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to turn on when it senses a certain pressure in the water line or at a certain temperature that it’s reading on a weather station. That is more than likely not AI,” he said. “What we’re looking for is for AI to be able to interpret data and make decisions that are above and beyond what’s programmed.” “A perfect example is if there are a couple of cold nights where the guns all of a sudden decided to go to 160 gallons a minute and are using a little bit more water than we wanted because we’re trying to ration it around the mountain,” said Wilber, “someone needs to manually go and dial that back a lit- tle bit” in the automated system. In the future, he said, AI would be able to adjust the output without human assistance and pri- oritize the amount of water or compressed air going to certain trails or areas based on the resort’s early season needs.
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From an efficiency and cost savings standpoint, the turning point will be “when we can start to get systems that aren’t typ- ically connected starting to speak to each other and interpret and use data together,” said Wilber, such as integrated grooming snow-depth technology and snowmaking systems. With integrated tools, resorts could better target high-traffic or erosion-prone terrain and avoid wasting resources elsewhere. “We can really hone our efficiency so we’re not making six feet of snow where we’re not going to need it in April,” said Wilbur. AI might also help fill the void of institutional knowledge as experienced workers age out. “Instead of us using our tribal knowledge of the guys who have been working out on the hill for the last 20 or 30 years,” said Wilber, “this is where AI can step in and help. You become less human reliant, and it protects the ski resort going into the future.” Wilber said that staff reaction to machine learning-led ops has been mixed, depending on their generation—many long- time snowmakers probably aren’t huge fans of automation. “But then some of the younger guys love it [because they] are looking for a more efficient way to do things instead of drag- ging hundreds of hoses out on the hill and having to go manu- ally check every gun,” he said. FORECASTING FOR THE FUTURE Cannon Mountain general manager Jace Wirth arrived in Fran- conia, N.H., from the West less than two years ago and imme- diately set out to understand the resort’s notoriously complex microclimate. “Snowmaking is one [challenge] that I wanted to get my arms around,” he said. Fortunately, Cannon has a data-rich partnership with its neighbor the Mount Washington Observatory, which operates automated weather stations on Cannon Mountain as part of a regional mesonet. “We’ve got weather stations at high and low elevations and basically just a treasure trove of data going back
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