Honeywell has announced the launch of Honeywell Forge Energy Optimization, a Cloud-based, closed-loop, machine learning (ML) solution that continuously studies a building’s energy consumption patterns and automatically adjusts to optimal energy saving settings without compromising occupant comfort levels.
Honeywell Forge Energy Optimization is focused on decreasing energy consumption, may deliver double-digit energy savings, decrease a building’s carbon footprint, and can be implemented without significant upfront capital expenses or changes to a building’s current operational processes, claimed Honeywell in a press release.
Honeywell said during a pilot at Hamdan Bin Mohammed Smart University (HBMSU) in Dubai, United Arab Emirates, its new solution had demonstrated an initial 10 percent energy savings.
“Buildings aren’t static steel and concrete – they’re dynamic ecosystems and their energy needs fluctuate based on ever-changing variables like weather and occupancy,” said David Trice, Vice-president and General Manager, Honeywell Connected Buildings, in the press release. “With Honeywell Forge Energy Optimization, we’re evolving building operations far beyond what would be possible even with a robust team of engineers and the rules they code in their building management system. By employing the latest self-learning algorithms coupled with autonomous control, we can help building portfolio owners fine-tune their energy expenditures to drive efficiencies and create more sustainable practices for our customers.”
Image credit: Honeywell