Subventions et des contributions :

Titre :
Signal and Information Processing for distributed and networked applications
Numéro de l’entente :
DGDND
Valeur d'entente :
120 000,00 $
Date d'entente :
14 juin 2017 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Québec, Autre, CA
Numéro de référence :
GC-2017-Q1-01416
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2020-2021)

Nom légal du bénéficiaire :
Labeau, Fabrice (Université McGill)
Programme :
Supplément aux subventions à la découverte MDN-CRSNG
But du programme :

The power of signal processing as a discipline is that it develops the algorithms and techniques that form the backbone of today’s Internet, cellular networks, or human-machine interfaces; it is constantly extending its reach to other domains, including healthcare, power and energy or social networks. This proposal is rooted in this tradition and proposes to examine several specific situations of application of signal processing to new and emerging areas, characterized by the distributed and/or networked nature of the signals or information considered. These areas include
the Internet-of-Things (IoT), Healthcare and the Energy Sector. The proposed research program will tackle projects that are motivated by some of concrete problems in these application domains, but will also strive to provide contributions that can be extended to other application domains.
This program will develop new technologies and algorithms (i) to enhance the lifetime of wireless sensor networks through carefully managed deployments of nodes and Radiofrequency Power harvesting; (ii) to enhance the security and resistance to cyber attacks of wireless data gathering mechanisms, including in the Smart Grid and healthcare; (iii) to monitor large streams of data created by networked sensors for data integrity and to improve networked environmental monitoring.
The program will provide training to at least 13 trainees at several levels (from undergraduate to PhD), in an environment that is connected to industry and rooted in international and national collaborations. The program will hence provide a stream of innovative solutions to serious challenges in networked systems while producing the next generation of highly skilled workers in the critical application domains cited above.