Staypoint detection from noisy GPS data is harder than previously thought; existing algorithms fail in realistic conditions, but unsupervised and supervised learning methods can substantially improve accuracy.
This paper creates the first large-scale benchmark for staypoint detection—converting raw GPS trajectories into meaningful locations like homes or workplaces.