RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home systems.Comment: 18 pages, 2 figures, 3 table

Localisation in wireless sensor networks for disaster recovery and rescuing in built environments

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyProgress in micro-electromechanical systems (MEMS) and radio frequency (RF) technology has fostered the development of wireless sensor networks (WSNs). Different from traditional networks, WSNs are data-centric, self-configuring and self-healing. Although WSNs have been successfully applied in built environments (e.g. security and services in smart homes), their applications and benefits have not been fully explored in areas such as disaster recovery and rescuing. There are issues related to self-localisation as well as practical constraints to be taken into account. The current state-of-the art communication technologies used in disaster scenarios are challenged by various limitations (e.g. the uncertainty of RSS). Localisation in WSNs (location sensing) is a challenging problem, especially in disaster environments and there is a need for technological developments in order to cater to disaster conditions. This research seeks to design and develop novel localisation algorithms using WSNs to overcome the limitations in existing techniques. A novel probabilistic fuzzy logic based range-free localisation algorithm (PFRL) is devised to solve localisation problems for WSNs. Simulation results show that the proposed algorithm performs better than other range free localisation algorithms (namely DVhop localisation, Centroid localisation and Amorphous localisation) in terms of localisation accuracy by 15-30% with various numbers of anchors and degrees of radio propagation irregularity. In disaster scenarios, for example, if WSNs are applied to sense fire hazards in building, wireless sensor nodes will be equipped on different floors. To this end, PFRL has been extended to solve sensor localisation problems in 3D space. Computational results show that the 3D localisation algorithm provides better localisation accuracy when varying the system parameters with different communication/deployment models. PFRL is further developed by applying dynamic distance measurement updates among the moving sensors in a disaster environment. Simulation results indicate that the new method scales very well

A wireless sensor network-based approach to large-scale dimensional metrology

In many branches of industry, dimensional measurements have become an important part of the production cycle, in order to check product compliance with specifications. This task is not trivial especially when dealing with largescale dimensional measurements: the bigger the measurement dimensions are, the harder is to achieve high accuracies. Nowadays, the problem can be handled using many metrological systems, based on different technologies (e.g. optical, mechanical, electromagnetic). Each of these systems is more or less adequate, depending upon measuring conditions, user's experience and skill, or other factors such as time, cost, accuracy and portability. This article focuses on a new possible approach to large-scale dimensional metrology based on wireless sensor networks. Advantages and drawbacks of such approach are analysed and deeply discussed. Then, the article briefly presents a recent prototype system - the Mobile Spatial Coordinate-Measuring System (MScMS-II) - which has been developed at the Industrial Metrology and Quality Laboratory of DISPEA - Politecnico di Torino. The system seems to be suitable for performing dimensional measurements of large-size objects (sizes on the order of several meters). Owing to its distributed nature, the system - based on a wireless network of optical devices - is portable, fully scalable with respect to dimensions and shapes and easily adaptable to different working environments. Preliminary results of experimental tests, aimed at evaluating system performance as well as research perspectives for further improvements, are discusse

GUARDIANS final report

Emergencies in industrial warehouses are a major concern for firefghters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist fire fighters in searching a large warehouse. In this report we discuss the technology developed for a swarm of robots searching and assisting fire fighters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also one of the means to locate the robots and humans. Thus the robot swarm is able to locate itself and provide guidance information to the humans. Together with the re ghters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

Acoustic underwater target tracking methods using autonomous vehicles

Marine ecological research related to the increasing importance which the fisheries sector has reached so far, new methods and tools to study the biological components of our oceans are needed. The capacity to measure different population and environmental parameters of marine species allows a greater knowledge of the human impact, improving exploitation strategies of these resources. For example, the displacement capacity and mobility patterns are crucial to obtain the required knowledge for a sustainable management of fisheries. However, underwater localisation is one of the main problems which must be addressed in subsea exploration, where no Global Positioning System (GPS) is available. In addition to the traditional underwater localisation systems, such as Long BaseLine (LBL) or Ultra-Short BaseLine (USBL), new methods have been developed to increase navigation performance, flexibility, and to reduce deployment costs. For example, the Range-Only and Single-Beacon (ROSB) is based on an autonomous vehicle which localises and tracks different underwater targets using slant range measurements conducted by acoustic modems. In a moving target tracking scenario, the ROSB target tracking method can be seen as a Hidden Markov Model (HMM) problem. Using Bayes' rule, the probability distribution function of the HMM states can be solved by using different filtering methods. Accordingly, this thesis presents different strategies to improve the ROSB localisation and tracking methods for static and moving targets. Determining the optimal parameters to minimize acoustic energy use and search time, and to maximize the localisation accuracy and precision, is therefore one of the discussed aspects of ROSB. Thus, we present and compare different methods under different scenarios, both evaluated in simulations and field tests. The main mathematical notation and performance of each algorithm are presented, where the best practice has been derived. From a methodology point of view, this work advances the understanding of accuracy that can be achieved by using ROSB target tracking methods with autonomous vehicles. Moreover, whereas most of the work conducted during the last years has been focused on target tracking using acoustic modems, here we also present a novel method called the Area-Only Target Tracking (AOTT). This method works with commercially available acoustic tags, thereby reducing the costs and complexity over other tracking systems. These tags do not have bidirectional communication capabilities, and therefore, the ROSB techniques are not applicable. However, this method can be used to track small targets such as jellyfish due to the reduced tag's size. The methodology behind the area-only technique is shown, and results from the first field tests conducted in Monterey Bay area, California, are also presented.La biologia marina junt amb la importància que ha adquirit el sector pesquer, fa que es requereixin noves eines per a l’estudi dels nostres oceans. La capacitat de mesurar diferents poblacions i paràmetres ambientals d’espècies marines permet millorar el coneixement de l’impacte que l’ésser humà té sobre elles, millorant-ne els mètodes d’explotació. Per exemple, la capacitat de desplaçament i els patrons de moviment són crucials per obtenir el coneixement necessari per a una explotació sostenible de les pescaries involucrades. No obstant, la localització submarina és un dels principals problemes que s’ha de resoldre en l’explotació dels recursos submarins, on el sistema de posició global (GPS) no es pot utilitzar. A part dels mètodes tradicionals de posicionament submarí, com per exemple el Long Base-Line (LBL) o el Ultra-Short Base-Line (USBL), nous mètodes han estat desenvolupats per tal de millorar la navegació, la flexibilitat, i per reduir els costos de desplegament. Per exemple, el Range-Only and Single-Beacon (ROSB) utilitza un vehicle autònom per a localitzar i seguir diferents objectius submarins mitjançant mesures de rang realitzades a partir de mòdems acústics. En un escenari on l’objectiu a seguir és mòbil, el mètode ROSB de seguiment pot ser vist com a un problema de Hidden Markov Model (HMM). Aleshores, utilitzant la regla de Bayes, la funció de distribució de probabilitat dels estats del HMM pot ser solucionat utilitzant diferents mètodes de filtratge. Per tant, s’estudien diferents estratègies per millorar el sistema de localització i seguiment basat en ROSB, tant per objectius estàtics com mòbils. En aquesta tesis, presentem i comparem diferents mètodes utilitzant diferents escenaris, els quals s’han avaluat tant en simulacions com en proves de camp reals. A més, es presenten les principals notacions matemàtiques de cada algoritme i les millors pràctiques a utilitzar. Per tant, des d’un punt de vista metodològic, aquest treball fa un pas endavant en el coneixement de l’exactitud que es pot assolir utilitzant els mètodes de localització i seguiment d’espècies mitjançant algoritmes ROSB i vehicles autònoms. A més a més, mentre molts dels treballs realitzant durant els últims anys es centren en l’ús de mòdems acústics per al seguiment d’objectius submarins, en aquesta tesis es presenta un innovador mètode anomenat Area-Only Target Tracking (AOTT). Aquest sistema utilitza petites etiquetes acústiques comercials (tag), la qual cosa, redueix el cost i la complexitat en comparació amb els altres mètodes. Addicionalment, gràcies a l’ús d’aquests tags de dimensions reduïdes, aquest sistema permet seguir espècies marines com les meduses. La metodologia utilitzada per el mètode AOTT es mostra en aquesta tesis, on també es presenten els primers experiments realitzats a la badia de Monterey a Califòrnia

Wireless indoor localisation within the 5G internet of radio light

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonNumerous applications can be enhanced by accurate and efficient indoor localisation using wireless sensor networks, however trade-offs often exist between these two parameters. In this thesis, realworld and simulation data is used to examine the hybrid millimeter wave and Visible Light Communications (VLC) architecture of the 5G Internet of Radio Light (IoRL) Horizon 2020 project. Consequently, relevant localisation challenges within Visible Light Positioning (VLP) and asynchronous sampling networks are identified, and more accurate and efficient solutions are developed. Currently, VLP relies strongly on the assumed Lambertian properties of light sources. However, in practice, not all lights are Lambertian. To support the widespread deployment of VLC technology in numerous environments, measurements from non-Lambertian sources are analysed to provide new insights into the limitations of existing VLP techniques. Subsequently, a novel VLP calibration technique is proposed, and results indicate a 59% accuracy improvement against existing methods. This solution enables high accuracy centimetre level VLP to be achieved with non- Lambertian sources. Asynchronous sampling of range-based measurements is known to impact localisation performance negatively. Various Asynchronous Sampling Localisation Techniques (ASLT) exist to mitigate these effects. While effective at improving positioning performance, the exact suitability of such solutions is not evident due to their additional processes, subsequent complexity, and increased costs. As such, extensive simulations are conducted to study the effectiveness of ASLT under variable sampling latencies, sensor measurement noise, and target trajectories. Findings highlight the computational demand of existing ASLT and motivate the development of a novel solution. The proposed Kalman Extrapolated Least Squares (KELS) method achieves optimal localisation performance with a significant energy reduction of over 50% when compared to current leading ASLT. The work in this thesis demonstrates both the capability for high performance VLP from non- Lambertian sources as well as the potential for energy efficient localisation for sequentially sampled range measurements.Horizon 202

3D Object Reconstruction from Hand-Object Interactions

Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Although these approaches are successful for a wide range of object classes, they rely on stable and distinctive geometric or texture features. Many objects like mechanical parts, toys, household or decorative articles, however, are textureless and characterized by minimalistic shapes that are simple and symmetric. Existing in-hand scanning systems and 3d reconstruction techniques fail for such symmetric objects in the absence of highly distinctive features. In this work, we show that extracting 3d hand motion for in-hand scanning effectively facilitates the reconstruction of even featureless and highly symmetric objects and we present an approach that fuses the rich additional information of hands into a 3d reconstruction pipeline, significantly contributing to the state-of-the-art of in-hand scanning.Comment: International Conference on Computer Vision (ICCV) 2015, http://files.is.tue.mpg.de/dtzionas/In-Hand-Scannin

Contributions to autonomous robust navigation of mobile robots in industrial applications

151 p.Un aspecto en el que las plataformas móviles actuales se quedan atrás en comparación con el punto que se ha alcanzado ya en la industria es la precisión. La cuarta revolución industrial trajo consigo la implantación de maquinaria en la mayor parte de procesos industriales, y una fortaleza de estos es su repetitividad. Los robots móviles autónomos, que son los que ofrecen una mayor flexibilidad, carecen de esta capacidad, principalmente debido al ruido inherente a las lecturas ofrecidas por los sensores y al dinamismo existente en la mayoría de entornos. Por este motivo, gran parte de este trabajo se centra en cuantificar el error cometido por los principales métodos de mapeado y localización de robots móviles,ofreciendo distintas alternativas para la mejora del posicionamiento.Asimismo, las principales fuentes de información con las que los robots móviles son capaces de realizarlas funciones descritas son los sensores exteroceptivos, los cuales miden el entorno y no tanto el estado del propio robot. Por esta misma razón, algunos métodos son muy dependientes del escenario en el que se han desarrollado, y no obtienen los mismos resultados cuando este varía. La mayoría de plataformas móviles generan un mapa que representa el entorno que les rodea, y fundamentan en este muchos de sus cálculos para realizar acciones como navegar. Dicha generación es un proceso que requiere de intervención humana en la mayoría de casos y que tiene una gran repercusión en el posterior funcionamiento del robot. En la última parte del presente trabajo, se propone un método que pretende optimizar este paso para así generar un modelo más rico del entorno sin requerir de tiempo adicional para ello

Trajectory optimization for target localisation with bearing-only measurement

This paper considers the problem of twodimensional (2D) constrained trajectory optimisation of a pointmass aerial robot for constant-manoeuvring target localisation using bearing-only measurement. A performance metric that can be utilised in trajectory optimisation to maximise target observability is proposed first based on geometric conditions. One-step optimal manoeuvre that maximises the observability criterion is then derived analytically for moving targets. The heading angle constraint is also incorporated in the proposed optimal manoeuvre derivation to support practical application. Numerical simulations with some comparisons are presented to validate the analytical findings

3D Sensor Placement and Embedded Processing for People Detection in an Industrial Environment

Papers I, II and III are extracted from the dissertation and uploaded as separate documents to meet post-publication requirements for self-arciving of IEEE conference papers.At a time when autonomy is being introduced in more and more areas, computer vision plays a very important role. In an industrial environment, the ability to create a real-time virtual version of a volume of interest provides a broad range of possibilities, including safety-related systems such as vision based anti-collision and personnel tracking. In an offshore environment, where such systems are not common, the task is challenging due to rough weather and environmental conditions, but the result of introducing such safety systems could potentially be lifesaving, as personnel work close to heavy, huge, and often poorly instrumented moving machinery and equipment. This thesis presents research on important topics related to enabling computer vision systems in industrial and offshore environments, including a review of the most important technologies and methods. A prototype 3D sensor package is developed, consisting of different sensors and a powerful embedded computer. This, together with a novel, highly scalable point cloud compression and sensor fusion scheme allows to create a real-time 3D map of an industrial area. The question of where to place the sensor packages in an environment where occlusions are present is also investigated. The result is algorithms for automatic sensor placement optimisation, where the goal is to place sensors in such a way that maximises the volume of interest that is covered, with as few occluded zones as possible. The method also includes redundancy constraints where important sub-volumes can be defined to be viewed by more than one sensor. Lastly, a people detection scheme using a merged point cloud from six different sensor packages as input is developed. Using a combination of point cloud clustering, flattening and convolutional neural networks, the system successfully detects multiple people in an outdoor industrial environment, providing real-time 3D positions. The sensor packages and methods are tested and verified at the Industrial Robotics Lab at the University of Agder, and the people detection method is also tested in a relevant outdoor, industrial testing facility. The experiments and results are presented in the papers attached to this thesis.publishedVersio