Unnecessary distractions while in deep concentration can be highly frustrating. To help reduce inopportune interruptions, Ruggero Scorcioni – a participant at an AT&T Mobile App Hackathon – developed Good Times. The solution filters incoming phone calls based on the receiver’s mental state, all without any user intervention.
Good Times uses Necomimi Cat Ears – a headset that records brainwaves – and AT&T’s Call Management and M2M APIs to process brainwaves and automatically route calls based on the specific mental state. The technology is designed to redirect phone calls when users are mentally busy. Callers who have been redirected will receive the following automated response to eliminate distractions and interruptions during key periods of focus: "This is not a good time to call, please try again later.”
Resulting from a string of last minute decisions, Good Times was brought to life at an AT&T Mobile App Hackathon in January 2013. As one of the first 100 developers to arrive at the hackathon, Ruggero Scorcioni received a pair of Necomimi Cat Ears. Intrigued by the cat ears and deeply immersed in brainstorming, the idea that he would prototype during the 26-hour competition was sparked – a service that would merge the cat ears with AT&T’s Call Management and M2M APIs to automate the prevention of distractions while in deep concentration.
Good Times is currently in the prototype phase and highlights the first step in enabling brain states to control individual environments. Using the $30,000 prize money won at the AT&T hackathon, Scorcioni’s future plans for the prototype include support for headsets with Bluetooth capabilities and the development of more sophisticated algorithms to detect additional brain states. Future developments for this technology may include:
- “Always Allow” Capabilities. This enhancement would ensure calls from important individuals are never missed while still limiting distractions from those not on the “always allow” list.
- Good Tunes. As a natural extension of this technology, future algorithms could enable brainwaves to select the right music to best fit different brain states.
After working for IBM as a Software Architect in the IBM Rome Tivoli Lab, Ruggero Scorcioni moved to the United States where he obtained a Ph.D. in Computational Neuroscience at George Mason University. Before starting brainYno, his first startup, Scorcioni was an Associate Fellow at the Neurosciences Institute in La Jolla, Calif. Scorcioni has attended several AT&T Hackathons where he has met a great community of developers and learned more about the mobile business where he isn’t as familiar.