Symbiotic Construction of Individual's Rich Location Dataset

Sensing our daily activities is essential for ubiquitous computing. Although smartphones and wearable devices can easily collect their owner's data, continuous sensing causes battery drain and consumes CPU power of those devices. This paper proposes a brand new framework utilizing the symbiotic construction of an individual's location dataset, one of the most typical daily activities, by combining infrequent sensed location logs of serendipitously nearby users including strangers. The proposed method estimates the location where the user was using other users' sensed sparse location logs. The user can obtain his/her detailed dense location history without increasing sensing frequency and CPU load of his/her device compared to those for normal daily use. Experimental results show a rich location dataset of the user can be estimated.