Understanding the sensing context of raw data is crucial for assessing the quality of large crowdsourced spatio-temporal datasets. Accelerometer’s precision can vary considerably depending on whether the phone is in-pocket or out-pocket, i.e., held …
Understanding the sensing context of raw data is crucial for assessing the quality of large crowdsourced spatio-temporal datasets. Detecting sensing contexts in the wild is a challenging task and requires features from smartphone sensors that are not …
There is a huge body of work that focuses on the understanding of human mobility characteristics utilizing various types of data. These works focus on a spatial scale to extract mobility characteristics. In our work, we study the impact of spatial …
Public transportation is essential for sustainable and economical development of cities. Several transport organizations aim to provide service information to commuters through web and mobile apps. This information includes possible routes between …
Large-scale mobile environments are characterized by, among others, a large number of mobile users, intermittent connectivity and non-homogeneous arrival rate of data to the users, depending on the region's context. Multiple application scenarios in …