Last week we presented at Data Tech 2019 - but the event was sold out and so we know not everyone who wanted to come was able to- so we have broken down our presentation to a few excerpts that we’ll share in the next few days.
Driving a machine that is worth more than your annual salary purely by satellite → inspiring.
While autonomous cars are not yet on the majority of roadways, pieces of equipment that are $0.5M are now being powered across fields globally using the same technology. It is truly revolutionary, and I highly encourage you if you ever have the opportunity, visit a farm and see what auto-steer feels like.
When I was growing up, and started helping my Dad on the farm, my swathing and combining did look a little more like snakes going up and down the fields than like straight lines. I zigged and zagged a little bit, I certainly overlapped, and in some cases underlapped (if that’s a word). So, while I would get the field done, it wasn’t the prettiest, and the stubble left behind always showed how straight I had gone, or in my case how off course I had gone.
So, when I went back to the farm to help with harvest again, about 10 years later, I was absolutely amazed. My parents had invested in auto-steer in all of their equipment. Honestly, all I was in the cab for was to turn corners at the end of the field. I had a good 10 minutes of “me time” in between the equipment having any need for me. It was absolutely amazing.
But not only was it amazing for me, it made business sense, and greatly improved environmental sustainability. So even if autonomous tractors and cars are not yet the norm, GPS and AI have enabled auto-steer for the majority of implements which has enabled:
Accuracy when seeding
Reduced overlap - critical when thinking of chemical and fertilizer application
Reduced carbon footprint - fewer passes across the field
Introduced capabilities in understanding fields at a greater level with big data with geospatial awareness
Enabled tracking of machinery
All from a tiny bubble placed on the roof of each machine.