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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/ProceedingsConference contribution

Published
Publication date2/06/2016
Host publicationProceedings of the 3rd International Workshop on Physical Analytics
Place of PublicationNew York
PublisherACM
Pages19-24
Number of pages6
ISBN (Electronic)9781450343282
<mark>Original language</mark>English

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.

Bibliographic note

© {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