In this paper, we aim at answering the question "at what frequency should one sample individual human movements so that they can be reconstructed from the collected samples with minimum loss of information?". Our quest for a response unveils (i) seemingly universal spectral properties of human mobility, and (ii) a linear scaling law of the localization error with respect to the sampling interval. We conduct analyses using fine-grained GPS trajectories of 119 users worldwide. Our findings have potential applications in ubiquitous computing and mobile service design, in terms of energy efficiency, location-based service operations, active probing of subscribers' positions in mobile networks and trajectory data compression.

On the Sampling Frequency of Human Mobility

Marco Fiore;Alberto Tarable
2017

Abstract

In this paper, we aim at answering the question "at what frequency should one sample individual human movements so that they can be reconstructed from the collected samples with minimum loss of information?". Our quest for a response unveils (i) seemingly universal spectral properties of human mobility, and (ii) a linear scaling law of the localization error with respect to the sampling interval. We conduct analyses using fine-grained GPS trajectories of 119 users worldwide. Our findings have potential applications in ubiquitous computing and mobile service design, in terms of energy efficiency, location-based service operations, active probing of subscribers' positions in mobile networks and trajectory data compression.
2017
Sampling; human mobility; spatial data
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/335877
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