Adaptive notification framework for converged environments

Arlein, Robert M.; Betgé-Brezetz, Stéphane; Ensor, J. Robert

doi:10.1002/bltj.20311

Cited by 6 publications

(3 citation statements)

References 1 publication

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“…Academia, however, recognized the need for ubiquitous notification management earlier. Arlein et al, for example, proposed a system that can distribute notification across PCs, phones, PDAs and other devices already in 2008 [1]. Previous work, however, either focused on systems for ubiquitous notifications without evaluating the effect or understanding the effects of notifications for specific device types.…”

Section: Introductionmentioning

confidence: 95%

Towards Smart Notifications using Research in the Large

Weber

Shirazi

Henze

2015

Proceedings of the 17th International Conference on Human-Computer Interaction With Mobile Devices and Services Adjunct

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Notifications are a core function of current smart devices. They inform users about a variety of events, such as new messages, comments on social networks posts or application updates. As such, notifications are the main mechanisms to proactively communicate with the user. Focusing on individual device types such as PCs and smartphones, previous work showed that notifications can be distractive and disruptive. The ongoing wave of smart devices makes it possible to reach the user through multiple devices at once -amplifying the effects of notifications. What is missing is an understanding of notifications in a multi-device environment to enable the smart management of notifications across devices. In this paper we present a system that is able to share notifications across smartphones, tablets, PCs, and smart TVs. It can further reach users through connected devices such as smart watches and smart glasses. The system currently distributes 5.3 million notifications by almost 30,000 users every day. It is not only intended to provide a holistic notification mechanism but also serves us to conduct large scale user studies to gain a deeper understanding of notifications in a multi-device environment.

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Section: Introductionmentioning

confidence: 95%

Towards Smart Notifications using Research in the Large

Weber

Shirazi

Henze

2015

Proceedings of the 17th International Conference on Human-Computer Interaction With Mobile Devices and Services Adjunct

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“…Finally, a notification framework architecture was proposed by Arlein et al [13]: it is similar to our system, in fact it allows notifications to be efficiently and effectively distributed and displayed in diverse new environments. However, it is different from our work due to a different approach to the problem.…”

Section: Background and Related Workmentioning

confidence: 99%

A context and user aware smart notification system

Corno

Russis

Montanaro

2015

2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)

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Nowadays, notifications are increasingly gaining momentum in our society. New smart devices and appliances are developed everyday with the ability to generate, send and show messages about their status, acquired data and/or information received from other devices and users. Consequently, the number of notifications received by a user is growing and the tolerance to them could decrease in a short time. This paper presents a smart notification system that uses machine learning algorithms to adequately manage incoming notifications. According to context awareness and user habits, the system decides: a) who should receive an incoming notification; b) what is the best moment to show the notification to the chosen user(s); c) on which device(s) the chosen user(s) should receive the notification; d) which is the best way to notify the incoming notification. After the design of a general architecture, as a first step in building such a system, three different machine learning algorithms were compared in the task of establishing the best device on which the incoming notification should be delivered. The algorithms were applied to a dataset derived from real data provided by the MIT Media Laboratory Reality Mining project, enriched with additional synthetic information.

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“…For this purpose, we propose an adaptive notification enabler that automatically selects -for a wide range of applications-the right delivery mode and optimizes the impact and efficiency of the notified information (Arlein et al, 2008). From semantic information on the notification (e.g., purpose of the notification, topics of the delivered information), this enabler automatically determines when (delivery time), how (delivery channel, display rendering, notification behaviour, terminal behaviour), what (part of content to be displayed) and who (person(s) within a group) will receive the notifications.…”

Section: Adaptive Notification Mechanismmentioning

confidence: 99%

Adaptive Services for Elderly People and Caregivers in ‘Assisted Living’ Homes

Betgé-Brezetz

Dupont

Kamga

et al. 2009

Proceedings of the International Conference on Health Informatics

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This paper presents an innovative medical grade telecommunication system (combining professional and consumer equipments) and its service platform extended with a personalization technology to automatically adapt the services to the end-user disabilities, preferences, and context. This system has been developed in the scope of an 'assisted living' home and several applications have been demonstrated upon it (e.g., activity proposition, reminders, and alerts). Such demonstrations have highlighted the added value of the adaptation technology to enhance the quality of life of elderly people as well as the efficiency of the caregivers' work.

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Adaptive notification framework for converged environments

Cited by 6 publications

References 1 publication

Towards Smart Notifications using Research in the Large

Towards Smart Notifications using Research in the Large

A context and user aware smart notification system

Adaptive Services for Elderly People and Caregivers in ‘Assisted Living’ Homes

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