The ambient intelligence paradigm involves one important challenge: to be adaptive to users and context through simple and natural interactions. To meet this goal, it is important to associate data with relevant everyday objects in the environment, including users themselves, and to enable interaction mechanisms between these objects. Following this premise, in this paper, we present a conceptual model to link contextual information with augmented elements acquired from user interactions in an implicit and transparent way. In this way, it is possible to personalize and enhance offered services in order to facilitate daily user activities. We call this contextual data awareness marks, and these awareness marks make it possible to offer novel services adapted from past events that were captured as they happened. Moreover, we have developed and evaluated a set of prototypes using Near Field Communication technology, which follows the presented model.
%0 Journal Article
%1 HervasBravoFontecha11puc
%A Hervás, Ramón
%A Bravo, José
%A Fontecha, Jesús
%D 2011
%J Personal and Ubiquitous Computing
%K v1205 springer paper embedded ai user interface interaction adaptive service design zzz.spm
%N 4
%P 409-418
%R 10.1007/s00779-010-0363-z
%T Awareness Marks: Adaptive Services through User Interactions with Augmented Objects
%V 15
%X The ambient intelligence paradigm involves one important challenge: to be adaptive to users and context through simple and natural interactions. To meet this goal, it is important to associate data with relevant everyday objects in the environment, including users themselves, and to enable interaction mechanisms between these objects. Following this premise, in this paper, we present a conceptual model to link contextual information with augmented elements acquired from user interactions in an implicit and transparent way. In this way, it is possible to personalize and enhance offered services in order to facilitate daily user activities. We call this contextual data awareness marks, and these awareness marks make it possible to offer novel services adapted from past events that were captured as they happened. Moreover, we have developed and evaluated a set of prototypes using Near Field Communication technology, which follows the presented model.
@article{HervasBravoFontecha11puc,
abstract = {The ambient intelligence paradigm involves one important challenge: to be adaptive to users and context through simple and natural interactions. To meet this goal, it is important to associate data with relevant everyday objects in the environment, including users themselves, and to enable interaction mechanisms between these objects. Following this premise, in this paper, we present a conceptual model to link contextual information with augmented elements acquired from user interactions in an implicit and transparent way. In this way, it is possible to personalize and enhance offered services in order to facilitate daily user activities. We call this contextual data awareness marks, and these awareness marks make it possible to offer novel services adapted from past events that were captured as they happened. Moreover, we have developed and evaluated a set of prototypes using Near Field Communication technology, which follows the presented model.},
added-at = {2012-05-30T10:47:35.000+0200},
author = {Herv\'{a}s, Ram\'{o}n and Bravo, Jos\'{e} and Fontecha, Jes\'{u}s},
biburl = {https://www.bibsonomy.org/bibtex/2efb8231f35a67b97bd9310ce38094d76/flint63},
doi = {10.1007/s00779-010-0363-z},
file = {SpringerLink:2011/HervasBravoFontecha11puc.pdf:PDF},
groups = {public},
interhash = {195231b891dacc442065cb5325501df2},
intrahash = {efb8231f35a67b97bd9310ce38094d76},
issn = {1617-4909},
journal = {Personal and Ubiquitous Computing},
keywords = {v1205 springer paper embedded ai user interface interaction adaptive service design zzz.spm},
month = {#apr#},
number = 4,
pages = {409-418},
timestamp = {2018-04-16T11:59:05.000+0200},
title = {Awareness Marks: Adaptive Services through User Interactions with Augmented Objects},
username = {flint63},
volume = 15,
year = 2011
}