Energy Modeling and Architecture Exploration for Emotion Detection Systems

Energy consumption is one of the main constraints which are faced by designers of communicating objects. Indeed, we are seeing a real increase in the number of communicating objects ranging from customer applications (video games, health care objects) to industrial applications (M2M, automatic car parking, drones). This paper presents a new high level model of autonomy estimation for wearable communicating objects, and more particularly for emotion detection systems and a design space exploration. The innovation in this methodology is to meet the autonomy constraint of health objects while maintaining a reasonable performance which is defined by the emotion recognition rate. The influence of the architecture (RF protocol, kind and number of sensors, ) and its configuration of the system autonomy and emotion recognition rate is studied in order to propose the most suitable system. The different results show that we can get a high recognition rate and a sufficient autonomy for users.