Tadashi Okoshi, Hideyuki Tokuda, Jin Nakazawa
2014 Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct Publication - UbiComp '14 Adjunct  
In progressing ubiquitous computing where number of devices, applications and the web services are ever increasing, human user's attention is a new bottleneck in computing. This paper proposes Attelia, a novel middleware that senses user's attention status on user's smart phones in real-time, without any dedicated psycho-physiological sensors. To find better delivery timings of interruptive notifications from various applications and services to mobile users, Attelia detects breakpoint[16] of
more » ... er's activity on the smart phones, with our novel "Application as a Sensor"(AsaS) approach and machine learning technique. Our initial evaluation of Attelia shows it can detect breakpoints of users with accuracy of 80-90%. user's "attention" remains unchanged while amount of information provided has been increasing in emerging ubiquitous computing age. The number of versatile networked devices, including user's carrying mobile devices, embedded sensors, or so-called "IoT" devices have been ever increasing [9, 6] . Also the number of used applications, web services, and communication channels for users are increasing based on the technological advancement of rapid software/service development, deployment, and distribution. Given such backgrounds, limited resource of human attention is the new bottleneck[7] in computing. From the view point of the human users, these excessive amount of provided information is often called "information overload" in a broad sense. Particularly in this research, we will focus on interruption overload, distraction for users caused by interruptions based on excessive amount and inappropriate delivery of notifications from computing systems.
doi:10.1145/2638728.2638802 dblp:conf/huc/OkoshiTN14 fatcat:2yrtffgvdbfyjatpydncp6ckvy