Design of Cloud-Based Real-Time Eye-Tracking Monitoring and Storage System

Basit Öğe Kaydı
dc.WoS.categoriesComputer Science, Artificial IntelligenceComputer Science, Theory & Methodsen_US
dc.authorid0009-0005-0931-4190en_US
dc.contributor.authorGürsesli, Mustafa Can
dc.contributor.authorSelek, Mehmet Emin
dc.contributor.authorSamur, Mustafa Oktay
dc.contributor.authorDuradoni, Mirko
dc.date.accessioned2024-04-15T13:47:20Z
dc.date.available2024-04-15T13:47:20Z
dc.date.issued2023-08-06
dc.description.abstractThe rapid development of technology has led to the implementation of data-driven systems whose performance heavily relies on the amount and type of data. In the latest decades, in the field of bioengineering data management, among others, eye-tracking data have become one of the most interesting and essential components for many medical, psychological, and engineering research applications. However, despite the large usage of eye-tracking data in many studies and applications, a strong gap is still present in the literature regarding real-time data collection and management, which leads to strong constraints for the reliability and accuracy of on-time results. To address this gap, this study aims to introduce a system that enables the collection, processing, real-time streaming, and storage of eye-tracking data. The system was developed using the Java programming language, WebSocket protocol, and Representational State Transfer (REST), improving the efficiency in transferring and managing eye-tracking data. The results were computed in two test conditions, i.e., local and online scenarios, within a time window of 100 seconds. The experiments conducted for this study were carried out by comparing the time delay between two different scenarios, even if preliminary results showed a significantly improved performance of data management systems in managing real-time data transfer. Overall, this system can significantly benefit the research community by providing real-time data transfer and storing the data, enabling more extensive studies using eye-tracking data.en_US
dc.fullTextLevelFull Texten_US
dc.identifier.doi10.3390/a16070355
dc.identifier.issn1999-4893
dc.identifier.scopus2-s2.0-85166378361en_US
dc.identifier.urihttps://hdl.handle.net/11411/5257
dc.identifier.urihttps://doi.org/10.3390/a16070355
dc.identifier.wosWOS:001034738300001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.issue7en_US
dc.language.isoenen_US
dc.nationalInternationalen_US
dc.numberofauthors6en_US
dc.publisherMDPIen_US
dc.relation.ispartofALGORITHMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectdata managementen_US
dc.subjectcloud computingen_US
dc.subjectRESTful APIen_US
dc.subjecteye trackingen_US
dc.subjectweb portalen_US
dc.titleDesign of Cloud-Based Real-Time Eye-Tracking Monitoring and Storage System
dc.typeArticle
dc.volume16en_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
2023WosSamur.pdf
Boyut:
669.99 KB
Biçim:
Adobe Portable Document Format
Açıklama:
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.71 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Faculty of Engineering and Natural Sciences
Scopus Indexed Publications
Web of Science Indexed Publications