Artificial Intelligence Applications for Sustainable Construction - Chapter 3: Machine learning applications in the development of sustainable building materials to reduce carbon emission

Elsevier, Artificial Intelligence Applications for Sustainable Construction, 2024, pages 93-121
Khokhar S.A., Shah M.U., Rehman F., Cheema H.B., Usman M.

Concrete is the most commonly used construction material and the source of around 8% of the world's CO2 emissions, which is very alarming to the environment. Therefore, to reduce the carbon footprint associated with building materials, researchers worldwide are engaged in the development of sustainable building materials. Considering sustainability, the design and processing of materials is a very time-consuming and tedious task. However, the recent advances in the field of machine learning (ML) provide researchers with an opportunity to focus on the above-mentioned challenges. ML allows using the previous literature as a dataset to develop ML predictive models. These predictive models are used to design optimized and sustainable composites. The estimated parameters of composites through these ML predictive models are accurate and have also been experimentally validated. Therefore, it is very easy to design sustainable composite building materials using ML. This chapter will comprehensively address all the essential elements of ML that are crucial for the development of sustainable composite building materials to reduce CO2 emissions.