Exploring sensor data management

The increasing availability of cheap, small, low-power sensor hardware and the ubiquity of wired and wireless networks has led to the prediction that `smart evironments' will emerge in the near future. The sensors in these environments collect detailed information about the situation people are in, which is used to enhance information-processing applications that are present on their mobile and `ambient' devices.\ud \ud Bridging the gap between sensor data and application information poses new requirements to data management. This report discusses what these requirements are and documents ongoing research that explores ways of thinking about data management suited to these new requirements: a more sophisticated control flow model, data models that incorporate time, and ways to deal with the uncertainty in sensor data

Applications of Antenna Technology in Sensors

During the past few decades, information technologies have been evolving at a tremendous rate, causing profound changes to our world and to our ways of living. Emerging applications have opened u[ new routes and set new trends for antenna sensors. With the advent of the Internet of Things (IoT), the adaptation of antenna technologies for sensor and sensing applications has become more important. Now, the antennas must be reconfigurable, flexible, low profile, and low-cost, for applications from airborne and vehicles, to machine-to-machine, IoT, 5G, etc. This reprint aims to introduce and treat a series of advanced and emerging topics in the field of antenna sensors

Early Abstraction of Inertial Sensor Data for Long-Term Deployments

Advances in microelectronics over the last decades have led to miniaturization of computing devices and sensors. A driving force to use these in various application scenarios is the desire to grasp physical phenomena from the environment, objects and living entities. We investigate sensing in two particularly challenging applications: one where small sensor modules are worn by people to detect their activities, and one where wirelessly networked sensors observe events over an area. This thesis takes a data-driven approach, focusing on human motion and vibrations caused by trains that are captured by accelerometer sensors as time series and shall be analyzed for characteristic patterns. For both, the acceleration sensor must be sampled at relatively high rates in order to capture the essence of the phenomena, and remain active for long stretches of time. The large amounts of gathered sensor data demand novel approaches that are able to swiftly process the data while guaranteeing accurate classification results. The following contributions are made in particular: * A data logger that would suit the requirements of long-term deployments is designed and evaluated. In a power profiling study both hardware components and firmware parameters are thoroughly tested, revealing that the sensor is able to log acceleration data at a sampling rate of 100 Hertz for up to 14 full days on a single battery charge. * A technique is proposed that swiftly and accurately abstracts an original signal with a set of linear segments, thus preserving its shape, while being twice as fast as a similar method. This allows for more efficient pattern matching, since for each pattern only a fraction of data points must be considered. A second study shows that this algorithm can perform data abstraction directly on a data logger with limited resources. * The railway monitoring scenario requires streaming vibration data to be analyzed for particular sparse and complex events directly on the sensor node, extracting relevant information such as train type or length from the shape of the vibration footprint. In a study conducted on real-world data, a set of efficient shape features is identified that facilitates train type prediction and length estimation with very high accuracies. * To achieve fast and accurate activity recognition for long-term bipolar patients monitoring scenarios, we present an approach that relies on the salience of motion patterns (motifs) that are characteristic for the target activity. These motifs are accumulated by using a symbolic abstraction that encodes the shape of the original signal. A large-scale study shows that a simple bag-of-words classifier trained with extracted motifs is on par with traditional approaches regarding the accuracy, while being much faster. * Some activities are hard to predict from acceleration data alone with the aforementioned approach. We argue that human-object interactions, captured as human motion and grasped objects through RFID, are an ideal supplement. A custom bracelet-like antenna to detect objects from up to 14 cm is proposed, along with a novel benchmark to evaluate such wearable setups. By aiming for wearable and wirelessly networked sensor systems, these contributions apply for particularly challenging applications that require long-term deployments of miniature sensors in general. They form the basis of a framework towards efficient event detection that relies heavily on early data abstraction and shape-based features for time series, while focusing less on the classification techniques

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools

Digital Beamforming Techniques for Passive UHF RFID Tag Localization

Radio-frequency identification (RFID) technology is on the way to substitute traditional bar codes in many fields of application. Especially the availability of passive ultra-high frequency (UHF) RFID transponders (or tags) in the frequency band between 860 MHz and 960 MHz has fostered the global application in supply chain management. However, the full potential of these systems will only be exploited if the identification of objects is complemented by accurate and robust localization. Passive UHF RFID tags are cost-effective, very small, extremely lightweight, maintenancefree, rugged and can be produced as adhesive labels that can be attached to almost any object. Worldwide standards and frequency regulations have been established and a wide infrastructure of identification systems is operated today. However, the passive nature of the technology requires a simple communication protocol which results in two major limitations with respect to its use for localization purposes: the small signal bandwidth and the small allocated frequency bandwidth. In the presence of multipath reflections, these limitations reduce the achievable localization accuracy and reliability. Thus, new methods have to be found to realize passive UHF RFID localization systems which provide sufficient performance in typical multipath situations. In this thesis, an enhanced transmission channel model for passive UHF RFID localization systems has been proposed which allows an accurate estimation of the channel behaviour to multipath. It has been used to design a novel simulation environment and to identify three solutions to minimize multipath interference: a) by varying the channel interface parameters, b) by applying diversity techniques, c) by installation of UHF absorbers. Based on the enhanced channel model, a new method for tag readability prediction with high reliability has been introduced. Furthermore, a novel way to rate the magnitude of multipath interference has been proposed. A digital receiver beamforming localization method has been presented which uses the Root MUSIC algorithm for angulation of a target tag and multipath reducing techniques for an optimum localization performance. A new multiangulation algorithm has been proposed to enable the application of diversity techniques. A novel transmitter beamforming localization approach has been presented which exploits the precisely defined response threshold of passive tags in order to achieve high robustness against multipath. The basic technique has been improved significantly with respect to angular accuracy and processing times. Novel experimental testbeds for receiver and transmitter beamforming have been designed, built and used for verification of the localization performance in real-world measurements. All the improvements achieved contribute to an enhancement of the accuracy and especially the robustness of passive UHF RFID localization systems in multipath environments which is the main focus of this researc

Angle of Arrival Estimation Utilising Frequency Diverse Radio Antenna Arrays

The purpose of this research is to investigate a novel way of combining carrier signals that are transmitted successively over Multiple Frequencies (MF) and traditional metrics to improve AoA estimation. Every signal contains three metrics, amplitude, phase, and frequency. To achieve localisation, current systems utilise the metrics of amplitude (also known as Received Signal Strength (RSS)) and phase that resolves the AoA. However, the metric of frequency is mostly used with Orthogonal Frequency-Division Multiplexing (OFDM) to increase the number of RSS and AoA metrics, which is not optimal. This research answers two questions. Can the use of MF improve AoA estimation? Also, how can MF and traditional metrics be combined for AoA estimation? The aim is to prove that the metric of frequency can be utilised more optimally. Therefore, measurements of RSS and AoA are performed in different environments for MF. To perform these measurements, ten frequency diverse Software Defined Radios (SDRs) are employed. A novel technique to time/frequency synchronise the SDRs is developed and presented. Moreover, a ten element Uniform Linear Array (ULA) is designed, simulated and manufactured. The outcomes of this research are two novel algorithms for the MF AoA estimation of a carrier transmitter. Findings of the first algorithm show that the use of MF with the RSS metric performs equally with current systems that have a higher cost and complexity. The second algorithm that utilises MF with the AoA metric demonstrates a significant reduction in the AoA estimation error, compared to current systems. Specifically, for 50\% of the measured cases the AoA estimation error is reduced by 3.7 degrees, while for 95\% of the measured cases the AoA estimation error is reduced by 27 degrees. Hence, this research proves that MF with traditional metrics can reduce system complexity and greatly improve AoA estimation

A Model for Automated Construction Materials Tracking

Materials management is a critical factor in construction project performance, particularly in the industrial sector. Research has shown that construction materials and installed equipment may constitute more than 50% of the total cost for a typical industrial project. Therefore the proper management of this single largest component can improve the productivity and cost efficiency of a project and help ensure its timely completion. One of the major problems associated with construction materials management is tracking materials in the supply chain and tracking their locations at job sites. Identification is integral to this process. Research projects conducted during the last decade to automate the identification and tracking of materials have concluded that such automation can increase productivity and cost efficiency as well as improve schedule performance, reduce the number of lost items, improve route and site optimization, and improve data entry. However, these technologies have been rapidly evolving, and knowledge concerning their implementation is sparse. One new approach enables locating of components within a few meters at a cost at least a magnitude lower than preceding technologies. It works by combining GPS located reads of RFID tags read at a rate of several thousand Hertz in order to estimate the location of these inexpensive tags which are attached to key construction materials. This technology was rapidly prototyped and deployed on two large industrial construction projects in 2007 and 2008. This thesis analyzes and synthesizes the data and experiences from these unique and large scale field trials as well as the literature in order to develop a general implementation model for automated construction materials tracking for industrial projects. It is concluded from the model that this new automated construction materials tracking technology is likely to be successful if implemented full scale on well selected future projects. This conclusion is supported by subsequent industry decisions

Activity-Based Data Fusion for the Automated Progress Tracking of Construction Projects

In recent years, many researchers have investigated automated progress tracking for construction projects. These efforts range from 2D photo-feature extraction to 3D laser scanners and radio frequency identification (RFID) tags. A multi-sensor data fusion model that utilizes multiple sources of information would provide a better alternative than a single-source model for tracking project progress. However, many existing fusion models are based on data fusion at the sensor and object levels and are therefore incapable of capturing critical information regarding a number of activities and processes on a construction site, particularly those related to non-structural trades such as welding, inspection, and installation activities. In this research, a workflow based data fusion framework is developed for construction progress, quality and productivity assessment. The developed model is based on tracking construction activities as well as objects, in contrast to the existing sensor-based models that are focussed on tracking objects. Data sources include high frequency automated technologies including 3D imaging and ultra-wide band (UWB) positioning. Foreman reports, schedule information, and other data sources are included as well. Data fusion and management process workflow implementation via a distributed computing network and archiving using a cloud-based architecture are both illustrated. Validation was achieved using a detailed laboratory experimental program as well as an extensive field implementation project. The field implementation was conducted using five months of data acquired on the University of Waterloo Engineering VI construction project, yielding promising results. The data fusion processes of this research provide more accurate and more reliable progress and earned value estimates for construction project activities, while the developed data management processes enable the secure sharing and management of construction research data with the construction industry stakeholders as well as with researchers from other institutions

The always best positioned paradigm for mobile indoor applications

In this dissertation, methods for personal positioning in outdoor and indoor environments are investigated. The Always Best Positioned paradigm, which has the goal of providing a preferably consistent self-positioning, will be defined. Furthermore, the localization toolkit LOCATO will be presented, which allows to easily realize positioning systems that follow the paradigm. New algorithms were developed, which particularly address the robustness of positioning systems with respect to the Always Best Positioned paradigm. With the help of this toolkit, three example positioning-systems were implemented, each designed for different applications and requirements: a low-cost system, which can be used in conjunction with user-adaptive public displays, a so-called opportunistic system, which enables positioning with room-level accuracy in any building that provides a WiFi infrastructure, and a high-accuracy system for instrumented environments, which works with active RFID tags and infrared beacons. Furthermore, a new and unique evaluation-method for positioning systems is presented, which uses step-accurate natural walking-traces as ground truth. Finally, six location based services will be presented, which were realized either with the tools provided by LOCATO or with one of the example positioning-systems.In dieser Doktorarbeit werden Methoden zur Personenpositionierung im Innen- und Außenbereich von Gebäuden untersucht. Es wird das ,,Always Best Positioned” Paradigma definiert, welches eine möglichst lückenlose Selbstpositionierung zum Ziel hat. Weiterhin wird die Lokalisierungsplattform LOCATO vorgestellt, welche eine einfache Umsetzung von Positionierungssystemen ermöglicht. Hierzu wurden neue Algorithmen entwickelt, welche gezielt die Robustheit von Positionierungssystemen unter Berücksichtigung des ,,Always Best Positioned” Paradigmas angehen. Mit Hilfe dieser Plattform wurden drei Beispiel Positionierungssysteme entwickelt, welche unterschiedliche Einsatzgebiete berücksichtigen: Ein kostengünstiges System, das im Zusammenhang mit benutzeradaptiven öffentlichen Bildschirmen benutzt werden kann; ein sogenanntes opportunistisches Positionierungssystem, welches eine raumgenaue Positionierung in allen Gebäuden mit WLAN-Infrastruktur ermöglicht, sowie ein metergenaues Positionierungssystem, welches mit Hilfe einer Instrumentierung aus aktiven RFID-Tags und Infrarot-Baken arbeitet. Weiterhin wird erstmalig eine Positionierungsevaluation vorgestellt, welche schrittgenaue, natürliche Bewegungspfade als Referenzsystem einsetzt. Im Abschluss werden 6 lokationsbasierte Dienste vorgestellt, welche entweder mit Hilfe von LOCATO oder mit Hilfe einer der drei Beispiel-Positionierungssysteme entwickelt wurden

Anthills built to order : automating construction with artificial swarms

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (leaves 110-116).Social insects build large, complex structures, which emerge through the collective actions of many simple agents acting with no centralized control or preplanning. These natural systems motivate investigating the use of artificial swarms to automate construction or fabrication. The goal is to be able to take an unspecified number of simple robots and a supply of building material, give the system a high-level specification for any arbitrary structure desired, and have a guarantee that it will produce that structure without further intervention. In this thesis I describe such a distributed system for automating construction, in which autonomous mobile robots collectively build user-specified structures from square building blocks. The approach preserves many desirable features of the natural systems, such as considerable parallelism and robustness to factors like robot loss and variable order or timing of actions. Further, unlike insect colonies, it can build particular desired structures according to a high-level design provided by the user. Robots in this system act without explicit communication or cooperation, instead using the partially completed structure to coordinate their actions.(cont.) This mechanism is analogous to that of stigmergy used by social insects, in which insects take actions that affect the environment, and the environmental state influences further actions. I introduce a framework of extended stigmergy in which building blocks are allowed to store, process or communicate information. Increasing the capabilities of the building material (rather than of the robots) in this way increases the availability of nonlocal structure information. Benefits include significant improvements in construction speed and in ability to take advantage of the parallelism of the swarm. This dissertation describes system design and control rules for decentralized teams of robots that provably build arbitrary solid structures in two dimensions. I present a hardware prototype, and discuss extensions to more general structures, including those built with multiple block types and in three dimensions.by Justin Werfel.Ph.D