Sensor networks for geospatial event detection - theory and applications

This thesis presents theories, analyses, and algorithms for detecting and estimating parameters of geospatial events with today's large, noisy sensor networks. A geospatial event is initiated by a significant change in the state of points in a region in a 3-D space over an interval of time. After the event is initiated it may change the state of points over larger regions and longer periods of time. Networked sensing is a typical approach for geospatial event detection. In contrast to traditional sensor networks comprised of a small number of high quality (and expensive) sensors, trends in personal computing devices and consumer electronics have made it possible to build large, dense networks at a low cost. The changes in sensor capability, network composition, and system constraints call for new models and algorithms suited to the opportunities and challenges of the new generation of sensor networks. This thesis offers a single unifying model and a Bayesian framework for analyzing different types of geospatial events in such noisy sensor networks. It presents algorithms and theories for estimating the speed and accuracy of detecting geospatial events as a function of parameters from both the underlying geospatial system and the sensor network. Furthermore, the thesis addresses network scalability issues by presenting rigorous scalable algorithms for data aggregation for detection. These studies provide insights to the design of networked sensing systems for detecting geospatial events. In addition to providing an overarching framework, this thesis presents theories and experimental results for two very different geospatial problems: detecting earthquakes and hazardous radiation. The general framework is applied to these specific problems, and predictions based on the theories are validated against measurements of systems in the laboratory and in the field.

Fabrication of an integrated Raman sensor by selective surface metallization using a femtosecond laser oscillator

We demonstrate that a Raman sensor integrated with a micro-heater, a microfluidic chamber, and a surface-enhanced Raman scattering (SERS) substrate can be fabricated in a glass chip by femtosecond laser micromachining. The micro-heater and the SERS substrate are fabricated by selective metallization on the glass surface using a femtosecond laser oscillator, whereas the microfluidic chamber embedded in the glass sample is fabricated by femtosecond laser ablation using a femtosecond laser amplifier. We believed that this new strategy for fabricating multifunctional integrated microchips has great potential application for lab-on-a-chips. (C) 2008 Elsevier B.V. All rights reserved.

Selective data gathering in community sensor networks

Smartphones and other powerful sensor-equipped consumer devices make it possible to sense the physical world at an unprecedented scale. Nearly 2 million Android and iOS devices are activated every day, each carrying numerous sensors and a high-speed internet connection. Whereas traditional sensor networks have typically deployed a fixed number of devices to sense a particular phenomena, community networks can grow as additional participants choose to install apps and join the network. In principle, this allows networks of thousands or millions of sensors to be created quickly and at low cost. However, making reliable inferences about the world using so many community sensors involves several challenges, including scalability, data quality, mobility, and user privacy.

This thesis focuses on how learning at both the sensor- and network-level can provide scalable techniques for data collection and event detection. First, this thesis considers the abstract problem of distributed algorithms for data collection, and proposes a distributed, online approach to selecting which set of sensors should be queried. In addition to providing theoretical guarantees for submodular objective functions, the approach is also compatible with local rules or heuristics for detecting and transmitting potentially valuable observations. Next, the thesis presents a decentralized algorithm for spatial event detection, and describes its use detecting strong earthquakes within the Caltech Community Seismic Network. Despite the fact that strong earthquakes are rare and complex events, and that community sensors can be very noisy, our decentralized anomaly detection approach obtains theoretical guarantees for event detection performance while simultaneously limiting the rate of false alarms.

Fiber Bragg grating temperature sensor for multiplexed measurement with high resolution

A novel fiber Bragg grating temperature sensor is proposed and experimentally demonstrated with a long-period grating as a linear response edge filter to convert wavelength into intensity-encoded information for interrogation. The sensor is embedded into an aluminum substrate with a larger coefficient of thermal expansion to enhance its temperature sensitivity. A large dynamic range of 110 degreesC and a high resolution of 0.02 degreesC are obtained in the experiments. The technique can be used for multiplexed measurements with one broadband source and one long-period grating, and therefore is low Cost. (C) 2004 Society of PhotoOptical Instrumentation Engineers.

Highly sensitive wave-front sensor with a non-zero-order phase plate

We propose a novel highly sensitive wave front detection method for a quick check of a flat wave front by taking advantage of a non-zero-order pi phase plate that yields a non-zero-order diffraction pattern. When a light beam with a flat wave front illuminates a phase plate, the zero-order intensity is zero. When there is a slight distortion of the wave front, the zero-order intensity increases. The ratio of first-order intensity to that of zero-order intensity is used as the criterion with which to judge whether the wave front under test is flat, eliminating the influence of background light. Experimental results demonstrate that this method is efficient, robust, and cost-effective and should be highly interesting for a quick check of a flat wave front of a large-aperture laser beam and adaptive optical systems. (c) 2005 Optical Society of America.

Coma measurement using a PSM and transmission image sensor

As feature size decreases, especially with the use of resolution enhancement technique, requirements for the coma aberrations in the projection lenses of the lithographic tools have become extremely severe. So, fast and accurate in situ measurement of coma is necessary. In the present paper, we present a new method for characterizing the coma aberrations in the projection lens using a phase-shifting mask and a transmission image sensor. By measuring the image positions at multiple NA and partial coherence settings, we are able to extract the coma aberration. The simulation results show that the accuracy of coma measurement increases approximately 20% compared to the previous straightforward measurement technique. (c) 2005 Elsevier GmbH. All rights reserved.

A novel fiber Bragg grating high-temperature sensor

A novel fiber Bragg grating (FBG) sensor for the measurement of high temperature is proposed and experimentally demonstrated. The interrogation system of the sensor system is simple, low cost but effective. The sensor head is comprised of one FBG and two metal rods. The lengths of the rods are different from each other. The coefficients of thermal expansion of the rods are also different from each other. The FBG will be strained by the sensor head when the temperature to be measured changes. The temperature is measured basis of the wavelength shifts of the FBG induced by strain. A dynamic range of 0-800 degrees C and a resolution of 1 degrees C have been obtained by the sensor system. The experiment results agree with theoretical analyses. (c) 2007 Elsevier GmbH. All rights reserved.

On a fiber grating sensor system with the capacity of cross-sensitivity discrimination

A novel fiber Bragg grating (FBG) sensor system based on an interrogating technique by two parallel matched gratings was designed and theoretically discussed. With an interrogation grating playing the role of temperature compensation grating simultaneously, the wavelength drifts induced by temperature and strain were discriminated. Additionally, the expressions of temperature and strain were deduced for our solution, and dual-value problem and cross sensitivity were solved synchronously through data processing. The influence of the FBG's parameters on the dynamic range and precision was discussed. Besides, the change of environment temperature cannot influence the dynamic range of the sensor system through temperature tuning. The system proposed in this paper will be of great significance to accelerate the real engineering applications of FBG sensing techniques. (c) 2007 Elsevier GmbH. All rights reserved.