Critic: Lorenzo Villaggi and Carlo Bailey
Team: Mike Howard, Nishant Jacob, Alex Waihoe Loh, Violet Whitney


spatial analytics, data analytics, measurement, data visualization, task tracking, space tracking, waste tracking


view online here


physical, digital and immaterial waste


So much of what goes into an architecture project is discarded. Laser cuts, coffee cups, crumpled trace, 300 MB PSD files. Beyond just physical waste -the design process that is typically considered constructive is equally wasteful in immaterial ways. Hours spent browsing the web for research or checking email are wasted when they don’t contribute to the design. The architecture building is also wasted during its many vacant hours when students return home.

My team and I were interested in quantifying the waste (material and immaterial) generated in the Columbia Architecture studios of Avery Hall over the course of the week. Employing an array of physical computing sensors, cameras, computer software, and scales we measured Avery over one week to observe the typical cycle of a GSAPP student. We defined waste as the unnecessary byproducts of the production cycle – both physical and digital.

Employing an array of physical computing sensors, cameras, computer software, and scales we measured Avery over one week to observe the typical cycle of waste from a GSAPP student. 


For data: an Arduino monitored air quality, OpenCV running on a Raspberry Pi recorded occupancy and movement in the studio, a scale weighed trash discarded outside of studio, a grasshopper script recorded the amount of laser cut-able material discarded after a cut job, and RescueTime software monitored how often and what types of software students used. Combined, the datasets offered a well-rounded view of both the physical and digital waste associated with a GSAPP student’s production.

The course pushed us to experiment with new forms of data representation with an N-Dimensional drawing. To convey the breadth of information we collected in static images, we employed the classically architectural techniques of section and perspective to place the viewer in a hallway of time where one experiences collected data in a more physical way – calling upon an intuitive sense of scale to understand a complex layering of data. 


Python with RescueTime API and Grasshopper Script: Software Usage


We developed a Grasshopper Script with the RescueTime API to track software usage for multiple students throughout the week. The script sums time spent by the participants in each software by minutes and seconds. For simplicity and privacy purposes, the time spent on specific websites (Pinterest, Facebook, Netflix) is composited together in a category called "web browsing". Because the diversity of softwares used, we visualized the most prevalent softwares used across all participants (Adobe Photoshop, XXXXX.

grasshopper script for tracking s usage

grasshopper script for tracking s usage


Open Computer Vision on Raspberry Pi: Occupancy Movement

Arduino Monitor: Air Quality

arduino setup for camera

arduino setup for camera