Honeywell launches first autonomous building sustainability solution to fight rising global energy consumption

Machine learning autonomously adjusts building energy settings to deliver up to double-digit energy savings and a seamless occupant experience

Honeywell, Honeywell Forge Energy Optimisation, Machine learning solution, Building’s energy consumption, Optimal energy saving, Autonomous building solution, Carbon footprint, Hamdan Bin Mohammed Smart University, Dubai, United Arab Emirates, Dr Mansoor Al Awar, David Trice, Honeywell Connected Buildings

Honeywell launched Honeywell Forge Energy Optimization, a cloud-based, closed-loop, machine learning 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 Optimisation, the first autonomous building solution 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.

During a pilot at Hamdan Bin Mohammed Smart University (HBMSU) in Dubai, United Arab Emirates, Honeywell Forge Energy Optimisation demonstrated an initial 10% energy savings. HBMSU is the first accredited smart university in the UAE and is known for its technology and innovation programmes.

Honeywell Forge Energy Optimisation was applied to HBMSU’s existing building management system, which uses competitor technology to demonstrate the platform’s open architecture and hardware-agnostic capabilities. The additional energy savings is especially significant because HBMSU is regarded as a highly smart, energy efficient building with fully connected lighting, cooling, building management, power and efficiency control that is optimised based on real-time occupancy. The pilot also uncovered local control issues with the chiller plant and fresh air handling unit that were not adjusting to set points.

“As a smart university, we look to deploy the latest technology across our campus and ensure our buildings are efficient. We were pleasantly surprised by the results we saw from Honeywell Forge and its ability to drive further energy savings beyond our achievable optimisation with the techniques we have,” said Dr Mansoor Al Awar, chancellor of Hamdan Bin Mohammed Smart University. “Our further partnership with Honeywell will help to support the advancement of artificial intelligence (AI) modeling for building automation and provide our students with first-hand applications of how AI and machine learning will drive operational efficiencies in buildings. Our goal is to collaborate with leading organisations like Honeywell that support our vision of educating the innovators of tomorrow.”

“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. “With Honeywell Forge Energy Optimisation, 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.”

Achieving Energy Savings Beyond Standard Techniques Energy consumption in commercial buildings is a significant issue because these buildings account for more than 36% of global final energy consumption and nearly 40% of total direct and indirect CO2 emissions.

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