Rights statement: © ACM, 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in UbiComp '17 Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers http://dx.doi.org/10.1145/3123024.3124559
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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Symbiotic attention management in the context of internet of things
AU - Jalaliniya, Shahram
AU - Pederson, Thomas
AU - Mardanbegi, Diako
N1 - © ACM, 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in UbiComp '17 Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers http://dx.doi.org/10.1145/3123024.3124559
PY - 2017/9/11
Y1 - 2017/9/11
N2 - In this position paper we stress the need for considering the nature of human attention when designing future potentially interruptive IoT and propose to let IoT devices share attention-related data and collaborate on the task of drawing human attention in order to achieve higher quality attention management with less overall system resources. Finally, we categorize some existing strategies for drawing people's attention according to a simple symbiotic (human-machine) attention management framework.
AB - In this position paper we stress the need for considering the nature of human attention when designing future potentially interruptive IoT and propose to let IoT devices share attention-related data and collaborate on the task of drawing human attention in order to achieve higher quality attention management with less overall system resources. Finally, we categorize some existing strategies for drawing people's attention according to a simple symbiotic (human-machine) attention management framework.
U2 - 10.1145/3123024.3124559
DO - 10.1145/3123024.3124559
M3 - Conference contribution/Paper
SN - 9781450351904
SP - 941
EP - 946
BT - UbiComp '17 Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
PB - ACM
CY - New York
ER -