How Programmable Construction Can Shape the Future of Sustainable Building in Italy

Silvia Mazzetto (), Haidar H. Hosamo and Mohamed Ezzat Al-Atroush
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Silvia Mazzetto: Sustainable Architecture Laboratory, Department of Architecture, College of Architecture and Design, Prince Sultan University, Riyadh 12435, Saudi Arabia
Haidar H. Hosamo: Sustainable Architecture Laboratory, Department of Architecture, College of Architecture and Design, Prince Sultan University, Riyadh 12435, Saudi Arabia
Mohamed Ezzat Al-Atroush: Civil and Environmental Engineering Program, College of Engineering, Prince Sultan University, Riyadh 12211, Saudi Arabia

Sustainability, 2025, vol. 17, issue 5, 1-27

Abstract: The construction industry has traditionally relied on labor-intensive methods, often resulting in inefficiencies, cost overruns, and extended project timelines. Despite advancements in automation and robotics, the potential of programmable construction to address these challenges remains underexplored, particularly in the context of small to medium-scale projects. This study investigates the impact of programmable construction on time, cost, and sustainability, using a detailed case study of a residential project in Italy. This research adopts a comparative approach, analyzing traditional construction techniques versus automated construction systems. Production rates from previous research and real-world applications are used to develop alternative schedules that reflect the efficiencies of these advanced technologies. The findings demonstrate that programmable construction can reduce project timelines by up to 82.6% and achieve cost savings of approximately 40.6%. Automated systems also offer significant environmental advantages, including a 70.25% reduction in carbon emissions and a 70% decrease in energy consumption in several tasks such as soil treatment. This study suggested that programmable construction sites can significantly shorten project timelines and reduce costs. The precision and speed of AI and robotics minimize reliance on human labor, streamline construction processes, and enhance project performance and work quality by reducing human error while promoting sustainability through reduced resource consumption and lower environmental impact.

Keywords: programmable construction; AI-driven machines; robotic automation; project efficiency; cost reduction; environmental impact (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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