Happy hour - improving mood with an emotionally aware application

Mobile sensing in Cyber-Physical Systems has been evolving proportionally with smartphones. In fact, we are witnessing a tremendous increase in systems that sense various facets of human beings and their surrounding environments. In particular, the detection of human emotions can lead to emotionally-aware applications that use this information to benefit people's daily lives. This work presents the implementation of a Human-inthe- loop emotionally-aware Cyber-Physical System that attempts to positively impact its user's mood through moderate walking exercise. Data from smartphone sensors, a smartshirt's electrocardiogram and weather information from a web API are processed through a machine learning algorithm to infer emotional states. When negative emotions are detected, the application timely suggests walking exercises, while providing real-time information regarding nearby points of interest. This information includes events, background music, attendance, agitation and general mood. In addition, the system also dynamically adapts privacy and networking configurations based on emotions. The sharing of the user's location on social networks and the device's networking interfaces are configured according to user-defined rules in order to reduce frustration and provide a better Quality of Experience.