Steven D. Glaser

OpenWSN: a standards‐based low‐power wireless development environment

The OpenWSN project is an open-source implementation of a fully standards-based protocol stack for capillary networks, rooted in the new IEEE802.15.4e Time Synchronized Channel Hopping standard. IEEE802.15.4e, coupled with Internet of Things standards, such as 6LoWPAN, RPL and CoAP, enables ultra-low-power and highly reliable mesh networks, which are fully integrated into the Internet. The resulting protocol stack will be cornerstone to the upcoming machine-to-machine revolution. This article gives an overview of the protocol stack, as well as key integration details and the platforms and tools developed around it. The pure-C OpenWSN stack was ported to four off-the-shelf platforms representative of hardware currently used, from older 16-bit microcontroller to state-of-the-art 32-bit Cortex-M architectures. The tools developed around the low-power mesh networks include visualisation and debugging software, a simulator to mimic OpenWSN networks on a PC, and the environment needed to connect those networks to the Internet. Experimental results presented in this article include a network where motes operate at an average radio duty cycle well below 0.1% and an average current draw of 68  μA on off-the-shelf hardware. These ultra-low-power requirements enable a range of applications, with motes perpetually powered by micro-scavenging devices. OpenWSN is, to the best of our knowledge, the first open-source implementation of the IEEE802.15.4e standard. Copyright

Some real-world applications of wireless sensor nodes

This paper presents two case histories of the use of wireless sensor Mote technologies. These are devices that incorporate communications, processing, sensors, sensor fusion, and power source into a package currently about two cubic inches in size -- networked autonomous sensor nodes. The first case discussed is the November, 2001, instrumentation of a blast-induced liquefaction test in Tokachi Port, Japan. The second case discussed is the dense-pak instrumentation of the seismic shaking test of a full-scale wood-frame building on the UCB Richmond shake table. The utility of dense instumentation is shown, and how it allows location of damage globally unseen. A methodology of interpreting structural seismic respose by Bayesian updating and extended Kalman filtering is presented. It is shown that dense, inexpensive instrumentation is needed to identify structural damage and prognosticate future behavior. The case studies show that the current families of Motes are very useful, but the hardware still has difficulties in terms of reliability and consistancy. It is apparent that the TinyOS is a wonderful tool for computer science education but is not an industrual quality instrumentation system. These are, of course, growing pains of the first incarnations of the Berkeley Smart Dust ideal. We expect the dream of easy to use, inexpensive, smart, wireless, sensor networks to become a reality in the next couple of years.

Physical Activity Monitoring for Assisted Living at Home

We propose a methodology to determine the occurrence of falls from among other common human movements. The source data is collected by wearable and mobile platforms based on three-axis accelerometers to measure subject kinematics. Our signal processing consists of preprocessing, pattern recognition and classification. One problem with data acquisition is the extensive variation in the morphology of acceleration signals of different patients and under various conditions. We explore several effective key features that can be used for classification of physical movements. Our objective is to enhance the accuracy of movement recognition. We employ classifiers based on neural networks and k-nearest neighbors. Our experimental results exhibit an average of 84% accuracy in movement tracking for four distinct activities over several test subjects.

Fault healing promotes high-frequency earthquakes in laboratory experiments and on natural faults

Faults strengthen or heal with time in stationary contact, and this healing may be an essential ingredient for the generation of earthquakes. In the laboratory, healing is thought to be the result of thermally activated mechanisms that weld together micrometre-sized asperity contacts on the fault surface, but the relationship between laboratory measures of fault healing and the seismically observable properties of earthquakes is at present not well defined. Here we report on laboratory experiments and seismological observations that show how the spectral properties of earthquakes vary as a function of fault healing time. In the laboratory, we find that increased healing causes a disproportionately large amount of high-frequency seismic radiation to be produced during fault rupture. We observe a similar connection between earthquake spectra and recurrence time for repeating earthquake sequences on natural faults. Healing rates depend on pressure, temperature and mineralogy, so the connection between seismicity and healing may help to explain recent observations of large megathrust earthquakes which indicate that energetic, high-frequency seismic radiation originates from locations that are distinct from the geodetically inferred locations of large-amplitude fault slip.

Hertzian impact: experimental study of the force pulse and resulting stress waves.

Ball impact has long been used as a repeatable source of stress waves in solids. The amplitude and frequency content of the waves are a function of the force-time history, or force pulse, that the ball imposes on the massive body. In this study, Glaser-type conical piezoelectric sensors are used to measure vibrations induced by a ball colliding with a massive plate. These measurements are compared with theoretical estimates derived from a marriage of Hertz theory and elastic wave propagation. The match between experiment and theory is so close that it not only facilitates the absolute calibration the sensors but it also allows the limits of Hertz theory to be probed. Glass, ruby and hardened steel balls 0.4 to 2.5 mm in diameter were dropped onto steel, glass, aluminum, and polymethylmethacrylate plates at a wide range of approach velocities, delivering frequencies up to 1.5 MHz into these materials. Effects of surface properties and yielding of the plate material were analyzed via the resulting stress waves and simultaneous measurements of the balls coefficient of restitution. The sensors are sensitive to surface normal displacements down to about +/-1 pm in the frequency range of 20 kHz to over 1 MHz.

Mobile Phones as Seismologic Sensors: Automating Data Extraction for the iShake System

There are a variety of approaches to seismic sensing, which range from collecting sparse measurements with high-fidelity seismic stations to non-quantitative, post-earthquake surveys. The sparse nature of the high-fidelity stations and the inaccuracy of the surveys create the need for a high-density, semi-quantitative approach to seismic sensing. To fill this void, the UC Berkeley iShake project designed a mobile client-backend server architecture that uses sensor-equipped mobile devices to measure earthquake ground shaking. iShake provides the general public with a service to more easily contribute more quantitatively significant data to earthquake research by automating the data collection and reporting mechanisms via the iShake mobile application. The devices act as distributed sensors that enable measurements to be taken and transmitted with a cellular network connection. Shaking table testing was used to assess the quality of the measurements obtained from the iPhones and iPods on a benchmark of 150 ground motions. Once triggered by a shaking event, the devices transmit sensor data to a backend server for further processing. After a seismic event is verified by high-fidelity stations, filtering algorithms are used to detect falling phones, as well as device-specific responses to the event. A method was developed to determine the absolute orientation of a device to estimate the direction of first motion of a seismic event. A “virtual earthquake” pilot test was conducted on the UC Berkeley campus to verify the operation of the iShake system. By designing and fully implementing a system architecture, developing signal processing techniques unique to mobile sensing, and conducting shaking table tests to confirm the validity of the sensing platform, the iShake project serves as foundational work for further studies in seismic sensing on mobile devices.

Results of Using a Wireless Inertial Measuring System to Quantify Gait Motions in Control Subjects

Gait analysis is important for the diagnosis of many neurological diseases such as Parkinsons. The discovery and interpretation of minor gait abnormalities can aid in early diagnosis. We have used an inertial measuring system mounted on the subjects foot to provide numerical measures of a subjects gait (3-D displacements and rotations), thereby creating an automated tool intended to facilitate diagnosis and enable quantitative prognostication of various neurological disorders in which gait is disturbed. This paper describes the process used for ensuring that these inertial measurement units yield accurate and reliable displacement and rotation data, and for validating the preciseness and robustness of the gait-deconstruction algorithms. It also presents initial results from control subjects, focusing on understanding the data recorded by the shoe-mounted sensor to quantify relevant gait-related motions.

Characterization of gait abnormalities in Parkinson's disease using a wireless inertial sensor system

Gait analysis is important in diagnosing and evaluating certain neurological diseases such as Parkinsons disease (PD). In this paper, we show the ability of our wireless inertial sensor system to characterize gait abnormalities in PD. We obtain physical features of pitch, roll, and yaw rotations of the foot during walking, use principal component analysis (PCA) to select features, and use the support vector machine (SVM) method to create a classification model. In the binary classification task of detecting the presence of PD by distinguishing between PD and control subjects, the model performs with over 93% sensitivity and specificity, and 97.7% precision. Using a cost-sensitive learner to reflect the different costs associated with misclassifying PD and control subjects, performance of 100% specificity and precision is achieved, while maintaining sensitivity of close to 89%. In the multi-class classification task of characterizing parkinsonian gait by distinguishing among PD with significant gait disturbance, PD with no significant gait disturbance, and control subjects, 91.7% class recall for control subjects is achieved and the model performs with 84.6% precision for PD subjects with significant gait disturbance. The features selected for this classification task indicate the features of gait that are principal in discriminating gait abnormalities due to PD compared to a normal gait. These results demonstrate the ability of our wireless inertial sensor system to successfully detect the presence of PD based on physical features of gait and to identify the specific features that characterize parkinsonian gait.

The streaming potential of liquid carbon dioxide in Berea sandstone

We report here, for the first time, evolution of the streaming potential coupling coefficient as liquid carbon dioxide infiltrates Berea sandstone. Using 125 Omega-m tap water, the coupling coefficient determined before and after each CO2 flood of five samples averaged approximately -30 mV/0.1 MPa. After liquid CO2 passed through the specimens displacing all mobile pore water, trapped water remained and the coupling coefficient was approximately -3 mV/0.1 MPa. A bound water limit of the coupling coefficient for liquid CO2 flow was foundusing an air-dried sample to be -0.02 mV/0.1 MPa. For initially water-saturated samples, bulk resistivity varied during CO2 invasion from 330 Ohm-m, to 150 Ohm-m during CO2/water mixing, to a final value of 380 Ohm-m. Results suggest that trapped and bound water control electrical conduction and the electrokinetic response. Applications include monitoring CO2 injectate in subsurface reservoirs using the self potential method.

Self-potential observations during hydraulic fracturing

Self-Potential Observations During Hydraulic Fracturing Jeffrey R. Moore Steven D. Glaser University of California, Berkeley Lawrence Berkeley National Laboratory Department of Civil and Environmental Engineering 760 Davis Hall Berkeley, CA USA E-mail: moore@ce.berkeley.edu Abstract The self-potential (SP) response during hydraulic fracturing of intact Sierra granite was investigated in the laboratory. Excellent correlation of pressure drop and SP suggests that the SP response is created primarily by electrokinetic coupling. For low pressures, the variation of SP with pressure drop is linear, indicating a constant coupling coefficient (Cc) of -200 mV/MPa. However for pressure drops >2 MPa, the magnitude of the Cc increases by 80% in an exponential trend. This increasing Cc is related to increasing permeability at high pore pressures caused by dilatancy of micro-cracks, and is explained by a decrease in the hydraulic tortuosity. Resistivity measurements reveal a decrease of 2% prior to hydraulic fracturing and a decrease of ~35% after fracturing. An asymmetric spatial SP response created by injectate diffusion into dilatant zones is observed prior to hydraulic fracturing, and in most cases this SP variation revealed the impending crack geometry seconds before failure. At rupture, injectate rushes into the new fracture area where the zeta potential is different than in the rock porosity, and an anomalous SP spike is observed. After fracturing, the spatial SP distribution reveals the direction of fracture propagation. Finally, during tensile cracking in a point load device with no water flow, a SP spike is observed that is caused by contact electrification. However, the time constant of this event is much less than that for transients observed during hydraulic fracturing, suggesting that SP created solely from material fracture does not contribute to the SP response during hydraulic fracturing. 1. Introduction Hydraulic fracturing creates a network of tensile fractures in low-permeability reservoir rock by introducing high fluid pressures at depth in a borehole. Permeability Moore and Glaser, in press JGR, B – 2006JB004373