2026 / Installation
Partial Perception
An installation about how inference shapes perception, using partial sensor data to examine how generative AI constructs its own version of reality.
- Generative AI
- Python
- Electronics
Overview
Project description
This installation uses a network of sensors to feed environmental data into an AI interpreter, which then sends its analysis to a Stable Diffusion model. The system generates an image that reflects its best interpretation of what the activity in the room resembles.
The sensors track temperature, humidity, air pressure, motion, distance, and sound. From that accumulated data, the AI estimates how many people are in the space and where they are positioned, then sends that reading to the image model. A new image is projected every 8 to 10 seconds.
The room is staged like the inside of a system. A table holding the microcontroller, projector, and laptop acts as the system's brain, while wires extend to sensors suspended from the ceiling. As people move through the room, the data shifts and the projected image updates with a new interpretation of the environment.
Media Gallery
Images and video documentation from the project folder.
