Full-View Coverage Problems in Camera Sensor Networks

Camera Sensor Networks (CSNs) have emerged as an information-rich sensing modality with many potential applications and have received much research attention over the past few years. One of the major challenges in research for CSNs is that camera sensors are different from traditional scalar sensors, as different cameras from different positions can form distinct views of the object in question. As a result, simply combining the sensing range of the cameras across the field does not necessarily form an effective camera coverage, since the face image (or the targeted aspect) of the object may be missed. The angle between the object\u27s facing direction and the camera\u27s viewing direction is used to measure the quality of sensing in CSNs instead. This distinction makes the coverage verification and deployment methodology dedicated to conventional sensor networks unsuitable. A new coverage model called full-view coverage can precisely characterize the features of coverage in CSNs. An object is full-view covered if there is always a camera to cover it no matter which direction it faces and the camera\u27s viewing direction is sufficiently close to the object\u27s facing direction. In this dissertation, we consider three areas of research for CSNS: 1. an analytical theory for full-view coverage; 2. energy efficiency issues in full-view coverage CSNs; 3. Multi-dimension full-view coverage theory. For the first topic, we propose a novel analytical full-view coverage theory, where the set of full-view covered points is produced by numerical methodology. Based on this theory, we solve the following problems. First, we address the full-view coverage holes detection problem and provide the healing solutions. Second, we propose $k$-Full-View-Coverage algorithms in camera sensor networks. Finally, we address the camera sensor density minimization problem for triangular lattice based deployment in full-view covered camera sensor networks, where we argue that there is a flaw in the previous literature, and present our corresponding solution. For the second topic, we discuss lifetime and full-view coverage guarantees through distributed algorithms in camera sensor networks. Another energy issue we discuss is about object tracking problems in full-view coverage camera sensor networks. Next, the third topic addresses multi-dimension full-view coverage problem where we propose a novel 3D full-view coverage model, and we tackle the full-view coverage optimization problem in order to minimize the number of camera sensors and demonstrate a valid solution. This research is important due to the numerous applications for CSNs. Especially some deployment can be in remote locations, it is critical to efficiently obtain accurate meaningful data

Air data measurement system for space shuttle

It is concluded that air data measurements of angle of attack and sideslip are needed to control the space shuttle vehicles. The basis for this conclusion, along with recommended sensor design and implementation, are described

Scanning nano-spin ensemble microscope for nanoscale magnetic and thermal imaging

Quantum sensors based on solid-state spins provide tremendous opportunities in a wide range of fields from basic physics and chemistry to biomedical imaging. However, integrating them into a scanning probe microscope to enable practical, nanoscale quantum imaging is a highly challenging task. Recently, the use of single spins in diamond in conjunction with atomic force microscopy techniques has allowed significant progress towards this goal, but generalisation of this approach has so far been impeded by long acquisition times or by the absence of simultaneous topographic information. Here we report on a scanning quantum probe microscope which solves both issues, by employing a nano-spin ensemble hosted in a nanodiamond. This approach provides up to an order of magnitude gain in acquisition time, whilst preserving sub-100 nm spatial resolution both for the quantum sensor and topographic images. We demonstrate two applications of this microscope. We first image nanoscale clusters of maghemite particles through both spin resonance spectroscopy and spin relaxometry, under ambient conditions. Our images reveal fast magnetic field fluctuations in addition to a static component, indicating the presence of both superparamagnetic and ferromagnetic particles. We next demonstrate a new imaging modality where the nano-spin ensemble is used as a thermometer. We use this technique to map the photo-induced heating generated by laser irradiation of a single gold nanoparticle in a fluid environment. This work paves the way towards new applications of quantum probe microscopy such as thermal/magnetic imaging of operating microelectronic devices and magnetic detection of ion channels in cell membranes.Comment: 22 pages including Supporting Information. Changes to v1: affiliations and funding information updated, plus minor revisions to the main tex

Self organization of sensor networks for energy-efficient border coverage

Networking together hundreds or thousands of cheap sensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. As sensor nodes are typically battery operated, it is important to efficiently use the limited energy of the nodes to extend the lifetime of the wireless sensor network (WSN). One of the fundamental issues in WSNs is the coverage problem. In this paper, the border coverage problem in WSNs is rigorously analyzed. Most existing results related to the coverage problem in wireless sensor networks focused on planar networks; however, three dimensional (3D) modeling of the sensor network would reflect more accurately real-life situations. Unlike previous works in this area, we provide distributed algorithms that allow the selection and activation of an optimal border cover for both 2D and 3D regions of interest. We also provide self-healing algorithms as an optimization to our border coverage algorithms which allow the sensor network to adaptively reconfigure and repair itself in order to improve its own performance. Border coverage is crucial for optimizing sensor placement for intrusion detection and a number of other practical applications

A new Measure for Optimization of Field Sensor Network with Application to LiDAR

This thesis proposes a solution to the problem of modeling and optimizing the field sensor network in terms of the coverage performance. The term field sensor is referred to a class of sensors which can detect the regions in 2D/3D spaces through non-contact measurements. The most widely used field sensors include cameras, LiDAR, ultrasonic sensor, and RADAR, etc. The key challenge in the applications of field sensor networks, such as area coverage, is to develop an effective performance measure, which has to involve both sensor and environment parameters. The nature of space distribution in the case of the field sensor incurs a great deal of difficulties for such development and, hence, poses it as a very interesting research problem. Therefore, to tackle this problem, several attempts have been made in the literature. However, they have failed to address a comprehensive and applicable approach to distinctive types of field sensors (in 3D), as only coverage of a particular sensor is usually addressed at the time. In addition, no coverage model has been proposed yet for some types of field sensors such as LiDAR sensors. In this dissertation, a coverage model is obtained for the field sensors based on the transformation of sensor and task parameters into the sensor geometric model. By providing a mathematical description of the sensor’s sensing region, a performance measure is introduced which characterizes the closeness between a single sensor and target configurations. In this regard, the first contribution is developing an Infinity norm based measure which describes the target distance to the closure of the sensing region expressed by an area-based approach. The second contribution can be geometrically interpreted as mapping the sensor’s sensing region to an n-ball using a homeomorphism map and developing a performance measure. The third contribution is introducing the measurement principle and establishing the coverage model for the class of solid-state (flash) LiDAR sensors. The fourth contribution is point density analysis and developing the coverage model for the class of mechanical (prism rotating mechanism) LiDAR sensors. Finally, the effectiveness of the proposed coverage model is illustrated by simulations, experiments, and comparisons is carried out throughout the dissertation. This coverage model is a powerful tool as it applies to the variety of field sensors

SeaWiFS technical report series. Volume 5: Ocean optics protocols for SeaWiFS validation

Protocols are presented for measuring optical properties, and other environmental variables, to validate the radiometric performance of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and to develop and validate bio-optical algorithms for use with SeaWiFS data. The protocols are intended to establish foundations for a measurement strategy to verify the challenging SeaWiFS accuracy goals of 5 percent in water-leaving radiances and 35 percent in chlorophyll alpha concentration. The protocols first specify the variables which must be measured, and briefly review rationale. Subsequent chapters cover detailed protocols for instrument performance specifications, characterizing and calibration instruments, methods of making measurements in the field, and methods of data analysis. These protocols were developed at a workshop sponsored by the SeaWiFS Project Office (SPO) and held at the Naval Postgraduate School in Monterey, California (9-12 April, 1991). This report is the proceedings of that workshop, as interpreted and expanded by the authors and reviewed by workshop participants and other members of the bio-optical research community. The protocols are a first prescription to approach unprecedented measurement accuracies implied by the SeaWiFS goals, and research and development are needed to improve the state-of-the-art in specific areas. The protocols should be periodically revised to reflect technical advances during the SeaWiFS Project cycle

Electromagnetic containerless processing requirements and recommended facility concept and capabilities for space lab

Containerless melting, reaction, and solidification experiments and processes which potentially can lead to new understanding of material science and production of new or improved materials in the weightless space environment are reviewed in terms of planning for spacelab. Most of the experiments and processes discussed are amenable to the employment of electromagnetic position control and electromagnetic induction or electron beam heating and melting. The spectrum of relevant properties of materials, which determine requirements for a space laboratory electromagnetic containerless processing facility are reviewed. Appropriate distributions and associated coil structures are analyzed and compared on the basis of efficiency, for providing the functions of position sensing, control, and induction heating. Several coil systems are found capable of providing these functions. Exchangeable modular coils in appropriate sizes are recommended to achieve the maximum power efficiencies, for a wide range of specimen sizes and resistivities, in order to conserve total facility power

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers