Grant: Alliance Grants
Toronto Metropolitan University
$60,000.00
Development of a Smart Building Digital Twin (SBDT) for Healthcare
FY 2023-24
Summary
To achieve Canada's GHG emissions targets, reduction of emissions across the buildings sector is required. Historically, hospitals have been unable to adopt the technologies necessary to reduce energy use and CO2 emissions due to the critical nature of their operations. This research project addresses this gap by focussing on improving the energy efficiency of hospitals while maintaining comfortable and healing-promoting indoor conditions for both staff and patients. A "Cognitive Digital Twin" will be developed to support facility management of the hospital, providing an interactive 3D environment to identify potential equipment issues and optimize operations for energy use and comfort. The Digital Twin will integrate both fault detection & diagnosis and online optimization smart and on-going commissioning functionalities and be designed to be rapidly deployable so that it can be implemented across multiple facilities. The project will be completed in partnership with H.H. Angus and the functionality of the digital twin will be developed and evaluated through two case studies in University Health Network and Sunnybrook Health Sciences Centre facilities. By integrating novel data pre-processing, fault detection and diagnosis, and smart and on-going commissioning methods, this research project will establish a foundation for improving energy efficiency in healthcare facilities, positioning Canada as a leader in this emerging market.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
580958-2022
Name nom
McArthur, Jennifer J
Department département
Architectural Science
Organization id
43
Institution établissement
Toronto Metropolitan University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2022
Award amount
60000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
306
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Energy efficiency
Area of application fr
Efficacité énergétique
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Artificial intelligence (computer vision, use2603)
Research subject en
Intelligence artificielle
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Application title
Development of a Smart Building Digital Twin (SBDT) for Healthcare
Keyword
Digital Twin; Energy Optimization; Fault Detection; HVAC Systems; Ongoing Commissioning; Smart Buildings; Smart Commissioning
Application summary
To achieve Canada's GHG emissions targets, reduction of emissions across the buildings sector is required. Historically, hospitals have been unable to adopt the technologies necessary to reduce energy use and CO2 emissions due to the critical nature of their operations. This research project addresses this gap by focussing on improving the energy efficiency of hospitals while maintaining comfortable and healing-promoting indoor conditions for both staff and patients. A "Cognitive Digital Twin" will be developed to support facility management of the hospital, providing an interactive 3D environment to identify potential equipment issues and optimize operations for energy use and comfort. The Digital Twin will integrate both fault detection & diagnosis and online optimization smart and on-going commissioning functionalities and be designed to be rapidly deployable so that it can be implemented across multiple facilities. The project will be completed in partnership with H.H. Angus and the functionality of the digital twin will be developed and evaluated through two case studies in University Health Network and Sunnybrook Health Sciences Centre facilities. By integrating novel data pre-processing, fault detection and diagnosis, and smart and on-going commissioning methods, this research project will establish a foundation for improving energy efficiency in healthcare facilities, positioning Canada as a leader in this emerging market.