Grants and Contributions:

Title:
Computational Algorithms for Energy Efficiency and Cost Reduction
Agreement Number:
EGP
Agreement Value:
$25,000.00
Agreement Date:
Jun 14, 2017 -
Organization:
Natural Sciences and Engineering Research Council of Canada
Location:
Ontario, CA
Reference Number:
GC-2017-Q1-00386
Agreement Type:
Grant
Report Type:
Grants and Contributions
Additional Information:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2018-2019)

Recipient's Legal Name:
Feng, Wenying (Trent University)
Program:
Engage Grants for Universities
Program Purpose:

Energy efficiency affects people's daily life, industry and social environment. For example, properly shiftingx000D
electricity usage can significantly reduce its cost and the demand during periods of limited supply. As a leadingx000D
company in the market of energy efficiency, Lowfoot Inc. has been developing innovative tools for energy costx000D
reduction by Artificial Intelligence approaches.x000D
Supported by Lowfoot Inc., the project will introduce computational algorithms that are efficient in predictionx000D
of electricity usage and provide recommendations to minimize user's energy cost. New advancement inx000D
Machine Learning, big data and related areas will be investigated for effective solutions. With theoreticalx000D
foundation in mathematical modeling and computing techniques, deep learning and cloud computing will bex000D
applied. The objective is to improve the forecast accuracy of the system.x000D
The work will contribute directly to today's fast moving areas of data analytics by deep artificial intelligence ofx000D
which Canada is at the forefront. The results will benefit consumers and small business on energy managementx000D
and have the potential of creating new employment for the Canadian society.