Dynamic Adaptation of Opportunistic Sensor Configurations for Continuous and Accurate Activity Recognition

An ever-larger availability of devices that are attached with different sensing capabilities (e.g., smart phones) shifted the challenge in activity and context recognition from the application specific deployment of new sensors to the utilization of already available devices. Therefore, a system that operates in an opportunistic way has to take advantage of the currently available sensing infrastructure in terms of utilizing sensors in form of ensembles that are best suited to execute a specific activity recognition task. Continuous, stable, and accurate activity recognition can be assured if such a system is able to react in real-time to such dynamics in the sensing infrastructure. In detail, this paper tackles the characteristic application cases where sensors spontaneously appear, disappear and reappear in the sensing infrastructure and evaluates the continuousness and stability of the self-adaption methods within the OPPORTUNITY Framework, which is a reference implementation of an opportunistic activity and context recognition system.