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The client faced limitations in their existing AI solution for highway safety due to dataset mislabeling (e.g., road signs occupying entire image areas), suboptimal model training approaches, and workflow inefficiencies. These issues hindered accurate asset counting (streetlights, road signs, crash barriers) and required expert intervention to optimize performance without overhauling the existing system.
An IT company providing digital products and services, specializing in highway safety monitoring solutions.
The solution will improve highway safety through accurate asset monitoring, reduce manual processing time by 70% via automated analysis, lower operational costs through optimized resource allocation, and empower the client's team with advanced ML implementation expertise while maintaining compatibility with existing infrastructure.