Vnomics Aiding Researchers to Predict Fuel Consumption
Vnomics Corp. is providing matching funds, data and expertise to support research at the University of Rochester into the use of machine learning to improve the fuel efficiency of commercial vehicles, according to the analytics company
Rochester, New York-based Vnomics said it uses proprietary algorithms in True Fuel, its tablet-size analytics product, to provide feedback to drivers and fleets to help achieve optimal fuel economy.
Machine learning is the method of combining statistical data, real-time analysis and algorithms to find patterns in data in order to deliver instant recommendations, according to the company.
“While we already use machine-learning principles to determine a particular vehicle’s potential fuel economy, our goal with this collaboration is to generate a new machine-learning model that can actually predict fuel consumption,” said Lloyd Palum, chief technology officer at Vnomics.
Vnomics' support is part of a grant awarded by the National Science Foundation for its Young Innovators Internship Program.
The program's objective is to identify opportunities for early career researchers to interact with companies to collaboratively explore how to apply data science approaches to solve substantial industry challenges, according to the company.
The recipient of the National Science Foundation grant and the matching funds being provided by Vnomics is University of Rochester Ph.D. student Shupeng Gui in the department of computer science.
“This is a valuable opportunity to apply modeling and analysis techniques, including dynamic system learning and optimization, to improve the understanding of both theories and practical problems,” Gui said in a statement.
