise any or all features of fuel control and management, including fuel inventory and delivery, pricing, ATG alarms, reconciliation ...

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23 Aug 2019

What Is Wetstock Management?

What is wetstock management? Wetstock management by simple definition is the management of fuel, whether that be at a retail forecourt, fuel depot, mine, bus depot etc. Good ...

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