Pushing the Energy Efficiency Frontier with Deep Learning
Deep learning will be imperative in optimizing our use of energy and ultimately supporting our global fight against climate change. More specifically, deep learning can be used to predict the energy consumption in real time of one of the world’s biggest energy consumers, buildings. Equipped with these predictions, it becomes possible to shift energy loads by creating thermal batteries within buildings, resulting in a more efficient use of energy resources and less waste. This talk will also introduce the concept of swarm intelligence applied to buildings and the ways in which it can benefit grid operators and ultimately the planet as a whole.
Jean-Simon Venne is a co-founder and CTO of BrainBox AI. As a technology expert specializing in the fast and efficient migration of technological innovations to commercial applications, Jean-Simon has over 25 years of experience developing and implementing new technology to solve long-standing commercial issues in the fields of telecommunications, biotechnology, and energy-efficiency.
Prior to joining BrainBox AI, he was responsible for the successful integration of M2M technology in over 200 Smart Buildings across North America, Europe, and the Middle East. Jean-Simon holds a B.Eng. in Industrial Engineering from École Polytechnique de Montréal and a Certificate in Logistics from the University of Georgia Tech.