2016
DOI: 10.4018/ijegr.2016040103
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A Location-Aware Architecture for an IoT-Based Smart Museum

Abstract: The Internet of Things, whose main goal is to automatically predict users' desires, can find very interesting opportunities in the art and culture field, as the tourism is one of the main driving engines of the modern society. Currently, the innovation process in this field is growing at a slower pace, so the cultural heritage is a prerogative of a restricted category of users. To address this issue, a significant technological improvement is necessary in the culture-dedicated locations, which do not usually a… Show more

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Cited by 11 publications
(11 citation statements)
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References 31 publications
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“…Liu, Huang, et al (2019), Chao and Lai (2015) Content analysis To analyse tourists' behaviour, experience, evaluations and satisfaction Park et al (2019) Content analysis To analyse campaigns using certain hashtag or terms Tang and Li (2016) Social network analysis To analyse the relationship network and evaluate the network structure through a series of indicators Onder (2017), Loaiza et al (2019) Semantic-based natural language data mining To compare tourists' expectations and real experiences and to assess contrasts between tourists' expectations and service providers' based on SNS content Accordingly, an IoT-based system for the smart museum was implemented to provide the user with a real interactive experience specifically for personalized navigation. By utilizing BLE (Bluetooth low energy) and computer vision techniques, tourists can obtain information related to the artworks (Fiore et al, 2016). Finally, by applying AI techniques to an Integrated Urban Tourism called Puglia Project, an e-tourism application so-called Semantic Web was developed.…”
Section: Content Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…Liu, Huang, et al (2019), Chao and Lai (2015) Content analysis To analyse tourists' behaviour, experience, evaluations and satisfaction Park et al (2019) Content analysis To analyse campaigns using certain hashtag or terms Tang and Li (2016) Social network analysis To analyse the relationship network and evaluate the network structure through a series of indicators Onder (2017), Loaiza et al (2019) Semantic-based natural language data mining To compare tourists' expectations and real experiences and to assess contrasts between tourists' expectations and service providers' based on SNS content Accordingly, an IoT-based system for the smart museum was implemented to provide the user with a real interactive experience specifically for personalized navigation. By utilizing BLE (Bluetooth low energy) and computer vision techniques, tourists can obtain information related to the artworks (Fiore et al, 2016). Finally, by applying AI techniques to an Integrated Urban Tourism called Puglia Project, an e-tourism application so-called Semantic Web was developed.…”
Section: Content Analysismentioning
confidence: 99%
“…Second, a design of a no-invasive indoor location-aware architecture, which improves the user experience in a museum, in Lecce (Italy) (Fiore et al, 2016). An IoT-based system for smart tourism services has been implemented towards smart museum navigation which improves visitor's cultural experience (Fiore et al, 2016).…”
Section: Smart Tourismmentioning
confidence: 99%
“…In addition to offering information or knowledge about the exhibits, ICT can provide openaccess personalized, flexible, immersive, interactive and virtual tours and experiences of GLAMs, but also sharing options before, during and after the visit. In culture, digital accessibility needs to be inclusive in order to reach wider audiences [37], [38]. Digital accessibility overcomes barriers of physical presence, which is substituted by online presence [37].…”
Section: Literature Reviewmentioning
confidence: 99%
“…A non-invasive indoor location-aware architecture was used to enhance the user experience in the museum. The system can be used from smartphones or wearable devices to retrieve the desired cultural content [38], [58].…”
Section: Smart Culture -Good Practice Examples and Underlying Tecmentioning
confidence: 99%
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