L. Gholamhosseini, A. Behmanesh, Somayeh Nasiri, S. Ehsanzadeh, F sadoughi
{"title":"Cloud-Based Internet of Things in Healthcare Applications: A Systematic Literature Review","authors":"L. Gholamhosseini, A. Behmanesh, Somayeh Nasiri, S. Ehsanzadeh, F sadoughi","doi":"10.30699/fhi.v12i0.451","DOIUrl":null,"url":null,"abstract":"Introduction: The Internet of Things (IoT) and Cloud computing are two recent technological advances whose potential have not been realized in a range of industries. These technologies have been used in healthcare systems to improve their performance. In this regard, the IoT generates a large amount of data; also, cloud computing is a viable option for data storage and complex computing. The purpose of this study is to identify and categorize various aspects of CIoT-based healthcare in terms of main application domains, sensors, wireless communication technologies, messaging protocols, cloud platforms, and artificial intelligence (AI) algorithms.Material and Methods: We conducted a literature systematic review and reported according to the PRISMA guideline. PubMed, IEEE, Scopus, and Web of Science were searched using the related keywords and their synonyms. Two independent authors reviewed the papers' eligibility according to the defined inclusion and exclusion criteria.Results: Of the 2,118 papers retrieved, 61 were eventually selected in the study. Results of the present study revealed that the majority of CIoT research works were applied to patient monitoring systems and cardiovascular patient monitoring systems using Amazon and IBM dominating Cloud platforms. In addition, the most widely used communication technologies for CIoT in healthcare are cellular networks (3G and 4G), Wi-Fi, and Bluetooth. Cardiovascular, environmental, and position sensors are also the most common types of sensors used in healthcare CIoT applications. Among the Cloud platform providers, Amazon and IBM have the highest utility in healthcare systems. The majority of the included studies used Cloud-based AI algorithms to diagnose, classify, and predict diseases.Conclusion: The integration of the Cloud into the IoT can support healthcare systems in terms of processing power, storage capacity, security, privacy, performance, reliability, and scalability. We suggest researchers conduct experimental studies to evaluate the effectiveness of the CIoT approach in healthcare applications.","PeriodicalId":154611,"journal":{"name":"Frontiers in Health Informatics","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30699/fhi.v12i0.451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: The Internet of Things (IoT) and Cloud computing are two recent technological advances whose potential have not been realized in a range of industries. These technologies have been used in healthcare systems to improve their performance. In this regard, the IoT generates a large amount of data; also, cloud computing is a viable option for data storage and complex computing. The purpose of this study is to identify and categorize various aspects of CIoT-based healthcare in terms of main application domains, sensors, wireless communication technologies, messaging protocols, cloud platforms, and artificial intelligence (AI) algorithms.Material and Methods: We conducted a literature systematic review and reported according to the PRISMA guideline. PubMed, IEEE, Scopus, and Web of Science were searched using the related keywords and their synonyms. Two independent authors reviewed the papers' eligibility according to the defined inclusion and exclusion criteria.Results: Of the 2,118 papers retrieved, 61 were eventually selected in the study. Results of the present study revealed that the majority of CIoT research works were applied to patient monitoring systems and cardiovascular patient monitoring systems using Amazon and IBM dominating Cloud platforms. In addition, the most widely used communication technologies for CIoT in healthcare are cellular networks (3G and 4G), Wi-Fi, and Bluetooth. Cardiovascular, environmental, and position sensors are also the most common types of sensors used in healthcare CIoT applications. Among the Cloud platform providers, Amazon and IBM have the highest utility in healthcare systems. The majority of the included studies used Cloud-based AI algorithms to diagnose, classify, and predict diseases.Conclusion: The integration of the Cloud into the IoT can support healthcare systems in terms of processing power, storage capacity, security, privacy, performance, reliability, and scalability. We suggest researchers conduct experimental studies to evaluate the effectiveness of the CIoT approach in healthcare applications.
导言:物联网(IoT)和云计算是最近的两项技术进步,其潜力尚未在一系列行业中实现。这些技术已用于医疗保健系统,以提高其性能。在这方面,物联网产生了大量的数据;此外,云计算是数据存储和复杂计算的可行选择。本研究的目的是根据主要应用领域、传感器、无线通信技术、消息传递协议、云平台和人工智能(AI)算法来识别和分类基于ciot的医疗保健的各个方面。材料和方法:我们进行了文献系统综述,并根据PRISMA指南进行了报道。使用相关关键词及其同义词对PubMed、IEEE、Scopus和Web of Science进行了搜索。两位独立作者根据确定的纳入和排除标准审查了论文的资格。结果:在检索到的2118篇论文中,有61篇最终入选本研究。本研究结果表明,大部分CIoT研究工作应用于使用亚马逊和IBM主导的云平台的患者监测系统和心血管患者监测系统。此外,医疗保健领域CIoT中使用最广泛的通信技术是蜂窝网络(3G和4G)、Wi-Fi和蓝牙。心血管、环境和位置传感器也是医疗保健CIoT应用中最常用的传感器类型。在云平台提供商中,亚马逊和IBM在医疗保健系统中的效用最高。大多数纳入的研究使用基于云的人工智能算法来诊断、分类和预测疾病。结论:云与物联网的集成可以在处理能力、存储容量、安全性、隐私性、性能、可靠性和可扩展性方面支持医疗保健系统。我们建议研究人员进行实验研究,以评估CIoT方法在医疗保健应用中的有效性。