Hello Atlanta !

Project Description | Hello Colorful Atlanta! Data visualization on Cesium platform!

The goal of this project is to research how smart a city can be, and how we can design a city in a smart way. In this project, we use Atlanta as the research subject. Atlanta is a city which has a convenient public transportation system, MARTA. As a busy public transportation system, MARTA is able to collect massive data by installing sensors on the trains, bus and stations. The data collected can be used to develop some applications and make this city respond to people's needs more quickly, or, real-timely. Hence, this project is aimed to input MARTA data to architecture design, urban design to develop a system for Atlanta citizens. The first take we did is to visualize the MARTA data in building scale.

Fig. 00. Heat Map of ATL - Dennis R. Shelden, Diego Osorio, T.C. Kurt Hong, 2017 Spring

Fig. 01. Real Time Updating Transportation - Dennis R. Shelden, Diego Osorio, T.C. Kurt Hong, 2017 Spring

Fig. 02. Data Visualization of ATL - T.C. Kurt Hong, 2017 Spring

Fig. 03. Data Visualization of ATL - T.C. Kurt Hong, 2017 Spring

Fig. 04. Data Visualization of ATL - T.C. Kurt Hong, 2017 Spring

Fig. 05. Coloring Test of ATL - T.C. Kurt Hong, 2017 Spring

CourtSpace | Generative System of Courthouse Design

Project Description | 

CourtSpace is a generative design software  which is based on rule-based design. Rules embedded in CourtSpace are from the analysis of the federal courthouses in US, this research is conducted by Dr. Thanos Economou at Georgia Tech and PhD candidates, Heather Ligler and James Park. In CourtSpace project, the goal is to develop a series of design vocabulary and integrate this design language into Rhinoceros platform, thereby providing architects a tool for courthouse design.

Fig.01 - Composition of courthouse, T.C. Kurt Hong, 2017 Spring

Fig.02 - Composition of courthouse, T.C. Kurt Hong, 2017 Spring

Fig.03 - Composition of courthouse, T.C. Kurt Hong, 2017 Spring

Fig.04 - Composition of courthouse, T.C. Kurt Hong, 2017 Spring

Fig.05 - Composition Test, T.C. Kurt Hong, 2017 Spring

Fig.06 Rules, T.C. Kurt Hong, Spring 2017

ARGO | Generalized shape search test

Description | ARGO - Topological Shape Search

ARGO is a project which is trying to capture some data features of each shape, thereby recognizing the shape embedded in a bigger shape on Rhinoceros. This project starts with an extension of the previous project, GRAPE, which is using an open-sourced graph engine, GRGen. However, GrGen is not designed specifically for shape grammar community, so there are some limitations in the future development. Thus, Allo is initiated with an ambitious goal that we try to build up our own graph engine and expand the search power. So far, Allo can search any embedded topological shape less than 5 lines (1-line to 4-line shape are working) in a bigger shape. In the future development, we will try to push the limit further and come up with a total solution for this project.


Demo Video link:
https://www.youtube.com/watch?v=r3riMnFAgKs

Fig.01 - Topological shape search, T. C. Kurt Hong, 2017 Spring

Fig.02 - Topological shape search, T. C. Kurt Hong, 2017 Spring

Fig.03 - Topological shape search, T. C. Kurt Hong, 2017 Spring

Fig.04 - Topological shape search, T. C. Kurt Hong, 2017 Spring