A Generic Approach for Energy Efficient Context Recognition Using Smart Phones

Abstract

Intelligent environments rely on context information for providing services to their users. Among various existing platforms for context recognition, smart phones are one of the most widely used. However, despite numerous advantages, smart phones exhibit limited energy resources. To mitigate this there exist approaches for energy efficient context recognition for smart phones but these approaches are usually fine-tuned for specific types of context. As a result their applicability to other context types is limited. In this paper, we present an energy efficient context recognition system for smart phones which provides generalized applicability of four generic energy efficiency techniques which have been described in the literature and applied to location sensing using mobile phones. These four techniques as termed by authors include Suppression, Substitution, Adaptation and Piggybacking. Our system provides their generalized applicability by modelling context recognition applications using a state machine abstraction. Consequently the resulting applications are structured as combinations of states and transitions. To aid rapid prototyping our system is equipped with an off-line development tool which allows the creation and (code) generation of state machines using a graphical editor. We evaluate our system by creating a test application. Using a precise hardware set up, we perform energy measurements to demonstrate the energy savings of these different techniques.