Energy-efficient context-aware software design for Ambient Assisted Living applications

The functionality of connected resource-limited body-worn sensors and smart-home devices in an ambient-assisted living scenario is usually hard-coded and generic, never being optimal to different contexts. Context-aware software design permits optimizations specific to scenarios and provides energy savings. Using this principle, this thesis proposes an adaptive compression algorithm for vital signal acquisition, and a middleware architecture for smart-home devices, in which the primary goal is the energy efficiency.