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Grant: Applied Research and Development Grants - Level 1

Seneca College of Applied Arts and Technology

$25,000.00

Using TensorFlow for Analysis, Learning and Optimization of Net-Zero Homes Energy Data

EF 2020-21

Résumé
I-EMS Group Ltd (I-EMS) is an advanced software and analytics solution provider for optimal planning, operation and control of smart distribution grids with multiple distributed energy resources. I-EMS provides an energy management system (EMS) as a coherent solution for the distributed energy market, utilizing cutting-edge technologies in forecasting, network analysis, and energy trade. The EMS is an autonomous program connected to all sensors within physical buildings that monitor the generation and consumption of energy assets and their respective loads. An abundance of data are generated and available for use from the array of Internet-of-Things (IoT) sensors and control devices and can be used to improve the efficiency and energy performance of connected systems. The goal of this collaborative project is to add advanced data analytics and big data components to I-EMS Group's existing EMS infrastructure, which can be implemented quickly to improve system efficiency and lower energy usage for I-EMS customers. Utilizing a year of IoT sensor/device data from net-zero energy homes, I-EMS Group is collaborating with Professor Nooshin Beheshti and Seneca's School of Information Technology Administration and Security to design, develop and test AI-based algorithms and data mining methods and implement them into new energy profile optimization modules.
Programme
Applied Research and Development Grants - Level 1
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
556133-2020
Name nom
Leaver, Chad
Department département
Head Office
Organization id
1803
Institution établissement
Seneca College of Applied Arts and Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2020
Award amount
25000
Program id
CARD1
Program name en
Applied Research and Development Grants - Level 1
Program name fr
Subventions de recherche et développement appliquée - niveau 1
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1561
Committee name en
Applied Research and Development Grants
Committee name fr
Subventions de recherche et développement appliquée
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
2713
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Algorithms
Research subject fr
Algorithmes
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
Using TensorFlow for Analysis, Learning and Optimization of Net-Zero Homes Energy Data
Keyword
NSERC
Application summary
I-EMS Group Ltd (I-EMS) is an advanced software and analytics solution provider for optimal planning, operation and control of smart distribution grids with multiple distributed energy resources. I-EMS provides an energy management system (EMS) as a coherent solution for the distributed energy market, utilizing cutting-edge technologies in forecasting, network analysis, and energy trade. The EMS is an autonomous program connected to all sensors within physical buildings that monitor the generation and consumption of energy assets and their respective loads. An abundance of data are generated and available for use from the array of Internet-of-Things (IoT) sensors and control devices and can be used to improve the efficiency and energy performance of connected systems. The goal of this collaborative project is to add advanced data analytics and big data components to I-EMS Group's existing EMS infrastructure, which can be implemented quickly to improve system efficiency and lower energy usage for I-EMS customers. Utilizing a year of IoT sensor/device data from net-zero energy homes, I-EMS Group is collaborating with Professor Nooshin Beheshti and Seneca's School of Information Technology Administration and Security to design, develop and test AI-based algorithms and data mining methods and implement them into new energy profile optimization modules.