Search

Ubiquitous Monitoring (UM) describes the continuous collection of data on a large scale, enabled by embedded, mobile, wireless, and sensory technologies [1]. This data will enable the envisioned applications of Ubiquitous Computing. Research has shown that monitoring can affect user behavior [2], which is problematic for ubiquitous computing because the data collected may not fully reflect the reality. Hence, any services provided may not fully align with user expectations or needs. One proposed solution is the use of deterministic models to predict the behaviors of users prior to deployment, reducing the undesirable effects of monitoring. The Perceptions of System Attributes?Behavioral Intention (PSA-BI) model was specifically designed for this purpose [1]. While the model has been validated, the moderating effect of culture has not yet been explored. As such, we present here results from a study carried out in the U.K. exploring the relationships in the PSA-BI model. This is then compared with a structural model from a previous study in Japan [3], [4], allowing us to explore any potential differences and similarities. [ABSTRACT FROM PUBLISHER]

Aworld of ubiquitous computing, full of networked mobile and embedded technologies, is approaching. The benefits of this technology are numerous, and act as the major driving force behind its development. These benefits are brought about, in part, by ubiquitous monitoring (UM): the continuous and wide spread collection of ?significant amounts of data about users [1]. [ABSTRACT FROM AUTHOR]