In response to Los Angeles County’s accelerating problems of transportation and air pollution, this research aims at rethinking the future of bike-share stations in the region. Through multiscale GIS analysis and high-resolution dynamic field measurements, this project proposes the optimal locations and functions of these bike-share networks. The goal is to amplify the awareness of the climatic data and increase sensitivity towards the built environment through interactive modes of visualization.
This research utilizes dynamic data collection techniques to map the air quality of the University of Southern California campus with the use of a dynamic visualization machines. The collected high-resolution climatic data - CO2, temperature and humidity concentration - are dictating the behavior of a 4-axis visualization machines that moves and behaves in simulated three-dimensional physical space. By separating various climatic variables and assigning them to different appendages of the visualization machine, the rhythmic differences are amplified in a way that one becomes aware of the concentrations and durations. The goal is to amplify the reading of the climatic data and increase sensitivity towards the built environment.
How are the citizens of Glendale feeling? This very moment, right now, Glendale is… a data-driven interactive light installation which reflects the emotional temperature of Glendale residents. They control it. A morphing, sweeping geometric grid suspended from the ceiling houses 140 vacuum formed partially translucent acrylic cells. Each of the cells has an individually addressable Neo-pixel RGB Light emitting diodes (LEDs) which change color. The pattern is effected locally by the community at large and also hyper-locally by users within the space.
DOT/O is an interactive installation as social experiment / game exploring the capacity and interest of a crowd to ‘complete’ a suggested structure. The project is inspired by ‘connect the dots’, in which numbered dots allow a player to discover a hidden drawing by following the correct order. For the purpose of the installation, the team developed a steel structure to act as host for a crowd-sourced threading experience. Users are invited to pick one of the wall-mounted spools of thread, and connect the dots discovering the 3D surfaces that exist between the different frames. The project was intended to slowly build density, and use color to map the progress of time and interaction through the structure. Simple rules like maximum distances were suggested but not enforced, allowing players to follow or ignore them, resulting in a combination of order and disorder. The stochastic nature of the installation challenges the idea of formal preconceived output, embracing the uncertainty of the social interaction. Slowly, though, the piece would accumulate enough threads where independent intentions would become less visible as an increasingly denser fabric would become the dominant collective creation. The final result, viewed as a social experiment, embraces the messiness of the initial experiment, speculating in the formats and mechanics of crowdsourcing for design. In this regard, we identified that the piece presents a model of cooperative crowdsourcing, not competitive; while many crowd-sourced projects seek to optimize a solution by finding a particular individual that can provide the best answer, DOT/O invites all players to be part of the experience and share the same output.
LOCATION: Keystone Art Space
TYPE: Installation / social game
SIZE: 100 sqft
MEDIUM: Custom bent steel frame + thread
TEAM: SomewhereSometing With PLETHORA PROJECT (JOSE SANCHEZ)
LA FABRICA + Alenoush Aghajanians, Anqi Yu, Arjun Mahesh, Avra Tomara, Belen Sanchez, Caroline Duncan, Guoyu Hu, JiaRui Su, Jimmie Li, Kevin Crooks, Mouna Lawrence, Olivia Tirado, Phong lee, Robbie Mehring, Sam Adelan, Setareh Ordoobadi, Vaheh Vartanian, Wu Qiong, Yueming Zhou
LOCATION: USC School of Architecture / Los Angeles / CA
SIZE: 250 sqft
MEDIUM: PVC pipe + thread
TEAM: Tim Chen, Elsie Cheng, Chi-En Hsieh, Matthew Kopp, Patrick Lee, Jessica Miksanek, Natalie Paolerci, David Rodriguez, Stephanie Schneidereit, Daniel Sigala, Bradley Silling, Cindy Yiin