Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease

Modelling smart domestic energy systems

The increasing price of fossil fuels, coupled with the increased worldwide focus on their contribution to climate change has driven the need to develop cleaner forms of energy generation. The transition to cleaner energy sources has seen a much higher penetration of renewable sources of electricity on the grid than ever before. Among these renewable generation sources are wind and solar power which provide intermittent and often unpredictable energy generation throughout the day depending on weather conditions. The connection of such renewable sources poses problems for electricity network operators whose legacy systems have been designed to use traditional generation sources where supply can be increased as required to meet demand. Among the solutions proposed to address this issue with intermittency in generation are storage systems and automation systems which aim to reduce demand in order to match the available renewable generation. Such a transition would introduce a requirement for more advanced technology within homes to provide network operators with greater control over domestic loads. Another aspect to the transition towards a low-carbon society is the change that will be required to domestic heating systems. Current domestic heating systems largely rely on Natural Gas as their fuel source. In order to meet carbon reduction targets, changes will need to be made to domestic buildings including insulation and other energy efficiency measures. It is also possible that present systems will begin to be replaced by new heating technologies such as ground and air source heat pumps. Due to the effect that such technological transitions will have on domestic end-users, it is important that these new technologies are designed with end-users in mind. It is therefore necessary that software tools are available to model and simulate these changes at the domestic level to guide the design of new systems. This thesis provides a summary of some of the existing building energy analysis tools that are available and shows that there is currently a shortcoming in the capabilities of existing tools when modelling future domestic smart grid technologies. Tools for developing these technologies must include a combination of building thermal characteristics, electrical energy generation and consumption, software control and communications. A new software package was developed which allows for the modelling of small smart grid systems, with a particular focus on domestic systems including electricity, heat transfer, software automation and control and communications. In addition to the modelling of electrical power flow and heat transfer that is available in existing building energy simulation packages, the package provides the novel features of allowing the simulation of data communication and human interaction with appliances. The package also provides a flexible framework that allows system components to be developed in full object-orientated programming languages at run time, rather than having to use additional third-party development environments. As well as describing the background to the work and the design of the new software, this thesis describes validation studies that were carried out to verify the accuracy of the results produced by the package. A simulation-based case study was also carried out to demonstrate the features offered by the new platform in which a smart domestic energy control system including photovoltaic generation, hot water storage and battery storage was developed. During the development of this system, new algorithms for obtaining the operating point of solar panels and photovoltaic maximum power point tracking were developed

Engineering and built environment project conference 2014: book of abstracts - Toowoomba, Australia, 22-26 September 2014

Book of Abstracts of the USQ Engineering and Built Environment Conference 2014, held Toowoomba, Australia, 22-26 September 2014. These proceedings include extended abstracts of the verbal presentations that are delivered at the project conference. The work reported at the conference is the research undertaken by students in meeting the requirements of courses ENG4111/ENG4112 Research Project for undergraduate or ENG8411/ENG8412 Research Project and Dissertation for postgraduate students