Reference number : GC-2017-Q2-00413, amendment number : , agreement type : G, recipient legal name : Weber, Jens Holger (University of Victoria), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Engage Grants for Universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Like many other industrialized nations, Canada faces the challenge of adapting to a rapidly aging demographic._x000D_
Our country requires innovative and transformative solutions in order for our health care and social systems to_x000D_
remain strong and sustainable, in presence of a growing population of senior citizens. The ability to "age in_x000D_
place" and remain living independently for a longer period of time is an important objective in this context._x000D_
Most Canadians prefer aging in place and independent living over other forms of care (e.g., residential care), if_x000D_
they feel adequately supported and cared for. Information and communication technologies (ICT) are expected_x000D_
to play a major role in enabling this vision. A senior's home environment equipped with smart sensors may be_x000D_
able to prevent or detect health and safety-related incidents, such as falls or the onset of an illness._x000D_
Since there is a large diversity of lifestyles and living environments, such "Smart Home" technologies must_x000D_
be adaptive to the particular habits and needs of an individual. Machine learning algorithms can be used to_x000D_
provide such intelligent adaptation based on activity data streams sourced from a variety of home-based_x000D_
sensors. Our company partner (Tochtech) is a healthcare technology provider start-up firm who is developing a_x000D_
Smart Home package in support of caring for independently living seniors. Tochtech's solution will be capable_x000D_
of monitoring daily activity data of seniors and raising alerts when detecting potential safety or health risks._x000D_
Tochtech is interested in exploring the use and evaluation of machine-learning algorithms, platforms and tools_x000D_
for the purpose of providing an adaptive incident detection system. They have engaged with the University of_x000D_
Victoria's LEAD lab to provide expertise and guidance. The objectives of this NSERC Engage project are (1)_x000D_
to evaluate current machine learning algorithms, platforms and tools and select the ones most suitable for the_x000D_
application problem, (2) to prototype a machine learning system for detecting two selected risk categories_x000D_
(accidental falls and acute illness), and (3) to design an extensible architecture platform for adding detection_x000D_
algorithms to address additional risk categories., program purpose french : Like many other industrialized nations, Canada faces the challenge of adapting to a rapidly aging demographic._x000D_
Our country requires innovative and transformative solutions in order for our health care and social systems to_x000D_
remain strong and sustainable, in presence of a growing population of senior citizens. The ability to "age in_x000D_
place" and remain living independently for a longer period of time is an important objective in this context._x000D_
Most Canadians prefer aging in place and independent living over other forms of care (e.g., residential care), if_x000D_
they feel adequately supported and cared for. Information and communication technologies (ICT) are expected_x000D_
to play a major role in enabling this vision. A senior's home environment equipped with smart sensors may be_x000D_
able to prevent or detect health and safety-related incidents, such as falls or the onset of an illness._x000D_
Since there is a large diversity of lifestyles and living environments, such "Smart Home" technologies must_x000D_
be adaptive to the particular habits and needs of an individual. Machine learning algorithms can be used to_x000D_
provide such intelligent adaptation based on activity data streams sourced from a variety of home-based_x000D_
sensors. Our company partner (Tochtech) is a healthcare technology provider start-up firm who is developing a_x000D_
Smart Home package in support of caring for independently living seniors. Tochtech's solution will be capable_x000D_
of monitoring daily activity data of seniors and raising alerts when detecting potential safety or health risks._x000D_
Tochtech is interested in exploring the use and evaluation of machine-learning algorithms, platforms and tools_x000D_
for the purpose of providing an adaptive incident detection system. They have engaged with the University of_x000D_
Victoria's LEAD lab to provide expertise and guidance. The objectives of this NSERC Engage project are (1)_x000D_
to evaluate current machine learning algorithms, platforms and tools and select the ones most suitable for the_x000D_
application problem, (2) to prototype a machine learning system for detecting two selected risk categories_x000D_
(accidental falls and acute illness), and (3) to design an extensible architecture platform for adding detection_x000D_
algorithms to address additional risk categories., agreement title english : Responsive Home - Integrating Machine Learning with Home-based Sensors to Provide Incident Response for Seniors Living Independently, agreement title french : Responsive Home - Integrating Machine Learning with Home-based Sensors to Provide Incident Response for Seniors Living Independently, agreement number : EGP, agreement value : 24280.0, agreement start date : 2017-08-23, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada