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  • Next Generation Physical Analytics for Digital Signage

    Rights statement: © {Owner/Author ACM}, 2016. 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 Proceedings of the 3rd International Workshop on Physical Analytics http://dx.doi.org/10.1145/2935651.2935658

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Next generation physical analytics for digital signage

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Next generation physical analytics for digital signage. / Mikusz, Mateusz Andrzej; Noulas, Anastasios; Davies, Nigel et al.
Proceedings of the 3rd International Workshop on Physical Analytics. New York: ACM, 2016. p. 19-24.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Mikusz, MA, Noulas, A, Davies, N, Clinch, S & Friday, A 2016, Next generation physical analytics for digital signage. in Proceedings of the 3rd International Workshop on Physical Analytics. ACM, New York, pp. 19-24. https://doi.org/10.1145/2935651.2935658

APA

Vancouver

Mikusz MA, Noulas A, Davies N, Clinch S, Friday A. Next generation physical analytics for digital signage. In Proceedings of the 3rd International Workshop on Physical Analytics. New York: ACM. 2016. p. 19-24 doi: 10.1145/2935651.2935658

Author

Mikusz, Mateusz Andrzej ; Noulas, Anastasios ; Davies, Nigel et al. / Next generation physical analytics for digital signage. Proceedings of the 3rd International Workshop on Physical Analytics. New York : ACM, 2016. pp. 19-24

Bibtex

@inproceedings{08d7c5181aec42cc86f225768550c53e,
title = "Next generation physical analytics for digital signage",
abstract = "Traditional digital signage analytics are based on a display-centric view of the world, reporting data on the content shown augmented with frequency of views and possibly classification of the audience demographics. What these systems are unable to provide, are insights into viewers' overall experience of content. This is problematic if we want to understand where, for example, to place content in a network of physically distributed digital signs to optimise content exposure. In this paper we propose a new approach that combines mobility simulations with comprehensive signage analytics data to provide viewer-centric physical analytics. Our approach enables us to ask questions of the analytics from the viewer's perspective for the first time, including estimating the exposure of different user groups to specific content across the entire signage network. We describe a proof of concept implementation that demonstrates the feasibility of our approach, and provide an overview of potential applications and analytics reports.",
author = "Mikusz, {Mateusz Andrzej} and Anastasios Noulas and Nigel Davies and Sarah Clinch and Adrian Friday",
note = "{\textcopyright} {Owner/Author ACM}, 2016. 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 Proceedings of the 3rd International Workshop on Physical Analytics http://dx.doi.org/10.1145/2935651.2935658",
year = "2016",
month = jun,
day = "2",
doi = "10.1145/2935651.2935658",
language = "English",
pages = "19--24",
booktitle = "Proceedings of the 3rd International Workshop on Physical Analytics",
publisher = "ACM",

}

RIS

TY - GEN

T1 - Next generation physical analytics for digital signage

AU - Mikusz, Mateusz Andrzej

AU - Noulas, Anastasios

AU - Davies, Nigel

AU - Clinch, Sarah

AU - Friday, Adrian

N1 - © {Owner/Author ACM}, 2016. 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 Proceedings of the 3rd International Workshop on Physical Analytics http://dx.doi.org/10.1145/2935651.2935658

PY - 2016/6/2

Y1 - 2016/6/2

N2 - Traditional digital signage analytics are based on a display-centric view of the world, reporting data on the content shown augmented with frequency of views and possibly classification of the audience demographics. What these systems are unable to provide, are insights into viewers' overall experience of content. This is problematic if we want to understand where, for example, to place content in a network of physically distributed digital signs to optimise content exposure. In this paper we propose a new approach that combines mobility simulations with comprehensive signage analytics data to provide viewer-centric physical analytics. Our approach enables us to ask questions of the analytics from the viewer's perspective for the first time, including estimating the exposure of different user groups to specific content across the entire signage network. We describe a proof of concept implementation that demonstrates the feasibility of our approach, and provide an overview of potential applications and analytics reports.

AB - Traditional digital signage analytics are based on a display-centric view of the world, reporting data on the content shown augmented with frequency of views and possibly classification of the audience demographics. What these systems are unable to provide, are insights into viewers' overall experience of content. This is problematic if we want to understand where, for example, to place content in a network of physically distributed digital signs to optimise content exposure. In this paper we propose a new approach that combines mobility simulations with comprehensive signage analytics data to provide viewer-centric physical analytics. Our approach enables us to ask questions of the analytics from the viewer's perspective for the first time, including estimating the exposure of different user groups to specific content across the entire signage network. We describe a proof of concept implementation that demonstrates the feasibility of our approach, and provide an overview of potential applications and analytics reports.

U2 - 10.1145/2935651.2935658

DO - 10.1145/2935651.2935658

M3 - Conference contribution/Paper

SP - 19

EP - 24

BT - Proceedings of the 3rd International Workshop on Physical Analytics

PB - ACM

CY - New York

ER -