Indoor Positioning and Navigation

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot

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

Enhancing the museum experience with a sustainable solution based on contextual information obtained from an on-line analysis of users’ behaviour

Human computer interaction has evolved in the last years in order to enhance users’ experiences and provide more intuitive and usable systems. A major leap through in this scenario is obtained by embedding, in the physical environment, sensors capable of detecting and processing users’ context (position, pose, gaze, ...). Feeded by the so collected information flows, user interface paradigms may shift from stereotyped gestures on physical devices, to more direct and intuitive ones that reduce the semantic gap between the action and the corresponding system reaction or even anticipate the user’s needs, thus limiting the overall learning effort and increasing user satisfaction. In order to make this process effective, the context of the user (i.e. where s/he is, what is s/he doing, who s/he is, what are her/his preferences and also actual perception and needs) must be properly understood. While collecting data on some aspects can be easy, interpreting them all in a meaningful way in order to improve the overall user experience is much harder. This is more evident when we consider informal learning environments like museums, i.e. places that are designed to elicit visitor response towards the artifacts on display and the cultural themes proposed. In such a situation, in fact, the system should adapt to the attention paid by the user choosing the appropriate content for the user’s purposes, presenting an intuitive interface to navigate it. My research goal is focused on collecting, in a simple,unobtrusive, and sustainable way, contextual information about the visitors with the purpose of creating more engaging and personalized experiences

Robust, Energy-Efficient, and Scalable Indoor Localization with Ultra-Wideband Technology

Ultra-wideband (UWB) technology has been rediscovered in recent years for its potential to provide centimeter-level accuracy in GNSS-denied environments. The large-scale adoption of UWB chipsets in smartphones brings demanding needs on the energy-efficiency, robustness, scalability, and crossdevice compatibility of UWB localization systems. This thesis investigates, characterizes, and proposes several solutions for these pressing concerns. First, we investigate the impact of different UWB device architectures on the energy efficiency, accuracy, and cross-platform compatibility of UWB localization systems. The thesis provides the first comprehensive comparison between the two types of physical interfaces (PHYs) defined in the IEEE 802.15.4 standard: with low and high pulse repetition frequency (LRP and HRP, respectively). In the comparison, we focus not only on the ranging/localization accuracy but also on the energy efficiency of the PHYs. We found that the LRP PHY consumes between 6.4–100 times less energy than the HRP PHY in the evaluated devices. On the other hand, distance measurements acquired with the HRP devices had 1.23–2 times lower standard deviation than those acquired with the LRP devices. Therefore, the HRP PHY might be more suitable for applications with high-accuracy constraints than the LRP PHY. The impact of different UWB PHYs also extends to the application layer. We found that ranging or localization error-mitigation techniques are frequently trained and tested on only one device and would likely not generalize to different platforms. To this end, we identified four challenges in developing platform-independent error-mitigation techniques in UWB localization, which can guide future research in this direction. Besides the cross-platform compatibility, localization error-mitigation techniques raise another concern: most of them rely on extensive data sets for training and testing. Such data sets are difficult and expensive to collect and often representative only of the precise environment they were collected in. We propose a method to detect and mitigate non-line-of-sight (NLOS) measurements that does not require any manually-collected data sets. Instead, the proposed method automatically labels incoming distance measurements based on their distance residuals during the localization process. The proposed detection and mitigation method reduces, on average, the mean and standard deviation of localization errors by 2.2 and 5.8 times, respectively. UWB and Bluetooth Low Energy (BLE) are frequently integrated in localization solutions since they can provide complementary functionalities: BLE is more energy-efficient than UWB but it can provide location estimates with only meter-level accuracy. On the other hand, UWB can localize targets with centimeter-level accuracy albeit with higher energy consumption than BLE. In this thesis, we provide a comprehensive study of the sources of instabilities in received signal strength (RSS) measurements acquired with BLE devices. The study can be used as a starting point for future research into BLE-based ranging techniques, as well as a benchmark for hybrid UWB–BLE localization systems. Finally, we propose a flexible scheduling scheme for time-difference of arrival (TDOA) localization with UWB devices. Unlike in previous approaches, the reference anchor and the order of the responding anchors changes every time slot. The flexible anchor allocation makes the system more robust to NLOS propagation than traditional approaches. In the proposed setup, the user device is a passive listener which localizes itself using messages received from the anchors. Therefore, the system can scale with an unlimited number of devices and can preserve the location privacy of the user. The proposed method is implemented on custom hardware using a commercial UWB chipset. We evaluated the proposed method against the standard TDOA algorithm and range-based localization. In line of sight (LOS), the proposed TDOA method has a localization accuracy similar to the standard TDOA algorithm, down to a 95% localization error of 15.9 cm. In NLOS, the proposed TDOA method outperforms the classic TDOA method in all scenarios, with a reduction of up to 16.4 cm in the localization error.Cotutelle -yhteisväitöskirj

Discovery of Transport Operations from Geolocation Data

Os dados de geolocalização identificam a localização geográfica de pessoas ou objetos e são fundamentais para empresas que dependem de veículos, como empresas logísticas e de transportes. Com o avanço da tecnologia, a recolha de dados de geolocalização tornou-se cada vez mais acessível e económica, gerando novas oportunidades de inteligência empresarial. Este tipo de dados tem sido utilizado principalmente para caracterizar o veículo em termos de posicionamento e navegação, mas também pode ter um papel preponderante na avaliação de desempenho em relação às atividades e operações executadas. A abordagem proposta consiste numa metodologia com várias etapas que recebe dados de geolocalização como entrada e permite a análise do processo de negócio no final. Em primeiro lugar, a preparação dos dados é aplicada para lidar com uma série de questões relacionadas com ruído e erros nos dados. Depois, a identificação dos eventos estacionários é realizada com base nos estados estacionários dos veículos. Em seguida, é realizada a inferência de operações com base numa análise espacial, que permite descobrir os locais onde os eventos estacionários ocorrem com frequência. Finalmente, as operações identificadas são classificadas com base nas suas características, e a sequência de eventos pode ser estruturada. A aplicação de técnicas de process mining é então possível e a consequente extração de conhecimento do processo. As etapas da metodologia também podem ser utilizadas separadamente para enfrentar desafios específicos, dando mais flexibilidade à sua aplicação. Três estudos de caso distintos são apresentados para demonstrar a eficácia e transversalidade da solução. Fluxos de dados de geolocalização em tempo real de autocarros de duas redes distintas de transporte público são usados para demonstrar a detecção de operações relacionadas com os veículos e comparar as distintas abordagens propostas por este trabalho. As operações dos autocarros produzem uma sequência estruturada de eventos que descreve o comportamento dos mesmos. Esse comportamento é mapeado por meio da aplicação de técnicas de process mining, para descobrir oportunidades de análise e gargalos no processo. Complementarmente, os dados de geolocalização de uma empresa de logística internacional são explorados para a monitorização de processos logísticos, nomeadamente para detecção de operações de logística em tempo real, demonstrando a eficácia da solução proposta para resolver problemas específicos da indústria. Os resultados deste trabalho revelam novas possibilidades no uso de dados de geolocalização e o seu potencial para gerar conhecimento acerca do processo. A exploração de dados de geolocalização nos contextos logísticos e de transportes públicos apresenta-se como uma oportunidade para melhorar a monitorização e gestão das operações baseadas em veículos. Isso pode originar melhorias na eficiência do processo e, consequentemente, maior lucro e melhor qualidade do serviço.Geolocation data identifies the geographic location of people or objects, and is fundamental for businesses relying on vehicles such as logistics and transportation. With the advance of technology, collecting geolocation data has become increasingly accessible and affordable, raising new opportunities for business intelligence. This type of data has been used mainly for characterizing the vehicle in terms of positioning and navigation, but it can also showcase its performance regarding the executed activities and operations. The proposed approach consists on a multi-step methodology that receives geolocation data as an input and allows the analysis of the business process in the end. Firstly, the preparation of the data is applied to handle a number of issues related to outliers, data noise, and missing or erroneous information. Then, the identification of stationary events is performed based on the motionless states of the vehicles. Next, the inference of operations based on a spatial analysis is performed, which allows the discovery of the locations where stationary events occur frequently. Finally, the identified operations are classified based on their characteristics, and the sequence of events can be structured into an event log. The application of process mining techniques is then possible and the consequently extraction of process knowledge. The steps of the methodology can also be used separately to tackle specific challenges, giving more flexibility to its application. Three distinct case studies are presented to demonstrate the effectiveness and transversality of the solution. Real-time geolocation data streams of buses from two distinct public transport networks are used to demonstrate the detection of vehicle-based operations and compare the distinct approaches proposed by this work. The buses operations produce a structured sequence of events that describes the behaviour of the buses. This behaviour is mapped through the application of process mining techniques uncovering analysis opportunities and discovering bottlenecks in the process. Geolocation data from an international logistics company is exploited for monitoring logistics processes, namely for detecting vehicle-based operations in real time, showing the effectiveness of the proposed solution to solve specific industry problems. The results of this work reveal new possibilities for geolocation data and its potential to generate process knowledge. The exploitation of geolocation data in the public transport and logistics contexts poses as an opportunity for improving the monitoring and management of vehicle-based operations. This can lead to into improvements in the process efficiency and consequently higher profit and better service quality

Napredna (edge computing) softverska arhitektura za upravljanje resursima i unutrašnje pozicioniranje

In Part I, this thesis aims to shed light on IoT and edge com-puting systems and accompanying computing and architectural paradigms, their definition, areas of application, and common use-cases, as well as operational, business, economical, social challenges and benefits. It illustrates modern needs and requests in building IoT systems and current State-of-The-Art (SoTA) approaches to designing them. Additionally, it discusses the security and privacy topics of IoT and edge computing systems. It also encompasses research, design, and implementation of an MQTT-based Resource Management Framework for Edge Com-puting systems that handle: resource management, failover detection and handover administration, logical and physical workload balancing and protection, and monitoring of physical and logical system resources designed for a real-world IoT platform. The thesis offers insights into modern requests for such frameworks, current SoTA approaches, and offer a solution in the form of a software framework, with minimal implementation and communication overhead. In Part II, the thesis elaborates on IPS, their definition, deploy-ment types, commonly used positioning techniques, areas of application, and common use-cases, as well as operational, business, economic, social challenges, and benefits. It specifically discusses designing IPS for the typical IoT infrastructure. It offers insights to modern IPS requests, current SoTA in solving them, and under-line original approaches from this thesis. It elaborates on the research, design and authors’ implementation of an IPS for the IoT – Bluetooth LowEnergyMicrolocation Asset Tracking (BLEMAT), including its software engines (collections of software components) for: indoor positioning, occupancy detection, visualization, pattern discovery and prediction, geofencing, movement pattern detection, visualization, discovery and prediction, social dynamics analysis, and indoor floor plan layout detection.Deo I teze ima je za cilj da rasvetli IoT i edge computing računarske sisteme i prateće računarske paradigme softverskih arhitektura, njihovu definiciju, područja primene i slučajeve uobičajene upotrebe, kao i operativne, poslovne, ekonomske, i socijalne izazove i koristi. Teza ilustruje savremene potrebe i zahtevi u izgradnji IoT sistema i najsavremeniji pristupi u njihovom dizajniranju. Raspravlja se o temama bezbednosti i privatnosti u IoT i edge computing računarskim sistemima. Kao još jedan glavni zadatak, teza je obuhvata istraživanje, dizajn i implementaciju softverske arhitekture za upravljanje resursima zasnovanim na MQTT komunikacionom protokolu za edge computing računarske sisteme koja se bavi: upravljanjem resursima, detekcijom prestanka rada upravljačkih algoritama i administracijom primopredaje tj. transporta upravljačkih algoritama, i logičkim i fizičkim balansiranjem i zaštitom radnog opterećenja sistema. Diskutuju se savremeni zahtevi za takve softverske arhitekture, trenutni pristupi. Na kraju, prikazuje se rešenje sa minimalnim troškovima implementacije i  komunikacije. Deo II teze ima za cilj da objasni sisteme za unutrašnje pozicioniranje, njihovu definiciju, vrste primene, najčešće korišćene tehnike pozicioniranja, područja primene i uobičajene slučajeve upotrebe, kao i operativne, poslovne, ekonomske, i socijalne izazove i koristi. Posebno se diskutuje o dizajniranju ovakvih sistema za tipičnu IoT infrastrukturu. Nudi se uvid u savremene zahteve sisteme za unutrašnje pozicioniranje, trenutne pristupe u rešavanju istih, i naglašeni su originalni pristupe iz ove teze. Dalje je fokus na istraživanju, dizajniranju i implementaciji sistema za unutrašnje pozicioniranje (BLEMAT), uključujući njegove softverske podsisteme (kolekcije softverskih komponenti) za: pozicioniranje u zatvorenom prostoru, detekciju zauzeća prostorija, vizualizaciju, otkrivanje i predviđanje obrazaca kretanja, geofencing, vizualizaciju i analizu društvene dinamike i detekciju rasporeda prostorija unutrašnjeg prostora

Rehabilitation Engineering

Population ageing has major consequences and implications in all areas of our daily life as well as other important aspects, such as economic growth, savings, investment and consumption, labour markets, pensions, property and care from one generation to another. Additionally, health and related care, family composition and life-style, housing and migration are also affected. Given the rapid increase in the aging of the population and the further increase that is expected in the coming years, an important problem that has to be faced is the corresponding increase in chronic illness, disabilities, and loss of functional independence endemic to the elderly (WHO 2008). For this reason, novel methods of rehabilitation and care management are urgently needed. This book covers many rehabilitation support systems and robots developed for upper limbs, lower limbs as well as visually impaired condition. Other than upper limbs, the lower limb research works are also discussed like motorized foot rest for electric powered wheelchair and standing assistance device

Using Bluetooth to estimate traffic metrics for traffic management applications

PhD Thesis‘Bluetooth’ is a technology that can be integrated into Intelligent Transport Systems (ITS) to facilitate smarter and enhanced traffic monitoring and management to reduce congestion. The current research focus on Bluetooth is principally on journey time management. However, the applicability and viability of Bluetooth potential in problematic urban areas remains unknown. Besides the generic problem of unavailability of processing algorithms, there is gap in knowledge regarding the variability and errors in Bluetooth-derived metrics. These unknown errors usually cause uncertainty about the conclusions drawn from the data. Therefore, a novel Bluetooth-based vehicle detection and Traffic Flow Origin-destination Speed and Travel-time (TRAFOST) model was developed to estimate and analyse key traffic metrics. This research utilised Bluetooth data and other independently measured traffic data collected principally from three study sites in Greater Manchester, UK. The Bluetooth sensors at these locations generated vehicle detection rates (7-16%) that varied temporally and spatially, based on the comparison with flows from ATC (Automatic Traffic Counters) and SCOOT (Split Cycle Offset Optimisation Technique) detectors. Performance evaluation of the estimation showed temporal consistency and accuracy at a high level of confidence (i.e. 95%) based on criteria such as Mean Absolute Deviation (MAD) - (0.031 – 0.147), Root Mean Square Error (RMSE) - (0.041 – 0.195), Mean Absolute Percentage Error (MAPE) - (0.822 – 4.917) and Kullback-Leibler divergence (KL-D) (0.004 – 0.044). This outcome provides evidence of reliability in the results as well as justification for further investigation of Bluetooth applications in ITS. However, the resulting accuracy depends significantly on sample size, network characteristics, and traffic flow regimes. The Bluetooth approach has enabled a deeper understanding of traffic flow regimes and spatio-temporal variations within the Greater Manchester Networks than is possible using conventional traffic data such as from SCOOT. Therefore, the application of Bluetooth technology in ITS to enhance traffic management to reduce congestion is a viable proposition and is recommended.Petroleum Technology Development Fund (PTDF) – for the award of a PhD Scholarship for 4 years; The University of Lagos – for the study leave with pay; Surveyors Council of Nigeria (SURCON) – for the additional support