Leveraging AI and Machine Learning for Targeted Program Improvement

In the evolving landscape of fire & emergency services, the integration of Artificial Intelligence (AI) and Machine Learning (ML) presents unprecedented opportunities to enhance quality and efficiency, and provide targeted resource allocation to CRR programs and operations. This presentation will delve into Halifax Regional Fire & Emergency's pioneering research project with funding from the Government of Canada through Defence Research and Development Canada (DRDC) Canadian Safety and Security Program (CSSP), in partnership with academic institutions and industry, aimed at revolutionizing emergency service decision support through advanced AI and ML technologies. Seeking to engage the Audience with the research questions at hand, and the theoretical concepts underpinning the application of the technologies.

This presentation plans to ask, discuss, and share some of the fundamental questions posed by this research and development challenge:

1. What resources can be optimized through the use of these technologies?
-Quality Improvement and Optimizatiion Theories

2. What challenges exist in adopting real-time field based AI/ML decision support tools, particularly for humans?
-User adoption, Human Systems Interface

3. Can AI/ML tools help overcome cognitive bias and reduce cognitive load for incident commanders?
-Human Factors Applications of digital tools for safety

4. Do we use all of our data to the maximum ability?
-Quality Analysis if Unstructured Data

Our research underscores the transformative potential of AI and ML in emergency services and considers how the humans interface with technology in a high-risk, high-high-reliabilty environment. By leveraging advanced technologies funded by a collaborative effort between government, industry, and academia, the project seeks to optimize resource allocation, enhance real-time decision support, conduct quality analysis, and improve programs and safety. Attendees will gain insights into the methodologies, challenges, and progress of integrating AI into fire & emergency service programs.

Keywords: Artificial Intelligence, Machine Learning, Fire Service, Community Risk Reduction, Emergency Services, Community Safety, Resource Allocation, Responder Safety, Human Factors.