Ubiquitous sensorization for multimodal assessment of driving patterns

Sustainability issues and sustainable behaviours are becoming concerns of increasing signi cance in our society. In the case of transportation systems, it would be important to know the impact of a given driving behaviour over sustainability factors. This paper describes a system that integrates ubiquitous mobile sensors available on devices such as smartphones, intelligent wristbands and smartwatches, in order to determine and classify driving patterns and to assess driving e ficiency and driver's moods. It first identi fies the main attributes for contextual information, with relevance to driving analysis. Next, it describes how to obtain that information from ubiquitous mobile sensors, usually carried by drivers. Finally, it addresses the multimodal assessment process which produces the analysis of driving patterns and the classi cation of driving moods, promoting the identifi cation of either regular or aggressive driving patterns, and the classi fication of mood types between aggressive and relaxed. Such an approach enables ubiquitous sensing of personal driving patterns across diff erent vehicles, which can be used in sustainability frameworks, driving alerts and recommendation systems.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012). It is also supported by a doctoral grant, SFRH/BD/78713/2011, issued by FCT in Portugal

Traffic expression through ubiquitous and pervasive sensorization - smart cities and assessment of driving behaviour

The number of portable and wearable devices has been increasing in the population of most developed countries. Meanwhile, the capacity to monitor and register not only data about people’s habits and locations but also more complex data such as intensity and strength of movements has created an opportunity to their contribution to the general wealth and sustainability of environments. Ambient Intelligence and Intelligent Decision Making processes can benefit from the knowledge gathered by these devices to improve decisions on everyday tasks such as planning navigation routes by car, bicycle or other means of transportation and avoiding route perils. Current applications in this area demonstrate the usefulness of real time system that inform the user of conditions in the surrounding area. Nevertheless, the approach in this work aims to describe models and approaches to automatically identify current states of traffic inside cities and relate such information with knowledge obtained from historical data recovered by ubiquitous and pervasive devices. Such objective is delivered by analysing real time contributions from those devices and identifying hazardous situations and problematic sites under defined criteria that has significant influence towards user well-being, economic and environmental aspects, as defined is the sustainability definition

Ambient intelligence and affective computing: a contribute to energetic sustainability

Tese de Doutoramento em Informática.economy and the citizen behaviours are putting stress on resources at increasing scales. Society demands sustainable solutions for these problems. However, these solutions need to compromise restrictions enforced by either society, physics and resources. This leads to the traditional dimensions of sustainability: economic, environmental and social, which need to be addressed as a whole in order to find sustainable configurations. Although not as old as sustainability itself, computational sustainability provides methods to specify and intervene in sustainability problems. The most used approaches to computational sustainability systems target constraint conditions, computer simulation and machine learning to solve sustainability problems. Computer science can leverage computational sustainability to acquire relevant information from environment and users, plan and predict approaches to problems and act upon physical systems. This thesis presents an archetype platform, the People Help Energy Savings and Sustainability (PHESS), which results from experiments upon computational sustainability problems with the aid of action-research methodology. It is aimed at intelligent environments such as smart cites and ambient assisted living, and makes use of ubiquitous technologies, such as the Internet of Things (IoT) and pervasive computing. More than just measuring and reporting tool, the archetype aims to promote behavioural change and continuous improvement through techniques taken from fields such as intelligent environments, gamification and affective computing which help improve sustainability scenarios. This archetype enabled the implementation of case studies where the platform was used to assess energy consumption to manage and monitor user environments, user comfort and urban transportation to demonstrate the adaptability of the archetype to different kinds of scenarios.A sociedade depara-se, muitas vezes, com problemas de sustentabilidade. É um facto que a evolução económica e os comportamentos dos cidadãos estão a colocar pressão sobre os recursos naturais numa escala cada vez maior. A sociedade exige soluções sustentáveis para estes problemas. No entanto, estas soluções devem harmonizar restrições impostas pela sociedade, a física e os recursos. Estes fatores conduzem às dimensões tradicionais da sustentabilidade: económica, ambiental e social, que precisam ser tratadas como um todo, com o intuito de encontrar configurações sustentáveis. Embora não tão antiga quanto a própria sustentabilidade, a sustentabilidade computacional fornece métodos para especificar e intervir nos problemas de sustentabilidade. As abordagens mais usadas para sistemas computacionais de sustentabilidade abordam restrição de condições, simulação por computador e aprendizagem máquina para resolver problemas de sustentabilidade. A ciência da computação pode melhorar o desempenho da sustentabilidade computacional através da criação de informação relevante a partir do ambiente e seus utilizadores, planear e prever abordagens para os problemas e agir sobre sistemas físicos. Esta tese de doutoramento apresenta um arquétipo, o Pessoas Ajudam na Economia de Energia e na Sustentabilidade (PHESS People Help Energy Savings and Sustainability), que é o resultado de experiências sobre problemas de sustentabilidade computacional com o aUXIlio da metodologia de action-research. É destinada a ambientes inteligentes, como por exemplo cidades inteligentes e ambientes de vida assistida e faz uso de tecnologias ubíquas, tais como a Internet das Coisas (IoT - Internet of Things) e computação pervasiva. Mais do que apenas medir e elaborar relatórios, o arquétipo tem como objetivo promover a mudança de comportamentos e a melhoria contínua através de técnicas de ramos como ambientes inteligentes, gamification e computação afetiva que ajudam a melhorar cenários de sustentabilidade. Este arquétipo possibilitou a implementação de diversos casos de estudo onde a plataforma foi usada para gerir e monitorizar ambientes e utilizadores, o conforto dos utilizadores e transportes urbanos, para demonstrar a capacidade de adaptação do arquétipo a diferentes cenários reais

A Computational Method based on Radio Frequency Technologies for the Analysis of Accessibility of Disabled People in Sustainable Cities

The sustainability strategy in urban spaces arises from reflecting on how to achieve a more habitable city and is materialized in a series of sustainable transformations aimed at humanizing different environments so that they can be used and enjoyed by everyone without exception and regardless of their ability. Modern communication technologies allow new opportunities to analyze efficiency in the use of urban spaces from several points of view: adequacy of facilities, usability, and social integration capabilities. The research presented in this paper proposes a method to perform an analysis of movement accessibility in sustainable cities based on radio frequency technologies and the ubiquitous computing possibilities of the new Internet of Things paradigm. The proposal can be deployed in both indoor and outdoor environments to check specific locations of a city. Finally, a case study in a controlled context has been simulated to validate the proposal as a pre-deployment step in urban environments

4th International Symposium on Ambient Intelligence (ISAmI 2013)

Ambient Intelligence (AmI) is a recent paradigm emerging from Artificial Intelligence (AI), where computers are used as proactive tools assisting people with their day-to-day activities, making everyone’s life more comfortable. Another main concern of AmI originates from the human computer interaction domain and focuses on offering ways to interact with systems in a more natural way by means user friendly interfaces. This field is evolving quickly as can be witnessed by the emerging natural language and gesture based types of interaction. The inclusion of computational power and communication technologies in everyday objects is growing and their embedding into our environments should be as invisible as possible. In order for AmI to be successful, human interaction with computing power and embedded systems in the surroundings should be smooth and happen without people actually noticing it. The only awareness people should have arises from AmI: more safety, comfort and wellbeing, emerging in a natural and inherent way. ISAmI is the International Symposium on Ambient Intelligence and aiming to bring together researchers from various disciplines that constitute the scientific field of Ambient Intelligence to present and discuss the latest results, new ideas, projects and lessons learned, namely in terms of software and applications, and aims to bring together researchers from various disciplines that are interested in all aspects of this area

Digital transformation and business models in maritime trade supply chains

rmation, and the adoption of certain business models in the context of the maritime trade supply chain industry. Most specifically, it enquires the impact that the former might have on the latter. The question’s relevance is twofold. On the one hand, the pace of both technological and business innovation has accelerated during the last 15 years, especially for certain industries. On the other hand, while there has been some degree of innovation in maritime trade supply chains, the industry lags behind other economic sectors; still working with technologies, business models and processes that predate the contemporary globalization era. Thus, understanding how and why the adoption of certain technologies might generate new ways of creating, delivering and capturing value in maritime trade supply chains, becomes a significant undertaking from both a theoretical and practical perspective. To address this enquiry, we have conducted four separate studies in this dissertation. In Chapter 2, we conduct a theoretical synthesis in order to provide a general theoretical background for the research conducted in the subsequent chapters. Chapter 3 is mainly concerned with physical flows. We investigate what impact does the adoption of Industry 4.0 technologies by seaports might have on their business models. To define these, we refer to the classification of seaports across a generational ladder: from 1st generation to 5th generation ports; referring as well to the novel construct of Port 4.0, and the commonly used “smart port” term. In Chapter 4 we turn to information flows. Most specifically, we explore the influence that distributed ledger technology (DLT) —most commonly known as blockchain— might have on the adoption of sustainable business models in the shipping industry. Chapter 5 focus on financial flows. It presents a design science study on a problem known as the trade finance gap; understood as the difference between the total supply of and demand for trade finance in international trade on a global level. The main question addressed is how to design a new business model that would address the causes behind the said trade finance gap. To conclude, this dissertation explores how digital transformation affects or impacts business models in maritime trade supply chains. It does so, by conducting studies on different contexts, each of them primarily focused on either physical, information or financial flows. From a theoretical perspective, the dissertation provides insights on the interplay between the three flows in maritime trade; with a special focus on how digital transformation, by affecting this interplay, drives or contributes to the adoption of new business models. Most specifically, Industry 4.0 technologies like IoT or DLT improve the way information flows interact with physical and financial flows. From a practical/managerial perspective, the research provides useful insights for business executives and policy makers, on how digital transformation should be faced at the strategic, tactical and operational level. By understanding how new technologies affect the ways in which value is created, delivered and captured, decision makers can design better business models, increasing competitiveness; or implement more adequate policies and strategies. Most importantly, the dissertation aims to serve as a source of ideas for those entrepreneurs who, through their startups, will design and develop innovative use cases and business models for the maritime industry.Aquesta investigació doctoral explora la interrelació entre els fenòmens contemporanis coneguts com a transformació digital i l’adopció de certs models de negoci en el context de la indústria de la cadena de subministrament del comerç marítim. Més concretament, indaga sobre l’impacte que els primers poguessin tenir sobre la segona. La rellevància de la pregunta és doble. D’una banda, el ritme de la innovació tant tecnològica com empresarial s’ha accelerat durant els darrers 15 anys, especialment per a determinades indústries. D’altra banda, si bé hi ha hagut cert grau d’innovació a les cadenes de subministrament del comerç marítim, la indústria va darrera d’altres sectors econòmics; segueix treballant amb tecnologies, models de negocis i processos anteriors a l’era de la globalització contemporània. Per tant, comprendre com i per què l’adopció de certes tecnologies pot generar noves maneres de crear, distribuir i capturar valor a les cadenes de subministrament del comerç marítim es converteix en una tasca important tant des d’una perspectiva teòrica com pràctica. Per indagar-hi, hem realitzat quatre estudis en aquesta dissertació. Al Capítol 2, duem a terme una síntesi teòrica per tal de proporcionar un marc teòric general per a la recerca realitzada en els capítols següents. El capítol 3 s’ocupa principalment dels fluxos físics. Investiguem quin impacte podria tenir l’adopció de tecnologies Indústria 4.0 per part dels ports marítims als seus models de negoci. Al Capítol 4 passem als fluxos d’informació. Més específicament, explorem la influència que la tecnologia de distributed ledger (DLT), més comunament coneguda com a blockchain, podria tenir en l’adopció de models de negoci sostenibles a la indústria del transport marítim. El capítol 5 se centra en els fluxos financers. Presenta un estudi de disseny sobre un problema conegut com la bretxa de finançament del comerç (trade finance gap); entès com la diferència entre l’oferta i la demanda total de finançament al comerç internacional a nivell global. Per concloure, aquesta dissertació explora com la transformació digital afecta o impacta els models de negoci a les cadenes de subministrament del comerç marítim. Ho fa mitjançant la realització d’estudis sobre diferents contextos, cadascun centrat principalment en els fluxos físics, d’informació o financers. Des d’una perspectiva teòrica, la dissertació proporciona informació sobre la interacció entre els tres fluxos al comerç marítim; amb un enfocament especial com la transformació digital, en afectar aquesta interacció, impulsa o contribueix a l’adopció de nous models de negoci. Més específicament, les tecnologies d'industria 4.0 com IoT o DLT milloren la manera com els fluxos d’informació interactuen amb els fluxos físics i financers. Des d’una perspectiva pràctica/gerencial, la recerca proporciona informació útil per als executius de negocis i els dissenyadors de polítiques sobre com cal enfrontar la transformació digital a nivell estratègic, tàctic i operatiu. En comprendre com les noves tecnologies afecten les formes en què es crea, distribueix i captura el valor, els prenedors de decisions poden dissenyar millors models de negoci, augmentant la competitivitat; o implementar polítiques i estratègies més adequades. El que és més important, la dissertació té com a objectiu servir com a font d’idees per als emprenedors que, a través de les startups, dissenyaran i desenvoluparan casos d’ús innovadors i models de negoci per a la indústria marítima.Esta investigación doctoral explora la interrelación entre los fenómenos contemporáneos conocidos como transformación digital y la adopción de ciertos modelos de negocio en el contexto de la industria de la cadena de suministro del comercio marítimo. Más concretamente, indaga sobre el impacto que los primeros pudieran tener sobre la segunda. La relevancia de la pregunta es doble. Por un lado, el ritmo de la innovación tanto tecnológica como empresarial se ha acelerado durante los últimos 15 años, especialmente para determinadas industrias. Por otro lado, si bien ha habido cierto grado de innovación en las cadenas de suministro del comercio marítimo, la industria va a la zaga de otros sectores económicos; sigue trabajando con tecnologías, modelos de negocios y procesos que son anteriores a la era de la globalización contemporánea. Por lo tanto, comprender cómo y por qué la adopción de ciertas tecnologías puede generar nuevas formas de crear, distribuir y capturar valor en las cadenas de suministro del comercio marítimo se convierte en una tarea importante tanto desde una perspectiva teórica como práctica. Para indagar sobre ello, hemos realizado cuatro estudios en esta disertación. En el Capítulo 2, llevamos a cabo una síntesis teórica con el fin de proporcionar un marco teórico general para la investigación realizada en los capítulos siguientes. Para ello, comenzamos desarrollando una base bibliográfica, fundamentada en 3 disciplinas: Estudios Marítimos, Ciencias de la Gestión e Investigación de Sistemas de Información. El enfoque central se basa entonces en la construcción de los tres flujos presentes en las cadenas de suministro del comercio marítimo: flujos físicos, de información y financieros. Para cada uno de los flujos nos hacemos tres preguntas básicas: ¿qué? (describiendo el contenido del flujo), ¿cómo? (describiendo los mecanismos), y ¿por qué? (comprender qué impulsa el flujo en cuestión). Para los flujos físicos, nos referimos a su contenido con el término global de “carga”, el mecanismo como multimodalidad y la causa impulsora como producción o consumo. Para los flujos de información, el contenido son datos o información (en sentido estricto), el mecanismo es en papel o electrónico, y la causa impulsora es su rol como recurso para la toma de decisiones. Los flujos financieros se refieren al dinero, que fluye ya sea por medio de pagos o créditos, bajo un modelo de flujo circular como lógica impulsora. Luego, el capítulo ofrece una explicación básica de cómo se integran los tres flujos: los flujos físicos y financieros se basan en intercambios mutuos entre actores a lo largo de la cadena de suministro (que se mueven en direcciones opuestas), mientras que los flujos de información se mueven en ambas direcciones, apoyando a los dos primeros. Finalmente, el capítulo tiene como objetivo contribuir a la comprensión del concepto de modelo de negocio, observando que los modelos de negocio pueden ser representados por descripciones específicas de los flujos físicos, financieros y de información entre una empresa y otros actores económicos. El Capítulo 3 se ocupa principalmente de los flujos físicos. Investigamos qué impacto podría tener la adopción de tecnologías Industria 4.0 por parte de los puertos marítimos en sus modelos de negocio. Para definirlos, nos referimos a la clasificación de los puertos marítimos a través de una escala generacional: desde puertos de 1ra hasta 5ta generación; refiriéndonos también al nuevo concepto de Puerto 4.0, y al común término “puerto inteligente”. Basándonos en la literatura de Estudios Marítimos, proporcionamos una lista de características y funcionalidades que caracterizarían a un puerto inteligente y ofrecemos una explicación general sobre lo que debería significar “inteligente” o “inteligencia” en este contexto. A continuación, desarrollamos un modelo conceptual expresado como una serie de proposiciones, construidas en torno a dos mecanismos de influencia tomados de las Ciencias de Gestión: el impulso tecnológico (technology push) y la atracción del mercado (market pull). Más específicamente, el modelo pretende explicar cómo las tecnologías de Industria 4.0, a través de estos mecanismos, influyen en los modelos de negocio de los puertos marítimos en tres áreas: operaciones, estrategias e inversiones. Para evaluar este modelo conceptual, llevamos a cabo un estudio de caso exploratorio sobre el puerto de Barcelona, basado en el análisis de contenido de fuentes documentales (especialmente el tercer y cuarto planes estratégicos), así como una entrevista semiestructurada. Nuestra evaluación muestra una primacía de los mecanismos de influencia del mercado y la evaluación comparativa (benchmarking), como la principal forma en que la adopción de la Industria 4.0 impulsa la innovación de modelos de negocio, al menos para los puertos marítimos con las características y circunstancias de Barcelona. En el Capítulo 4 pasamos a los flujos de información. Más específicamente, exploramos la influencia que la tecnología de distributed ledger (DLT), más comúnmente conocida como blockchain, podría tener en la adopción de modelos de negocio sostenibles en la industria del transporte marítimo. Uno de los pilares teóricos centrales del estudio es la concepción de la información como recurso, proporcionada por la disciplina Gestión de Recursos de Información. Sobre esta concepción, proponemos el concepto de la circularidad de la información, que tiene lugar cuando la información que se genera como subproducto o resultado de procesos comerciales, se utiliza luego como entrada/recurso para procesos posteriores. Posteriormente, desarrollamos un modelo conceptual que representa la relación entre DLT y el transporte marítimo sostenible, expresado como 5 proposiciones. Para evaluar el modelo, realizamos un estudio de caso exploratorio sobre TradeLens, una plataforma de información basada en DLT para cadenas de suministro globales, utilizando la técnica de análisis de contenido. Nuestra evaluación preliminar encuentra que la DLT, al permitir una mayor circularidad de la información y comportamientos asociativos entre los actores de la cadena de suministro, se convierte en un catalizador para modelos de negocio sostenibles, que a su vez impulsan prácticas sostenibles en la industria del transporte marítimo. La investigación amplía la literatura previa sobre la tecnología DLT y su impacto en la economía circular, los modelos de negocios asociativos y la coordinación inter-empresarial en general, en el contexto del transporte marítimo. El capítulo 5 se centra en los flujos financieros. Presenta un estudio de diseño sobre un problema conocido como la brecha de financiación del comercio (trade finance gap); entendido como la diferencia entre la oferta y la demanda total de financiamiento en el comercio internacional a nivel global. La principal pregunta que se aborda es cómo diseñar un nuevo modelo de negocio que aborde las causas detrás de dicha brecha de financiamiento comercial. Como primer paso, basándonos en literatura académica y gris, clasificamos un conjunto de causas detrás de la problemática, según estén relacionadas con la oferta (es decir, que pertenezcan a la capacidad de las instituciones financieras para proporcionar financiamiento comercial) relacionadas con la demanda (relativas a las empresas que necesitan financiación comercial), o ambas. Adentrándonos en la teoría de la intermediación financiera, analizamos a continuación el novedoso concepto de finanzas descentralizadas (DeFi), proponiendo un significado más amplio que el prevaleciente, que lo reduce a funciones basadas en tecnología blockchain y criptomonedas. Nuestro significado más amplio se basa en cuatro perspectivas: DeFi como desintermediación, como disminución de la concentración, como desagregación de las funciones financieras y como financiación alternativa. Luego, el capítulo presenta un modelo de un sistema basado en DeFi para la financiación del comercio, más específicamente, para el procesamiento de créditos documentarios. En él, describimos cómo el modelo difiere y mejora el instrumento de financiación comercial más tradicional: la carta de crédito. Lo que es más importante, en línea con la metodología de Investigación de Diseño Científico (Design Science Research), evaluamos cómo el modelo aborda las causas detrás de la problemática de la brecha de financiamiento comercial, así como sus contribuciones teóricas. La conclusión es que un modelo basado en DeFi para la financiación del comercio puede reducir los costes de transacción, aumentar la liquidez y proporcionar mejor información sobre las empresas para mejorar su evaluación de la solvencia. Para concluir, esta disertación explora cómo la transformación digital afecta o impacta los modelos de negocio en las cadenas de suministro del comercio marítimo. Lo hace mediante la realización de estudios sobre diferentes contextos, cada uno de ellos centrado principalmente en los flujos físicos, de información o financieros. Desde una perspectiva teórica, la disertación proporciona información sobre la interacción entre los tres flujos en el comercio marítimo; con un enfoque especial en cómo la transformación digital, al afectar esta interacción, impulsa o contribuye a la adopción de nuevos modelos de negocio. Más específicamente, las tecnologías de Industria 4.0 como IoT o DLT mejoran la forma en que los flujos de información interactúan con los flujos físicos y financieros. Desde una perspectiva práctica/gerencial, la investigación proporciona información útil para los ejecutivos de negocios y los diseñadores de políticas sobre cómo se debe enfrentar la transformación digital a nivel estratégico, táctico y operativo. Al comprender cómo las nuevas tecnologías afectan las formas en que se crea, distribuye y captura el valor, los tomadores de decisiones pueden diseñar mejores modelos de negocio, aumentando la competitividad; o implementar políticas y estrategias más adecuadas. Lo que es más importante, la disertación tiene como objetivo servir como fuente de ideas para aquellos emprendedores que, a través de sus startups, diseñarán y desarrollarán casos de uso innovadores y modelos de negocio para la industria marítima.Postprint (published version

Technological drivers of seaports' business model innovation: An exploratory case study on the port of Barcelona

The role of seaports has evolved from being simple sea/land interfaces to becoming increasingly value-adding entities in global supply chains. A port that is today at the forefront of this trend is characterized as a fifth generation (5G) port, a “smart port” or, more recently, a Port 4.0. These characterisations, introduced by Maritime Studies literature, are closely equivalent to the business model concept developed by the Strategic Management literature in the last decades. This research paper inquires on the influence that Industry 4.0 technologies might have on the adoption of more sophisticated business models by seaports, and the mechanisms through which this influence is driven: in particular the role that technology push and market pull mechanisms might play. To this end, it develops a conceptual model that aims to provide an explanation of the relationship between the adoption of Industry 4.0 technologies and the evolution of seaports’ business models. This model is then evaluated against an exploratory case study on the port of Barcelona. Finally, the paper explores what would “smartness” mean in a seaport context.Postprint (published version

SHELDON Smart habitat for the elderly.

An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare

Creating intelligible metrics road traffic analysis

Dissertação de mestrado em Computer ScienceThe increasing pervasiveness and lower cost of electronic devices equipped with sensors is leading to a greater and cheaper availability of localized information. The advent of the internet has brought phenomena such as crowd-sourced maps and related data. The combination of the availability of mobile information, community built maps, with the added convenience of retrieving information over the internet creates the opportunity to contextualize data in new ways. This work takes that opportunity and attempts to generalize the detection of driving events which are deemed problematic as a function of contextual factors, such as neighbouring buildings, areas, amenities, the weather, and the time of day, week or month. In order to research the problem at hand, the issue is first contextualized properly, providing an overview of important factors, namely Smart Cities, Data Fusion, and Machine Learning. That is followed by a chapter concerning the state of the art, that showcases related projects and how the various facets of road traffic expression are being approached. The focus is then turned to creating a solution. At first this consists in aggregating data so as to create a richer context than would be present otherwise, this includes the retrieval from different services, as well as the composition of a unique view of the same driving situation with new dimensions added to it. And then Models were created using different Machine Learning methods, and a comparison of results according to selected and justified evaluation metrics was made. The compared Methods are Decision Tree, Naive Bayes, and Support Vector Machine. The different types of information were evaluated on their own as potential classifiers and then were evaluated together, leading to the conclusion that the various types combined allow for the creation of better models capable of finding problems with more confidence in such results. According to the tests performed the chosen approach can improve the performance over a baseline approach and point out problematic situations with a precision of over 90%. As expected by not using factors concerning the driver state or acceleration the scope of problems which are detected is limited in domain.A expansão e menor custo de dispositivos eletrónicos equipados com sensores está a levar a uma maior e mais barata disponibilidade de informação localizada. O advento da internet criou fenómenos como a criação de mapas e dados relacionados gerados por comunidades. A combinação da disponibilidade de informação móvel e mapas construídos pela comunidade, em conjunto com uma obtenção de informação através da internet mais conveniente, criou a oportunidade de contextualizar os dados de novas maneiras. Este trabalho faz uso dessa oportunidade e tenta generalizar eventos de condução que são considerados problemáticos em função de factores contextuais, tais como a presença de edifícios, áreas, e comodidades na vizinhança, o clima, e a hora do dia, a semana, ou o mês. De modo a investigar esta questão, o problema é contextualizado como emergente no tópico de Cidades Inteligentes, e explorado com recurso a Fusão de Dados e a Aprendizagem Máquina. O estado da arte é exposto, através de projectos relacionados à expressão do tráfego rodoviário, dando relevo às várias facetas até então investigadas por outros autores de modo a enquadrar o trabalho presente. Dado o enquadramento e concretização do problema, é proposta uma solução. Esta solução passa por inicialmente agregar dados de modo a enriquecer o contexto, incluindo a recolha destes de vários serviços, e uma composição dos dados recolhidos numa perspectiva única referente a uma situação de condução. Após este enriquecimento dos dados, são criados modelos com base em diferentes técnicas de Aprendizagem Máquina. Os métodos utilizados são Decision Tree, Naive Bayes, e Support Vector Machine. Os resultados conseguidos com estes modelos são depois comparados de acordo com as métricas de avaliação seleccionadas. Uma comparação foi feita também com diferentes tipos de informação separadamente e também em conjunto, levando à conclusão de que os vários tipos combinados permitem a criação de melhores modelos capazes de encontrar problemas com mais confiança nos resultados produzidos. De acordo com os testes executados a abordagem escolhida consegue melhorar resultados de um modelo base e descobrir situações problemáticas de condução com uma precisão acima dos 90%. No entanto, como seria de esperar, o âmbito dos problemas detectados tem um domínio limitado aos aspectos seleccionados

Methods and techniques for analyzing human factors facets on drivers

Mención Internacional en el título de doctorWith millions of cars moving daily, driving is the most performed activity worldwide. Unfortunately, according to the World Health Organization (WHO), every year, around 1.35 million people worldwide die from road traffic accidents and, in addition, between 20 and 50 million people are injured, placing road traffic accidents as the second leading cause of death among people between the ages of 5 and 29. According to WHO, human errors, such as speeding, driving under the influence of drugs, fatigue, or distractions at the wheel, are the underlying cause of most road accidents. Global reports on road safety such as "Road safety in the European Union. Trends, statistics, and main challenges" prepared by the European Commission in 2018 presented a statistical analysis that related road accident mortality rates and periods segmented by hours and days of the week. This report revealed that the highest incidence of mortality occurs regularly in the afternoons during working days, coinciding with the period when the volume of traffic increases and when any human error is much more likely to cause a traffic accident. Accordingly, mitigating human errors in driving is a challenge, and there is currently a growing trend in the proposal for technological solutions intended to integrate driver information into advanced driving systems to improve driver performance and ergonomics. The study of human factors in the field of driving is a multidisciplinary field in which several areas of knowledge converge, among which stand out psychology, physiology, instrumentation, signal treatment, machine learning, the integration of information and communication technologies (ICTs), and the design of human-machine communication interfaces. The main objective of this thesis is to exploit knowledge related to the different facets of human factors in the field of driving. Specific objectives include identifying tasks related to driving, the detection of unfavorable cognitive states in the driver, such as stress, and, transversely, the proposal for an architecture for the integration and coordination of driver monitoring systems with other active safety systems. It should be noted that the specific objectives address the critical aspects in each of the issues to be addressed. Identifying driving-related tasks is one of the primary aspects of the conceptual framework of driver modeling. Identifying maneuvers that a driver performs requires training beforehand a model with examples of each maneuver to be identified. To this end, a methodology was established to form a data set in which a relationship is established between the handling of the driving controls (steering wheel, pedals, gear lever, and turn indicators) and a series of adequately identified maneuvers. This methodology consisted of designing different driving scenarios in a realistic driving simulator for each type of maneuver, including stop, overtaking, turns, and specific maneuvers such as U-turn and three-point turn. From the perspective of detecting unfavorable cognitive states in the driver, stress can damage cognitive faculties, causing failures in the decision-making process. Physiological signals such as measurements derived from the heart rhythm or the change of electrical properties of the skin are reliable indicators when assessing whether a person is going through an episode of acute stress. However, the detection of stress patterns is still an open problem. Despite advances in sensor design for the non-invasive collection of physiological signals, certain factors prevent reaching models capable of detecting stress patterns in any subject. This thesis addresses two aspects of stress detection: the collection of physiological values during stress elicitation through laboratory techniques such as the Stroop effect and driving tests; and the detection of stress by designing a process flow based on unsupervised learning techniques, delving into the problems associated with the variability of intra- and inter-individual physiological measures that prevent the achievement of generalist models. Finally, in addition to developing models that address the different aspects of monitoring, the orchestration of monitoring systems and active safety systems is a transversal and essential aspect in improving safety, ergonomics, and driving experience. Both from the perspective of integration into test platforms and integration into final systems, the problem of deploying multiple active safety systems lies in the adoption of monolithic models where the system-specific functionality is run in isolation, without considering aspects such as cooperation and interoperability with other safety systems. This thesis addresses the problem of the development of more complex systems where monitoring systems condition the operability of multiple active safety systems. To this end, a mediation architecture is proposed to coordinate the reception and delivery of data flows generated by the various systems involved, including external sensors (lasers, external cameras), cabin sensors (cameras, smartwatches), detection models, deliberative models, delivery systems and machine-human communication interfaces. Ontology-based data modeling plays a crucial role in structuring all this information and consolidating the semantic representation of the driving scene, thus allowing the development of models based on data fusion.I would like to thank the Ministry of Economy and Competitiveness for granting me the predoctoral fellowship BES-2016-078143 corresponding to the project TRA2015-63708-R, which provided me the opportunity of conducting all my Ph. D activities, including completing an international internship.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: José María Armingol Moreno.- Secretario: Felipe Jiménez Alonso.- Vocal: Luis Mart