Grant: Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
The Governing Council of the University of Toronto
$283,800.00
AI enabled tools to reduce risks to first responders in responding to freight transportation fire incidents
FY 2020-21 · 2021-01-12
Summary
Early identification of the type of hazardous materials within freight fires is
particularly important for the safety of public as well as first responders. First
responders routinely confront unknown hazards which might cause
explosions or toxicant release in response to ordinary fire extinguishers.
Therefore, the objective of this Project is the development of an Artificial
Intelligence (AI) tool that assists first responders in identifying hazards, along
with a set of recommendations associated with the most effective mitigation
measures. The AI tool will consist of data gathering sensors to collect real
time information on freight fires, a machine learning-based classifier to
identify the type of material burning, and a real-time search algorithm to
recommend mitigation measures.
Department
Program
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Location
Toronto|Toronto, Ontario, Canada
Recipient Type
Academia
Business Number
108162330
Type
Grant
Source
Proactive Disclosure - Grants and Contributions
Amendments
Each version of the agreement as published, oldest first, with its total as of that version. The amount above is the latest.
| Amendment | Date | Fiscal Year | Total |
|---|---|---|---|
| 0 | 2021-01-12 | 2020-21 | $283,800.00 |
| 1 | 2021-01-12 | 2020-21 | $283,800.00 |
As published
Additional Information
This agreement has been amended 1 time(s). The end date of this agreement has been modified by 243 days.
Additional Information (French)
Cet accord a été modifié 1 fois. La date de fin du présent accord a été changé de 243 jours.
Agreement End Date
2024-08-31
Agreement Number
964412
Agreement Start Date
2021-01-12
Agreement Title
AI enabled tools to reduce risks to first responders in responding to freight transportation fire incidents
Agreement Title (French)
Outils basés sur l’IA pour réduire les risques encourus par les premiers intervenants lors d’un incendie impliquant un transporteur de fret
Agreement Type
Grant
Agreement Value
$283,800.00
Amendment Date
2023-07-25
Amendment Number
1
Description
Early identification of the type of hazardous materials within freight fires is
particularly important for the safety of public as well as first responders. First
responders routinely confront unknown hazards which might cause
explosions or toxicant release in response to ordinary fire extinguishers.
Therefore, the objective of this Project is the development of an Artificial
Intelligence (AI) tool that assists first responders in identifying hazards, along
with a set of recommendations associated with the most effective mitigation
measures. The AI tool will consist of data gathering sensors to collect real
time information on freight fires, a machine learning-based classifier to
identify the type of material burning, and a real-time search algorithm to
recommend mitigation measures.
Description (French)
Une détection rapide du type de matières dangereuses présent lors d’un incendie impliquant un transporteur de fret est d’une grande importance pour la sécurité du public et des premiers intervenants. Ces derniers doivent régulièrement faire face à des dangers inconnus qui pourraient provoquer des explosions ou des rejets de substances toxiques en réponse à l’usage d’extincteurs courants. Dans le cadre de ce projet, on souhaite mettre au point un outil basé sur l’intelligence artificielle (IA) pour aider les premiers intervenants à déterminer les dangers et leur fournir un ensemble de recommandations associées aux mesures d’atténuation les plus efficaces. L’outil d’IA consistera en des capteurs de collecte de données pour recueillir des informations en temps réel sur les incendies de fret, un classificateur basé sur l’apprentissage automatique pour déterminer le type de matériau qui brûle, et un algorithme de recherche en temps réel pour recommander des mesures d’atténuation.
Expected Results
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Expected Results (French)
À court terme, les résultats prévus seront des collaborations renforcées entre l'industrie, le milieu universitaire et le gouvernement pour soutenir l'excellence en recherche. À moyen terme, les résultats attendus seront le développement de nouvelles technologies potentiellement perturbatrices avec des collaborateurs. À long terme, trouver des solutions collaboratives aux défis des politiques publiques et créer des systèmes d'innovation plus solides.
Federal Riding
University–Rosedale
Federal Riding (French)
University–Rosedale
Federal Riding Number
35110
NAICS Code
541710
Organization Code
nrc-cnrc
Organization
National Research Council Canada | Conseil national de recherches Canada
Program Name
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Name (French)
Programme de collaboration en science, en technologie et en innovation - Initiatives de collaboration en R-D
Program Purpose
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
Program Purpose (French)
Collaborer à des programmes multipartites de recherche-développement dans le but de profiter de la synergie entre la recherche transformatrice à haut risque et à haut rendement et le potentiel de découvertes scientifiques et de percées technologiques révolutionnaires dans des secteurs d’intervention prioritaires.
Recipient Business Number
108162330
Recipient City
Toronto|Toronto
Recipient Country
CA
Recipient Legal Name
The Governing Council of the University of Toronto
Recipient Postal Code
M5G 1L5
Recipient Province or Territory
ON
Recipient Type
S
Reference Number
172-2020-2021-Q4-964412