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An IoT data analytics approach for cultural heritage

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Abstract

The ability to integrate, manage, and analyze large amounts of data extracted from different sources is becoming a key asset for businesses, organizations, and research institutions that deal with the cultural heritage domain. Nowadays, it is well known that modern technologies and the massive use of mobile devices can contribute to generate an enormous flow of data, whose collection, analysis, and interpretation allows for real-time analysis related to the behaviors, preferences, and opinions of users. In this paper, we present and discuss a data analytics approach relying on an Internet of Things framework. The main goal is to assess how the collection of behavioral IoT data coming from the cultural heritage domain can be opportunely exploited by means of data science and data analytics techniques in order to produce useful insights. Experimental results performed in a real case study demonstrate how the cultural heritage domain, and the related stakeholders, can benefit from these kind of applications.

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Acknowledgments

This work was supported by the Cultural Equipment with Transmedial Recommendation Analytics - C.E.T.R.A. research project [Regione Campania - Bando RIS3 2018 - Fase 2]. We also thank to the High Technology District for Cultural Heritage - DATABENC (http://www.databenc.it) and Databooz Italia srl company for the support.

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Authors and Affiliations

  1. Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy

    Francesco Piccialli

  2. Databooz Italia s.r.l., Naples, Italy

    Paolo Benedusi

  3. Department of Mathematics and Applications “Renato Caccioppoli”, University of Naples Federico II, Naples, Italy

    Luca Carratore

  4. Centro Servizi Metrologici e Tecnologici Avanzati (CeSMA), University of Naples Federico II, Naples, Italy

    Giovanni Colecchia

Authors
  1. Francesco Piccialli
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  2. Paolo Benedusi
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  3. Luca Carratore
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  4. Giovanni Colecchia
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Correspondence to Francesco Piccialli.

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Piccialli, F., Benedusi, P., Carratore, L. et al. An IoT data analytics approach for cultural heritage. Pers Ubiquit Comput 24, 429–436 (2020). https://doi.org/10.1007/s00779-019-01323-z

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  • DOI: https://doi.org/10.1007/s00779-019-01323-z

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