*HUBBUB 25 Winning Project: Most Scalable Project*
*HUBBUB 25 Winning Project: Most Responsive Project*

This BCIT ISSP project supports the City of Vancouver’s goals around modernization, digital transformation, and reliable fleet-based service delivery. By enabling a more proactive maintenance approach, it has the potential to reduce operational costs, increase the reliability of municipal services, and improve how labor and equipment resources are allocated. It also contributes to the City’s environmental and sustainability objectives by extending vehicle lifespan and minimizing waste from premature component failures.

A significant early challenge in the project was gaining clarity on what, exactly, we were trying to predict while simultaneously familiarizing ourselves with a complex dataset. Although the initial project meeting outlined the overall scope, it was difficult to translate that broad description into smaller, actionable tasks. As the project evolved, our understanding of the objectives became much more focused.

The project represents a meaningful opportunity to apply machine learning to generate predictive insights that can enhance the City of Vancouver’s daily operations. With additional time and refinement, this work has strong potential to significantly improve the workflow, efficiency, and long-term planning capacity of the City’s fleet repair garages.