Website
http://dataportal.arc.gov.au/NCGP/API/grants/LP190100991
Funding Status
Active
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Funded Activity Summary
Machine learning techniques for fuel loss detection at service stations. This project aims to develop effective techniques to identify the sources of fuel losses, such as leaks and calibration errors in underground storage tanks at service stations. Monitoring fuel losses at service stations is influenced by many external factors which can be difficult to predict. The project expects to use machine learning to develop the techniques and test them with live data at service stations. The expected outcomes are a set of tailor-made machine learning techniques for effective fuel loss detection and a software suite that can be easily incorporated into the normal operation of service stations. This should reduce the costs to the petroleum industry from wasteful leaks and the environmental damage caused by these leaks.Funded Activity Details
Start Date: 03-2021
End Date: 06-2024
Funding Scheme: Linkage Projects
Funding Amount: $315,000.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Neural, Evolutionary and Fuzzy Computation | Business Information Management (incl. Records, Knowledge and Information Management, and Intelligence) | Artificial Intelligence and Image Processing
ANZSRC Socio-Economic Objective (SEO)
Energy Transmission and Distribution (excl. Hydrogen) | Energy Storage (excl. Hydrogen) |
