Tommy TafazzoliRESEARCHER · EDUCATOR · ENGINEER
← All research spotlights

RESEARCH SPOTLIGHT · 2025

How AI Can Reduce HVAC Energy Use

The review helps building professionals see AI as an operational tool rather than an abstract algorithm.

Sustainability & resilienceSystematic reviewJournal article

The question

HVAC systems account for a substantial share of building energy demand, but the practical value of AI control and maintenance methods varies across settings. This review examined what recent evidence says about performance and implementation.

What we did

The review synthesized studies published from 2018 onward on machine learning, deep learning, and other computational techniques applied to HVAC control and maintenance. It considered energy performance, occupant comfort, practical deployment, and the science-to-practice gap.

What we found

  • Reviewed AI-driven control strategies reported energy reductions of up to 40% in appropriate applications.
  • Dynamic responses to occupancy and environmental conditions are a recurring advantage of AI-based control.
  • Implementation still depends on data quality, system integration, and validation in realistic building contexts.

Why it matters

The review helps building professionals see AI as an operational tool rather than an abstract algorithm. Its value lies in connecting energy reduction with comfort, maintenance, and the constraints of existing building systems. Read together, the question, method, and findings show how this publication fits within Tafazzoli’s broader program of connecting built-environment evidence with practical decisions. The page intentionally separates documented results from interpretation and directs readers to the complete paper for methodological detail. The study also illustrates a recurring principle across this research portfolio: a useful result must be understood in its original setting before it is transferred to another project, organization, population, or policy context.

Diagram summarizing How AI Can Reduce HVAC Energy Use

AI-enabled HVAC management. This original synthesis graphic is based on the study’s documented question, method, or principal contribution; consult the paper for complete figures, labels, units, and uncertainty.

Original website synthesis based on the cited publication.

View full-size figure ↗

READ THE PAPER

Artificial intelligence approaches to energy management in HVAC systems: A systematic review

Published · 2025 · Journal article

Aghili, S. A., Haji Mohammad Rezaei, A., Tafazzoli, M., Khanzadi, M., & Rahbar, M. (2025). Artificial intelligence approaches to energy management in HVAC systems: A systematic review. Buildings, 15(7), 1008. https://doi.org/10.3390/buildings15071008

Read at publisher ↗

DOI: 10.3390/buildings15071008

CONTINUE EXPLORING

Related research

Publication list ↗