Presentation by Paul Marsolan, Battle Motors

What does it take to ship production AI on an 80,000-pound refuse truck — a vehicle that fights vibration, heat, dust, and intermittent LTE on every shift, and where a single missed detection can mean a hopper fire from a discarded lithium battery?

This talk goes inside Fortris™, Battle Motors' edge vision platform: eight RGB cameras, three vision models running in parallel on a Jetson Orin Nano, sub-200 ms decision latency, and a bidirectional cloud plane that turns every route into a labeled dataset. We'll walk through the real architecture — specialist + generalist + action-detection models, OTA model deployment with per-truck rollback, ADAS sensor fusion — and the production lessons behind it. Deploying a model to 1,000 trucks is not deploying to 1,000 web servers; reversibility is a product feature, not a nice-to-have.

You'll leave with a concrete picture of what edge AI looks like when it has to work in one of the harshest commercial environments in America — and why the cab of an 80,000-pound truck might be the next great human-AI interface.