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Grant: Discovery Grants Program - Individual

Carleton University

$56,000.00

Sensors and Data Analytics for Smart Homes

EF 2023-24

Résumé
The long-term objective of this project is to design smart homes that are capable of monitoring the health and wellbeing of their occupants. The project focusses on the design of smart homes for the independent living of seniors. Keeping seniors active in their own homes longer improves their quality of life, cognition and mobility. Furthermore, the proposed solutions could detect early signs of health deterioration which could lead to better medical outcomes and healthy aging. This research program is divided into 3 projects. The first project deals with the detection and characterization of sound events in the environment. The objectives of this project is to recognize coughing, snoring and distress sounds such as screaming. Classification algorithms will be proposed to monitor respiratory conditions and react to emergencies. The second project proposes using a bed-based smart pressure-sensitive mat solution to monitor breathing, bed exit characteristics, and weight distribution of bed occupants. The objective of this project is the early detection of some health conditions such sleep apnea, sleep quality problems, instability and Congestive Heart Failure (CHF). In CHF body fluid accumulates in the lower limbs during the day and dissipates to the rest of the body at night. The third project proposes novel context-aware sensor fusion solutions to maximize the information extracted from the sensors. Deep learning algorithms will use sensor modality substitution where a sensor designed to measure a certain modality (e.g. temperature) is used to measure another modality (e.g. water flow). The objective of this project is to improve the system performance, reliability and cost. In each case, the project will critically assess existing systems, evaluates possible solutions and recommend feasible ones. The work will be conducted by graduate students who will gain valuable multidisciplinary training and will be encouraged to publish their work in the most prestigious journals and conferences. We expect that in addition to the academic and societal impacts described above, the project will have a significant economic development potential. The proposed solutions will create new business opportunities for Canadian companies in the area of health and wellbeing monitoring in homes and long-term care facilities. This includes multinational telecom companies looking for creating vertical markets, cloud-based data analytics companies looking for new services, and home security companies looking at expanding their scope. It will also create new entrepreneurship opportunities for start-up companies in the area of sensor and data analytics. In order to ensure that our proposed solutions are feasible, our research team will be interacting on a regular basis with potential users (technology acceptance, needs assessment, ease of use, privacy), healthcare professionals, policy makers and industrial designers.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2019-06260
Name nom
Goubran, Rafik
Department département
Engineering and Design, Faculty of - Engineering and Design, Faculty of
Organization id
23
Institution établissement
Carleton University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2019
Award amount
56000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
515
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Instrumentation technology
Area of application fr
Technologie de l'instrumentation
Research subject code
1901
Research subject group en
Biomedical engineering
Research subject group fr
Biomedical technology
Research subject en
Génie biomédical
Research subject fr
Technologie biomédicale
Application title
Sensors and Data Analytics for Smart Homes
Keyword
Adaptive Systems; Biomedical Engineering; Classification and Decision Support Systems; Data Analytics and Deep Learning; Feature Extraction and Pattern Recongnition; Instrumentation and Measurements; Sensors Data Acquisition and Sensor Fusion; Signal Enhancement and Noise Cancellation; Signal Processing; Smart Homes
Application summary
The long-term objective of this project is to design smart homes that are capable of monitoring the health and wellbeing of their occupants. The project focusses on the design of smart homes for the independent living of seniors. Keeping seniors active in their own homes longer improves their quality of life, cognition and mobility. Furthermore, the proposed solutions could detect early signs of health deterioration which could lead to better medical outcomes and healthy aging. This research program is divided into 3 projects. The first project deals with the detection and characterization of sound events in the environment. The objectives of this project is to recognize coughing, snoring and distress sounds such as screaming. Classification algorithms will be proposed to monitor respiratory conditions and react to emergencies. The second project proposes using a bed-based smart pressure-sensitive mat solution to monitor breathing, bed exit characteristics, and weight distribution of bed occupants. The objective of this project is the early detection of some health conditions such sleep apnea, sleep quality problems, instability and Congestive Heart Failure (CHF). In CHF body fluid accumulates in the lower limbs during the day and dissipates to the rest of the body at night. The third project proposes novel context-aware sensor fusion solutions to maximize the information extracted from the sensors. Deep learning algorithms will use sensor modality substitution where a sensor designed to measure a certain modality (e.g. temperature) is used to measure another modality (e.g. water flow). The objective of this project is to improve the system performance, reliability and cost. In each case, the project will critically assess existing systems, evaluates possible solutions and recommend feasible ones. The work will be conducted by graduate students who will gain valuable multidisciplinary training and will be encouraged to publish their work in the most prestigious journals and conferences. We expect that in addition to the academic and societal impacts described above, the project will have a significant economic development potential. The proposed solutions will create new business opportunities for Canadian companies in the area of health and wellbeing monitoring in homes and long-term care facilities. This includes multinational telecom companies looking for creating vertical markets, cloud-based data analytics companies looking for new services, and home security companies looking at expanding their scope. It will also create new entrepreneurship opportunities for start-up companies in the area of sensor and data analytics. In order to ensure that our proposed solutions are feasible, our research team will be interacting on a regular basis with potential users (technology acceptance, needs assessment, ease of use, privacy), healthcare professionals, policy makers and industrial designers.