NewVu
By Isa Murray & Cole Krivak
NewVu aims to generate unique learning environments and predict the possible student capacity of each space. We utilized statistics from the student body such as preferred rooms, square footage, wall type, and student density, and compiled them into a generative algorithm. This algorithm genorates rooms by placing floor and wall tiles according to the hallway location and other parameters.
Thesis
Precedents
Sketches
Prototypes
Initial Data
Prototype 2
Updated Data
Prototype 3
Artwork/style
1.
2.
Room Generation Process
3.
4.
Room Generation Process Cont.
Final Photo
Final photo of project (delete this)
Room Gen Final Examples
Room Gen Final Examples
Room Gen Final Examples
3750 sq ft
unregulated door placement
optimal student rooms:
square
625 sq ft
low glass wall density
NewVu aims to generate unique learning environments and predict the possible student capacity of each space. We utilized statistics from the student body such as preferred rooms, square footage, wall type, and student density, and compiled them into a generative algorithm.