Date of Award


Document Type

Master Thesis

Degree Name

Master of Engineering (Research)


Electronic Engineering

First Advisor

Dr. Alan McGibney

Second Advisor

Dr. Dirk Pesch


The combination of sensing, processing, communication and actuation has made the monitoring and operation of buildings a significant emerging application area for Wireless Sensor Networks (WSN). The design, implementation and management of WSN is a complex task requiring a broad spectrum of disciplines such as networking and protocols, information management and embedding engineering to be successful. Indoor environments in particular pose a number of challenges that make the design of wireless networks a difficult task. These include the influence of obstacles and people on radio propagation, ever evolving building layout and interference from other wireless networks. The large-scale adoption of wireless sensing for building monitoring and control has been hindered due to the perception that wireless sensors are inaccurate, prone to failure and require significant effort to manage the infrastructure. This is largely due to a lack of formal design methodologies and tools to support the planning and deployment of indoor wireless networks. To contribute to the development of these methodologies the research presented in this thesis demonstrates that the rise of a software tool encapsulating an automated design methodology can reduce the complexity of the design process, minimise the cost of these systems, and produce reliable design outputs for wireless applications within buildings. As part of this research work, a number of models that support the WSN design process have been developed. The main contribution of this thesis is the development of an agent-based optimisation algorithm which has the capability to support the automatic design of wireless sensing infrastructures according to application specific requirements. The optimisation approach and software tool developed as part of the work presented in this thesis has been evaluated using real WSN deployments and design scenarios.

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