A Survey of Attention Management Systems in Ubiquitous Computing Environments

@article{Anderson2018ASO,
  title={A Survey of Attention Management Systems in Ubiquitous Computing Environments},
  author={Christoph Anderson and Isabel Fernanda H{\"u}bener and Ann-Kathrin Seipp and Sandra Ohly and Klaus David and Veljko Pejovi{\'c}},
  journal={Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},
  year={2018},
  volume={2},
  pages={1 - 27}
}
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. [] Key Method 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…

Figures and Tables from this paper

Toward Cognitive Load Inference for Attention Management in Ubiquitous Systems
TLDR
The achievements toward enabling large-scale unobtrusive cognitive load inference are presented, which rely on mining sensor data collected by commodity wearable devices, and software-defined radio-based wireless radars.
UbiTtention 2017: 2nd international workshop on smart & ambient notification and attention management
TLDR
The UbiTtention 2017 workshop brings together researchers and practitioners from academy and industry to explore the managements of human attention and notifications, and considers versatile devices and smart situations to overcome information overload and overchoice.
Wireless Ranging for Contactless Cognitive Load Inference in Ubiquitous Computing
TLDR
Wi-Mind is a system for remote cognitive load assessment through wireless sensing based on a software-defined radio radar that measures sub-millimeter movements related to a person’s breathing and heart beats, which allows the system to infer the person's cognitive load.
UbiTtention 2019: 4th international workshop on smart & ambient notification and attention management
TLDR
The UbiTtention 2019 workshop brings together researchers and practitioners from academia and industry to explore the management of human attention and notifications across versatile devices and contexts to overcome information overload and over-choice.
Attention computing: overview of mobile sensing applied to measuring attention
TLDR
This paper argues how attention levels can be effectively measured with existing technologies and methodologies by adapting continuous measurements of attention fluctuations and invites co-researchers to assess the use of novel ways to measure attention in their future endeavours.
Interrupting Drivers for Interactions
TLDR
This work aims to develop a machine learning model that can find opportune moments for the driver to engage in proactive auditory-verbal tasks by using the vehicle and environment sensor data and iteratively develops the experimental framework through an extensive literature review and four pilot studies.
Where am I? Predicting user location semantics from engagement with smartphone notifications
TLDR
It is demonstrated that it is possible to semantically label a user’s location based on their notification handling behaviour, even when location coordinates are obfuscated so as not to precisely match known venue locations, and that Places API data can only be reliably used for some venue categories.
Interrupting Drivers for Interactions: Predicting Opportune Moments for In-vehicle Proactive Auditory-verbal Tasks
TLDR
This work aims to develop a machine learning model that can find opportune moments for the driver to engage in proactive auditory-verbal tasks by using the vehicle and environment sensor data and iteratively develops the experimental framework through an extensive literature review and four pilot studies.
Trading energy for accuracy in mobile interruptiblity inference
TLDR
An interruptiblity management systems that uses the classifier confidence as a knob allowing fine-grain tuning along the trade-off front, thus enabling user- and application- specific energy-optimal interruptibility management.
Can you Turn it Off?
TLDR
It is shown that perceptions of disturbance are strongly related to the social norms surrounding the place, such as whether the place is considered private or public, even when controlling for the number of people around the user.
...
...

References

SHOWING 1-10 OF 135 REFERENCES
Designing content-driven intelligent notification mechanisms for mobile applications
TLDR
This paper presents a study of mobile user interruptibility with respect to notification content, its sender, and the context in which a notification is received, and shows that classifiers lead to a more accurate prediction of users' interruptibility than an alternative approach based on user-defined rules of their own interruptibility.
Interruptibility prediction for ubiquitous systems: conventions and new directions from a growing field
TLDR
A meta-analysis of this area is presented, decomposing and comparing historical and recent works that seek to understand and predict how users will perceive and respond to interruptions to identify research gaps, questions and opportunities that characterise this important emerging field for pervasive technology.
Attention and engagement-awareness in the wild: A large-scale study with adaptive notifications
TLDR
The results show that in most cases delaying the notification delivery until an interruptible moment is detected is beneficial to users and results in significant reduction of user response time compared to delivering the notifications immediately.
A Cloud-based Interaction Management System Architecture for Mobile Devices
Multimodal estimation of user interruptibility for smart mobile telephones
TLDR
This work learns the structure and parameters of a user state model from continuous ambient audio and visual information from periodic still images, and attempts to associate the learned states with user-reported interruptibility levels.
Reducing users' perceived mental effort due to interruptive notifications in multi-device mobile environments
TLDR
Attelia II is proposed, a novel middleware that identifies breakpoints in users' lives while using those devices, and delivers notifications at these moments, and results in a 71.8% greater reduction of users' perception of workload, compared with the previous system that used UI events only.
A Mobile Intelligent Interruption Management System
TLDR
The architecture of a system named Mobile Intelligent Interruptions Management (MIIM), created for the automated administration of personal unavailability with regard to cell phones, is proposed and Simulation and evaluation results show that its computational volumes are low enough for a mobile device.
Attelia: sensing user's attention status on smart phones
TLDR
Attelia is 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.
An IoT infrastructure for ubiquitous notifications in intelligent living environments
TLDR
An infrastructure for homes and offices that enables designers and web-developers to design and deploy context sensitive notification strategies using arbitrary connected things and smart home products such as TVs, tablets, projections, lamps, speakers and many more is introduced.
Using context-aware computing to reduce the perceived burden of interruptions from mobile devices
TLDR
A context-aware mobile computing device was developed that automatically detects postural and ambulatory activity transitions in real time using wireless accelerometers and was used to experimentally measure the receptivity to interruptions delivered at activity transitions relative to those delivered at random times, suggesting a viable strategy forcontext-aware message delivery in sensor-enabled mobile computing devices.
...
...