  Today's information and communication devices provide always-on connectivity,
instant access to an endless repository of information, and represent the most
direct point of contact to almost any person in the world. Despite these
advantages, devices such as smartphones or personal computers lead to the
phenomenon of attention fragmentation, continuously interrupting individuals'
activities and tasks with notifications. Attention management systems aim to
provide active support in such scenarios, managing interruptions, for example,
by postponing notifications to opportune moments for information delivery. In
this article, we review attention management system research with a particular
focus on ubiquitous computing environments. We first examine cognitive theories
of attention and extract guidelines for practical attention management systems.
Mathematical models of human attention are at the core of these systems, and in
this article, we review sensing and machine learning techniques that make such
models possible. We then discuss design challenges towards the implementation
of such systems, and finally, we investigate future directions in this area,
paving the way for new approaches and systems supporting users in their
attention management.
