MULTI-SENSOR LOCALIZATION AND TRACKING IN DISASTER MANAGEMENT AND INDOOR WAYFINDING FOR VISUALLY IMPAIRED USERS

This dissertation proposes a series of multi-sensor localization and tracking algorithms particularly developed for two important application domains, which are disaster management and indoor wayfinding for blind and visually impaired (BVI) users. For disaster management, we developed two different localization algorithms, one each for Radio Frequency Identification (RFID) and Bluetooth Low Energy (BLE) technology, which enable the disaster management system to track patients in real-time. Both algorithms work in the absence of any pre-deployed infrastructure along with smartphones and wearable devices. Regarding indoor wayfinding for BVI users, we have explored several types of indoor positioning techniques including BLE-based, inertial, visual and hybrid approaches to offer accurate and reliable location and orientation in complex navigation spaces. In this dissertation, significant contributions have been made in the design and implementation of various localization and tracking algorithms under different requirements of certain applications

Indoor navigation for the visually impaired : enhancements through utilisation of the Internet of Things and deep learning

Wayfinding and navigation are essential aspects of independent living that heavily rely on the sense of vision. Walking in a complex building requires knowing exact location to find a suitable path to the desired destination, avoiding obstacles and monitoring orientation and movement along the route. People who do not have access to sight-dependent information, such as that provided by signage, maps and environmental cues, can encounter challenges in achieving these tasks independently. They can rely on assistance from others or maintain their independence by using assistive technologies and the resources provided by smart environments. Several solutions have adapted technological innovations to combat navigation in an indoor environment over the last few years. However, there remains a significant lack of a complete solution to aid the navigation requirements of visually impaired (VI) people. The use of a single technology cannot provide a solution to fulfil all the navigation difficulties faced. A hybrid solution using Internet of Things (IoT) devices and deep learning techniques to discern the patterns of an indoor environment may help VI people gain confidence to travel independently. This thesis aims to improve the independence and enhance the journey of VI people in an indoor setting with the proposed framework, using a smartphone. The thesis proposes a novel framework, Indoor-Nav, to provide a VI-friendly path to avoid obstacles and predict the user s position. The components include Ortho-PATH, Blue Dot for VI People (BVIP), and a deep learning-based indoor positioning model. The work establishes a novel collision-free pathfinding algorithm, Orth-PATH, to generate a VI-friendly path via sensing a grid-based indoor space. Further, to ensure correct movement, with the use of beacons and a smartphone, BVIP monitors the movements and relative position of the moving user. In dark areas without external devices, the research tests the feasibility of using sensory information from a smartphone with a pre-trained regression-based deep learning model to predict the user s absolute position. The work accomplishes a diverse range of simulations and experiments to confirm the performance and effectiveness of the proposed framework and its components. The results show that Indoor-Nav is the first type of pathfinding algorithm to provide a novel path to reflect the needs of VI people. The approach designs a path alongside walls, avoiding obstacles, and this research benchmarks the approach with other popular pathfinding algorithms. Further, this research develops a smartphone-based application to test the trajectories of a moving user in an indoor environment

Research on port AGV composite positioning based on UWB/RFID

In recent years, ports in various countries have successively carried out research and application of fully automated terminal. The terminal adopts the "Double car shore bridge + AGV + ARMG" automation process, which is the most widely used and relatively mature fully automated solution. At present, the AGV navigation of the terminal is based on RFID magnetic nail positioning and the accuracy is good. However, nowadays UWB technology has become the most popular technology in ranging and positioning. The research in this work is based on UWB/RFID composite positioning, which is mainly used for the specific localization tasks in the port and it can accurately locate the position of the AGV. This MSc work studies the UWB positioning system first and then researches the traditional 3D positioning algorithm. Importance contribution expressed by 3D TOA localization algorithm. For RFID system, this connection between the reader and the carrier is designed, and the reference tag is buried. At last, data-based on RFID localization algorithm in scene analysis method is adopted for positioning. Secondly, the basis of the composite positioning system is data fusion technology. The most widely used and mature fusion algorithm is the Kalman filter algorithm and Particle filter. Finally, the experimental analysis of UWB and RFID composite positioning system is implemented. The results indicate that UWB and RFID composite positioning system can reduce the cost of the positioning system. Higher positioning accuracy and robustness are characterizing the developed system.Nos últimos anos, portos de vários países realizaram sucessivamente pesquisas e aplicações de terminais totalmente automatizados. O terminal adota o processo de automação "Double car shore bridge + AGV + ARMG", que é a solução totalmente automatizada mais amplamente utilizada e relativamente madura. Atualmente, a navegação AGV do terminal é baseada no posicionamento da etiqueta RFID e a precisão é boa. No entanto, hoje em dia, a tecnologia UWB tornou-se na tecnologia mais popular relativamente ao alcance e posicionamento. A pesquisa neste trabalho é baseada no posicionamento composto por UWB / RFID, usado principalmente para tarefas de localização específicas nos portos, podendo desta forma localizar-se com precisão a posição do AGV. Este projeto de mestrado estuda em primeiro lugar o sistema de posicionamento UWB, e depois um algoritmo tradicional de posicionamento 3D. A contribuição da importância expressa pelo algoritmo de posicionamento “time of arrival” (TOA) 3D foi proposta. Para o sistema de posicionamento RFID, a conexão entre o leitor e a transportadora é projetada e a etiqueta de referência é ocultada. Por fim, o algoritmo de “k-nearest neighbor” baseado numa base de dados e no método de análise de cena é adotado para realizar o posicionamento. Em segundo lugar, a base do sistema de posicionamento composto é a tecnologia de fusão de dados. O algoritmo de fusão mais amplamente utilizado e maduro é o algoritmo de filtro Kalman e o filtro de partículas. Finalmente, é realizada a análise experimental do sistema de posicionamento composto UWB e RFID. Os resultados experimentais mostram que o sistema de posicionamento composto UWB e RFID pode reduzir o custo do sistema de posicionamento. O sistema desenvolvido é caracterizado por uma maior precisão de posicionamento e robustez

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

A Bayesian strategy to enhance the performance of indoor localization systems

This work describes the probabilistic modelling af a Bayesian-based mechanism to improve location estimates of an already deployed location system by fusing its outputs with low-cost binary sensors. This mechanism takes advantege of the localization captabilities of different technologies usually present in smart environments deployments. The performance of the proposed algorithm over a real sensor deployment is evaluated using simulated and real experimental data

Passive low frequency RFID for non-destructive evaluation and monitoring

Ph. D ThesisDespite of immense research over the years, defect monitoring in harsh environmental conditions still presents notable challenges for Non-Destructive Testing and Evaluation (NDT&E) and Structural Health Monitoring (SHM). One of the substantial challenges is the inaccessibility to the metal surface due to the large stand-off distance caused by the insulation layer. The hidden nature of corrosion and defect under thick insulation in harsh environmental conditions may result in it being not noticed and ultimately leading to failures. Generally electromagnetic NDT&E techniques which are used in pipeline industries require the removal of the insulation layer or high powered expensive equipment. Along with these, other limitations in the existing techniques create opportunities for novel systems to solve the challenges caused by Corrosion under Insulation (CUI). Extending from Pulsed Eddy Current (PEC), this research proposes the development and use of passive Low Frequency (LF) RFID hardware system for the detection and monitoring of corrosion and cracks on both ferrous and non-ferrous materials at varying high temperature conditions. The passive, low cost essence of RFID makes it an enchanting technique for long term condition monitoring. The contribution of the research work can be summarised as follows: (1) implementation of novel LF RFID sensor systems and the rig platform, experimental studies validating the detection capabilities of corrosion progression samples using transient feature analysis with respect to permeability and electrical conductivity changes along with enhanced sensitivity demonstration using ferrite sheet attached to the tag; (2) defect detection using swept frequency method to study the multiple frequency behaviour and further temperature suppression using feature fusion technique; (3) inhomogeneity study on ferrous materials at varying temperature and demonstration of the potential of the RFID system; (4) use of RFID tag with ceramic filled Poly-tetra-fluoro-ethyulene (PTFE) substrate for larger applicability of the sensing system in the industry; (5) lift-off independent defect monitoring using passive sweep frequency RFID sensors and feature extraction and fusion for robustness improvement. This research concludes that passive LF RFID system can be used to detect corrosion and crack on both ferrous and non-ferrous materials and then the system can be used to compensate for temperature variation making it useful for a wider range of applications. However, significant challenges such as permanent deployment of the tags for long term monitoring at higher temperatures and much higher standoff distance, still require improvement for real-world applicability.Engineering and Physical Sciences Research Council (EPSRC) CASE, National Nuclear Laboratory (NNL)

A Review of Wireless Sensor Technologies and Applications in Agriculture and Food Industry: State of the Art and Current Trends

The aim of the present paper is to review the technical and scientific state of the art of wireless sensor technologies and standards for wireless communications in the Agri-Food sector. These technologies are very promising in several fields such as environmental monitoring, precision agriculture, cold chain control or traceability. The paper focuses on WSN (Wireless Sensor Networks) and RFID (Radio Frequency Identification), presenting the different systems available, recent developments and examples of applications, including ZigBee based WSN and passive, semi-passive and active RFID. Future trends of wireless communications in agriculture and food industry are also discussed

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods