OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 15.03.2026, 17:09

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

Cloud-Based Digital Twins’ Storage in Emergency Healthcare

2023·25 Zitationen·˜The œInternational journal of networked and distributed computingOpen Access
Volltext beim Verlag öffnen

25

Zitationen

3

Autoren

2023

Jahr

Abstract

Abstract In a medical emergency situation, real-time patient data sharing may improve the survivability of a patient. In this paper, we explore how Digital Twin (DT) technology can be used for real-time data storage and processing in emergency healthcare. We investigated various enabling technologies, including cloud platforms, data transmission formats, and storage file formats, to develop a feasible DT storage solution for emergency healthcare. Through our analysis, we found Amazon AWS to be the most suitable cloud platform due to its sophisticated real-time data processing and analytical tools. Additionally, we determine that the MQTT protocol is suitable for real-time medical data transmission, and FHIR is the most appropriate medical file storage format for emergency healthcare situations. We propose a cloud-based DT storage solution, in which real-time medical data are transmitted to AWS IoT Core, processed by Kinesis Data Analytics, and stored securely in AWS HealthLake. Despite the feasibility of the proposed solution, challenges such as insufficient access control, lack of encryption, and vendor conformity must be addressed for successful practical implementation. Future work may involve Hyperledger Fabric technology and HTTPS protocol to enhance security, while the maturation of DT technology is expected to resolve vendor conformity issues. By addressing these challenges, our proposed DT storage solution has the potential to improve data accessibility and decision-making in emergency healthcare settings.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

Digital Transformation in IndustryIoT and Edge/Fog ComputingArtificial Intelligence in Healthcare and Education
Volltext beim Verlag öffnen