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Supporting Cultural Heritage Preservation Through Game-Based Crowdsourcing

Lazaros Toumanidis (), Enkeleda Bocaj, Panagiotis Kasnesis and Charalampos Z. Patrikakis ()
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Lazaros Toumanidis: University of West Attica
Enkeleda Bocaj: University of West Attica
Panagiotis Kasnesis: University of West Attica
Charalampos Z. Patrikakis: University of West Attica

A chapter in Strategic Innovative Marketing and Tourism, 2019, pp 989-997 from Springer

Abstract: Abstract It has been decades since the research community has put efforts into combining human and machine intelligence. With the rapidly surging of mobile sensing, gamification techniques have contributed on making the crowd-sourcing computing techniques a promising paradigm for large-scale data sensing. In this paper, starting from a study of gamification and crowd-sourcing techniques, we present an alternative way of combining gamification techniques with crowd-sourcing in order to preserve cultural heritage sites. The proposed application is a scavenger hunt like game where the players have to complete a series of tasks in the form of riddles. Each task may include sending the location of the user, answering a question, uploading media files or annotating some image or audio files related to the pace of visit. Except from empirical input which comes from the experts, our approach collects external data, engaging the sightseeing visitors with sensing and computing devices collectively share data, related to site’s or monument’s physical structure condition. The collected data are clustered together by archaeological site location and used in machine learning to extract information about the physical condition of the cultural heritage site. Through the application’s results, the experts will take the appropriate decisions in order to estimate and predict if there is any need of intervention to maintain the archaeological site or monument in good condition.

Keywords: Crowd-sensing; Gamification; Cultural heritage; Machine learning (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/978-3-030-12453-3_114

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