Internet of Things as a Service (iTaaS): challenges and solutions for management of sensor data on the Cloud and the Fog

Building upon cloud, IoT and smart sensors technologies we design and de- velop 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 two-fold 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 frame- work and uses BLE pulse oximeter and heart rate monitoring sensing devices. The experimental analysis shows fast data collection, as (for our experimental setup) data is transmitted from the IoT side (i.e. the gateway) to the cloud in less than 130ms. We also stress the back-end system with high user concurrency (for example with 40 users per second) and high data streams (for example 240 data records per second) and we show that the requests are executed at around 1 second, a number that signifies a satisfactory performance by considering the number of requests, the network latency and the relatively small size of the Virtual Machines implementing services on the cloud (2GB RAM, 1 CPU and 20GB hard disk size)

Healthcare sensor data management on the cloud

The quality of medical services can be significantly improved by supporting health care procedureswith 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

Management of health sensor data in the cloud

Summarization: The quality of health 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 in real time becomes a requirement especially for chronic patients and the elderly. A possible solution is the use wearable sensors connected to the Internet and capable of transmitting patient health status to the cloud and from there to the health care personnel. In this thesis, we will focus on the management of health related information on the cloud. Sensor information relates mainly to patients vital measurements like cardiac pulse rate and blood oxygen saturation and is acquired with the aid of special purpose medical sensors. We extend “Inteligate” (a mobile application that supports the collection of vital measurement collected from BLE sensors to Androids devices) with cloud functionality. Building upon principles of Service Oriented Architectures (SOA) and FIWARE, the application enables sensor data to connect to the Cloud where this data is processed, stored and communicated with the health care personnel. The cloud application is extended with new awareness services for both health care providers and patients minimizing the risk of data loss or late response to emergency conditions as defined by rules encoding patient specific reaction plans, especially in cases where normal medical measurement levels exceed the predefined limits. The performance of the system on the cloud has been experimentally evaluated using synthetic data loads that simulate the use of the system by hundreds of users who simultaneously send sensor data to the Cloud. The results of this evaluation reveal that the system on the cloud is able to respond close to real time even under heavy loads approaching the limits of a typical Apache Web server on the cloud that receives service request. Beyond this point, it a responsibility of the system designer to allocate more cloud resources (including Apache servers) to handle excessive data loads.Περίληψη: Η ποιότητα των παρεχόμενων υπηρεσιών υγείας καθώς και ο βαθμός ικανοποίησης των ασθενών, μπορεί να βελτιωθεί σημαντικά εντάσσοντας την τεχνολογία του υπολογιστικού νέφους συνδυαστικά με την ιδεά του διαδικτύου των πραγμάτων, στις ιατρικές διαδικασίες που χρησιμοποιούνται στον ιατρικό τομέα. Ασθένειες που εξελίσσονται με το χρόνο χρειάζονται μια μέθοδο που θα κάνει την παρακολούθηση της κατάστασης της υγείας του ασθενούς πιο εύκολη, άμεση και αποτελεσματική. Η χρήση φορητών αισθητήρων, σε συνδυασμό με τη δυνατότητα συνδεσιμότητάς τους στο διαδίκτυο παρέχει σε ιατρικό προσωπικό ή αργανισμούς παροχής υπηρεσιών υγείας, τα παραπάνω οφέλη ακόμα και για ασθενείς που βρίσκονται μακρυά από ιατρικές μονάδες ή ιατρικό προσωπικό, διευκολύνοντας τη ζωή των ανθρώπων και σε μερικές περιπτώσεις συνεισφέρουν στη μείωση του κόστους παροχής υπηρεσιών υγείας. Σε αυτή την εργασία, επικεντρωνόμαστε κυρίως σε μεθόδους και τεχνολογίες διαχείρισης πληροφορίας που αφορούν ζωτικής σημασίας μετρήσεις, όπως ο καρδιακός παλμός και η ποσότητα οξυγόνου στο αίμα. Αποτελεί επέκταση της έξυπνης εφαρμογης «Intelligate», για κινητές συσκευές android που συλλέγει δεδομένα που παράγονται από αισθητήρες Bluetooth Low Energy (BLE) και αποστέλλονται μέσω διαδικτύου για επεξεργασία και αρχειοθέτηση στο Υπολογιστικό Νέφος. Το σύστημα αναπτύσει υπηρεσίες που προσφέρουν συνδεσιμότητα και επικοινωνία με χρήστες και φορητές συσκευές αλλά επιπλέον διαχειρίζονται την κατάσταση της υγείας των ασθενών όταν οι μετρήσεις ξεπερνούν προκαθορισμένα όρια και με βάση κανόνες αντίδρασης που έχουν οριστεί. Το σύστημά μας έχει υλοποιηθεί με βάση τα πρότυπα της υπηρεσιο-κεντρικής αρχιτεκτονικής με τη χρήση υπηρεσιών γενικού σκοπού μέσω του FIWARE και της υποδομής Νέφους Intellicloud. Τέλος, προσφέρει υπηρεσίες διαχείρισης χρηστών και των δικαιωμάτων πρόσβασης σε υπηρεσίες ή δεδομένα, αλλά και υπηρεσίες διαχείρισης συσκευών ή αισθητήρων. Η απόδοση του συστήματος μετρήθηκε πειραματικά με χρήση συνθετικών δεδομένων που προσομειώνουν τη χρήση του από εκατοντάδες χρήστες που στέλνουν δεδομένα ταυτόχρονα για επεξεργασία στο υπολογιστικό νέφος. Οι πειραματικές μετρήσεις υπόσχονται καλή απόδοση του συστήματος σε πραγματικό χρόνο και πραγματικές συνθήκες

The role and prospects of IoT and cloud computing in remote health monitoring

Summarization: Cloud computing emerges as the key platform for IoT data storage, processing and analytics due to its simplicity, scalability and affordability (i.e. no up-front investment, low operation costs). Remote patient monitoring in particular can benefit from for this technology in many ways: (a) the new solution is acceptable by many user categories and provides invaluable assistance to chronic patients and the elderly, (b) it is expected to increase users autonomy and confidence and enable self-managing of their condition with the help of caregivers remotely, (c) it reduces the need for face-to-face appointments with doctors and days in hospital. This work reviews key challenges for reliable and secure remote health monitoring based on experience and lessons learned from applying the above technology to the problem of real-time data collection using both wide-range and short-rage wireless protocols and health sensors.Παρουσιάστηκε στο: 19th International Conference on Bioinformatics and Bioengineerin