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Home » Study finds AI can assist building become more secure, resilient and more sustainable

Study finds AI can assist building become more secure, resilient and more sustainable

Tarun Khanna by Tarun Khanna
October 8, 2025
in Artificial Intelligence
Reading Time: 2 mins read
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Study finds AI can assist building become more secure, resilient and more sustainable

Photo Credit: https://techxplore.com/

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Artificial intelligence (AI) could be key to designing buildings which are resilient to each climate extremes and infectious disease threats, according to the study with Charles Darwin University (CDU).

The study took place via the University of Tehran, CDU and Australian Catholic University carried out a review of how AI is being used in smart buildings, with a target on energy efficiency and management.

“Applications of Explainable Artificial Intelligence (XAI) and interpretable Artificial Intelligence (AI) in smart buildings and energy savings in buildings: A systematic review” was posted within the Journal of Building Engineering.

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Buildings generates more than two-thirds of global carbon emissions and energy consumption, but managing and saving energy in buildings is difficult and high priced.

Co-author and CDU adjunct Associate Professor Niusha Shafiabady said of note, the evaluation found AI could be precious in improving building ventilation and thermal comfort.

Associate Professor Shafiabady stated at present, most buildings use static heating, ventilation and air conditioning (HVAC) structures, that may effect structure sustainability and the health of occupants.

“Overheated or poorly ventilated spaces not most effective, but decrease occupant comfort however also boom the probability of airborne disease spread,” Associate Professor Shafiabady stated.

“Static HVAC designs fall short below fluctuating climate conditions. The study supports the use adaptive thermal control systems that reply to occupancy, external climate, and internal heat gains in real time.

“This opens the door for AI-driven optimization, where machine learning can expect and adjust thermal conditions to balance comfort, energy efficiency, and health outcomes.”

The stuudy proposes a framework that permits building designers and facility managers to use AI to simulate thermal eventualities and compare their effect on airborne transmission risk.

“It’s modular, scalable, and adaptable to different building types, from lecture rooms to hospital wards,” Associate Professor Shafiabady stated.

“Significantly, it gives a quantitative basis for decision-making, allowing stakeholders to prioritize interventions that enhance both thermal comfort and infection control.”

This research was performed alongside lead author Mohammadreza Haghighat from the University of Tehran and co-author Ehsan Mohammadi Savadkoohi from CDU.

Future potential research consists of integrating this framework with real-time sensor data and AI algorithms, the use of this studies to assist inform building regulatory standards.

“This research bridges engineering and epidemiology, providing practical guidance for architects, facility managers, and policymakers seeking to in future-proof buildings towards health threats,” Associate Professor Shafiabady stated.

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Tarun Khanna

Tarun Khanna

Founder DeepTech Bytes - Data Scientist | Author | IT Consultant
Tarun Khanna is a versatile and accomplished Data Scientist, with expertise in IT Consultancy as well as Specialization in Software Development and Digital Marketing Solutions.

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