Grant: Discovery Grants Program - Individual
Toronto Metropolitan University
$29,000.00
Machine Learning and Artificial Intelligence for Future Generation Communication Networks
EF 2024-25
Résumé
With the implementation of the fifth generation of mobile systems (5G) and the emergence of internet-of-things (IoT), the number of devices connected to the Internet is expected to grow tremendously over the next few decades. At the same time, machine learning (ML) and artificial intelligence (AI) are becoming an integral part of many applications that run on mobile devices. This raises two interesting questions. First, with the complexity of the modern-day communication networks, how can ML and AI be leveraged to improve the design of these systems? And second, how can communication networks help improve distributed ML and AI?
This research program develops cutting edge technologies for IoT using ML and AI in three key areas: a) how ML and AI can help improve localization and authentication at the physical layer; b) how ML and AI can be used to detect chemical sources in complex networks of vessels; and c) how deep neural networks can be distributed and trained over IoT devices, edge nodes, and cloud servers in the present of communication links that introduce errors and delay. The ML- and AI-based technologies arising from this proposed research are expected to significantly improve the speed, performance and dynamic adaptability of wireless networks, thereby enabling enhanced communications among IoT devices and infrastructure within multiple sectors. This will have a profound impact in smart cities, smart health monitoring, and other areas where distributed sensing, localization, authentication, and deep learning are required (e.g. manufacturing, robotics and autonomous vehicles).
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-2020-04926
Name nom
Farsad, Nariman
Department département
Computer Science
Organization id
43
Institution établissement
Toronto Metropolitan University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2020
Award amount
29000
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
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
803
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer communications
Area of application fr
Téléinformatique
Research subject code
2721
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Multimedia systems and networks
Research subject fr
Systèmes et réseaux multimédias
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Machine Learning and Artificial Intelligence for Future Generation Communication Networks
Keywords
future generation communication systems; computer networks; machine learning; artificial intelligence; deep learning; edge computing; distributed computing; optimization
Application summary
With the implementation of the fifth generation of mobile systems (5G) and the emergence of internet-of-things (IoT), the number of devices connected to the Internet is expected to grow tremendously over the next few decades. At the same time, machine learning (ML) and artificial intelligence (AI) are becoming an integral part of many applications that run on mobile devices. This raises two interesting questions. First, with the complexity of the modern-day communication networks, how can ML and AI be leveraged to improve the design of these systems? And second, how can communication networks help improve distributed ML and AI?
This research program develops cutting edge technologies for IoT using ML and AI in three key areas: a) how ML and AI can help improve localization and authentication at the physical layer; b) how ML and AI can be used to detect chemical sources in complex networks of vessels; and c) how deep neural networks can be distributed and trained over IoT devices, edge nodes, and cloud servers in the present of communication links that introduce errors and delay. The ML- and AI-based technologies arising from this proposed research are expected to significantly improve the speed, performance and dynamic adaptability of wireless networks, thereby enabling enhanced communications among IoT devices and infrastructure within multiple sectors. This will have a profound impact in smart cities, smart health monitoring, and other areas where distributed sensing, localization, authentication, and deep learning are required (e.g. manufacturing, robotics and autonomous vehicles).