Machine Learning (Artificial Intelligence) in Architecture Design Process

Abstract

Technology, as it develops is always considered to save time and resources. Machine Learning is a practical sub-category of the main subject called “Artificial Intelligence” which learns from its experience and improves the efficiency without programming it from the scratch. Architecture is a field of practicality and theory combined in a precise way. It needs constant supervision over the design process in the office as well as on site. The only limitation is the possibility of human error in the process, which can be reduced by hiring experts to supervise the work which can not be feasible in every situation. Machine Learning can be introduced in the field of architecture to manage various works such as supervising the GFC Drawings before execution, supervising the labor attendance using face recognition, managing the quantity of material at site, Passenger Head Count survey for the design/redevelopment of transport terminals which is labor-intensive work and increases the chance of human error. Machine Learning can further be used to generate the basic ideation/layout of the project with several design alternatives with the choice of using any building controls or byelaws. This article presents examples of architecture design process with the help of concepts of machine learning environment.