Agent-based Modelling and Big Data: Applications for Maritime Traffic Analysis

Agent based modeling (ABM) is a powerful tool for examining complex systems in many scientific applications, including maritime transport systems. Growing demands for freight transport and increased industry emphasis on reducing environmental impacts have heightened the focus on vessel and port efficiency. This research aimed to create a maritime route planning model to simulate vessel movement in all waterways. The goal of the ship routing model developed in this research was to develop a simulation tool capable of reproducing real world shipping routes useful for navigation planning, with emphasis on port scheduling and potential application for further use and exploration. A modified breadth-first search algorithm was implemented as a NetLogo ABM in this research. With increasing volumes of ship location monitoring data, new approaches are now possible for examining performance-based metrics and to improve simulations with more precise verification and analysis. A Satellite Automatic Identification System dataset with over 500,000 vessel logs travelling across the Pacific Ocean and into the Port of Metro Vancouver was used as the focal area for model development and validation in this study. Automatic identification system (AIS) is the global standard for maritime navigation and traffic management, and data derived from AIS messages can be used for calibrating simulation model scenarios. In this analysis, the results examined how changes in simulation parameters alter route choice behaviour and how effective large AIS datasets are for validating and calibrating model results. Using large AIS datasets, model results can be quantified to examine how closely they resemble real-time vessels in the same region. Heatmaps provide a data visualization tool that effectively uses large data sets and calculates how closely model results resemble AIS data from the same region. In the case of PMV, the Maritime Ship Routing Model (MSRM) was able to replicate path likeness with a high level of accuracy, generating realistic navigation paths between the many islands on the eastern side of southern Vancouver Island, B.C., a busy marine traffic region and sensitive ecological area. This research highlights the use of ABM as a powerful, user-friendly tool for developing maritime shipping models useful for port scheduling and route analysis. The results of this study emphasize the use of large data sets that are applicable, clean, and reliable as a crucial source for validating and calibrating the MSRM

A general cognitive framework for context-aware systems: extensions and applications for high level information fusion approaches

Mención Internacional en el título de doctorContext-aware systems aims at the development of computational systems that process data acquired from different datasources and adapt their behaviour in order to provide the 'right' information, at the 'right' time, in the 'right' place, in the 'right' way to the 'right' person (Fischer, 2012). Traditionally computational research has tried to answer these needs by means of low-level algorithms. In the last years the combination of numeric and symbolic approaches has offered the opportunity to create systems to deal with these issues. However, although the performance of algorithms and the quality of the data directly provided by computers and devices has quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted to smart environments. This lack of representation does not allow to take advantage of the semantic quality of the information provided by new sensors. This dissertation proposes a set of extensions and applications focused on a cognitive framework for the implementation of context-aware systems based on a general model inspired by the Information Fusion paradigm. This model is stepped in several abstraction levels from low-level raw data to high level scene interpretation whose structure is determined by a set of ontologies. Each ontology level provides a skeleton that includes general concepts and relations to describe entities and their connections. This structure has been designed to promote extensibility and modularity, and might be refined to apply this model in specific domains. This framework combines a priori context knowledge represented with ontologies with real data coming from sensors to support logic-based high-level interpretation of the current situation and to automatically generate feedback recommendations to adjust data acquisition procedures. This work advocates for the introduction of general purpose cognitive layers in order to obtain a closer representation to the human cognition, generate additional knowledge and improve the high-level interpretation. Extensibility and adaptability of the basic ontology levels is demonstrated with the introduction of these traverse semantic layers which are able to be present and represent information at several granularity levels of knowledge using a common formalism. Context-based system must be able to reason about uncertainty. However the reasoning associated to ontologies has been limited to classical description logic mechanisms. This research also tackle the problem of reasoning under uncertainty circumstances through a logic-based paradigm for abductive reasoning: the Belief-Argumentation System. The main contribution of this dissertation is the adaptation of the general architecture and the theoretical proposals to several context-aware application areas such as Ambient Intelligence, Social Signal Processing and surveillance systems. The implementation of prototypes and examples for these areas are explained along this dissertation to progressively illustrate the improvements and extensions in the framework. To initially depict the general model, its components and the basic reasoning mechanisms a video-based Ambient Intelligence application is presented. The advantages and features of the framework extensions through traverse cognitive layers are demonstrated in a Social Signal Processing case for the elaboration of automatic market researches. Finally, the functioning of the system under uncertainty circumstances is illustrated with several examples to support decision makers in the detection of potential threats in common harbor scenarios.Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaPresidente: José Manuel Molina López.- Secretario: Ángel Arroyo.- Vocal: Nayat Sánchez P

Challenges and potential of technology integration in modern ship management practices

This thesis explores the challenges and potential of technology integration in current ship management practices. While technology advancements were designed to be contributing to minimising task complexity, issues such as fatigue, increased administrative burden and technology assisted accidents still plague the industry. In spite of the clearly recognisable benefits of using modern technology in the management of ships, in practice its application appears lacking by a considerable margin. The main driver of the study was to appreciate the cause of this disparity. The study first reviewed a wide body of literature on issues involving the use of technology which included academic literature with empirical evidences and theoretical explanations of implementation of technology at work. With the help of the extant knowledge this research embarked on providing an explanation to the gap that existed in the application of technology in the shipping industry. By taking a case study approach the thesis looked into the induction and integration of technology in the management and operation of ships that primarily interfaced closely between the ship and its management unit on shore. Three companies with mutually diverse management setup were studied. The fourth case comprised of purposefully selected senior members of ships’ staff. The analysis of the data revealed that the manifestation of the gap in technology implementation is caused by deeper influences at work in the shipping industry. The un-optimised technology integration results in the seafarer, who is the keystone to the technology application, becoming a victim of the circumstances. The technology that was intended to ease operations and burdens ends up in controlling him, even leaving him under-resourced and causing fatigue.This was not an unintended outcome but the result of weak regulatory practices, short-term capital outlook and weakened labour practices in the shipping industry all caused by wider social and economic developments affecting not just this industry but businesses globally. The impact of such influences was however more acute in this industry resulting in such extreme consequence. By bringing to light the limited application of some fundamental principles of human-systems integration, this study has attempted to expand the boundaries of research on the subject and contributed to the holistic understanding of the various underlying factors that influence technology integration in ship management processes

Transport 2040 : Impact of Technology on Seafarers - The Future of Work

https://commons.wmu.se/lib_reports/1091/thumbnail.jp

A taxonomy and survey of cyber-physical intrusion detection approaches for vehicles

With the growing threat of cyber and cyber-physical attacks against automobiles, drones, ships, driverless pods and other vehicles, there is also a growing need for intrusion detection approaches that can facilitate defence against such threats. Vehicles tend to have limited processing resources and are energy-constrained. So, any security provision needs to abide by these limitations. At the same time, attacks against vehicles are very rare, often making knowledge-based intrusion detection systems less practical than behaviour-based ones, which is the reverse of what is seen in conventional computing systems. Furthermore, vehicle design and implementation can differ wildly between different types or different manufacturers, which can lead to intrusion detection designs that are vehicle-specific. Equally importantly, vehicles are practically defined by their ability to move, autonomously or not. Movement, as well as other physical manifestations of their operation may allow cyber security breaches to lead to physical damage, but can also be an opportunity for detection. For example, physical sensing can contribute to more accurate or more rapid intrusion detection through observation and analysis of physical manifestations of a security breach. This paper presents a classification and survey of intrusion detection systems designed and evaluated specifically on vehicles and networks of vehicles. Its aim is to help identify existing techniques that can be adopted in the industry, along with their advantages and disadvantages, as well as to identify gaps in the literature, which are attractive and highly meaningful areas of future research

Context Awareness for Navigation Applications

This thesis examines the topic of context awareness for navigation applications and asks the question, “What are the benefits and constraints of introducing context awareness in navigation?” Context awareness can be defined as a computer’s ability to understand the situation or context in which it is operating. In particular, we are interested in how context awareness can be used to understand the navigation needs of people using mobile computers, such as smartphones, but context awareness can also benefit other types of navigation users, such as maritime navigators. There are countless other potential applications of context awareness, but this thesis focuses on applications related to navigation. For example, if a smartphone-based navigation system can understand when a user is walking, driving a car, or riding a train, then it can adapt its navigation algorithms to improve positioning performance. We argue that the primary set of tools available for generating context awareness is machine learning. Machine learning is, in fact, a collection of many different algorithms and techniques for developing “computer systems that automatically improve their performance through experience” [1]. This thesis examines systematically the ability of existing algorithms from machine learning to endow computing systems with context awareness. Specifically, we apply machine learning techniques to tackle three different tasks related to context awareness and having applications in the field of navigation: (1) to recognize the activity of a smartphone user in an indoor office environment, (2) to recognize the mode of motion that a smartphone user is undergoing outdoors, and (3) to determine the optimal path of a ship traveling through ice-covered waters. The diversity of these tasks was chosen intentionally to demonstrate the breadth of problems encompassed by the topic of context awareness. During the course of studying context awareness, we adopted two conceptual “frameworks,” which we find useful for the purpose of solidifying the abstract concepts of context and context awareness. The first such framework is based strongly on the writings of a rhetorician from Hellenistic Greece, Hermagoras of Temnos, who defined seven elements of “circumstance”. We adopt these seven elements to describe contextual information. The second framework, which we dub the “context pyramid” describes the processing of raw sensor data into contextual information in terms of six different levels. At the top of the pyramid is “rich context”, where the information is expressed in prose, and the goal for the computer is to mimic the way that a human would describe a situation. We are still a long way off from computers being able to match a human’s ability to understand and describe context, but this thesis improves the state-of-the-art in context awareness for navigation applications. For some particular tasks, machine learning has succeeded in outperforming humans, and in the future there are likely to be tasks in navigation where computers outperform humans. One example might be the route optimization task described above. This is an example of a task where many different types of information must be fused in non-obvious ways, and it may be that computer algorithms can find better routes through ice-covered waters than even well-trained human navigators. This thesis provides only preliminary evidence of this possibility, and future work is needed to further develop the techniques outlined here. The same can be said of the other two navigation-related tasks examined in this thesis

Tecnologia assistiva para crianças com transtorno do espectro autista que vivenciam estresse e ansiedade

With the development of current technology and influences that have been made by the Industry 4.0 utilizing ICTs, IoT, smart systems and products and many others, Assistive Technology (AT) is an important and integral part of the daily life of many people who experience disabilities. Autism Spectrum Disorder (ASD) is a special category of disorder that can greatly benefit from its use. The purpose of this research is to collect data of Assistive Technology aimed at the detection, prevention and improvement of anxiety and stress (a characteristic of which has been proven to exist and is expressed in various ways in people with ASD). In the introduction, basic definitions regarding the neurobiology of stress and ASD are analyzed. In the main part AT, stress and anxiety correlations are made with ASD and AT devices are described and documented regarding their use for anxiety and stress in children and adolescents with ASD. The Assistive equipment and devices are divided into 2 main categories, 1) Low-tech and 2) Mid-High tech. The results of the research reveal a significant research gap in the use of AT to combat stress and anxiety and the difficulty of many promising options (especially in the domain of Mid-High tech) to be an easy and economical solution in integrating them into the daily life of people with ASD.Con el desarrollo de la tecnología actual y las influencias que ha tenido la Industria 4.0 utilizando TIC, IoT, sistemas y productos inteligentes y muchos otros, la Tecnología de asistencia (TA) es una parte importante e integral de la vida diaria de muchas personas que sufren de discapacidad. . . El trastorno del espectro autista (TEA) es una categoría especial de trastorno que puede beneficiarse enormemente de su uso. El objetivo de esta investigación es recopilar datos de Tecnología Asistiva dirigidos a detectar, prevenir y mejorar la ansiedad y el estrés (una característica que está comprobada y se expresa de diferentes formas en las personas con TEA). En la introducción se analizan definiciones básicas sobre la neurobiología del estrés y el TEA. En su mayor parte se realizan correlaciones de TA, estrés y ansiedad con los TEA y se describen y documentan los dispositivos de TA en relación a su uso para la ansiedad y el estrés en niños y adolescentes con TEA. Los equipos y dispositivos de asistencia se dividen en 2 categorías principales, 1) Tecnología baja y 2) Tecnología media-alta. Los resultados de la encuesta revelan una importante brecha de investigación en el uso de TA para combatir el estrés y la ansiedad y la dificultad de que muchas opciones prometedoras (especialmente en el dominio tecnológico medio-alto) sean una solución fácil y rentable para integrarlas en la vida cotidiana. de personas con TEA.Com o desenvolvimento da tecnologia atual e as influências que foram feitas pela Indústria 4.0 utilizando TICs, IoT, sistemas e produtos inteligentes e muitos outros, a Tecnologia Assistiva (TA) é uma parte importante e integrante da vida diária de muitas pessoas que sofrem de deficiência. O Transtorno do Espectro do Autismo (TEA) é uma categoria especial de transtorno que pode se beneficiar muito com seu uso. O objetivo desta pesquisa é coletar dados de Tecnologia Assistiva voltados para a detecção, prevenção e melhora da ansiedade e do estresse (característica que comprovadamente existe e se expressa de diversas formas em pessoas com TEA). Na introdução, são analisadas definições básicas sobre a neurobiologia do estresse e do TEA. Na parte principal, são feitas correlações de TA, estresse e ansiedade com ASD e dispositivos de TA são descritos e documentados em relação ao seu uso para ansiedade e estresse em crianças e adolescentes com TEA. Os equipamentos e dispositivos assistivos são divididos em 2 categorias principais, 1) Low-tech e 2) Mid-High tech. Os resultados da pesquisa revelam uma lacuna significativa de pesquisa no uso de TA para combater o estresse e a ansiedade e a dificuldade de muitas opções promissoras (especialmente no domínio da tecnologia média-alta) serem uma solução fácil e econômica em integrá-las ao cotidiano de pessoas com TEA

Visual Impairment and Blindness

Blindness and vision impairment affect at least 2.2 billion people worldwide with most individuals having a preventable vision impairment. The majority of people with vision impairment are older than 50 years, however, vision loss can affect people of all ages. Reduced eyesight can have major and long-lasting effects on all aspects of life, including daily personal activities, interacting with the community, school and work opportunities, and the ability to access public services. This book provides an overview of the effects of blindness and visual impairment in the context of the most common causes of blindness in older adults as well as children, including retinal disorders, cataracts, glaucoma, and macular or corneal degeneration