Grant: Alliance Grants
McMaster University
$877,500.00
Smart devices and systems for next-generation transportation systems
FY 2023-24
Summary
This project will improve the performance of existing camera-based systems for transportation applications by developing multi-modal smart devices (SDs) that integrate radar and/or lidar sensors and use machine vision techniques to address current limitations presented by poor weather and low-visibility conditions. We will design and develop: novel SD hardware and architectures; machine learning (ML) and deep learning (DL) models for multi-modal sensor fusion, and the associated detection models that will be required at the sensor level; and methods for deploying these models on the hardware.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
580266-2022
Name nom
Emadi, Ali A
Department département
Electrical and Computer Engineering
Organization id
27
Institution établissement
McMaster University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2022
Award amount
877500
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
700
Area of application group en
Transportation systems and services
Area of application group fr
Services et systèmes de transport
Area of application en
Transportation systems and services
Area of application fr
Services et systèmes de transport
Research subject code
1600
Research subject group en
Industrial engineering
Research subject group fr
Industrial engineering
Research subject en
Génie industriel
Research subject fr
Génie industriel
Application title
Smart devices and systems for next-generation transportation systems
Keyword
Artificial intelligence; Dataset development; Deep learning; Machine learning; Multi-modal sensor fusion; Sensor fusion; Smart devices; Smart sensors; Smart systems; Smart transportation
Application summary
This project will improve the performance of existing camera-based systems for transportation applications by developing multi-modal smart devices (SDs) that integrate radar and/or lidar sensors and use machine vision techniques to address current limitations presented by poor weather and low-visibility conditions. We will design and develop: novel SD hardware and architectures; machine learning (ML) and deep learning (DL) models for multi-modal sensor fusion, and the associated detection models that will be required at the sensor level; and methods for deploying these models on the hardware.
