Code and the City:
Data driven Urbanism through Deep Learning in Mathematica
Main Lecturer: Joo-Haeng Lee
Unit Instructors: Taeyoon Kim + Dae Song Lee + Jinseok Park
1. Unit Brief
Unit 1 will be constructing an interactive and data-driven digital model of the city, which can simulate and visualise the flux of population and tourism within Gangnam area of Seoul. Through data and machine learning, we expose the unseen aspect of the urban environment; the dynamics of the city.
Taking the traditional 3D heatmaps one step further, we adopt the dimension of time and simulate how the topography of dynamics can shift through machine learning.
The unit will utilise Mathematica as the main tool to process, analyse, and visualise data. Exploring how Mathematica can be utilised in Urbanism & Architecture, we’ll explore how the live connection between Rhino, Grasshopper & Mathematica can work in unison to produce this digital model of Gangnam, embedded with machine-learned data.
Rhino, Grasshopper( + RhinoLink for Mathematica connection )
3. Aim and Scope
Construct interactive and data-driven digital model of the city, which can simulate and visualise the dynamics of the city.
Identify & define the sources that influence in the flux of population/tourism as the parameters driving the simulation
4. Expected Workshop Outcome
Daily build up of portfolio for discussion and feedback
Edited Video or interactable online model of the project
Composite Drawings and diagrams to visualise the logic, and process