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    Acoustic source localisation : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Mathematics at Massey University, Palmerston North, New Zealand
    (Massey University, 2019) White, Alexander Lyndon
    Many New Zealand native bird species are under threat, and as such conservationists are interested in obtaining accurate estimates of population density in order to closely monitor the changes in abundance of these species over time. One method of estimating the presence and abundance of birdlife in an area is using acoustic recorders; currently, omnidirectional microphones are used, which provide no estimate of the direction of arrival of the call. An estimate of the direction from which each sound came from would help to discern one individual calling multiple times, from multiple birds calling in succession - thus providing more accurate information to models of population density. The estimation of this direction-of-arrival (or DOA) for each source is known as acoustic source localisation, and is the subject of this work. This thesis contains a discussion and application of two families of algorithm for acoustic source localisation: those based on the Generalised Cross-Correlation (GCC) algorithm, which applies weightings to the calculation of the cross-correlation of two signals; and those based on the Multiple Signal Classification (MUSIC) algorithm, which provides an estimate of source direction based on subspaces generated by the covariance matrix of the data. As the MUSIC algorithm was originally described for narrowband signals - an assumption not applicable to birdsong - we discuss several adaptations of MUSIC to the broadband scenario; one such adaptation requiring the use of polynomial matrices, which are described herein. An experiment was conducted during this work to determine the effect that the distance between the microphones in a microphone array has on the ability of that array to localise various acoustic signals, including the New Zealand native North Island Brown Kiwi, Apteryx mantelli. It was found that both GCC and MUSIC benefit from larger inter-array spacings, and that a variant of the MUSIC algorithm known as autofocusing MUSIC (or AF-MUSIC) provided the most precise DOA estimates. Though native birdlife was the motivator for the research, none of the methods described within this thesis are necessarily bound only to work on recordings of birdsong; indeed, any multichannel audio which satisfies the necessary assumptions for each algorithm would be suitable. As well as a description of the algorithms, an implementation of GCC, MUSIC, and AF-MUSIC was produced in the Python 3 programming language, and is available at https://github.com/alexW335/Locator.
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    Integrated sensor and controller framework : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Information and Telecommunications Engineering at Massey University, Palmerston North, New Zealand
    (Massey University, 2007) Weir, Ryan David
    This thesis presents a software platform to integrate sensors, controllers, actuators and instrumentation within a common framework. This provides a flexible, reusable, reconfigurable and sealable system for designers to use as a base for any sensing and control platform. The purpose of the framework is to decrease system development time, and allow more time to be spent on designing the control algorithms, rather than implementing the system. The architecture is generic, and finds application in many areas such as home, office and factory automation, process and environmental monitoring, surveillance and robotics. The framework uses a data driven design, which separates the data storage areas (dataslots) from the components of the framework that process the data (processors). By separating all the components of the framework in this way, it allows a flexible configuration. When a processor places data into a dataslot, the dataslot queues all the processors that use that data to run. A system that is based on this framework is configured by a text file. All the components are defined in the file, with the interactions between them. The system can be thought of as multiple boxes, with the text file defining how these boxes are connected together. This allows rapid configuration of the system, as separate text files can be maintained for different configurations. A text file is used for the configuration instead of a graphical environment to simplify the development process, and to reduce development time. One potential limitation of the approach of separating the computational components is an increased overhead or latency. It is acknowledged that this is an important consideration in many control applications, so the framework is designed to minimise the latency through implementation of prioritized queues and multitasking. This prevents one slow component from degrading the performance of the rest of the system. The operation of the framework is demonstrated through a range of different applications. These show some of the key features including: acquiring data, handling multiple dataslots that a processor reads from or writes to, controlling actuators, how the virtual instrumentation works, network communications, where controllers fit into the framework, data logging, image and video dataslots. timers and dynamically linked libraries. A number of experiments show the framework under real conditions. The framework's data passing mechanisms are demonstrated, a simple control and data logging application is shown and an image processing application is shown to demonstrate the system under load. The latency of the framework is also determined. These illustrate how the framework would operate under different hardware and software applications. Work can still be done on the framework, as extra features can be added to improve the usability. Overall, this thesis presents a flexible system to integrate sensors, actuators, instrumentation and controllers that can be utilised in a wide range of applications.