Wed. Oct 4th, 2023
    How Smart Systems and Machine Learning are Transforming Building Efficiency

    Toronto’s Humber College has seen a significant reduction in energy use and greenhouse gas emissions thanks to the implementation of smart systems and energy-efficient initiatives. These smart systems include precooling buildings to avoid peak demand time, using occupancy sensors to control lights, and redirecting heat from crowded spaces to other buildings. The collaboration between Humber College and Siemens Canada has also resulted in the development of the Sustainable Microgrid and Renewable Technology (SMART) lab, which teaches students about microgrids and how to manage energy generation, storage, and consumption.

    Siemens Canada’s President and CEO, Faisal Kazi, believes that as the number of data-collection devices in buildings increases, there is a need for tools to analyze the gathered information. He emphasizes that the future lies in machine learning, where systems can automatically analyze vast amounts of data and make improvements without human intervention. Digital twinning, the process of creating virtual models of physical assets, has been used in the past to optimize building performance. However, Siemens’ new platform, Siemens Xcelerator, integrates all building systems and communicates with power grids to maximize collective performance.

    The ability to quickly analyze and communicate data between systems has improved with advancements in technology, allowing for more efficient decision-making and optimization. Machine learning plays a crucial role in this process, as it can analyze large amounts of data and make adjustments in real-time to improve building performance. The SMART lab at Humber College incorporates sustainable digital technology, such as microgrid monitoring systems, distribution infrastructure, battery energy storage systems, and solar power generation. These technologies enable more efficient and sustainable use of electrical power, contributing to the college’s goal of achieving net-zero greenhouse gas emissions by 2050.

    The implementation of smart systems and machine learning in buildings not only reduces energy consumption and emissions but also improves productivity and shareholder value. The ability to align building environments, lighting, and air quality to keep occupants comfortable has a significant impact on productivity. Additionally, integrating various building management systems into a single platform reduces initial investment and additional costs for building owners.

    Sources: The Globe and Mail