Author: Gihan Gunasekara
Gunasekara, Gihan, 2019 The end-to-end demonstration of health IoT data capture, transfer, manipulation, feedback and visualization using “CISCO Kinetic” platform, Flinders University, College of Science and Engineering
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The Internet of Things (IoT) is a widely used concept across many industries, as it can be used to collect real time data in an environment using many devices. These devices can be smart phones, tablets, appliances, vehicles, sensors and actuators. The underlying connectivity is a combination of people, things and data. This project explores how to capture and extract data that relates to everyday interactions with the technology to provide a proof-of-concept to support the broader Campus Mental Wellness project. The Campus Mental Wellness project aims to enhance the experience of university students, improve engagement of university services and contribute to monitoring and promotion of the wellbeing of students. This project aims to demonstrate the capabilities of the Cisco Kinetic platform and the level to which dataflow modelling is possible using such a platform. The project used a design science methodology to investigate how health IoT data can be extracted, manipulated and moved to various applications depending on the output requirements. This allowed modelling of the end-to-end dataflow which tracks upstream data from IoT devices to the Cisco Kinetic Platform and subsequently to a storage, analytics or visualisation system. Data-flow mapping and creating a visualization exemplar of the capability of the Cisco Kinetic platform is fundamental to understanding the platform and its potential capability. The resulting conceptual dataflow framework for the health IoT end-to-end process is vital to explore the possibilities for health IoT data use in the Campus Mental Wellness project using this platform. The result of this project is to provide a proof-of-concept of the end-to-end dataflow of health IoT data capture, transfer, manipulation, feedback and visualization using Cisco Kinetic platform. The impact is that it will make modelling of new device data easier for researchers, as well as contribute to helping non-technical (clinical) collaborators in the mental wellness project to understanding the capture and use of data for the project. This proof-of-concept will be used to explore further how specific health IoT devices can be used to meet the broader aims of the parent Campus Mental Wellness research project.
Keywords: Internet of Things, IoT Architecture, IoT Capabilities, IoT Platforms, IoT Application Domains, IoT in Health, Cisco Kinetic
Subject: Computer Science thesis
Thesis type: Masters
Completed: 2019
School: College of Science and Engineering
Supervisor: Prof. Trish Williams