Low cost, low power wireless sensors (motes) promise to revolutionize environmental data collection, but are they currently refined enough for widespread use by hydrologists? Their viability as a replacement for traditional data collection techniques was investigated in a 7 ha forested watershed in south-western British Columbia. The watershed included 41 instrument clusters measuring air and soil temperature, humidity, throughfall, soil moisture content, overland flow and groundwater head. The foundation of each cluster was a data box containing a MDA300 data acquisition board and a MICA2 processor board from Crossbow Technologies, Inc.™ that allowed for short range wireless data collection. The 41 motes each recorded data every 15 minutes from July, 2006, to April, 2007. In addition to reporting on the reliability of the motes and sensors during the 10 months deployment, the high spatial and temporal resolution data collected by this study gave the opportunity for many analyses of catchment processes. As soil moisture and throughfall are two influential processes in the exchange of water between the earth and the atmosphere, these were the focus of the data analysis. The first analysis was a resampling experiment on seven different events selected from the full data set. Comparing 100 different subsamples each of 5, 10 and 20 points for throughfall and soil moisture showed if increasing the sample size eventually produced diminishing returns in the ability to reproduce the true catchment mean. With significant differences in prediction ability for both soil moisture and throughfall at times of differing hydrologic activity, this analysis provides further support for the theories of changing moisture states of soil moisture and threshold values for throughfall. The second analysis described how the organization of soil moisture and throughfall changed during a range of weather conditions and timescales. Spatial representation of normalized values and Pearson correlation coefficients showed that there were distinct differences between wet and dry periods for soil moisture and between long and short analysis periods for throughfall.

Low cost, low power wireless sensors (motes) promise to revolutionize environmental data collection, but are they currently refined enough for widespread use by hydrologists? Their viability as a replacement for traditional data collection techniques was investigated in a 7 ha forested watershed in south-western British Columbia. The watershed included 41 instrument clusters measuring air and soil temperature, humidity, throughfall, soil moisture content, overland flow and groundwater head. The foundation of each cluster was a data box containing a MDA300 data acquisition board and a MICA2 processor board from Crossbow Technologies, Inc.™ that allowed for short range wireless data collection. The 41 motes each recorded data every 15 minutes from July, 2006, to April, 2007. In addition to reporting on the reliability of the motes and sensors during the 10 months deployment, the high spatial and temporal resolution data collected by this study gave the opportunity for many analyses of catchment processes. As soil moisture and throughfall are two influential processes in the exchange of water between the earth and the atmosphere, these were the focus of the data analysis. The first analysis was a resampling experiment on seven different events selected from the full data set. Comparing 100 different subsamples each of 5, 10 and 20 points for throughfall and soil moisture showed if increasing the sample size eventually produced diminishing returns in the ability to reproduce the true catchment mean. With significant differences in prediction ability for both soil moisture and throughfall at times of differing hydrologic activity, this analysis provides further support for the theories of changing moisture states of soil moisture and threshold values for throughfall. The second analysis described how the organization of soil moisture and throughfall changed during a range of weather conditions and timescales. Spatial representation of normalized values and Pearson correlation coefficients showed that there were distinct differences between wet and dry periods for soil moisture and between long and short analysis periods for throughfall.

Low cost, low power wireless sensors (motes) promise to revolutionize environmental data collection, but are they currently refined enough for widespread use by hydrologists? Their viability as a replacement for traditional data collection techniques was investigated in a 7 ha forested watershed in south-western British Columbia. The watershed included 41 instrument clusters measuring air and soil temperature, humidity, throughfall, soil moisture content, overland flow and groundwater head. The foundation of each cluster was a data box containing a MDA300 data acquisition board and a MICA2 processor board from Crossbow Technologies, Inc.™ that allowed for short range wireless data collection. The 41 motes each recorded data every 15 minutes from July, 2006, to April, 2007. In addition to reporting on the reliability of the motes and sensors during the 10 months deployment, the high spatial and temporal resolution data collected by this study gave the opportunity for many analyses of catchment processes. As soil moisture and throughfall are two influential processes in the exchange of water between the earth and the atmosphere, these were the focus of the data analysis. The first analysis was a resampling experiment on seven different events selected from the full data set. Comparing 100 different subsamples each of 5, 10 and 20 points for throughfall and soil moisture showed if increasing the sample size eventually produced diminishing returns in the ability to reproduce the true catchment mean. With significant differences in prediction ability for both soil moisture and throughfall at times of differing hydrologic activity, this analysis provides further support for the theories of changing moisture states of soil moisture and threshold values for throughfall. The second analysis described how the organization of soil moisture and throughfall changed during a range of weather conditions and timescales. Spatial representation of normalized values and Pearson correlation coefficients showed that there were distinct differences between wet and dry periods for soil moisture and between long and short analysis periods for throughfall. / Forestry, Faculty of / Graduate

Wireless sensors and their applications have become increasingly attractive for industry, building automation and energy control, paving the way for new applications of sensor networks which go well beyond traditional sensor applications. In recent years, there has been a rapid growth in the number of wireless devices operating in close proximity to the human body. Wearable sensor nodes are growing popular not only in our normal living lifestyle, but also within healthcare and military applications, where different radio units operating in/on/off body communicate pervasively. Expectations go beyond the research visions, towards deployment in real-world applications that would empower business processes and future business cases. Although theoretical and simulation models give initial results of the antenna behaviour and the radio channel performance of wireless body area network (WBAN) devices, empirical data from different set of measurements still form an essential part of the radio propagation models. Usually, measurements are performed in laboratory facilities which are equipped with bulky and expensive RF instrumentation within calibrated and controllable environments; thus, the acquired data has the highest possible reliability. However, there are still measurement uncertainties due to cables and connections and significant variations when designs are deployed and measured in real scenarios, such as hospitals wards, commercial buildings or even the battle field. Consequently, more flexible and less expensive measurement tools are required. In this sense, wireless sensor nodes offer not only easiness to deploy or flexibility, but also adaptability to different environments. In this thesis, custom-built wireless sensor nodes are used to characterise different on-body radio channels operating in the IEEE 802.15.4 communication standard at the 2.45 GHz ISM band. Measurement results are also compared with those from the conventional technique using a Vector Network Analyser. The wireless sensor nodes not only diminished the effect of semi-rigid or flexible coaxial cables (scattering or radiation) used with the Vector Network Analyser (VNA), but also provided a more realistic response of the radio link channel. The performance of the wireless sensors is presented over each of the 16 different channels present at the 2.45 GHz band. Additionally, custom-built wireless sensors are used to characterise and model the performance of different on-body radio links in dynamic environments, such as jogging, rowing, and cycling. The use of wireless sensors proves to be less obstructive and more flexible than traditional measurements using coaxial cables, VNA or signal generators. The statistical analysis of different WBAN channels highlighted important radio propagation features which can be used as sport classifiers models and motion detection. Moreover, specific on-body radio propagation channels are further explored, with the aim to recognize physiological features such as motion pattern, breathing activity and heartbeat. The time domain sample data is transformed to the frequency domain using a non-parametric FFT defined by the Welch’s periodogram. The Appendix-Section D explores other digital signal processing techniques which include spectrograms (STFT) and wavelet transforms (WT). Although a simple analysis is presented, strong DSP techniques proved to be good for signal de-noising and multi-resolution analysis. Finally, preliminary results are presented for indoor tracking using the RSS recorded by multiple wireless sensor nodes deployed in an indoor scenario. In contrast to outdoor environments, indoor scenarios are subject to a high level of multipath signals which are dependent on the indoor clutter. The presented algorithm is based on path loss analysis combined with spatial knowledge of each wireless sensor.

Wireless surface acoustic wave (SAW) sensors offer unique advantages over other sensor technologies because of their inherent ability to operate in harsh environments and completely passive operation, providing a reliable, maintenance-free life cycle. For certain SAW sensor applications the challenge is building a wirelessly interrogatable device with the same lifetime as the SAW substrate. The design of these application intensive sensors is complicated by the degradation of device bond wires, die adhesive, and antenna substrate. In an effort to maximize the benefits of the platform, this dissertation demonstrates wafer-level integrated SAW sensors that directly connect the thin film SAW to a thick film on-wafer antenna. Fully integrated device embodiments are presented that operate over a wide range of temperatures using different fabrication techniques, substrates, and coding principles.

No description available.

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / In performing its mission, the Air Force SEEK EAGLE Office (AFSEO) conducts a wide variety of tests with heavy emphasis on open-air flight tests. As budget pressures drive a reduction in the number of test sorties, maximizing the amount of quality data from each flight test is of paramount importance. This paper describes an AFSEO effort to develop a low cost, intelligent, subminiature telemetry and sensor system based on modern commercial wireless technologies. The instrumentation system is completely self-contained and can be externally mounted, thus eliminating the requirement for extensive aircraft modifications and minimizing the need for specially instrumented test aircraft. The system will make maximum use of Commercial Off The Shelf (COTS) components to reduce cost and insure availability. MicroElectroMechanical Systems (MEMS) technology will be incorporated as the technology matures.

<div>Wireless sensor networks are highly integrated across numerous industries from industrial</div><div>manufacturing to personal health monitoring. They provide several key benefits over</div><div>traditional wired systems including positioning flexibility, modularity, interconnectivity, and</div><div>robust data routing schemes. However, their adoption into certain sectors such as vacuum</div><div>and aerospace has been slow due to tight regulation, data security concerns, and device</div><div>reliability.</div><div>Lyophilization is a desiccation technique used to stabilize sensitive food and drug products</div><div>using vacuum sublimation. A series of wireless devices based on the Pirani architecture are</div><div>developed to quantify the spatial variations in pressure and temperature throughout this</div><div>process. The data is coupled to computational fluid dynamics simulations to estimate the</div><div>sublimation rate over time. This information is then used to quantify the heat and mass</div><div>transfer characteristics of the product, allowing estimates of product temperature and mass</div><div>flux to be obtained for an arbitrary cycle. This capability is significant, having the ability</div><div>to accelerate process development and reduce manufacturing time.</div><div>Drying performance during lyophilization is highly sensitive to the dynamics of the freezing</div><div>process. This work therefore also develops a wireless network to monitor both gas</div><div>pressure and temperature throughout the controlled ice nucleation process, a technique used</div><div>to improve batch uniformity by inducing simultaneous and widespread ice nucleation via</div><div>adiabatic decompression. The effects of initial charge pressure, ballast composition, and vial</div><div>size are investigated. Experimental data is supported by numerical modeling to describe the</div><div>evolution of the true gas temperature during the discharge event.</div><div>Finally, The mechanisms governing the lyophilization process are directly applied to the</div><div>aerospace industry in the form of a novel milliNewton-class evaporation-based thruster concept.</div><div>The device was tested under vacuum using a torsional balance and demonstrated peak</div><div>thrust magnitudes on the order of 0.5 mN. A state observer model was then implemented</div><div>to decouple the dynamics of the balance with the time-dependent thrust input. With this</div><div>model the true time-dependent thrust output and corresponding thruster performance are</div><div>analyzed.</div>

In a wide range of industries, machine condition monitoring is one of the most cost effective ways to minimise maintenance efforts and machine downtime. To implement such a system, wireless solutions have increasingly become an attractive proposition due to the ease of installation and minimal infrastructure alternation. However, currently most wireless sensors in the world are powered by a finite battery source. The dependence of batteries not only requires frequent maintenance, but also has adverse environmental consequences associated with battery disposal. These reasons render massive deployment of wireless sensors in the industry problematic. With the advances in semiconductors, power consumption of wireless sensors has been continuously decreasing. It is an inevitable trend for self-powered wireless sensors to emerge and become the norm for machine and environmental monitoring. In this research, vibration is chosen to be the energy source to enable self-powered wireless sensors due to its ubiquitousness in machinery and industrial environments. As a result of relying on resonance, the biggest challenge for vibration-based energy harvesters is their narrow bandwidth. Even a small deviation of the vibration frequency can dramatically reduce the power output. The primary goal of this research is to address this problem. In particular, Piezoelectric generators are identified to be the most suitable technology. In this work, extensive theoretical and experimental studies are conducted in single mass and multi-modal harvesters, and in resonance tuning harvesters by modulus and impedance matching as well as by mechanical actuation. Mathematical modelling plays a significant role in energy harvester designs. A dynamic model that generalises the single degree of freedom models and the continuum models is derived and validated by experiments. The model serves as the building block for the whole research, and it is further refined for the investigation of modulus and impedance matching. In the study of multi-modal harvesters, a continuum model for double-mass piezoelectric cantilever beams is derived and experimentally validated. To study the feasibility of resonance tuning by mechanical means, prototypes were built and performance evaluated. This document details the theoretical basis, concepts and experimental results that extend the current knowledge in the field of energy harvesting. This research work, being highly industrially focused, is believed to be a very significant step forward to a commercial energy harvester that works for a wide range of vibration frequencies.

Due to the unprecedented spatial and temporal resolution they offer, wireless sensor networks are considered an enabling technology for the distributed monitoring of industrial, military, and natural environments. As these systems migrate into vastly different and novel applications, new constraints are discovered that affect network reliability and utility. For example, wireless sensors are typically statically deployed and, unlike mobile systems, cannot move to a new location for better radio reception. As a result, the signal fades caused by non-optimal environmental conditions can increase the outage probability of the system, potentially rendering the network unreliable and ineffectual. Stochastic models that quantify link reliability and the effectiveness of diversity methods are often employed to understand the impact of such fading. However, the performance of these models applied to wireless sensor networks is entirely dependent on the appropriateness of the model with respect to the environment. This work first presents an empirical study of the propagation environment for a wingless, rotary aircraft, showing that the wireless environment within exhibits frequency-selective fading much more severe than predicted by current worst-case models (i.e., Rayleigh). An analysis is then given of the effectiveness of several diversity methods operating within such environments (referred to as hyper-Rayleigh). These fade mitigation techniques are simple enough to be employed for use with low-complexity wireless sensor hardware, and include spatial diversity, polar diversity, two-element passive combining, and two-element phased combining. Two-element phased combining is further developed by examining the effect that smaller element spacing has on diversity gain. A demonstration of a wireless