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Machine learning based calibration techniques for low-cost air quality sensors : thesis for Doctor of Philosophy, Electronic and Computer Engineering, Massey University
(Massey University, 2024-05-28) Ali, Mohammad Sharafat
Breathable air is the single most essential element for life on earth. Polluted air poses numerous risks to health and the environment, especially in urban areas with large populations and many active sources of air pollution. Therefore, researchers from a wide range of disciplines have been working on mitigating the impact of air pollution. Monitoring ambient air pollution is one of the means to ensure public health safety, raise public awareness and build a sustainable urban environment. However, conventional air quality monitoring stations are mostly confined to a few locations due to their costly equipment and large sizes. As a result, although these monitoring stations provide accurate air pollution data, they can only offer a low-fidelity picture of air quality in a large city, leading to a poor spatial resolution of urban pollution data. Low-cost sensor (LCS) technologies aim to address this challenge and intend to make it possible to monitor air quality at a high spatio-temporal resolution. The pollutant data captured by these LCSs are less accurate than their conventional counterparts and thus require calibration techniques to improve their accuracy and reliability. Researchers have proposed different calibration methods and techniques to improve the accuracy of the LCSs, including machine learning based calibration models. This thesis investigates and proposes several machine learning-based calibration techniques and rigorously benchmarks their performance using a robust training, validation and testing method. Based on the findings, One Dimensional Convolutional Neural Network (1DCNN) and Gradient Boosting Regression (GBR) based calibration techniques provide consistently accurate performance. Both of these machine learning techniques, which have not been widely used or evaluated for low-cost ambient gas sensor calibration, can improve the state of the art. This research also demonstrates that readily available and previously unemployed co-variate data, namely the number of days the sensor has been deployed and the time of day at which the reading is taken, can significantly improve the accuracy of Machine Learning based calibration algorithms.
Device-free indoor localisation with non-wireless sensing techniques : a thesis by publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Electronics and Computer Engineering, Massey University, Albany, New Zealand
(Massey University, 2021) Faulkner, Nathaniel
Global Navigation Satellite Systems provide accurate and reliable outdoor positioning to support a large number of applications across many sectors. Unfortunately, such systems do not operate reliably inside buildings due to the signal degradation caused by the absence of a clear line of sight with the satellites. The past two decades have therefore seen intensive research into the development of Indoor Positioning System (IPS). While considerable progress has been made in the indoor localisation discipline, there is still no widely adopted solution. The proliferation of Internet of Things (IoT) devices within the modern built environment provides an opportunity to localise human subjects by utilising such ubiquitous networked devices. This thesis presents the development, implementation and evaluation of several passive indoor positioning systems using ambient Visible Light Positioning (VLP), capacitive-flooring, and thermopile sensors (low-resolution thermal cameras). These systems position the human subject in a device-free manner (i.e., the subject is not required to be instrumented). The developed systems improve upon the state-of-the-art solutions by offering superior position accuracy whilst also using more robust and generalised test setups. The developed passive VLP system is one of the first reported solutions making use of ambient light to position a moving human subject. The capacitive-floor based system improves upon the accuracy of existing flooring solutions as well as demonstrates the potential for automated fall detection. The system also requires very little calibration, i.e., variations of the environment or subject have very little impact upon it. The thermopile positioning system is also shown to be robust to changes in the environment and subjects. Improvements are made over the current literature by testing across multiple environments and subjects whilst using a robust ground truth system. Finally, advanced machine learning methods were implemented and benchmarked against a thermopile dataset which has been made available for other researchers to use.
Printed sensors for indoor air quality : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering, Massey University, Albany, New Zealand
(Massey University, 2022) Rehmani, Muhammad Asif Ali
On average, a human inhale about 14,000 litres of air every day. The quality of inhaled air is highly important as the presence of pathogens and contaminants in air can adversely affect human health. Generally, the probability of pathogens/contaminant is high in indoor environment where humans spend an estimated 90% of their total lifetime. Continuous urbanization, increasing population, technological advancement and automation has further increased the time spent indoors. The length of exposure and indoor activities such as cooking, smoking, ventilation and frequency of cleaning can further aggravate the health risk due to localized higher concentrations of the contaminants. According to the Environmental Protection Agency (EPA), poor indoor air quality (IAQ) is considered one of the top environmental dangers to the public as increasing number of people are suffering from asthma, allergies, heart disease, and even lung cancer. In New Zealand, poor air quality is estimated to cause 730 premature deaths and cost over one billion dollars in restricted activity days per year. The above premise cannot be validated until and unless there are means and measures of continually monitoring the indoor air pollutants with emphasis that the same can be fabricated using low cost and energy efficient methods. Furthermore, any remedial actions cannot be undertaken if the quantitative values of the environmental pollutants are unknown. Existing solutions for the air quality monitoring are expensive and can only be applied in certain numbers, leaving areas of the houses, offices, and schools unmonitored. Therefore, a ubiquitous system of air quality monitoring is needed, the one that can be applied on large areas like walls, roofs and so on. Such a prevalent system will allow sensing of air quality parameters rapidly, continuously, and with low power consumption. To realize the bigger objective of achieving sensing and aware surfaces for indoor air quality, this research proposes to print sensors on large surfaces rather than making them in batches and packaging in discrete units. Recent advancements in inkjet printing provide solutions which can enable the implementation of such sensors. However, the choice of inkjet printing method has major impact on the efficacy of printed sensors. Therefore, we have explored printing techniques based on conventional screen printing and non-conventional electrohydrodynamic (EHD) inkjet printing. These printing methods offer low-cost, rapid prototyping and high-thorough-put conductive printing of features as compared to other inkjet printing methods with the latter bringing further advantages of improved resolution, scalability, customization and little or no environmental waste printing solution. For screen printing, laser ablation process has been used to implement several customized transduction schemes. The utility of this technique is demonstrated by humidity sensing. It has been found that the designs of the transduction electrodes can easily be customized, and large area printing can be realized on the substrate. The fabricated humidity sensor provides higher sensitivity through bio-compatible sensing layer with good response and recovery time. Next, EHD printing was explored for high-resolution conductive printing on flexible substrates. Current EHD printing focuses on improving the print resolution by decreasing the printhead nozzle diameter thus limiting the type of ink to be used for printing purpose. In the proposed EHD printhead design we overcame this major shortcoming by improving the resolution of printed feature with a bigger nozzle of 0.5 mm diameter. This resulted in the printed feature resolution of less than 10 µm in general with the highest achieved resolution 1.85 µm. The effective nozzle diameter to printed feature ratio of more than 250 was achieved. The use of bigger nozzle for fine resolution printing opens the avenue for utilizing higher concentration of metallic nano-particles inks through EHD printing. The hallmark of the presented EHD printhead design is the utilization of off-the-shelf components which does not require expensive manufacturing process while highlighting the importance of wetting area profile of the nozzle to facilitate fine resolution printing which until now has not been explored in detail. Furthermore, the work highlights the issue of crack development during EHD printing in the conductive tracks while using available piezoelectric inkjet ink. Later the ink was modified to minimise the cracks in EHD printed features. Finally, a comprehensive study on the 3D printed microfluidic channels was conducted. The study highlights the variation of pressure developed in different microfluidic channel designs and the susceptibility of leakages from microfluidic devices. The work presents the possibility of utilizing the 3D printed microfluidics with printed sensors for deploying as lab-on-a-chip in various applications, such as passing a stream of air through sensors integrated in a microfluidic device for analysing the volatile organic compounds, humidity, toxic gases, and other analytes of interest. Overall, the presented work demonstrates the feasibility of using conventional and non-conventional printing methods through simple implementations for the fabrication of IAQ sensors with high degree of customization, low processing cost and scalability.
Micro implantable pressure sensors for lifetime monitoring of intracranial pressure : this dissertation is submitted for the degree of Doctor of Philosophy, School of Engineering and Advanced Technology, Massey University
(Massey University, 2019) Sodavaram, Nireekshan Kumar
The elevation of intracranial pressure (ICP) associated with traumatic brain injury (TBI), hydrocephalus and other neurological conditions is a serious concern. If left untreated, increased pressure in the brain will reduce cerebral blood flow (CBF) and can lead to brain damage or early death. Currently, ICP is monitored through invasive catheters inserted into the brain along with a shunt. However, insertion of catheters or shunts is an invasive procedure that introduces vulnerability to infection. In principle, the risk of infection would be overcome by a fully implantable pressure monitoring system. This would be particularly valuable for hydrocephalus patients if lifetime monitoring was available. An implantable pressure monitoring system relies on a thin flexible membrane as part of the pressure sensor. The thin film membrane displaces under load and correspondingly induces a change in a relevant electrical quantity (resistance, or capacitance). Micro-electro-mechanical system (MEMS) is the technology that helps in creating micro/nano-mechanical structures integrated with signal conditioning electronics. These micro structures can be inserted into the brain, where the thin film is exposed to a corrosive fluid (saline/blood) at a temperature of approximately 37 ◦C. The miniaturization in MEMS permits examination, sensing and monitoring from inside the patient for longer durations. However, the accuracy, particularly in terms of sensor drift over long durations, is a key concern. In general, the issue of drift is attributed to the aging and mechanical fatigue of thin film structures, particularly the thin flexible membrane. Therefore, it is essential to analyze the thin film deflection and fatigue behaviour of MEMS pressure sensors for achieving long-term reliability and accuracy. Thus, the high-level goal of this research is to identify a viable approach to producing a flexible membrane suitable for deployment as a lifetime implantable pressure measuring system. In this context, finite-element modelling (FEM) and finite-element analysis (FEA) of thin film deflection and fatigue behaviour have been conducted. The FEM was implemented in COMSOL Multiphysics with geometries resembling a capacitive type pressure sensor with titanium (Ti) thin film membrane deposited onto the silicon substrate. The mechanical behavior of thin film structures including stresses, strains, elastic strain energy density, and thin film displacements of several thicknesses (50 μm, 25 μm, 4 μm, 1 μm, 500 nm, 200 nm) have been studied. In addition, fatigue physics module has been added to the FEM to analyze the fatigue life of thin film structures. The FEA results in the form of fatigue usage factors have been plotted. Finally, to analyze the effect of fluid pressure transmission of the thin film membrane inside the closed skull, fluid-structure interaction has been modelled. The model represents a 2D fluid medium with the thin film membrane. The velocity magnitude, displacement, shear rate (1/s) and kinetic energy density (J/m3) of 4 μm and 25 μm thick Ti films has been plotted. From this analysis, 4 μm thin film membrane showed good tradeoff for thickness, pressure transmission, and mechanical behaviour. To validate the FEM, a custom designed acoustic-based thin film deflection and fatigue life experiments have been set up. The experimental design comprised of: (1) A voice coil-based multimedia speaker and subwoofer system to assist in displacing the thin film membranes, (2) A laser displacement sensor to capture the displacements, (3) A spectrum analyzer palette for generating random vibrations, (4) Dataloggers to record the input vibrations and thin film displacements, and (5) Scanning electron microscopy (SEM) to visualize the surface topography of thin film structures. Thin film titanium (Ti) foils of 4 μm and 25 μm thick were obtained from William Gregor Ltd, Ti-shop, London. The thin-film specimens were clamped to 3mm acrylic substrates and bonded to the subwoofer system. The Gaussian random vibrations generated from the spectrum analyzer loaded the voice coil of the multi-media speaker system, which assists in displacing the thin films. The SEM surface observations are divided into two regions: (1) Pre-cycle observation, where the thin film surfaces are observed before the application of any load, and (2) Post-cycle observation, where the thin films surfaces are observed after application of cyclic loadings. Based on the understanding of the FEM and experimental studies, a conceptual framework of MEMS pressure sensor has been developed. In this part of the work, initially, underlying concepts of complementary-metal-oxide silicon (CMOS) circuit simulation, MEMS modelling, and CMOS layout design have been discussed. Next the MEMS fabrication process involving deposition (sputtering), etching, and final packaging have been discussed. Finally, an optimized design process of the membrane-based sealed cavity MEMS pressure sensors has been outlined.
Planar electromagnetic sensors : characterization and experimental results : a project report submitted in partial fulfilment of the requirements for the degree of Master of Engineering in Information and Telecommunications Engineering
(Massey University, 2005) Gooneratne, Chinthaka P
Planar type electromagnetic sensors have simple structures and are very useful for the inspection of material properties, in a non-destructive and non-invasive way. The operating principle of the sensing technique is based on the interaction of electromagnetic fields with the materials under test. Three types of planar sensors: meander, mesh and interdigital configuration have been analyzed to determine their characteristics. Finite element software has been used for the analysis of flux distribution for all three types of sensors. The nature of the impedance characteristics has also been obtained through experiments. It has been reported that meander and mesh type sensors respond well at moderately high frequencies. To avoid relatively costly instrumentation systems at high frequencies, interdigital sensors having good response at low frequencies have been considered. The response of all the sensors, especially the interdigital types to milk of varying fat content, quality estimation of saxophone reeds and non-invasive estimation of fat content of pork belly cuts have been determined. The different types of sensors can be made as a sensor array, to estimate the properties of mixtures of electric, magnetic and dielectric materials. A microcontroller based low cost sensing system is under development.
CMOS radiation sensor design in 130nm CMOS technology : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Electronics and Computer Engineering at School of Engineering and Advanced Technology, Massey University, Albany Campus
(Massey University, 2017) Zhang, Chaoping
This research work deals with a CMOS radiation sensor design, which covers a new open source floating-gate MOSFET (FGMOSFET) device model for analog circuit design, Floating Gate Radiation Field Effect Transistor (FGRADFET) design, FGRADFET sensor output circuit design and their layout implementation using the 130nm IBM CMOS process. At first, a new FGMOSFET device model to facilitate circuit design is presented. In this model, the floating gate is charged by the Fowler-Nordheim tunneling effect. The equations representing the new device model were explored and verified on MATLAB. Verilog-A script was employed to transfer the equations and build the complete device model. The new FGMOSFET circuit model was plugged-in as a pop-up menu component in a standard 130 nm CMOS technology design library so that it can be instanced directly on a schematic editor palette for analog circuit simulation and design in a similar fashion as the standard MOSFET devices. Furthermore, the thesis describes the radiation sensor of FGRADFET that has an extra silicon area (125μm×200μm) as an antenna to sense the radiation from the environment. There are 16 PMOS transistors (1μm×2μm each) beneath the edge of the antenna to charge the floating gate. A radiation sensor readout circuit is also designed for this sensor. This circuit includes differentiator, pre-amplify buffer, chopper amplifier, low-pass filter and single-ended output amplifier. This integrated dosimeter has a 3.205mW power consumption and 2.33mGy- 23mGy measuring range (The single-ended output voltage changes from 26mV to 967mV), which could be used for tremendous radiation exposure applications such as radiation therapy.
Energy scavenging using piezoelectric materials : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University, Palmerston North, New Zealand
(Massey University, 2008) Liang, Huangbo
In recent years, wireless devices have been developing rapidly for various uses that run on batteries. However, when the devices are made smaller and the networks increase in number, it is not practical to replace the depleted batteries, such as in areas difficult to access. Alternative method is to scavenge power available in the environment where the wireless device is placed. This thesis is focused on scavenging power via vibrations as a power source. According to the literature piezoelectric material is the best choice to convert mechanical forces into electric field. Piezoelectric generator devices have been modelled and analyzed. A case study of power generator for use in traffic monitoring sensors is assumed. The thesis describes such a piezoelectric power generator, developed based on a cantilever beam and using modelling techniques available in literature. The design is optimized by Sequential Quadratic Programming method. A prototype of the generator is built and tested extensively. The generated power is stored in a specially built circuit. The experiments show that the prototype piezoelectric power generator can provide 0.09J in a simulated traffic scenario. Also the generated energy can be stored in the electric circuit which gives a stable 5 V DC output. It is noted that piezoelectric material is very brittle and was cracked during the experiment. As a consequence, the most of the experiment were conducted with a slightly modified generator. In conclusion, this thesis research has developed successfully both mathematical and a physical model of the piezoelectric power generator for wireless traffic monitoring sensors. Further work will still be in order in improving the current design.
Viability of commercial depth sensors for the REX medical exoskeleton : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University, Albany, New Zealand
(Massey University, 2016) Lange, Manu F
Closing the feedback loop of machine control has been a known method for gaining stability. Medical exoskeletons are no exception to this phenomenon. It is proposed that through machine vision, their stability control can be enhanced in a commercially viable manner. Using machines to enhance human’s capabilities has been a concept tried since the 19th century, with a range of successful demonstrations since then such as the REX platform. In parallel, machine vision has progressed similarly, and while applications that could be considered to be synonymous have been researched, using computer vision for traversability analysis in medical exoskeletons still leaves a lot of questions unanswered. These works attempt to understand better this field, in particular, the commercial viability of machine vision system’s ability to enhance medical exoskeletons. The key method to determine this will be through implementation. A system is designed that considers the constraints of working with a commercial product, demonstrating integration into an existing system without significant alterations. It shows using a stereo vision system to gather depth information from the surroundings and amalgamate these. The amalgamation process relies on tracking movement to provide accurate transforms between time-frames in the three dimensional world. Visual odometry and ground plane detection is employed to achieve this, enabling the creation of digital elevation maps, to efficiently capture and present information about the surroundings. Further simplification of this information is accomplished by creating traversability maps; that directly relate the terrain to whether the REX device can safely navigate that location. Ultimately a link is formed between the REX device and these maps, and that enables user movement commands to be intercepted. Once intercepted, a binary decision is computed whether that movement will traverse safe terrain. If however the command is deemed unsafe (for example stepping backwards off a ledge), this will not be permitted, hence increasing patient safety. Results suggest that this end-to-end demonstration is capable of improving patient safety; however, plenty of future work and considerations are discussed. The underlying data quality provided by the stereo sensor is questioned, and the limitations of macro vs. micro applicability to the REX are identified. That is; the works presented are capable of working on a macro level, but in their current state lack the finer detail to improve patient safety when operating a REX medical exoskeleton considerably.
Design and development of a modular framework to integrate sensors and actuators : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Engineering in Mechatronics at Massey University, Manawatu, New Zealand
(Massey University, 2016) Taylor, Brendan
This thesis details the research and development of a versatile electronic monitoring and control platform, influenced by the Internet of Things (IoT), mass configurability, modularity, expandability and ease of use. The generic framework which has been designed and tested aims to provide a platform to build a wide variety of specialised systems to integrate sensors and actuators. A central processing unit manages modular hardware devices connected by a serial network. Only the required hardware units are chosen to constitute a system for an application. The processing unit uses modular task handlers to manage the system. The web-based user interface provides multi-platform system access using a web browser. The website is dynamically generated from the system configuration. While the framework is generic, for testing its efficacy, it was applied to a seed and fertilizer spreader to monitor and control the application rate. This application requires coordinated control of actuators using inputs from multiple sources, including sensors, machine states, a database, other processing tasks, and the operator. The implementation was successful in achieving reliable control of the seeding rate, based on the tractor ground speed. The practical implementation exhibited a high level of expandability and modularity. The prototype system has also highlighted a few issues which can be addressed in future revisions to improve the versatility and robustness of the framework.
Novel planar interdigital sensors for the detection of bacterial endotoxins : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philososphy in Electronics Engineering at Massey University, Palmerston North, New Zealand
(Massey University, 2012) Abdul Rahman, Mohd Syaifudin Bin
Food poisoning caused by endotoxins or Lipopolysaccharide (LPS) are associated with Gram-negative bacteria. Foodborne pathogens, Escherichia coli (E. coli) and Salmonella are examples of Gram-negative bacteria which could cause large food poisoning outbreaks. New types of planar interdigital sensors have been fabricated with different coating materials to assess their response to endotoxins. A carboxyl-funtional polymer, APTES (3-Aminopropyltriethoxysilane) and Thionine were chosen for coating the novel interdigital sensors. All coated sensors were immobilized with PmB (Polymyxin B) which has specific binding properties to LPS. The sensors were tested with different concentrations of LPS O111:B4, ranging from 0.1 μg/ml to 1000 μg/ml. Analyses of sensors’ performance were based on the Impedance Spectroscopy method. The impedance spectra were modelled using a Constant Phase-Element (CPE) equivalent circuit, and a Principal Component Analysis (PCA) was used for data classification. Sensors coated with APTES have shown better selectivity towards LPS detection. The experiments were repeated by coating APTES and immobilizing PmB to a newly improved design of silicon based interdigital sensor. Scanning electron microscope (SEM) and atomic force microscope (AFM) images were taken to analyse the APTES coating surface and PmB immobilization. The images of non-coated sensors and coated silicon sensors were studied and the thickness of a single layer coating was estimated ([approximately equal to] 268 nm). Analyses of results with LPS O111:B4 showed that these silicon sensors have higher sensitivity and selectivity to the target biomolecule LPS. The complex non-linear least squares (CNLS) fitting method was used to fit the measured impedance spectra based on chosen equivalent circuit model. PCA results were clustered, showing the parameters were related and have identified process which related to the diffusion, charge transfer and adsorption of molecules on sensors’ surface. It was also found that these sensors can detect the standard endotoxin as low as 0.01 EU/ml which is equivalent to 1 pg/ml. Selectivity, stability and sensitivity of different thickness of coated sensors were analysed. It was observed that the optimum thickness layer is 3-layers of coating which is equivalent to 800 nm. Analyses of results with food samples have shown the developed novel interdigital sensors can detect the presence of endotoxin in contaminated food samples.

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