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.

As wireless devices are becoming more powerful, more flexible and less costly to produce, they are often being applied in new ways. Combining wireless technology with new types of sensors results in the ability to monitor and control the environment in ways not previously possible. For example, an intelligent wireless sensor system that consists of a sensor, digital processor and a transceiver can be mounted on a board the size of a coin. The data collected by these devices are then transmitted to a central unit which is able to thoroughly process and store this data. Not only can the central processing station provide reports about certain physical parameters in the environment, it can also control the environment and other parameters of interest. The design process of these wireless sensor platforms is a well-developed area of research that covers concepts like networking, circuit design, Radio-Frequency (RF) circuits and antenna design. The design of a wireless sensor can be as simple as putting together a microcontroller, a transceiver and a sensor chip or as complicated as implementing all the necessary circuitry into a single integrated circuit. One of the main applications of the sensors is in a control loop which controls physical characteristics in an environment. Specifically, if the objective of a control system is to limit the amount of vibrations in a structure, vibration sensors such as accelerometers are usually used. In environments where the use of wires is costly or impossible, it makes sense to use wireless accelerometers instead. Among the numerous applications that can use such devices are the automotive and medical vibration control systems. In the automotive industry it is desirable to reduce the amount of vibrations in the vehicle felt by the passengers. These vibrations can originate from the engine or the uneven road, but they are damped using passive mechanical elements like rubber, springs and shocks. It is possible however, to have a more effective vibration suppression using active sensor-actuator systems. Since adding and maintaining wires in a vehicle is costly, a wireless accelerometer can be put to good use there. A medical application for wireless accelerometers can be used with a procedure called Deep Brain Stimulation (DBS). DBS is a relatively new and very effective treatment for advanced Parkinson’s disease. The purpose of DBS is to reduce tremors in the patients. In DBS a set of voltages is applied to the brain of the patient as some optimum combinations of voltages will have a very positive effect on the tremors. Those optimum voltages are currently found by trial and error while a doctor is observing the patient for tremors. Wireless accelerometers with the use of a computer algorithm can assist in this process by finding the optimum voltages using the feedback provided by the accelerometers. The algorithm will assist the doctor in making decisions and has the potential of finding the optimums completely on its own.

As wireless devices are becoming more powerful, more flexible and less costly to produce, they are often being applied in new ways. Combining wireless technology with new types of sensors results in the ability to monitor and control the environment in ways not previously possible. For example, an intelligent wireless sensor system that consists of a sensor, digital processor and a transceiver can be mounted on a board the size of a coin. The data collected by these devices are then transmitted to a central unit which is able to thoroughly process and store this data. Not only can the central processing station provide reports about certain physical parameters in the environment, it can also control the environment and other parameters of interest. The design process of these wireless sensor platforms is a well-developed area of research that covers concepts like networking, circuit design, Radio-Frequency (RF) circuits and antenna design. The design of a wireless sensor can be as simple as putting together a microcontroller, a transceiver and a sensor chip or as complicated as implementing all the necessary circuitry into a single integrated circuit. One of the main applications of the sensors is in a control loop which controls physical characteristics in an environment. Specifically, if the objective of a control system is to limit the amount of vibrations in a structure, vibration sensors such as accelerometers are usually used. In environments where the use of wires is costly or impossible, it makes sense to use wireless accelerometers instead. Among the numerous applications that can use such devices are the automotive and medical vibration control systems. In the automotive industry it is desirable to reduce the amount of vibrations in the vehicle felt by the passengers. These vibrations can originate from the engine or the uneven road, but they are damped using passive mechanical elements like rubber, springs and shocks. It is possible however, to have a more effective vibration suppression using active sensor-actuator systems. Since adding and maintaining wires in a vehicle is costly, a wireless accelerometer can be put to good use there. A medical application for wireless accelerometers can be used with a procedure called Deep Brain Stimulation (DBS). DBS is a relatively new and very effective treatment for advanced Parkinson’s disease. The purpose of DBS is to reduce tremors in the patients. In DBS a set of voltages is applied to the brain of the patient as some optimum combinations of voltages will have a very positive effect on the tremors. Those optimum voltages are currently found by trial and error while a doctor is observing the patient for tremors. Wireless accelerometers with the use of a computer algorithm can assist in this process by finding the optimum voltages using the feedback provided by the accelerometers. The algorithm will assist the doctor in making decisions and has the potential of finding the optimums completely on its own.

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.

ABSTRACT For a variety of wireless sensor network applications, sensor nodes may find their received signal strengths dominated by small-scale propagation effects. Particularly impacted are applications designed to monitor structural health and environmental conditions in metal cavities such as aircraft, busses, and shipping containers. Small changes in each sensor’s position or carrier frequency can cause large variations in this received signal strength, thereby compromising link connectivity. We leverage a technique called Wireless Sensors Sensing Wireless (WSSW) in which wireless sensors act as scalar network analyzers in order to characterize their own environment. WSSW data can enable sensors to react to particularly bad fading, such as hyper-Rayleigh, by switching to a good channel or by implementing other mitigation techniques, such as utilizing a diversity antenna. In this work, the WSSW concept has been extended to accommodate mesh networks and include a spectrum analysis capability for recognizing potentially interfering wireless activity. The test of mitigation techniques is often problematic since application sites are far from controlled environments and are often difficult to access. To address this problem, we have developed a Compact Reconfigurable Channel Emulator (CRCE) to create a laboratory environment that is configurable to a variety of repeatable fading scenarios. With the CRCE, fading characteristics found at a specific wireless sensor network location may be replicated inside the chamber to discover the connectivity capabilities of the sensors and the effectiveness of diversity schemes (e.g., channel switching or multi-element antenna arrays).