Use of live data in predicting Pre and Post Infrastructural impact of Bangla Academy MRT Station

This design explores the implementation of live data in architecture and urban design process, which can predict the growth of a design, based on existing and predicted data, which assists the design process into an optimal path. Here, live data is a form of real-time data which continuously gathers people's physical and behavioral properties in a quantifiable mode.
Share on facebook
Facebook
Share on twitter
Twitter
Share on linkedin
LinkedIn

Designer(s) : Ahmad Abdul Wasi

University : Bangladesh University of Engineering & Technology

Tutor(s) : Dr. Khandaker Shabbir Ahmed

This design explores the implementation of live data in the architecture and urban design process, which can predict the growth of a design, based on existing and predicted data, which assists the design process into an optimal path. Here, live data is a form of real-time data which continuously gathers people’s physical and behavioural properties in a quantifiable mode. This concept of real-time data with the help of artificial intelligence will bring about changes in the present social paradigms. Newer technologies are enabling us to acquire live data from public places and to use them to determine the infrastructural impact of a new structure in the urban fabric. The focus of the study is densely populated Dhaka city’s future MRT system which will create an epoch in the city’s urban fabric. The impact of the MRT system should be as humane as possible for the urban populous. One of the MRT stations is ‘Bangla Academy MRT station’ which is selected as the site of the study. The site, surrounded by parks, squares, and a university campus, works as a vibrant urban hub with a significant historical impact. Here live data enables the possibility of placemaking and creating permeability while integrating the MRT station with other public places. Real-time live data is gathered from the existing crowd and their behavioural pattern. The process consists of several steps that use live data to create a functional solution of the design from macro to micro-scale. This data is not static and can be used even after the design is completed to adapt to different social and demographic situations. The research culminates in a point where live data helps to guide the design process setting various parameters for optimization and making an adaptive design that becomes timeless, as it changes to the user’s needs in real-time.