Sensors, Interfaces, and Interactive Machine Learning for Music
|Morning||Theoretical background: Overview of different types of sensors, interfaces, and suppliers. The particular case of wireless sensors;|
Hands-on exercises: use the programming environments Arduino and Energia.
|Afternoon||Hands-on exercises : master the basics of programming in Arduino and Energia, first simple examples of coding, uploading code towards the Arduino and R-IoT interfaces.|
|Morning||Theoretical background: introduction to Max, in particular to objects and libraries that can interface with Arduino and R-IoT and to automatic learning/recognition of patterns based on acquired data;|
Hands-on exercises: make Max communicate with the Arduino and R-IoT interfaces.
|Afternoon||Hands-on exercises: recuperate, process, route, and map the data acquired in a sonification system made in Max.|
|Morning||Hands-on exercises: create a sonification system: physiological capture (heart beats, breathing) via sensors connected to the R-IoT interface, recuperation of data and sonification in Max.|
|Afternoon||Theoretical background: Technical description of examples of advanced use of motion capture and gesture recognition in a sonification project and performance art.|