We, a group of students from the Amsterdam University of Applied Science, are doing research on improving the attention towards public screens by using Computer Vision techonlogy.

We have a physical setup at our local university building with a screen and a webcam. VANturelabs has provided us with audience measurement software running on the setup. Skynet listens to this system and uses this to:

1. Adapt the content on the screen in realtime to the audience.
2. Gather statistics of the attention of the audience.

Skynet consists of a (nodejs) server application and a (webbased) client application which listens to the server for when to display what kind of content. The content used in our tests where user generated Vine videos.

The server consists of a couple of things:

• A websocket communication with the clients to (see server/socket.js):
  • tell the client the segment it needs to play (adaptive content)
  • listen to which video the client has picked to store in a database.
• A webserver which the Audience Measurement uses to let skynet know who is in front of the camera (see server/app.js).
• A datastore (in redis) to store counters of how many people pass by the screen
• A database (mongo) to store complex data like how many people stood in front of the screen during which Vine, and how long the looked towards the screen. (see server/mongoose.js).
• A small API which the dashboard uses to retrieve data from the database. (see server/api.js).

MIT