Advanced sensor control implementations for energy optimization in commercial buildings using machine learning and data visualisation applied to building automation systems

The objective of the research is to develop a system leveraging data captured for commercial building management systems (BMS) to take decisions in to reduce energy consumption without affecting comfort. The idea is to showcase how intelligent control can be implemented in existing BMS to optimize energy consumption. The project is divided in three parts: data visualization and insight (discovery of potential avenues for the improvement of energy optimization), time-series prediction (prediction future energy consumption), and control (acting on said predictions).

Faculty Supervisor:

Jeremy Cooperstock

Student:

Marc Demers

Partner:

Maxen

Discipline:

Engineering - computer / electrical

Sector:

University:

McGill University

Program:

Accelerate

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