Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

CONVR 2011 : Proceedings of the 11th International Conference on Construction Applications of Virtual Reality

Proceedings of the 11th International Conference on Construction Applications of Virtual Realit

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

Proceedings of the 3rd International Conference on Models and Technologies for Intelligent Transportation Systems 2013

Challenges arising from an increasing traffic demand, limited resource availability and growing quality expectations of the customers can only be met successfully, if each transport mode is regarded as an intelligent transportation system itself, but also as part of one intelligent transportation system with “intelligent” intramodal and intermodal interfaces. This topic is well reflected in the Third International Conference on “Models and Technologies for Intelligent Transportation Systems” which took place in Dresden 2013 (previous editions: Rome 2009, Leuven 2011). With its variety of traffic management problems that can be solved using similar methods and technologies, but with application specific models, objective functions and constraints the conference stands for an intensive exchange between theory and practice and the presentation of case studies for all transport modes and gives a discussion forum for control engineers, computer scientists, mathematicians and other researchers and practitioners. The present book comprises fifty short papers accepted for presentation at the Third Edition of the conference. All submissions have undergone intensive reviews by the organisers of the special sessions, the members of the scientific and technical advisory committees and further external experts in the field. Like the conference itself the proceedings are structured in twelve streams: the more model-oriented streams of Road-Bound Public Transport Management, Modelling and Control of Urban Traffic Flow, Railway Traffic Management in four different sessions, Air Traffic Management, Water Traffic and Traffic and Transit Assignment, as well as the technology-oriented streams of Floating Car Data, Localisation Technologies for Intelligent Transportation Systems and Image Processing in Transportation. With this broad range of topics this book will be of interest to a number of groups: ITS experts in research and industry, students of transport and control engineering, operations research and computer science. The case studies will also be of interest for transport operators and members of traffic administration

Indoor positioning system for wireless sensor networks

Tese de Doutoramento - Programa Doutoral em Engenharia Electrónica e ComputadoresPositioning technologies are ubiquitous nowadays. From the implementation of the global positioning system (GPS) until now, its evolution, acceptance and spread has been unanimous, due to the underlying advantages the system brings. Currently, these systems are present in many different scenarios, from the home to the movie theatre, at work, during a walk in the park. Many applications provide useful information, based on the current position of the user, in order to provide results of interest. Positioning systems can be implemented in a wide range of contexts: in hospitals to locate equipment and guide patients to the necessary resources, or in public spaces like museums, to guide tourists during visits. They can also be used in a gymnasium to point the user to his next workout machine and, simultaneously, gather information regarding his fitness plan. In a congress or conference, the positioning system can be used to provide information to its participants about the on-going presentations. Devices can also be monitored to prevent thefts. Privacy and security issues are also important in positioning systems. A user might not want to be localized or its location to be known, permanently or during a time interval, in different locations. This information is therefore sensitive to the user and influences directly the acceptance of the system itself. Concerning outdoor systems, GPS is in fact the system of reference. However, this system cannot be used in indoor environment, due to the high attenuation of the satellite signals from non-line-of-sight conditions. Another issue related to GPS is the power consumption. The integration of these devices with wireless sensor networks becomes prohibitive, due to the low power consumption profile associated with devices in this type of networks. As such, this work proposes an indoor positioning system for wireless sensor networks, having in consideration the low energy consumption and low computational capacity profile. The proposed indoor positioning system is composed of two modules: the received signal strength positioning module and the stride and heading positioning module. For the first module, an experimental performance comparison between several received signal strength based algorithms was conducted in order to assess its performance in a predefined indoor environment. Modifications to the algorithm with higher performance were implemented and evaluated, by introducing a model of the effect of the human body in the received signal strength. In the case of the second module, a stride and heading system was proposed, which comprises two subsystems: the stride detection and stride length estimation system to detect strides and infer the travelled distance, and an attitude and heading reference system to provide the full three-dimensional orientation stride-by-stride. The stride detection enabled the identification of the gait cycle and detected strides with an error percentage between 0% and 0.9%. For the stride length estimation two methods were proposed, a simplified method, and an improved method with higher computational requirements than the former. The simplified method estimated the total distance with an error between 6.7% and 7.7% of total travelled distance. The improved method achieved an error between 1.2% and 3.7%. Both the stride detection and the improved stride length estimation methods were compared to other methods in the literature with favourable results. For the second subsystem, this work proposed a quaternion-based complementary filter. A generic formulation allows a simple parameterization of the filter, according to the amount of external influences (accelerations and magnetic interferences) that are expected, depending on the location that the device is to be attached on the human body. The generic formulation enables the inclusion/exclusion of components, thus allowing design choices according to the needs of applications in wireless sensor networks. The proposed method was compared to two other existing solutions in terms of robustness to interferences and execution time, also presenting a favourable outcome.Os sistemas de posicionamento fazem parte do quotidiano. Desde a implementação do sistema GPS (Global Positioning System) até aos dias que correm, a evolução, aceitação e disseminação destes sistemas foi unânime, derivada das vantagens subjacentes da sua utilização. Hoje em dia, eles estão presentes nos mais variados cenários, desde o lar até́ à sala de cinema, no trabalho, num passeio ao ar livre. São várias as aplicações que nos fornecem informação útil, usando como base a descrição da posição atual, de modo a produzir resultados de maior interesse para os utilizadores. Os sistemas de posicionamento podem ser implementados nos mais variados contextos, como por exemplo: nos hospitais, para localizar equipamento e guiar os pacientes aos recursos necessários, ou nas grandes superfícies públicas, como por exemplo museus, para guiar os turistas durante as visitas. Podem ser igualmente utilizados num ginásio para indicar ao utilizador qual a máquina para onde se deve dirigir durante o seu treino e, simultaneamente, obter informação acerca desta mesma máquina. Num congresso ou conferência, o sistema de localização pode ser utilizado para fornecer informação aos seus participantes sobre as apresentações que estão a decorrer no momento. Os dispositivos também podem ser monitorizados para prevenir roubos. Existem também questões de privacidade e segurança associados aos sistemas de posicionamento. Um utilizador poderá não desejar ser localizado ou que a sua localização seja conhecida, permanentemente ou num determinado intervalo de tempo, num ou em vários locais. Esta informação é por isso sensível ao utilizador e influencia diretamente a aceitação do próprio sistema. No que diz respeito aos sistemas utilizados no exterior, o GPS (ou posicionamento por satélite) é de facto o sistema mais utilizado. No entanto, em ambiente interior este sistema não pode ser usado, por causa da grande atenuação dos sinais provenientes dos satélites devido à falta de linha de vista. Um outro problema associado ao recetor GPS está relacionado com as suas características elétricas, nomeadamente os consumos energéticos. A integração destes dispositivos nas redes de sensores sem fios torna-se proibitiva, devido ao perfil de baixo consumo associado a estas redes. Este trabalho propõe um sistema de posicionamento para redes de sensores sem fio em ambiente interior, tendo em conta o perfil de baixo consumo de potência e baixa capacidade de processamento. O sistema proposto é constituído por dois módulos: o modulo de posicionamento por potência de sinal recebido e o módulo de navegação inercial pedestre. Para o primeiro módulo foi feita uma comparação experimental entre vários algoritmos que utilizam a potência do sinal recebido, de modo a avaliar a sua utilização num ambiente interior pré-definido. Ao algoritmo com melhor prestação foram implementadas e testadas modificações, utilizando um modelo do efeito do corpo na potência do sinal recebido. Para o segundo módulo foi proposto um sistema de navegação inercial pedestre. Este sistema é composto por dois subsistemas: o subsistema de deteção de passos e estimação de distância percorrida; e o subsistema de orientação que fornece a direção do movimento do utilizador, passo a passo. O sistema de deteção de passos proposto permite a identificação das fases da marcha, detetando passos com um erro entre 0% e 0.9%. Para o sistema de estimação da distância foram propostos dois métodos: um método simplificado de baixa complexidade e um método melhorado, mas com maiores requisitos computacionais quando comparado com o primeiro. O método simplificado estima a distância total com erros entre 6.7% e 7.7% da distância percorrida. O método melhorado por sua vez alcança erros entre 1.2% e 3.7%. Ambos os sistemas foram comparados com outros sistemas da literatura apresentando resultados favoráveis. Para o sistema de orientação, este trabalho propõe um filtro complementar baseado em quaterniões. É utilizada uma formulação genérica que permite uma parametrização simples do filtro, de acordo com as influências externas (acelerações e interferências magnéticas) que são expectáveis, dependendo da localização onde se pretende colocar o dispositivo no corpo humano. O algoritmo desenvolvido permite a inclusão/exclusão de componentes, permitindo por isso liberdade de escolha para melhor satisfazer as necessidades das aplicações em redes de sensores sem fios. O método proposto foi comparado com outras soluções em termos de robustez a interferências e tempo de execução, apresentando também resultados positivos

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity