An IoT data analytics approach for cultural heritage

被引:0
作者
Francesco Piccialli
Paolo Benedusi
Luca Carratore
Giovanni Colecchia
机构
[1] University of Naples Federico II,Department of Electrical Engineering and Information Technology
[2] Databooz Italia s.r.l.,Department of Mathematics and Applications “Renato Caccioppoli”
[3] University of Naples Federico II,Centro Servizi Metrologici e Tecnologici Avanzati (CeSMA)
[4] University of Naples Federico II,undefined
来源
Personal and Ubiquitous Computing | 2020年 / 24卷
关键词
Cultural heritage; Data analytics; Data science; Internet of Things;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:429 / 436
页数:7
相关论文
共 18 条
[1]  
Martella C(2017)Visualizing, clustering, and predicting the behavior of museum visitors Pervasive Mobile Comput 38 430-443
[2]  
Miraglia A(2017)Reviewing automated sensor-based visitor tracking studies: beyond traditional observational methods? Visitor Stud 20 202-217
[3]  
Frost J(2014)An analysis of visitors’ behavior in the louvre museum: a study using bluetooth data Environ Planning B: Plan Des 41 1113-1131
[4]  
Cattani M(2015)The museum experience: mapping the experience of fine art Curator: Museum J 58 169-193
[5]  
Steen M(2009)Timing and tracking: unlocking visitor behavior Visit Stud 12 47-64
[6]  
Mygind L(undefined)undefined undefined undefined undefined-undefined
[7]  
Bentsen P(undefined)undefined undefined undefined undefined-undefined
[8]  
Yoshimura Y(undefined)undefined undefined undefined undefined-undefined
[9]  
Sobolevsky S(undefined)undefined undefined undefined undefined-undefined
[10]  
Ratti C(undefined)undefined undefined undefined undefined-undefined