Grant: Strategic Projects - Group
Concordia University
$172,600.00
Using big data analytics to improve decision making of system-on-module based solutions
FY 2018-19
Summary
Wearable devices are becoming increasingly popular and are estimated to reach 245 million units and be worth 25 billion dollars by 2019. To enable the rapid advancement of wearable devices for a variety of applications, system-on-module (SoM) solutions have been proposed. As SoM solutions become more powerful and prominent, they are playing a more intelligent role, and are being used in various applications such as sports training and rehab/therapy. Hence, SoM stakeholders are in need of analytics to improve the decisions made based on their solutions.*To advance the state-of-the-art and keep Canadian manufacturers of SoM technology in the forefront, we propose the use of big data analytics for SoM-based solutions. The proposal aims to 1) apply techniques to enable effective data collection and analytics, 2) build SoM-specific analytics, and models that leverage these analytics, to enable the effective detection of user activities and 3) provide interface and user experience design for seamless feedback of extracted analytics. The proposed project aims to target a largely under-researched area, which is how to best use big data analytics and HCI to improve decision making for SoM applications. The potential outcome of the completed research will have impact on both industry and research. For industry, our research will lead to better SoM technology that is not only driven by hardware advances, but also driven by data and intelligent analytics. For the research community, our proposed research will spearhead the area of big data analytics for SoM, which to the best of our knowledge remains largely unexplored. In addition to being original, the proposed research is timely since it is projected that wearable technology will transform the future of many fields, including athletics, medicine, navigation and even shopping.*
Program
Strategic Projects - Group
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
506894-2017
Name nom
Shihab, Emad
Department département
Computer Science and Software Engineering
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2017
Award amount
172600
Program id
STPGP
Program name en
Strategic Projects - Group
Program name fr
Projets stratégiques - De groupe
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1588
Committee name en
Strategic Projects - ICT
Committee name fr
Projets stratégiques - ICT
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2706
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Software engineering
Research subject fr
Génie logiciel
Partie
2
Nb partie
2
Application title
Using big data analytics to improve decision making of system-on-module based solutions
Keyword
NSERC
Application summary
Wearable devices are becoming increasingly popular and are estimated to reach 245 million units and be worth 25 billion dollars by 2019. To enable the rapid advancement of wearable devices for a variety of applications, system-on-module (SoM) solutions have been proposed. As SoM solutions become more powerful and prominent, they are playing a more intelligent role, and are being used in various applications such as sports training and rehab/therapy. Hence, SoM stakeholders are in need of analytics to improve the decisions made based on their solutions.*To advance the state-of-the-art and keep Canadian manufacturers of SoM technology in the forefront, we propose the use of big data analytics for SoM-based solutions. The proposal aims to 1) apply techniques to enable effective data collection and analytics, 2) build SoM-specific analytics, and models that leverage these analytics, to enable the effective detection of user activities and 3) provide interface and user experience design for seamless feedback of extracted analytics. The proposed project aims to target a largely under-researched area, which is how to best use big data analytics and HCI to improve decision making for SoM applications. The potential outcome of the completed research will have impact on both industry and research. For industry, our research will lead to better SoM technology that is not only driven by hardware advances, but also driven by data and intelligent analytics. For the research community, our proposed research will spearhead the area of big data analytics for SoM, which to the best of our knowledge remains largely unexplored. In addition to being original, the proposed research is timely since it is projected that wearable technology will transform the future of many fields, including athletics, medicine, navigation and even shopping.*