Abstract Manager

Pothole identification and patching is one of the most visible and resource-intensive roadway maintenance activities for municipalities. Traditional approaches often rely heavily on public complaints and periodic inspections, which can result in reactive responses, uneven service coverage, and limited network-level insight into roadway condition.

The City of Winnipeg’s InfraAI initiative applies automated roadway condition intelligence to improve how pothole patching is planned, prioritized, and delivered. Imagery collected from operational vehicles is analyzed to identify potholes and surface defects at scale, producing an objective and repeatable dataset that complements existing inspection practices. Rather than operating as a standalone technology solution, this condition data is integrated directly into existing GIS and work management systems to support asset-based planning and operational decision-making.

This presentation will focus on how automated condition intelligence is being used to strengthen pothole patching planning strategies, including spatial aggregation of defects, severity classification, network-level prioritization, and integration with work management workflows. These integrations enable closed-loop processes that connect identified defects to maintenance activities and outcomes, supporting consistent tracking from identification through repair.

A key outcome of this approach is a shift away from prioritizing the loudest or most frequent complaints toward a more objective and equitable service model based on observed roadway condition. Automated condition intelligence allows the City to proactively identify potholes and initiate repairs before service requests are submitted. Public-facing communication tools are used to indicate when issues are already known and being addressed, helping to manage expectations and reduce duplicate complaints. When service requests are received, automated status updates are provided upon repair completion, closing the communication loop with residents without additional manual effort.

The presentation will also discuss lessons learned related to operational adoption, data governance, and change management, as well as the potential to extend this planning approach to other right-of-way maintenance activities. Practical insights will be shared for municipalities seeking to improve asset management planning through proactive, data-driven strategies.