Sifting through the Rubble of Big Data for the Human Face of Mobile

No ratings

Presented at AsiaARES 2014 by

Ismail Khalil

As the landscape around Big data continues to exponentially evolve, the « big » facet of Big data is no more number one priority of researchers and IT professionals. The race has recently become more about how to sift through torrents of data to find the hidden diamond and engineer a better, smarter and healthier world. The ease with which our mobile captures daily data about ourselves makes it an exceptionally suitable means for ultimately improving the quality of our lives and gaining valuable insights into our affective, mental and physical state. This talk takes the first exploratory step into this direction by presenting motivating cases, discussing research directions and describing how to use mobiles to process and analyze the “digital exhaust” it collects about us to automatically recognize our emotional states and automatically respond to them in the most effective and “human” way possible. To achieve this we treat all theoretical, technical, psycho-somatic, and cognitive aspects of emotion observation and prediction, and repackage all these elements into a mobile multimodal emotion recognition system that can be used on any mobile device.