Data management of sensor signals for high bandwidth data streaming to the cloud

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

doi:10.1109/sarnof.2016.7846764

Cited by 12 publications

(16 citation statements)

References 4 publications

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“…Several approaches to IoT systems design are known to exist and many of them have been implemented in commercialized IoT platforms 5 facilitating the implementation of applications or, in custom solutions tailored to the needs of a particular application domain such as manufacturing [15], monitoring of users activity [16], assisted living [2], e-Health [17] and remote health monitoring [18,12,13,1,19] etc. Interesting surveys covering important aspects of IoT system design and implementation have been published in [5,20,4,21,3,7].…”

Section: Related Work and Backgroundmentioning

confidence: 99%

“…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%

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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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Section: Related Work and Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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“…The efficiently evacuation planning system is the key, which attracts more and more attentions of governments, academia and industry around the world. In addition, the emergence of Fog, Internet of Things (IoT) and Cloud computing highlight new opportunities [26] for example in the area of disaster management planning and management [29], data processing [27] as well as in healthcare provisioning [28]. IoT allows fast user data collection based on the peoples' smart devices, while Cloud offers the platform and infrastructure for scalable data analytics and storage.…”

Section: Introductionmentioning

confidence: 99%

CLOTHO: A Large-Scale Internet of Things-Based Crowd Evacuation Planning System for Disaster Management

Zhang

Sotiriadis

et al. 2018

IEEE Internet Things J.

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In recent years, different kinds of natural hazards or man-made disasters happened that were diversified and difficult to control with heavy casualties. In this work, we focus on the rapid and systematic evacuation of large-scale densities of people after disasters to reduce loss in an effective manner. The optimal evacuation planning is a key challenge and becomes a hotspot of research and development. We design our system based on an Internet of Things (IoT) scenario that utilizes a mobile Cloud computing platform in order to develop the Crowd Lives Oriented Track and Help Optimizition system (CLOTHO). CLOTHO is an evacuation planning system for large-scale densities of people in disasters. It includes the mobile terminal (IoT side) for data collection and the Cloud backend system for storage and analytics. We build our solution upon a typical IoT/fog disaster management scenario and we propose an IoT application based on an evacuation planning algorithm that uses the Artificial Potential Field (APF), which is the core of CLOTHO. APF is conceptualized as an IoT service, and can determine the direction of evacuation automatically according to the gradient direction of the potential field, suitable for rapid evacuation of large population. People are usually in panic, which easily causes the chaos of evacuation and brings secondary disasters. Based on APF, we propose an evacuation planning algorithm names as Artificial Potential Field with Relationship Attraction (APF-RA). APF-RA guides the evacuees with relationship to move to the same shelter as much as possible, to calm evacuees and realize a more humanitarian evacuation. The experimental results show that CLOTHO (using APF and APF-RA) can effectively improve convergence rate, shorten the evacuation route length and evacuation time, and make the remaining capacity of the surrounding shelters well balanced.

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“…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%

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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Data management of sensor signals for high bandwidth data streaming to the cloud

Cited by 12 publications

References 4 publications

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

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

CLOTHO: A Large-Scale Internet of Things-Based Crowd Evacuation Planning System for Disaster Management

Healthcare Sensor Data Management on the Cloud

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