URI: | http://purl.tuc.gr/dl/dias/05121735-501D-49B5-B098-75AFB91D68F3 | ||
Year | 2017 | ||
Type of Item | Diploma Work | ||
License |
|
||
Bibliographic Citation | Pelagia Tsiachri-Renta, "Management of health sensor data in the cloud", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2017 https://doi.org/10.26233/heallink.tuc.67725 | ||
Appears in Collections | |||
Relations with other Items | Has Complement Item: |
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.