Axiom Cloud
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Axiom debuts ‘Early Leak Detection’ for cold storage

Sept. 1, 2023
New AI-powered module ‘revolutionizes’ refrigerant management by catching leaks faster—regardless of location—without adding physical sensors.

Axiom Cloud recently released its Early Leak Detection (ELD) module for commercial use in North America.

The patent-pending module, formerly in beta, leverages artificial intelligence-powered algorithms, instead of physical sensors, to detect leaks earlier than most cold storage facilities and grocery stores can today, the company said. ELD helps facilities reduce refrigerant leak rates and Scope 1 greenhouse gas (GHG) emissions, and enables faster, more efficient service calls through clear, location-specific notifications.

“I am more excited about our Early Leak Detection module than any other new technology we have introduced in the refrigeration industry to date,” Axiom CEO Amrit Robbins said in a news release. “Across the 240-plus sites where it’s already operating today, the ELD module has proven it can increase Axiom Cloud’s greenhouse gas impact by more than 10 times, which is incredibly motivating to me and the Axiom team.

“I’m excited to partner with the big grocery and cold storage companies to deploy ELD in thousands of facilities fast, so we can realize these climate and financial benefits at scale soon.”

Axiom also released a case study featuring the ELD module providing value at a Sprouts Farmers Market store near Sacramento, California. The module detected back-to-back leaks at the facility that were otherwise overlooked, avoiding two emergency cooling outages, saving approximately 300 pounds of leaked R407F refrigerant (equivalent to 550,000 lbs. of CO2 emissions), and saving the facility approximately $9,600 in refrigerant costs alone, Axiom said.

Axiom Cloud is listed by the California Air Resources Board (CARB) as an Automatic Leak Detection (ALD) system, which means the ELD module enables facilities to avoid required quarterly or monthly manual leak checks while simultaneously lowering a facility’s leak rate.

The module leverages a combination of AI-powered algorithms and 11-plus indicators derived from system-level models to detect variations that indicate refrigerant leaks. By operating without the need for PPM sniffers or receiver-level sensors, ELD can be applied uniformly across a disparate portfolio of stores, streamlines most leak detection strategies into a single process, and catches leaks earlier than other methods.

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