52 research outputs found

    Triaxial Accelerometer Error Coefficients Identification with a Novel Artificial Fish Swarm Algorithm

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    Artificial fish swarm algorithm (AFSA) is one of the state-of-the-art swarm intelligence techniques, which is widely utilized for optimization purposes. Triaxial accelerometer error coefficients are relatively unstable with the environmental disturbances and aging of the instrument. Therefore, identifying triaxial accelerometer error coefficients accurately and being with lower costs are of great importance to improve the overall performance of triaxial accelerometer-based strapdown inertial navigation system (SINS). In this study, a novel artificial fish swarm algorithm (NAFSA) that eliminated the demerits (lack of using artificial fishes’ previous experiences, lack of existing balance between exploration and exploitation, and high computational cost) of AFSA is introduced at first. In NAFSA, functional behaviors and overall procedure of AFSA have been improved with some parameters variations. Second, a hybrid accelerometer error coefficients identification algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS) approaches. This combination leads to maximum utilization of the involved approaches for triaxial accelerometer error coefficients identification. Furthermore, the NAFSA-identified coefficients are testified with 24-position verification experiment and triaxial accelerometer-based SINS navigation experiment. The priorities of MCS-NAFSA are compared with that of conventional calibration method and optimal AFSA. Finally, both experiments results demonstrate high efficiency of MCS-NAFSA on triaxial accelerometer error coefficients identification

    Micro-Inertial-Aided High-Precision Positioning Method for Small-Diameter PIG Navigation

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    Pipeline leakage or explosion has caused huge economic losses, polluted the environments and threatened the safety of civilian’s lives and assets, which even caused negative influences to the society greatly. Fortunately, pipeline inspection gauge (PIG) could accomplish the pipeline defect (corrosions, cracks, grooves, etc.) inspection effectively and meanwhile to localize these defects precisely by navigation sensors. The results are utilized for pipeline integrity management (PIM) and pipeline geographic information system construction. Generally, the urban underground pipeline presents with small-diameter and complicated-distribution properties, which are of great challenges for the pipeline defects positioning by PIG. This chapter focuses on in-depth research of the high-precision positioning method for small-diameter PIG navigation. In the beginning, the problems and system errors statement of MEMS SINS-based PIG are analyzed step by step. Then, the pipeline junction (PJ) identification method based on fast orthogonal search (FOS) is studied. After that, a PIG positioning system that comprises of micro-inertial/AGM/odometer/PJ is proposed, and also the application mechanism of extended Kalman filter and its smoothing technology on PIG navigation system is researched to improve the overall positioning precision for the small-diameter PIG. Finally, the proposed methods and research conclusions are verified by the indoor wheel robot simulation platform

    A Review of the Family of Artificial Fish Swarm Algorithms: Recent Advances and Applications

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    The Artificial Fish Swarm Algorithm (AFSA) is inspired by the ecological behaviors of fish schooling in nature, viz., the preying, swarming, following and random behaviors. Owing to a number of salient properties, which include flexibility, fast convergence, and insensitivity to the initial parameter settings, the family of AFSA has emerged as an effective Swarm Intelligence (SI) methodology that has been widely applied to solve real-world optimization problems. Since its introduction in 2002, many improved and hybrid AFSA models have been developed to tackle continuous, binary, and combinatorial optimization problems. This paper aims to present a concise review of the family of AFSA, encompassing the original ASFA and its improvements, continuous, binary, discrete, and hybrid models, as well as the associated applications. A comprehensive survey on the AFSA from its introduction to 2012 can be found in [1]. As such, we focus on a total of {\color{blue}123} articles published in high-quality journals since 2013. We also discuss possible AFSA enhancements and highlight future research directions for the family of AFSA-based models.Comment: 37 pages, 3 figure

    IoT in smart communities, technologies and applications.

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    Internet of Things is a system that integrates different devices and technologies, removing the necessity of human intervention. This enables the capacity of having smart (or smarter) cities around the world. By hosting different technologies and allowing interactions between them, the internet of things has spearheaded the development of smart city systems for sustainable living, increased comfort and productivity for citizens. The Internet of Things (IoT) for Smart Cities has many different domains and draws upon various underlying systems for its operation, in this work, we provide a holistic coverage of the Internet of Things in Smart Cities by discussing the fundamental components that make up the IoT Smart City landscape, the technologies that enable these domains to exist, the most prevalent practices and techniques which are used in these domains as well as the challenges that deployment of IoT systems for smart cities encounter and which need to be addressed for ubiquitous use of smart city applications. It also presents a coverage of optimization methods and applications from a smart city perspective enabled by the Internet of Things. Towards this end, a mapping is provided for the most encountered applications of computational optimization within IoT smart cities for five popular optimization methods, ant colony optimization, genetic algorithm, particle swarm optimization, artificial bee colony optimization and differential evolution. For each application identified, the algorithms used, objectives considered, the nature of the formulation and constraints taken in to account have been specified and discussed. Lastly, the data setup used by each covered work is also mentioned and directions for future work have been identified. Within the smart health domain of IoT smart cities, human activity recognition has been a key study topic in the development of cyber physical systems and assisted living applications. In particular, inertial sensor based systems have become increasingly popular because they do not restrict users’ movement and are also relatively simple to implement compared to other approaches. Fall detection is one of the most important tasks in human activity recognition. With an increasingly aging world population and an inclination by the elderly to live alone, the need to incorporate dependable fall detection schemes in smart devices such as phones, watches has gained momentum. Therefore, differentiating between falls and activities of daily living (ADLs) has been the focus of researchers in recent years with very good results. However, one aspect within fall detection that has not been investigated much is direction and severity aware fall detection. Since a fall detection system aims to detect falls in people and notify medical personnel, it could be of added value to health professionals tending to a patient suffering from a fall to know the nature of the accident. In this regard, as a case study for smart health, four different experiments have been conducted for the task of fall detection with direction and severity consideration on two publicly available datasets. These four experiments not only tackle the problem on an increasingly complicated level (the first one considers a fall only scenario and the other two a combined activity of daily living and fall scenario) but also present methodologies which outperform the state of the art techniques as discussed. Lastly, future recommendations have also been provided for researchers

    Vibration-based damage localisation: Impulse response identification and model updating methods

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    Structural health monitoring has gained more and more interest over the recent decades. As the technology has matured and monitoring systems are employed commercially, the development of more powerful and precise methods is the logical next step in this field. Especially vibration sensor networks with few measurement points combined with utilisation of ambient vibration sources are attractive for practical applications, as this approach promises to be cost-effective while requiring minimal modification to the monitored structures. Since efficient methods for damage detection have already been developed for such sensor networks, the research focus shifts towards extracting more information from the measurement data, in particular to the localisation and quantification of damage. Two main concepts have produced promising results for damage localisation. The first approach involves a mechanical model of the structure, which is used in a model updating scheme to find the damaged areas of the structure. Second, there is a purely data-driven approach, which relies on residuals of vibration estimations to find regions where damage is probable. While much research has been conducted following these two concepts, different approaches are rarely directly compared using the same data sets. Therefore, this thesis presents advanced methods for vibration-based damage localisation using model updating as well as a data-driven method and provides a direct comparison using the same vibration measurement data. The model updating approach presented in this thesis relies on multiobjective optimisation. Hence, the applied numerical optimisation algorithms are presented first. On this basis, the model updating parameterisation and objective function formulation is developed. The data-driven approach employs residuals from vibration estimations obtained using multiple-input finite impulse response filters. Both approaches are then verified using a simulated cantilever beam considering multiple damage scenarios. Finally, experimentally obtained data from an outdoor girder mast structure is used to validate the approaches. In summary, this thesis provides an assessment of model updating and residual-based damage localisation by means of verification and validation cases. It is found that the residual-based method exhibits numerical performance sufficient for real-time applications while providing a high sensitivity towards damage. However, the localisation accuracy is found to be superior using the model updating method

    Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice

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    This Special Issue shows a range of potential opportunities for the application of wearable movement sensors in motor rehabilitation. However, the papers surely do not cover the whole field of physical behavior monitoring in motor rehabilitation. Most studies in this Special Issue focused on the technical validation of wearable sensors and the development of algorithms. Clinical validation studies, studies applying wearable sensors for the monitoring of physical behavior in daily life conditions, and papers about the implementation of wearable sensors in motor rehabilitation are under-represented in this Special Issue. Studies investigating the usability and feasibility of wearable movement sensors in clinical populations were lacking. We encourage researchers to investigate the usability, acceptance, feasibility, reliability, and clinical validity of wearable sensors in clinical populations to facilitate the application of wearable movement sensors in motor rehabilitation

    Context Aware Computing or the Sense of Context

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    ITALIANO: I sistemi ubiquitous e pervasivi, speciali categorie di sistemi embedded (immersi), possono essere utilizzati per rilevare il contesto che li circonda. In particolare, i sistemi context-aware sono in grado di alterare il loro stato interno e il loro comportamento in base all’ambiente (context) che percepiscono. Per aiutare le persone nell’espletare le proprie attivitá, tali sistemi possono utilizzare le conoscenze raccolte attorno a loro. Un grande sforzo industriale e di ricerca, orientato all’innovazione dei sensori, processori, sistemi operativi, protocolli di comunicazione, e framework, offre molte tecnologie definibili abilitanti, come le reti di sensori wireless o gli Smartphone. Tuttavia, nonostante tale sforzo significativo, l’adozione di sistemi pervasivi che permettano di migliorare il monitoraggio dello sport, l’allenamento e le tecnologie assistive é ancora piuttosto limitato. Questa tesi individua due fattori determinanti per questo basso utilizzo delle tecnologie pervasive, principalmente relativi agli utenti. Da un lato il tentativo degli esperti e dei ricercatori dell’informatica di indurre l’adozione di soluzioni informatiche, trascurando parzialmente l’interazione con gli utenti finali, dall’altro lato una scarsa attenzione all’interazione tra uomo e computer. Il primo fattore puó essere tradotto nella mancanza di attenzione a ció che é rilevante nel contesto dei bisogni (speciali) dell’utente. Il secondo é rappresentato dall’utilizzo diffuso di interfacce grafiche di presentazione delle informazioni, che richiede un elevato livello di sforzo cognitivo da parte degli utenti. Mentre lo studio della letteratura puó fornire conoscenze sul contesto dell’utente, solo il contatto diretto con lui arricchisce la conoscenza di consapevolezza, fornendo una precisa identificazione dei fattori che sono piú rilevanti per il destinatario dell’applicazione. Per applicare con successo le tecnologie pervasive al campo dello sport e delle tecnologie assistive, l’identificazione dei fattori rilevanti é una premessa necessaria, Tale processo di identificazione rappresenta l’approccio metodologico principale utilizzato per questa tesi. Nella tesi si analizzano diversi sport (canottaggio, nuoto, corsa ) e una disabilitá (la cecitá), per mostrare come la metodologia di investigazione e di progettazione proposta venga messa in pratica. Infatti i fattori rilevanti sono stati identificati grazie alla stretta collaborazione con gli utenti e gli esperti nei rispettivi campi. Si descrive il processo di identificazione, insieme alle soluzioni elaborate su misura per il particolare campo d’uso. L’uso della sonificazione, cioé la trasmissione di informazioni attraverso il suono, si propone di affrontare il secondo problema presentato, riguardante le interfacce utente. L’uso della sonificazione puó facilitare la fruizione in tempo reale delle informazioni sulle prestazioni di attivitá sportive, e puó contribuire ad alleviare parzialmente la disabilitá degli utenti non vedenti. Nel canottaggio, si é identificato nel livello di sincronia del team uno dei fattori rilevanti per una propulsione efficace dell’imbarcazione. Il problema di rilevare il livello di sincronia viene analizzato mediante una rete di accelerometri wireless, proponendo due diverse soluzioni. La prima soluzione é basata sull’indice di correlazione di Pearson e la seconda su un approccio emergente chiamato stigmergia. Entrambi gli approcci sono stati testati con successo in laboratorio e sul campo. Inoltre sono state sviluppate due applicazioni, per smartphone e PC, per fornire la telemetria e la sonificazione del moto di una barca a remi. Nel campo del nuoto é stata condotta una ricerca in letteratura riguardo la convinzione diffusa di considerare la cinematica come il fattore rilevante della propulsione efficace dei nuotatori. Questa indagine ha richiamato l’attenzione sull’importanza di studiare il cosiddetto feel-for-water (sensazione-dell’-acqua) percepito dai nuotatori d’alto livello. É stato progettato un innovativo sistema, per rilevare e comunicare gli effetti fluidodinamici causati dallo spostamento delle masse d’acqua intorno alle mani dei nuotatori. Il sistema é in grado di trasformare la pressione dell’acqua, misurata con sonde Piezo intorno alle mani, in un bio-feedback auditivo, pensato per i nuotatori e gli allenatori, come base per un nuovo modo di comunicare la sensazione-dell’acqua. Il sistema é stato testato con successo nel campo e ha dimostrato di fornire informazioni in tempo reale per il nuotatore e il formatore. Nello sport della corsa sono stati individuati due parametri rilevanti: il tempo di volo e di contatto dei piedi. É stato progettato un sistema innovativo per ottenere questi parametri attraverso un unico accelerometro montato sul tronco del corridore ed é stato implementato su uno smartphone. Per ottenere il risultato voluto é stato necessario progettare e realizzare un sistema per riallineare virtualmente gli assi dell’accelerometro e per estrarre il tempo di volo e di contatto dal segnale dell’accelerometro riallineato. L’applicazione per smartphone completa é stata testata con successo sul campo, confrontando i valori con quelli di attrezzature specializzate, dimostrando la sua idoneitá come ausilio pervasivo all’allenamento di corridori. Per esplorare le possibilitá della sonificazione usata come una base per tecnologia assistiva, abbiamo iniziato una collaborazione con un gruppo di ricerca presso l’Universitá di Scienze Applicate, Ginevra, in Svizzera. Tale collaborazione si é concentrata su un progetto chiamato SeeColOr (See Color with an Orchestra - vedere i colori con un’orchestra). In particolare, abbiamo avuto l’opportunitá di implementare il sistema SeeColOr su smartphone, al fine di consentire agli utenti non vedenti di utilizzare tale tecnologia su dispositivi leggeri e a basso costo. Inoltre, la tesi esplora alcune questioni relative al campo del rilevamento ambientale in ambienti estremi, come i ghiacciai, utilizzando la tecnologia delle Wireless Sensor Networks. Considerando che la tecnologia é simile a quella usata in altri contesti presentati, le considerazioni possono facilmente essere riutilizzate. Si sottolinea infatti che i problemi principali sono legati alla elevata difficoltá e scarsa affidabilitá di questa tecnologia innovativa rispetto alle altre soluzioni disponibili in commercio , definite legacy, basate solitamente su dispositivi piú grandi e costosi, chiamati datalogger. La tesi presenta i problemi esposti e le soluzioni proposte per mostrare l’applicazione dell’approccio progettuale cercato e definito durante lo sviluppo delle attività sperimentali e la ricerca che le ha implementate. ---------------------------------------- ENGLISH: Ubiquitous and pervasive systems, special categories of embedded systems, can be used to sense the context in their surrounding. In particular, context-aware systems are able to alter their internal state and their behaviour based on the context they perceive. To help people in better performing their activities, such systems must use the knowledge gathered about the context. A big research and industrial effort, geared towards the innovation of sensors, processors, operating systems, communication protocols, and frameworks, provides many "enabling" technologies, such as Wireless Sensor Networks or Smartphones. However, despite that significant effort, the adoption of pervasive systems to enhance sports monitoring, training and assistive technologies is still rather small. This thesis identifies two main issues concerning this low usage of pervasive technologies, both mainly related to users. On one side the attempt of computer science experts and researchers to induce the adoption of information technology based solutions, partially neglecting interaction with end users; on the other side a scarce attention to the interaction between humans and computers. The first can be translated into the lack of attention at what is relevant in the context of the user’s (special) needs. The second is represented by the widespread usage of graphical user interfaces to present information, requiring a high level of cognitive effort. While literature studies can provide knowledge about the user’s context, only direct contact with users enriches knowledge with awareness, providing a precise identification of the factors that are more relevant to the user. To successfully apply pervasive technologies to the field of sports engineering and assistive technology, the identification of relevant factors is an obliged premise, and represents the main methodological approach used throughout this thesis. This thesis analyses different sports (rowing, swimming, running) and a disability (blindness), to show how the proposed design methodology is put in practice. Relevant factors were identified thanks to the tight collaboration with users and experts in the respective fields. The process of identification is described, together with the proposed application tailored for the special field. The use of sonification, i.e. conveying information as sound, is proposed to leverage the second presented issue, that regards the user interfaces. The usage of sonification can ease the exploitation of information about performance in real-time for sport activities and can help to partially leverage the disability of blind users. In rowing, the synchrony level of the team was identified as one of the relevant factors for effective propulsion. The problem of detecting the synchrony level is analysed by means of a network of wireless accelerometers, proposing two different solutions. The first solution is based on Pearson’s correlation index and the second on an emergent approach called stigmergy. Both approaches were successfully tested in laboratory and in the field. Moreover two applications, for smartphones and PCs, were developed to provide telemetry and sonification of a rowing boat’s motion. In the field of swimming, an investigation about the widespread belief considering kinematics as the relevant factor of effective propulsion of swimmers drew attention to the importance of studying the so called "feel-for-water" experienced by elite swimmers. An innovative system was designed to sense and communicate fluid-dynamic effects caused by moving water masses around swimmers hands. The system is able to transform water pressure, measured with Piezo-probes, around hands into an auditive biofeedback, to be used by swimmers and trainers, as the base for a new way of communication about the "feel-for-water". The system was successfully tested in the field and proved to provide real-time information for the swimmer and the trainer. In running sports two relevant parameters are time of flight and contact of feet. An innovative system was designed to obtain these parameters using a single trunk mounted accelerometer and was implemented on a smartphone. To achieve the intended result it was necessary to design and implement a system to virtually realign the axes of the accelerometer and to extract time of flight and time of contact phases from the realigned accelerometer signal. The complete smartphone application was successfully tested in the field with specialized equipment, proving its suitability in enhancing training of runners with a pervasive system. To explore possibilities of sonification applied as an assistive technology, we started a collaboration with research group from University of Applied Science, Geneva, Switzerland, focused on a project called SeeColOr (See Color with an Orchestra). In particular we had the opportunity to implement the SeeColOr system on smartphones, in order to enable blind users to use that technology on low cost and lightweight devices. Moreover, the thesis exposes some issues related to a field, environmental sensing in extreme environments, like glaciers, using the innovative Wireless Sensor Networks technology. Considering that the technology is similar to the one used in other presented contexts, learned lessons can easily be reused. It is emphasized that the main problems are related to the high difficulty and low reliability of that innovative technology with respect to other "legacy" commercially available solutions, based on expensive and bigger devices, called dataloggers. The thesis presents the exposed problems and proposed solutions to show the application of the design approach strived during the development and research

    Group Activity Recognition Using Wearable Sensing Devices

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    Understanding behavior of groups in real time can help prevent tragedy in crowd emergencies. Wearable devices allow sensing of human behavior, but the infrastructure required to communicate data is often the first casualty in emergency situations. Peer-to-peer (P2P) methods for recognizing group behavior are necessary, but the behavior of the group cannot be observed at any single location. The contribution is the methods required for recognition of group behavior using only wearable devices

    Collective Behaviour: From Cells to Humans

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    Living in organised groups is a strategy that can be observed in a multitude of diverse species. Among such species, the behaviour of an individual on their own is not the same as within a group: the environment is modified by the presence of more subjects, individuals interact with each other, and from those interactions complex patterns of behaviour can emerge. Some species of animals almost exclusively exist as groups, and as a consequence, studying them in a social context is the only way to understand their behaviour in nature. This is the idea that drives all the research presented in this thesis: the particular behaviour exhibited by the group is so robust that it will emerge even in a very simplified environment. By observing the individual and the group in those simplified experimental conditions, it is possible to deduce rules that might govern the interaction. The importance of interactions in the group’s behaviour can then be demonstrated by implementing a computer model of agents following those rules and comparing it with natural and experimental behaviour. This thesis presents different examples of such analyses, and gives illustrations of the range of questions that can be answered through this method. Groups of stem cells, juvenile sea bass and human beings were successively observed and tracked in suitable environments, with or without perturbation. The data extracted from those experiments were then processed so as to correct recording errors, and individual and collective behaviours were derived from those data, returning new insights on the nature of the interaction at the individual level, their consequences at the global level, as well as the effects of the interaction on both. Finally, I present the computer models derived from those analyses. Many systems in nature share this property of global behaviours emerging from deterministic local interaction, and as a consequence studies of this kind could shed light on important questions, of which cancer treatment, ocean acidification and human organisations are but a few examples

    Inverse Dynamics Problems

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    The inverse dynamics problem was developed in order to provide researchers with the state of the art in inverse problems for dynamic and vibrational systems. Contrasted with a forward problem, which solves for the system output in a straightforward manner, an inverse problem searches for the system input through a procedure contaminated with errors and uncertainties. An inverse problem, with a focus on structural dynamics, determines the changes made to the system and estimates the inputs, including forces and moments, to the system, utilizing measurements of structural vibration responses only. With its complex mathematical structure and need for more reliable input estimations, the inverse problem is still a fundamental subject of research among mathematicians and engineering scientists. This book contains 11 articles that touch upon various aspects of inverse dynamic problems
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