Internet of Things data management in the cloud for Bluetooth Low Energy (BLE) devices

Soultanopoulos, Theodoros; Sotiriadis, Stelios; Petrakis, Euripides G. M.; Amza, Cristiana

doi:10.1145/2962564.2962568

Cited by 5 publications

(4 citation statements)

References 10 publications

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“… The Google Cloud Messaging Service [8]: It is a service responsible for managing the physician's messages to the patient as described in [2,3]. These are the services that implement the functionality of medical users.…”

Section: Description Of the System Servicesmentioning

confidence: 99%

“…The proposed system involves two kinds of services, the smart cellphone service (called gateway), that is installed in the user device, while the Cloud system is responsible for data storage and processing. The smart phone gateway service is based on [2] and [3], is dynamic and allows automated sensor discovery and registration of new sensors, where an XML schema declares each sensor. In addition, it has the ability to recognize and register new characteristic values of BLE sensors (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Healthcare Sensor Data Management on the Cloud

Renta

Sotiriadis

Petrakis

2017

Proceedings of the 2017 Workshop on Adaptive Resource Management and Scheduling for Cloud Computing

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The quality of medical services can be significantly improved by supporting health care procedures with new technologies such as Cloud computing and Internet of Things (IoTs). The need to monitor patient's health remotely and in real time becomes more and more a vital requirement, especially for chronic patients and elderly. In this work, we focus on the management of health care related data stored on the Cloud produced by Bluetooth low energy devices. We present a Cloud based IoT Management System that collects vital user data (e.g. cardiac pulse rate and blood oxygen saturation) on real time. Our solution enables sensor data collection and processing fast and efficient, while users such as medical personnel can subscribe to patient's data and get notifications. The system is designed based on microservices and includes a notification service for both health care providers and patients minimizing the risk of late response to emergency conditions. Alerts are produced according to predefined rules and on patient specific reaction plans. We present an experimental study where we evaluate our system based on real world sensors, while we generate a synthetic dataset for simulating thousands of users. The results are prosperous, as the system responds close to real time even under heavy loads binding to the limits of the web server that receives the service request. The heaviest workload simulates 2000 user requests (while 80 are executed concurrently) is completed in less than 13 seconds when the system deployed in a virtual machine of 2GB RAM, 1 VCPU and 20GB Disk.

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Section: Description Of the System Servicesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Healthcare Sensor Data Management on the Cloud

Renta

Sotiriadis

Petrakis

2017

Proceedings of the 2017 Workshop on Adaptive Resource Management and Scheduling for Cloud Computing

Self Cite

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“…data analytics) or modified on the fly without requiring that the system be stopped or re-designed. iTaaS solution (design and its implementation) is based on previous work by the authors presented in one conference [12] and two workshops [13,14].…”

Section: Introductionmentioning

confidence: 99%

“…The architecture of the iTaaS gateway for on the fly data collection is shown in [12,14]. Design and implementation of the back-end solution is shown in [13].…”

Section: Introductionmentioning

confidence: 99%

Internet of Things as a Service (iTaaS): Challenges and solutions for management of sensor data on the cloud and the fog

et al. 2018

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Building upon cloud, IoT and smart sensors technologies we design and develop an IoT as a Service (iTaaS) framework, that transforms a user device (e.g. a smart phone) to an IoT gateway that allows for fast and efficient data streams transmission to the cloud. We develop a twofold solution, based on micro-services for the IoT (users' smart devices) and the cloud side (back-end services). iTaaS includes configurations for (a) the IoT side to support data collection from IoT devices to a gateway on a real time basis and, (b) the cloud back-end side to support data sharing, storage and processing. iTaaS provides the technology foreground to enable immediate application deployments in the domain of interest. An obvious and promising implementation of this technology is e-Health and remote health monitoring. As a proof of concept we implement a real time remote patient monitoring system that integrates the proposed framework and uses BLE pulse oximeter and heart rate monitoring sensing devices. The experimental analysis shows fast data collection, as

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