Dan McCann, CEO of Precision AI, explains how his company combines AI, computer vision, and drones to cut pesticide use by an estimated 80 to 90 percent. He walks through the two-part system, survey drones that build precision maps for ground sprayers, and spraying drones that spot-dose weeds directly, and makes the case that the accessibility of a per-acre drone service closes the gap between what large and small operations can afford. The origin story, an image-recognition app built for a completely different purpose, is the unexpected hook.
Most in-crop spraying still works the same way it did decades ago: load the sprayer, cover the whole field, hope the chemical lands where it's needed. Dan McCann's estimate is that roughly 80 percent of it doesn't. It hits bare dirt or a plant that was never a threat.
Precision AI's answer is computer vision built for the field: drones flying up to 70 km/h with sub-millimeter resolution, trained to tell a wild oat from a wheat plant at the 2-leaf stage. What a farm does with that data is where the real shift happens.
What's Inside
- Why traditional high-clearance spraying wastes an estimated 80 percent of applied chemical on bare dirt or non-target plants
- How sub-millimeter computer vision tells weed species apart from crop at flight speeds up to 70 km/h
- The two-part system: survey drones that build precision weed maps for ground sprayers with individual nozzle control, and spraying drones that spot-dose weeds directly from the air
- Why drone spraying avoids soil compaction and can work wet fields that would get a ground rig stuck
- The cost gap between $150,000 to $200,000 sprayer retrofits and a per-acre drone survey fee, and what that means for smaller operations
- How an app built to catalog garage items led to a company solving crop protection
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