IoT-Based Big Data Secure Transmission and Management over Cloud System: A Healthcare Digital Twin Scenario

被引:4
作者
Stergiou, Christos L. [1 ]
Koidou, Maria P. [1 ]
Psannis, Konstantinos E. [1 ]
机构
[1] Univ Macedonia, Dept Appl Informat, Thessaloniki 54636, Greece
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 16期
关键词
Internet of Things; smart; healthcare; video processing; Mobile Cloud Computing; monitoring; wireless network; data management; secure; SURVEILLANCE SYSTEM; SMART SURVEILLANCE; MONITORING-SYSTEM; SPECIAL SECTION; VIDEO;
D O I
10.3390/app13169165
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The Internet of Things (IoT) was introduced as a recently developed technology in the telecommunications field. It is a network made up of real-world objects, things, and gadgets that are enabled by sensors and software that can communicate data with one another. Systems for monitoring gather, exchange, and process video and image data captured by sensors and cameras across a network. Furthermore, the novel concept of Digital Twin offers new opportunities so that new proposed systems can work virtually, but without differing in operation from a "real" system. This paper is a meticulous survey of the IoT and monitoring systems to illustrate how their combination will improve certain types of the Monitoring systems of Healthcare-IoT in the Cloud. To achieve this goal, we discuss the characteristics of the IoT that improve the use of the types of monitoring systems over a Multimedia Transmission System in the Cloud. The paper also discusses some technical challenges of Multimedia in IoT, based on Healthcare data. Finally, it shows how the Mobile Cloud Computing (MCC) technology, settled as base technology, enhances the functionality of the IoT and has an impact on various types of monitoring technology, and also it proposes an algorithm approach to transmitting and processing video/image data through a Cloud-based Monitoring system. To gather pertinent data about the validity of our proposal in a more safe and useful way, we have implemented our proposal in a Digital Twin scenario of a Smart Healthcare system. The operation of the suggested scenario as a Digital Twin scenario offers a more sustainable and energy-efficient system and experimental findings ultimately demonstrate that the proposed system is more reliable and secure. Experimental results show the impact of our proposed model depicts the efficiency of the usage of a Cloud Management System operated over a Digital Twin scenario, using real-time large-scale data produced from the connected IoT system. Through these scenarios, we can observe that our proposal remains the best choice regardless of the time difference or energy load.
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页数:28
相关论文
共 76 条
[1]  
Abreu B., 2000, P 2000 INT VEH C DEA
[2]  
Ajiboye S.O., 2015, P SPIE INT SOC OPTIC
[3]  
Ali AMM, 2014, 2014 4TH WORLD CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGIES (WICT), P199, DOI 10.1109/WICT.2014.7076905
[4]  
[Anonymous], 2015, Dx@ safeprocess
[5]  
[Anonymous], 2018, Sustainable Cloud and Energy Services: Principles and Practice
[6]  
BALASUBRAMANIAN A., 2010, Proceedings of MobiSys, P209, DOI DOI 10.1145/1814433.1814456
[7]   Advanced multimedia service provisioning based on efficient interoperability of adaptive streaming protocol and high efficient video coding [J].
Batalla, Jordi Mongay .
JOURNAL OF REAL-TIME IMAGE PROCESSING, 2016, 12 (02) :443-454
[8]   IoT Software Infrastructure for Energy Management and Simulation in Smart Cities [J].
Brundu, Francesco Gavino ;
Patti, Edoardo ;
Osello, Anna ;
Del Giudice, Matteo ;
Rapetti, Niccolo ;
Krylovskiy, Alexandr ;
Jahn, Marco ;
Verda, Vittorio ;
Guelpa, Elisa ;
Rietto, Laura ;
Acquaviva, Andrea .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (02) :832-840
[9]   Covert Channels in Personal Cloud Storage Services: The Case of Dropbox [J].
Caviglione, Luca ;
Podolski, Maciej ;
Mazurczyk, Wojciech ;
Ianigro, Massimo .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (04) :1921-1931
[10]   Cloud-based authenticated protocol for healthcare monitoring system [J].
Chandrakar, Preeti ;
Sinha, Sonam ;
Ali, Rifaqat .
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2020, 11 (08) :3431-3447