Spinner is a rather theoretical project by MIT grad student Mathew Laibowitz that gathers together data from a variety of wearable and environmental sensors “order to develop a parametric model of effective narratives that can be mapped onto sensor-detectable elements of human behavior.”
Spinner is a novel sensor network system designed to detect and capture fragmented events of human behavior that can be collected and sequenced into a cohesive narrative that conveys a larger overall meaning. Research into narratology will be performed in order to develop a parametric model of effective narratives that can be mapped onto sensor-detectable elements of human behavior. The network will be comprised of wearable sensors, environmental sensors, and video sensors that can identify and record events that fit specific narratives. Alternatively, the system can capture all events along with narrative meta-data for cataloging and browsing.
This research seeks to provide new perspectives into everyday events by incorporating them into a larger story flow. It further seeks to create a new form of entertainment and journaling in which users are automatically presented with coherent videos created from their naturally-occurring events that follow the dynamics of a specific story of their choice or creation. An overall goal of this research is to investigate a method for understanding, reducing, and presenting large amounts of data using our innate ability to understand and interpret stories.
I can imagine some cool open source project where thousands of hackers download specs and create these wearable sensors and the data is processed by some sort of unimaginably cryptic algorithm. Anywho, read Laibowitz’s full thesis proposal or watch an explicatory video to learn more. [via spime.org]