An Efficient Cloud Framework for Health Care Monitoring System

Reddy, B. Eswara; Kumar, T. V. Suresh; Ramu, Gandikota

doi:10.1109/iscos.2012.11

Cited by 20 publications

(13 citation statements)

References 9 publications

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“…In respect to reliable communication, Reddy et al, 27 Doukas et al, 28 Cubo et al, 24 and Rahmani et al 23 27 Balasubramanian and Stranieri 25 , and M-Hub/SDDL explicitly mentioned the ability to add new computing resources to meet an increased demand from its users. This gateway is equipped with a Bluetooth communication module for gathering data from the sensors and uses a WLAN to forward them to the cloud where applications, like a medical record system or an emergency detection platform, are executed.…”

Section: Related Workmentioning

confidence: 99%

“…Dragino IoT Gateway is a stationary hardware designed to be installed indoor. In respect to reliable communication, Reddy et al, 27 Doukas et al, 28 Cubo et al, 24 and Rahmani et al 23 Reddy et al, 27 Balasubramanian and Stranieri 25 , and M-Hub/SDDL explicitly mentioned the ability to add new computing resources to meet an increased demand from its users. We believe that only the addition of computing resources to a cloud infrastructure is, by itself, not always enough, because part of the resources may become overloaded if the system load is not appropriately distributed.…”

Section: Related Workmentioning

confidence: 99%

“…Reddy et al present a web‐based telemedicine/healthcare cloud support for connecting high‐complexity hospitals (that provide very specialized treatments), community health centers, and emergency care units, with the aim to provide access to remote areas. The proposed system is called Cloud Framework for Health Care Monitoring System.…”

Section: Related Workmentioning

confidence: 99%

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

Gomes

Muniz

Silva

et al. 2016

Concurrency and Computation

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Ambient Assisted Living (AAL) main goal is the development of health monitoring systems for patients with chronic diseases and elderly people through the use of body, home, and environmental sensors that increase their degree of independence and mobility. A comprehensive software infrastructure for AAL systems should be able to cover scenarios involving several patient mobility levels, locations, and physical and cognitive abilities. Cloud computing can provide to AAL systems the ability to extend the limited processing power of mobile devices, but its main role is to integrate all stakeholders through the storage and processing of health data and the orchestration of healthcare business logic. On the other hand, the Internet of Things (IoT) provides the ability to connect sensors and actuators, integrating and making them available through the Internet. This paper presents the Mobile-Hub/Scalable Data Distribution Layer, a middleware for AAL based on cloud computing and IoT. We discuss how this middleware can handle the requirements of the main health monitoring scenarios and present results that demonstrate the ability to opportunistically discover and connect with sensors in a timely manner and the scalability necessary for handling the connection and data processing of many connected patients. KEYWORDSambient assisted living, cloud computing, health monitoring systems, internet of things (IoT) 1 range of other applications for AAL systems, such as rescue and emer-gency response systems, fall detection, video surveillance systems, etc.Nowadays, AAL systems are regarded as a trend in a context of increasing awareness of how the Internet can be used to personal healthcare. Ambient Assisted Living systems are composed of several technologies: sensors and actuators, portable/wearable devices, heterogeneous wireless networks, medical applications executing on mobile devices (handhelds), personal computers, or in a cloud computing infrastructure. Among the variety of low-level sensors that can be applied in AAL systems, there are the wearable medical sensors, able to collect data from physiological signals (e.g., Electrocardiogram [ECG], Electromyogram, heart rate, and oxygen consumption) or data reflecting the body movement (e.g., accelerometer). Personal mobile devices, such as smartphones, are also usually equipped with motion and location sensors (e.g., accelerometer and GPS). Environmental sensors can also be used, as they collect information that helps determine if environmental conditions (e.g., temperature, light, humidity, and carbon dioxide levels) favor or not the patient's health. In addition to gathering data Concurrency Computat: Pract Exper. 2017;29:e4043. wileyonlinelibrary.com/journal/cpe

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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

Gomes

Muniz

Silva

et al. 2016

Concurrency and Computation

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show abstract

“…A number of works in the literature, such as the ones in [2], [6], [16], and [25] describe some approaches for the design and implementation of several health related services (such as the EHR or health monitoring systems) on the Cloud. Instead, the focus of this paper is different from these works because we take for granted that the X1.V1 platform is already designed for being executed on the Cloud, and we focus on the design, implementation and validation of a tool which eases the exploitation of the Cloud elasticity, in order to allow the X1.V1 platform to take maximum benefit from the Cloud environment.…”

Section: Related Workmentioning

confidence: 99%

A Tool for Managing the X1.V1 Platform on the Cloud

Marzini¹,

Mori²,

Bona³

et al. 2015

SCPE

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Abstract. The X1.V1 platform is a service oriented architecture, deployed on a set of Virtual Machines, that integrates services for managing fundamental activities in the ehealth scenario, such as Patient Identification, Clinical Document Repository, Prescription, and many others. The efficient provisioning of such services to citizens and to health professionals requires the adoption of increasingly powerful computing systems, in order to ensure that the growing number of service requests are served in acceptable time, even in case of computational peaks. Porting the X1.V1 platform on the Cloud could address the problem of the computational requirement mutability, since Cloud elasticity allows the reallocation of resources to Virtual Machines when necessary. This paper proposes a framework for managing the execution of the X1.V1 platform on the Cloud. This framework enables an easy, quick, and secure management of the Cloud resources allocation and reallocation to X1.V1 Virtual Machines, in order to enhance the platform performances, optimize resource utilization and, consequently, reduce the whole services cost. The design of the framework is focused on security aspects as well, because unauthorized accesses could lead to serious inefficiencies of the ehealth services. Finally, besides describing the architecture design and implementation of the X1.V1 Cloud manager framework, this paper also presents a set of experimental results which confirm the validity of the proposed approach to solve the X1.V1 platform performance issues in distinct reference scenarios.

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“…These enhancements made are accounted as tremendous changes in medical systems and in reducing of critical sudden conditions of patients during an emergency and in reducing the effects of diseases, as the diseases are diagnosed and handled before going to be critical. The remote monitoring of patients' health or telemonitoring systems via sensor devices and the use of wireless sensor networks play an important role in making a coordination between the patients and medical advisor and also between medical sensor devices and other parts of the telemonitoring system [11][12][13][14][15]. Upon the requirements, which commonly specified by health organizations and the health center (or hospital) in our case, building a private healthcare system also mainly targets the security obstacles as its main goal.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Cloud-Based Health Tracking and Monitoring System in Designed Boundary for Cardiology Patients

Shahzad

Lee

et al. 2018

Journal of Sensors

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Telemonitoring is not a new term, in information technology (IT), which has been employed to remotely monitor the health of patients that are located not in common places, such hospitals or medical centers. For that, wearable medical sensors, such as electrocardiography sensors, blood pressure sensors, and glucometer, have commonly been used to make possible to acquire the real-time information from the remotely located patients; therefore, the medical information is further carried, via the Internet, to perform medical diagnosis and the corresponding treatments. Like in other IT sectors, there has been tremendous progress accounted in medical sectors (and in telemonitoring systems) that changes the human life protection against several chronic diseases, and the patient’s medical information can be accessed wirelessly via Wi-Fi and cellular systems. Further, with the advents of cloud computing technology, medical systems are now more efficient and scalable in processing, such as storage and access, the medical information with minimal development costs. This study is also a piece of enhancement made to track and monitor the real-time medical information, bounded in authorized area, through the modeling of private cloud computing. The private cloud-based environment is designed, for patient health monitoring called bounded telemonitoring system, to acquire the real-time medical information of patients that resided in the boundary, inside medical wards and outside medical wards, of the medical center. A new wireless sensor network scenario is designed and modeled to keep or monitor the patients’ health information whole day, 24 hours. This research is a new secured sight towards medical information access and gives directions for future developments in the medical systems.

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An Efficient Cloud Framework for Health Care Monitoring System

Cited by 20 publications

References 9 publications

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

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

A Tool for Managing the X1.V1 Platform on the Cloud

Real-Time Cloud-Based Health Tracking and Monitoring System in Designed Boundary for Cardiology Patients

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