Inferring Complex Activities for Context-aware Systems within Smart Environments

The rising ageing population worldwide and the prevalence of age-related conditions such as physical fragility, mental impairments and chronic diseases have significantly impacted the quality of life and caused a shortage of health and care services. Over-stretched healthcare providers are leading to a paradigm shift in public healthcare provisioning. Thus, Ambient Assisted Living (AAL) using Smart Homes (SH) technologies has been rigorously investigated to help address the aforementioned problems. Human Activity Recognition (HAR) is a critical component in AAL systems which enables applications such as just-in-time assistance, behaviour analysis, anomalies detection and emergency notifications. This thesis is aimed at investigating challenges faced in accurately recognising Activities of Daily Living (ADLs) performed by single or multiple inhabitants within smart environments. Specifically, this thesis explores five complementary research challenges in HAR. The first study contributes to knowledge by developing a semantic-enabled data segmentation approach with user-preferences. The second study takes the segmented set of sensor data to investigate and recognise human ADLs at multi-granular action level; coarse- and fine-grained action level. At the coarse-grained actions level, semantic relationships between the sensor, object and ADLs are deduced, whereas, at fine-grained action level, object usage at the satisfactory threshold with the evidence fused from multimodal sensor data is leveraged to verify the intended actions. Moreover, due to imprecise/vague interpretations of multimodal sensors and data fusion challenges, fuzzy set theory and fuzzy web ontology language (fuzzy-OWL) are leveraged. The third study focuses on incorporating uncertainties caused in HAR due to factors such as technological failure, object malfunction, and human errors. Hence, existing studies uncertainty theories and approaches are analysed and based on the findings, probabilistic ontology (PR-OWL) based HAR approach is proposed. The fourth study extends the first three studies to distinguish activities conducted by more than one inhabitant in a shared smart environment with the use of discriminative sensor-based techniques and time-series pattern analysis. The final study investigates in a suitable system architecture with a real-time smart environment tailored to AAL system and proposes microservices architecture with sensor-based off-the-shelf and bespoke sensing methods. The initial semantic-enabled data segmentation study was evaluated with 100% and 97.8% accuracy to segment sensor events under single and mixed activities scenarios. However, the average classification time taken to segment each sensor events have suffered from 3971ms and 62183ms for single and mixed activities scenarios, respectively. The second study to detect fine-grained-level user actions was evaluated with 30 and 153 fuzzy rules to detect two fine-grained movements with a pre-collected dataset from the real-time smart environment. The result of the second study indicate good average accuracy of 83.33% and 100% but with the high average duration of 24648ms and 105318ms, and posing further challenges for the scalability of fusion rule creations. The third study was evaluated by incorporating PR-OWL ontology with ADL ontologies and Semantic-Sensor-Network (SSN) ontology to define four types of uncertainties presented in the kitchen-based activity. The fourth study illustrated a case study to extended single-user AR to multi-user AR by combining RFID tags and fingerprint sensors discriminative sensors to identify and associate user actions with the aid of time-series analysis. The last study responds to the computations and performance requirements for the four studies by analysing and proposing microservices-based system architecture for AAL system. A future research investigation towards adopting fog/edge computing paradigms from cloud computing is discussed for higher availability, reduced network traffic/energy, cost, and creating a decentralised system. As a result of the five studies, this thesis develops a knowledge-driven framework to estimate and recognise multi-user activities at fine-grained level user actions. This framework integrates three complementary ontologies to conceptualise factual, fuzzy and uncertainties in the environment/ADLs, time-series analysis and discriminative sensing environment. Moreover, a distributed software architecture, multimodal sensor-based hardware prototypes, and other supportive utility tools such as simulator and synthetic ADL data generator for the experimentation were developed to support the evaluation of the proposed approaches. The distributed system is platform-independent and currently supported by an Android mobile application and web-browser based client interfaces for retrieving information such as live sensor events and HAR results

Automatic Generation of Personalized Recommendations in eCoaching

Denne avhandlingen omhandler eCoaching for personlig livsstilsstøtte i sanntid ved bruk av informasjons- og kommunikasjonsteknologi. Utfordringen er å designe, utvikle og teknisk evaluere en prototyp av en intelligent eCoach som automatisk genererer personlige og evidensbaserte anbefalinger til en bedre livsstil. Den utviklede løsningen er fokusert på forbedring av fysisk aktivitet. Prototypen bruker bærbare medisinske aktivitetssensorer. De innsamlede data blir semantisk representert og kunstig intelligente algoritmer genererer automatisk meningsfulle, personlige og kontekstbaserte anbefalinger for mindre stillesittende tid. Oppgaven bruker den veletablerte designvitenskapelige forskningsmetodikken for å utvikle teoretiske grunnlag og praktiske implementeringer. Samlet sett fokuserer denne forskningen på teknologisk verifisering snarere enn klinisk evaluering.publishedVersio

A Semantic Interoperability Model Based on the IEEE 1451 Family of Standards Applied to the Industry 4.0

The Internet of Things (IoT) has been growing recently. It is a concept for connecting billions of smart devices through the Internet in different scenarios. One area being developed inside the IoT in industrial automation, which covers Machine-to-Machine (M2M) and industrial communications with an automatic process, emerging the Industrial Internet of Things (IIoT) concept. Inside the IIoT is developing the concept of Industry 4.0 (I4.0). That represents the fourth industrial revolution and addresses the use of Internet technologies to improve the production efficiency of intelligent services in smart factories. I4.0 is composed of a combination of objects from the physical world and the digital world that offers dedicated functionality and flexibility inside and outside of an I4.0 network. The I4.0 is composed mainly of Cyber-Physical Systems (CPS). The CPS is the integration of the physical world and its digital world, i.e., the Digital Twin (DT). It is responsible for realising the intelligent cross-link application, which operates in a self-organised and decentralised manner, used by smart factories for value creation. An area where the CPS can be implemented in manufacturing production is developing the Cyber-Physical Production System (CPPS) concept. CPPS is the implementation of Industry 4.0 and CPS in manufacturing and production, crossing all levels of production between the autonomous and cooperative elements and sub-systems. It is responsible for connecting the virtual space with the physical world, allowing the smart factories to be more intelligent, resulting in better and smart production conditions, increasing productivity, production efficiency, and product quality. The big issue is connecting smart devices with different standards and protocols. About 40% of the benefits of the IoT cannot be achieved without interoperability. This thesis is focused on promoting the interoperability of smart devices (sensors and actuators) inside the IIoT under the I4.0 context. The IEEE 1451 is a family of standards developed to manage transducers. This standard reaches the syntactic level of interoperability inside Industry 4.0. However, Industry 4.0 requires a semantic level of communication not to exchange data ambiguously. A new semantic layer is proposed in this thesis allowing the IEEE 1451 standard to be a complete framework for communication inside the Industry 4.0 to provide an interoperable network interface with users and applications to collect and share the data from the industry field.A Internet das Coisas tem vindo a crescer recentemente. É um conceito que permite conectar bilhões de dispositivos inteligentes através da Internet em diferentes cenários. Uma área que está sendo desenvolvida dentro da Internet das Coisas é a automação industrial, que abrange a comunicação máquina com máquina no processo industrial de forma automática. Essa interligação, representa o conceito da Internet das Coisas Industrial. Dentro da Internet das Coisas Industrial está a desenvolver o conceito de Indústria 4.0 (I4.0). Isso representa a quarta revolução industrial que aborda o uso de tecnologias utilizadas na Internet para melhorar a eficiência da produção de serviços em fábricas inteligentes. A Indústria 4.0 é composta por uma combinação de objetos do mundo físico e do mundo da digital que oferece funcionalidade dedicada e flexibilidade dentro e fora de uma rede da Indústria 4.0. O I4.0 é composto principalmente por Sistemas Ciberfísicos. Os Sistemas Ciberfísicos permitem a integração do mundo físico com seu representante no mundo digital, por meio do Gémeo Digital. Sistemas Ciberfísicos são responsáveis por realizar a aplicação inteligente da ligação cruzada, que opera de forma auto-organizada e descentralizada, utilizada por fábricas inteligentes para criação de valor. Uma área em que o Sistema Ciberfísicos pode ser implementado na produção manufatureira, isso representa o desenvolvimento do conceito Sistemas de Produção Ciberfísicos. Esse sistema é a implementação da Indústria 4.0 e Sistema Ciberfísicos na fabricação e produção. A cruzar todos os níveis desde a produção entre os elementos e subsistemas autónomos e cooperativos. Ele é responsável por conectar o espaço virtual com o mundo físico, permitindo que as fábricas inteligentes sejam mais inteligentes, resultando em condições de produção melhores e inteligentes, aumentando a produtividade, a eficiência da produção e a qualidade do produto. A grande questão é como conectar dispositivos inteligentes com diferentes normas e protocolos. Cerca de 40% dos benefícios da Internet das Coisas não podem ser alcançados sem interoperabilidade. Esta tese está focada em promover a interoperabilidade de dispositivos inteligentes (sensores e atuadores) dentro da Internet das Coisas Industrial no contexto da Indústria 4.0. O IEEE 1451 é uma família de normas desenvolvidos para gerenciar transdutores. Esta norma alcança o nível sintático de interoperabilidade dentro de uma indústria 4.0. No entanto, a Indústria 4.0 requer um nível semântico de comunicação para não haver a trocar dados de forma ambígua. Uma nova camada semântica é proposta nesta tese permitindo que a família de normas IEEE 1451 seja um framework completo para comunicação dentro da Indústria 4.0. Permitindo fornecer uma interface de rede interoperável com utilizadores e aplicações para recolher e compartilhar os dados dentro de um ambiente industrial.This thesis was developed at the Measurement and Instrumentation Laboratory (IML) in the University of Beira Interior and supported by the portuguese project INDTECH 4.0 – Novas tecnologias para fabricação, que tem como objetivo geral a conceção e desenvolvimento de tecnologias inovadoras no contexto da Indústria 4.0/Factories of the Future (FoF), under the number POCI-01-0247-FEDER-026653

Legal Ontology for Nexus: Water, Energy and Food in EU Regulations

Objectives of the thesis are – (a) to identify the problems in water-energy-food nexus from ICT and Law point of view and to propose theoretically a legal knowledge framework for water-energy-food nexus in order to reduce those problems technologically, (b) to construct and implement legal ontology for nexus extracted from EU water, energy and food Regulations in OWL 2 language, which is a part of the grater work of implementing legal knowledge framework for water-energy-food nexus pro-posed through the compilation of objective (a). Considering these objectives, this thesis presents total five chapters. Chapter 1 is dedicated to fulfill the requirement of objective (a) and the rest chapters are devoted for objective (b). More particularly chapter four presents technical descriptions of the legal ontology for nexus, while chapter two and three articulate methodological aspect of it. Chapter five evaluates legal ontology for nexus. Additionally, besides the list of references, annex 1 delivers all asserted restrictions used in this ontology and annex 2 provides the links of all modules and documentations of legal ontology for nexus.Erasmus Mundus Joint Doctorate programme in “Law, Science and Technology

Consistency of UML based designs using ontology reasoners

Software plays an important role in our society and economy. Software development is an intricate process, and it comprises many different tasks: gathering requirements, designing new solutions that fulfill these requirements, as well as implementing these designs using a programming language into a working system. As a consequence, the development of high quality software is a core problem in software engineering. This thesis focuses on the validation of software designs. The issue of the analysis of designs is of great importance, since errors originating from designs may appear in the final system. It is considered economical to rectify the problems as early in the software development process as possible. Practitioners often create and visualize designs using modeling languages, one of the more popular being the Uni ed Modeling Language (UML). The analysis of the designs can be done manually, but in case of large systems, the need of mechanisms that automatically analyze these designs arises. In this thesis, we propose an automatic approach to analyze UML based designs using logic reasoners. This approach firstly proposes the translations of the UML based designs into a language understandable by reasoners in the form of logic facts, and secondly shows how to use the logic reasoners to infer the logical consequences of these logic facts. We have implemented the proposed translations in the form of a tool that can be used with any standard compliant UML modeling tool. Moreover, we authenticate the proposed approach by automatically validating hundreds of UML based designs that consist of thousands of model elements available in an online model repository. The proposed approach is limited in scope, but is fully automatic and does not require any expertise of logic languages from the user. We exemplify the proposed approach with two applications, which include the validation of domain specific languages and the validation of web service interfaces

Quantitative Legal Prediction--or--How I Learned to Stop Worrying and Start Preparing for the Data-Driven Future of the Legal Services Industry

Welcome to law\u27s information revolution-revolution already in progress

Modelling Human Routines: Conceptualising Social Practice Theory for Agent-Based Simulation

Our routines play an important role in a wide range of social challenges such as climate change, disease outbreaks and coordinating staff and patients in a hospital. To use agent-based simulations (ABS) to understand the role of routines in social challenges we need an agent framework that integrates routines. This paper provides the domain-independent Social Practice Agent (SoPrA) framework that satisfies requirements from the literature to simulate our routines. By choosing the appropriate concepts from the literature on agent theory, social psychology and social practice theory we ensure SoPrA correctly depicts current evidence on routines. By creating a consistent, modular and parsimonious framework suitable for multiple domains we enhance the usability of SoPrA. SoPrA provides ABS researchers with a conceptual, formal and computational framework to simulate routines and gain new insights into social systems

Handling Live Sensor Data on the Semantic Web

The increased linking of objects in the Internet of Things and the ubiquitous flood of data and information require new technologies in data processing and data storage in particular in the Internet and the Semantic Web. Because of human limitations in data collection and analysis, more and more automatic methods are used. Above all, these sensors or similar data producers are very accurate, fast and versatile and can also provide continuous monitoring even places that are hard to reach by people. The traditional information processing, however, has focused on the processing of documents or document-related information, but they have different requirements compared to sensor data. The main focus is static information of a certain scope in contrast to large quantities of live data that is only meaningful when combined with other data and background information. The paper evaluates the current status quo in the processing of sensor and sensor-related data with the help of the promising approaches of the Semantic Web and Linked Data movement. This includes the use of the existing sensor standards such as the Sensor Web Enablement (SWE) as well as the utilization of various ontologies. Based on a proposed abstract approach for the development of a semantic application, covering the process from data collection to presentation, important points, such as modeling, deploying and evaluating semantic sensor data, are discussed. Besides the related work on current and future developments on known diffculties of RDF/OWL, such as the handling of time, space and physical units, a sample application demonstrates the key points. In addition, techniques for the spread of information, such as polling, notifying or streaming are handled to provide examples of data stream management systems (DSMS) for processing real-time data. Finally, the overview points out remaining weaknesses and therefore enables the improvement of existing solutions in order to easily develop semantic sensor applications in the future