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smArt: Open and Interactive Indoor Cultural Data

Published: 13 October 2015 Publication History

Abstract

In this demo we present smArt, a low-cost framework to quickly set up indoor exhibits featuring a smart navigation system for museums. The framework is web-based and allows the design on a digital map of a sensorized museum environment and the dynamic and assisted definition of the multimedia materials and sensors associated to the artworks. The knowledge-base uses semantic technologies and it is exploited by museum visitors to get directions and to have multimedia insights in a natural way. Indoor localisation and routing is provided taking advantage of active and passive sensors advertisements and user interactions. In this way we overcome the Global Positioning System (GPS) unavailability issue in indoor environments.

Reference

[1]
P. Martin, B.-J. Ho, N. Grupen, S. Munoz, and M. Srivastava. An ibeacon primer for indoor localization: Demo abstract. In Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings, BuildSys '14, pages 190--191, New York, NY, USA, 2014. ACM.

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cover image ACM Conferences
MM '15: Proceedings of the 23rd ACM international conference on Multimedia
October 2015
1402 pages
ISBN:9781450334594
DOI:10.1145/2733373
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 October 2015

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Author Tags

  1. beacon
  2. cultural heritage
  3. museum guide
  4. open linked data
  5. sensors
  6. web applications

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  • Demonstration

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MM '15
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MM '15: ACM Multimedia Conference
October 26 - 30, 2015
Brisbane, Australia

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MM '15 Paper Acceptance Rate 56 of 252 submissions, 22%;
Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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