RE:SETTLE - IAAC MaCAD Thesis22

The rapid population growth of cities affects the acquisition of land tenure, land security, and production of good quality housing. The constant pressure of living in highly urbanized cities forced the working class to live in lower-quality housing. In return, these people have reverted to living in areas within the poorer residential districts of the city.

Due to the low enforcement of zoning laws in some cities, people living in such conditions tend to build housing settlements in no-build or high-risk flood zones to survive, making the community vulnerable to disasters.

So the question is:

Is there a need to rethink these communities' current housing development strategies?

Rethinking current housing designs can be a platform for designers and planners to provide new innovative solutions. Understanding the current housing conditions can be used as a learning tool to achieve the effectiveness and efficiency of new housing design strategies.

The project aims to create a tool to analyze housing strategies by employing machine learning to predict the performances of different housing iterations and democratizes the design process by deploying the parametric model to the web. The participatory approach to design would hopefully empower the users and planners with the ability to infer, analyze, and improve on different possible solutions interactively.