A comprehensive and scalable middleware for Ambient Assisted Living based on cloud computing and Internet of Things

Gomes, Berto de Tácio Pereira; Muniz, Luiz Carlos Melo; Silva, Francisco José da Silva e; Rios, Luis Eduardo Talavera; Endler, Markus

doi:10.1002/cpe.4043

Cited by 22 publications

(10 citation statements)

References 23 publications

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“…The calculation of the cross-correlation function is also a two-level nested loop body calculation task, but its input signal is sampled data from two different channels, and the rest is the same as the calculation of the autocorrelation function [23].…”

Section: Time-frequency Domain Processing Of Vibration Signalsmentioning

confidence: 99%

Medical Monitoring and Management System of Mobile Thyroid Surgery Based on Internet of Things and Cloud Computing

Kong

Chen

2021

Wireless Communications and Mobile Computing

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With the rapid development of the Internet of Things and cloud computing technologies, the Internet of Things technology based on comprehensive perception and interconnection and cloud computing based on virtualization, dynamic resources, and parallel computing have become the driving force for the innovation and development of informatization and intelligence. The cloud-based Internet of Things mobile medical is an ecosystem of health information and medical information, with the medical Internet of Things at its core and highly mobile and highly shared information. Therefore, in the context of in-depth research on mobile medical care, research on mobile postoperative thyroid monitoring and management systems based on the Internet of Things and cloud computing is a practical tool for promoting the development of mobile medical systems. Monitoring and Management. In this experiment, 48 cases of patients undergoing thyroid surgery were selected from a hospital. The experimental group was informed by the experiment that they need to be equipped with sensors. The control panel and GPS positioning module are used to obtain the exact position of the patient at the first time. The loading of the sensor is agreed by the patient and the patient’s family. Afterward, the control group will not be processed. It will conduct functional tests and software performance tests on the mobile medical monitoring and management system and analyze the satisfaction of medical staff with the mobile medical monitoring and management system. Experiments have proved that the cloud computing medical monitoring and management system is used to obtain the exact location of the patient in the first time, and the response time needs to be shorter. The response time of the system increases with the increase of the number of sensors ( P < 0.05 ), which shows that the mobile medical monitoring and management system is essential for medical care and medical care. Obtaining the exact position of the patient for the first time is of great importance for the successful rescue of the patient.

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Section: Time-frequency Domain Processing Of Vibration Signalsmentioning

confidence: 99%

Medical Monitoring and Management System of Mobile Thyroid Surgery Based on Internet of Things and Cloud Computing

Kong

Chen

2021

Wireless Communications and Mobile Computing

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“…In previous work [ 4 , 57 , 58 , 59 , 60 , 61 , 62 , 63 ], M-Hub has used the Scalable Data Distribution Layer (SDDL) as the default mechanism for the dissemination and processing of context data. SDDL uses two distinct communication protocols in the path between context producers and consumers: Mobile Reliable UDP (MR-UDP) and Data Distribution Service (DDS) [ 64 ].…”

Section: Proposed Solution: M-hub/cddlmentioning

confidence: 99%

A Middleware with Comprehensive Quality of Context Support for the Internet of Things Applications

Gomes

Muniz

Silva

et al. 2017

Sensors

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Context aware systems are able to adapt their behavior according to the environment in which the user is. They can be integrated into an Internet of Things (IoT) infrastructure, allowing a better perception of the user’s physical environment by collecting context data from sensors embedded in devices known as smart objects. An IoT extension called the Internet of Mobile Things (IoMT) suggests new scenarios in which smart objects and IoT gateways can move autonomously or be moved easily. In a comprehensive view, Quality of Context (QoC) is a term that can express quality requirements of context aware applications. These requirements can be those related to the quality of information provided by the sensors (e.g., accuracy, resolution, age, validity time) or those referring to the quality of the data distribution service (e.g, reliability, delay, delivery time). Some functionalities of context aware applications and/or decision-making processes of these applications and their users depend on the level of quality of context available, which tend to vary over time for various reasons. Reviewing the literature, it is possible to verify that the quality of context support provided by IoT-oriented middleware systems still has limitations in relation to at least four relevant aspects: (i) quality of context provisioning; (ii) quality of context monitoring; (iii) support for heterogeneous device and technology management; (iv) support for reliable data delivery in mobility scenarios. This paper presents two main contributions: (i) a state-of-the-art survey specifically aimed at analyzing the middleware with quality of context support and; (ii) a new middleware with comprehensive quality of context support for Internet of Things Applications. The proposed middleware was evaluated and the results are presented and discussed in this article, which also shows a case study involving the development of a mobile remote patient monitoring application that was developed using the proposed middleware. This case study highlights how middleware components were used to meet the quality of context requirements of the application. In addition, the proposed middleware was compared to other solutions in the literature.

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“…Gomes et al, in their article A Comprehensive and Scalable Middleware for Ambient Assisted Living Based on Cloud Computing and IoT , introduce a middleware for Ambient‐Assisted Living (AAL) based on cloud computing and IoT aspects to cope with several challenges, mainly scalability, reliability, and the suitability to different AAL scenarios. The authors handled these challenges through 2 components: the Scalable Data Distribution Layer (SDDL) and M‐Hub.…”

Section: Themes Of This Special Issuementioning

confidence: 99%

“…After rigorous reviews, 7 papers were accepted for publication and are briefly described in the rest of this section. Gomes et al, in their article 11 A Comprehensive and Scalable…”

mentioning

confidence: 99%

Cloud computing and big data: Technologies and applications

Zbakh

Bakhouya

Essaaidi

2017

Concurrency and Computation

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to cloud computing and big data technologies, applications, and services.Authors of the selected papers were invited to submit an expanded version to this special issue. These papers were reviewed in the same manner as regular submissions to this edition. After rigorous reviews, 7 papers were accepted for publication and are briefly described in the rest of this section. and the results show that the proposed algorithm outperforms 2 other task-scheduling algorithms in cost and throughput. | Mobile and cloud computing technologiesPrivacy and security in cloud computing is one of the most important issues, which still need to be tackled. As a contribution in this field, Souza et al, in their paper 9 Privacy-ensuring electronic health records on the cloud, present a solid access control framework in the context of Electronic Health Records (EHRs). This framework encompasses hybrid cryptography at the client side and an authentication technique to guarantee a secure key management protocol. They use the homomorphic and order-preserving encryption as a viable solution for the computation of regular searches over EHRs in the cloud, while preserving data confidentiality and patients' privacy. Furthermore, they introduce a trusted element, in the form of a browser extension that can prevent attacks from malicious providers. An HER-based prototype was developed to show the usefulness of the proposed framework. | Cloud computing applications and big dataThe | CONCLUSIONSThe papers presented in this special issue provide research works related to recent advances in cloud computing and big data. In particular, these research works focus on different topics including resources optimization, privacy and security, mobile cloud, cloud computing, and big data applications and services. We hope that the readers of this special issue will benefit from the research ideas and concepts presented in these research works.

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A comprehensive and scalable middleware for Ambient Assisted Living based on cloud computing and Internet of Things

Cited by 22 publications

References 23 publications

Medical Monitoring and Management System of Mobile Thyroid Surgery Based on Internet of Things and Cloud Computing

Medical Monitoring and Management System of Mobile Thyroid Surgery Based on Internet of Things and Cloud Computing

A Middleware with Comprehensive Quality of Context Support for the Internet of Things Applications

Cloud computing and big data: Technologies and applications

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