A knowledge-based approach towards human activity recognition in smart environments

For many years it is known that the population of older persons is on the rise. A recent report estimates that globally, the share of the population aged 65 years or over is expected to increase from 9.3 percent in 2020 to around 16.0 percent in 2050 [1]. This point has been one of the main sources of motivation for active research in the domain of human activity recognition in smart-homes. The ability to perform ADL without assistance from other people can be considered as a reference for the estimation of the independent living level of the older person. Conventionally, this has been assessed by health-care domain experts via a qualitative evaluation of the ADL. Since this evaluation is qualitative, it can vary based on the person being monitored and the caregiver\u2019s experience. A significant amount of research work is implicitly or explicitly aimed at augmenting the health-care domain expert\u2019s qualitative evaluation with quantitative data or knowledge obtained from HAR. From a medical perspective, there is a lack of evidence about the technology readiness level of smart home architectures supporting older persons by recognizing ADL [2]. We hypothesize that this may be due to a lack of effective collaboration between smart-home researchers/developers and health-care domain experts, especially when considering HAR. We foresee an increase in HAR systems being developed in close collaboration with caregivers and geriatricians to support their qualitative evaluation of ADL with explainable quantitative outcomes of the HAR systems. This has been a motivation for the work in this thesis. The recognition of human activities \u2013 in particular ADL \u2013 may not only be limited to support the health and well-being of older people. It can be relevant to home users in general. For instance, HAR could support digital assistants or companion robots to provide contextually relevant and proactive support to the home users, whether young adults or old. This has also been a motivation for the work in this thesis. Given our motivations, namely, (i) facilitation of iterative development and ease in collaboration between HAR system researchers/developers and health-care domain experts in ADL, and (ii) robust HAR that can support digital assistants or companion robots. There is a need for the development of a HAR framework that at its core is modular and flexible to facilitate an iterative development process [3], which is an integral part of collaborative work that involves develop-test-improve phases. At the same time, the framework should be intelligible for the sake of enriched collaboration with health-care domain experts. Furthermore, it should be scalable, online, and accurate for having robust HAR, which can enable many smart-home applications. The goal of this thesis is to design and evaluate such a framework. This thesis contributes to the domain of HAR in smart-homes. Particularly the contribution can be divided into three parts. The first contribution is Arianna+, a framework to develop networks of ontologies - for knowledge representation and reasoning - that enables smart homes to perform human activity recognition online. The second contribution is OWLOOP, an API that supports the development of HAR system architectures based on Arianna+. It enables the usage of Ontology Web Language (OWL) by the means of Object-Oriented Programming (OOP). The third contribution is the evaluation and exploitation of Arianna+ using OWLOOP API. The exploitation of Arianna+ using OWLOOP API has resulted in four HAR system implementations. The evaluations and results of these HAR systems emphasize the novelty of Arianna+

User preferences in intelligent environments

Intelligent Environments and other Computer Science sub-fields based on the concepts of context and context-awareness are created with the explicit or implicit intention of providing services which are satisfying to the intended users of those environments. This article discusses the pragmatic importance of Preferences within the process of developing Intelligent Environments as a conceptual tool to achieve that system-user alignment and we also look at the practical challenges of implementing different aspects of the concept of Preferences. This study is not aimed at providing a definitive solution, rather to assess the advantages and disadvantages of different available options with the view to inform the next wave of developments in the area

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

Representação da informação incerta por meio de ontologias: um framework para smart homes

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Ciências da Educação, Programa de Pós-Graduação em Ciência da Informação, Florianópolis, 2019.Nas smart homes e outros cenários da Internet das Coisas (IoT), muitas vezes, as informações coletadas estão sujeitas a interferências externas. Além disso, pode ser necessário representar situações nas quais não é possível se obter informações completas ou precisas sobre determinado fenômeno, gerando a necessidade de se lidar com a informação incerta. As ontologias apresentam um formato amplamente utilizado para a representação das informações coletadas nas smart homes. Sendo assim, atualmente existem várias abordagens não padronizadas na literatura baseadas em ontologias para a representação da informação incerta, ou ontologias incertas . Diante desse contexto, o objetivo deste trabalho é propor um framework para ser utilizado como ferramenta de referência no processo de seleção de ontologias incertas para cenários de smart homes. Para isso, foram identificadas ontologias incertas para smart homes por meio de uma Revisão Sistemática da Literatura (RSL) e foram realizadas pesquisas nos anais do International Workshop on Uncertainty Reasoning for the Semantic Web (URSW). O framework proposto é composto por dois artefatos gerados a partir de informações extraídas das ontologias incertas identificadas: a) questionário para auxiliar na identificação das necessidades de representação da informação incerta; e b) quadro de referência para ser consultado durante a seleção de uma ontologia incerta de acordo com as necessidades de representação da informação incerta. Ao todo, foram identificados 16 trabalhos que propõem ontologias incertas. Com base nestes trabalhos, elaborou-se o questionário com seis questões e diferentes opções de respostas que remetem as ontologias incertas. O quadro de referência foi elaborado contendo os 16 trabalhos identificados e as características das ontologias incertas propostas por cada trabalho. O framework foi aplicado em nove cenários de smart homes que utilizam ontologias, mas não representam a informação incerta, de modo a exemplificar o papel do framework como ferramenta de referência. Como resultado de sua aplicação, para cada cenário, exceto um, identificou-se uma ou mais opções de ontologias incertas. Isto indica que as ontologias incertas disponíveis cobrem grande parte das necessidades de representação atualmente, mas não completamente. Espera-se que o framework proposto possa ser utilizado como referência para facilitar o acesso e uso das ontologias incertas pelos profissionais interessados na construção de ontologias. Finalmente, espera-se gerar oportunidades para que sejam desenvolvidas aplicações que elevem a qualidade e capacidade dos cenários de smart homes tendo em vista principalmente as necessidades e bem-estar das pessoas.Abstract : In smart homes and other Internet of Things (IoT) scenarios, often information collected is subject to external interference. Moreover, it may be necessary to represent situations in which it is not possible to obtain complete or accurate information about a specific phenomenon, causing the need to deal with uncertain information. Ontologies provides a widespread format for representing information collected in smart homes. This way, nowadays there are many non-standard ontology-based approaches in literature focused in the task of uncertain information representation, or \"uncertain ontologies\". Given this context, the objective of this work is to propose a framework to be used as a reference tool in the process of selecting uncertain ontologies for smart home scenarios. For this purpose, uncertain ontologies for smart homes and other IoT scenarios are identified by means of a Systematic Review of Literature (RSL) and by research in proceedings from International Workshop on Uncertainty Reasoning for the Semantic Web (URSW). The proposed framework is composed by two artifacts generated from information extracted from identified uncertain ontologies: a) a survey to assist in identifying the needs for representing uncertain information; and b) a reference table which can be used for selection of uncertain ontologies according to the representation needs. Altogether, 16 uncertain ontologies proposals have been identified. Based on these proposals, the questionnaire was elaborated with six questions and different options of answers referring to uncertain ontologies. The reference table was built containing the 16 ontologies proposals and its specific features. The framework was applied in nine scenarios of smart homes which use ontologies, but do not represent the uncertain information, in order to exemplify the role of the framework as a reference tool. As a result of its application one or more uncertain ontologies options were identified for most of the work. This indicates that the available uncertain ontologies cover most of the representation needs currently, but not all. It is expected that the proposed framework will be used as a reference to ease the access and use of uncertain ontologies by professionals interested in the creation of ontologies. Finally, it is expected to generate opportunities to develop applications which raise the quality and capacity of smart home scenarios especially in view of the needs and well-being of people

A Novel Ontology Consistent with Acknowledged Standards in Smart Homes

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.With the development of Internet of Things, the Smart Home equipped with various sensors and devices has become a hot area attracting global attention and concern. In order to get a better understanding of ambient environments, adding semantics to sensor data plays a significant role. Researchers are attempting to build semantic models in order to satisfy their own requirements, which leads to little reusability between different models. This paper aims to provide a novel ontology which follows publicly acknowledged standards for achieving sensor data semantization in smart homes, including modeling sensors, context and activities with semantics. For keeping consistent with current accepted standards, the proposed ontology is based on the Semantic Sensor Network Ontology. In addition, we enrich the ontologies by incorporating spatiotemporal information and user profiles. The ontology is designed using Protégé and a use case is demonstrated to show the great potentiality in daily activity recognition in smart homes

Modélisation d'une interaction système-résident contextuelle, personnalisée et adaptative pour l'assistance cognitive à la réalisation des activités de la vie quotidienne dans les maisons connectées

Alors que le nombre de personnes vivant avec des déficits cognitifs qui découlent d’un traumatisme craniocérébral (TCC) va en croissant, les technologies d’assistance sont de plus en plus développées pour résoudre les problèmes qu’ils induisent dans la réalisation des activités de la vie quotidienne. L’Internet des objets et l’intelligence ambiante offrent un cadre pour fournir des services d’assistance sensibles au contexte, adaptatifs, autonomes et personnalisés pour ces personnes ayant des besoins particuliers. Une revue de la littérature sur le sujet permet de constater que les systèmes existants offrent très souvent une assistance excessive, quand l’aide contient plus d’information que nécessaire ou quand elle est fournie automatiquement à chaque étape de l’activité. Cette assistance, inadaptée aux besoins et aux capacités de la personne, est contraire à certains principes de la réadaptation cognitive qui prônent la fourniture d’une assistance minimale pour encourager la personne à agir au meilleur de ses capacités. Cette thèse propose des modèles pour automatiser l’assistance cognitive sous forme de dialogue contextuel entre une personne ayant des déficits cognitifs dus au TCC et un système lui fournissant l’assistance appropriée qui l’encourage à réaliser ses activités par lui-même. Les principales contributions sont : (1) un modèle ontologique comme support de l’assistance cognitive dans les maisons connectées ; (2) un modèle d’interaction entre l’agent intelligent d’une maison connectée et une personne ayant subi un TCC, dans le cadre de l’assistance cognitive. Le modèle ontologique proposé s’appuie sur les actes de langages et les données probantes de la réadaptation cognitive afin que l’assistance reflète la pratique clinique. Il vise à fournir aux maisons intelligentes la sémantique des données nécessaires pour caractériser les situations où il y a besoin d’assistance, les messages d’assistance de gradations différentes et les réactions de la personne. Informé par le modèle ontologique, le modèle d’interaction basé sur des arbres de comportement (« behaviour trees ») permet alors à un agent intelligent de planifier dynamiquement la diffusion de messages d’assistance progressifs avec des ajustements si nécessaire, en fonction du profil et du comportement du résident de la maison connectée lors de l’accomplissement de ses activités. Une validation préliminaire montre l’applicabilité des modèles dans l’implémentation de scénarios relatifs à l’utilisation sécuritaire d’une cuisinière connectée dédiée aux personnes ayant subi un TCC

Innovative Technologies and Services for Smart Cities

A smart city is a modern technology-driven urban area which uses sensing devices, information, and communication technology connected to the internet of things (IoTs) for the optimum and efficient utilization of infrastructures and services with the goal of improving the living conditions of citizens. Increasing populations, lower budgets, limited resources, and compatibility of the upgraded technologies are some of the few problems affecting the implementation of smart cities. Hence, there is continuous advancement regarding technologies for the implementation of smart cities. The aim of this Special Issue is to report on the design and development of integrated/smart sensors, a universal interfacing platform, along with the IoT framework, extending it to next-generation communication networks for monitoring parameters of interest with the goal of achieving smart cities. The proposed universal interfacing platform with the IoT framework will solve many challenging issues and significantly boost the growth of IoT-related applications, not just in the environmental monitoring domain but in the other key areas, such as smart home, assistive technology for the elderly care, smart city with smart waste management, smart E-metering, smart water supply, intelligent traffic control, smart grid, remote healthcare applications, etc., signifying benefits for all countries

Semantic Selection of Internet Sources through SWRL Enabled OWL Ontologies

This research examines the problem of Information Overload (IO) and give an overview of various attempts to resolve it. Furthermore, argue that instead of fighting IO, it is advisable to start learning how to live with it. It is unlikely that in modern information age, where users are producer and consumer of information, the amount of data and information generated would decrease. Furthermore, when managing IO, users are confined to the algorithms and policies of commercial Search Engines and Recommender Systems (RSs), which create results that also add to IO. this research calls to initiate a change in thinking: this by giving greater power to users when addressing the relevance and accuracy of internet searches, which helps in IO. However powerful search engines are, they do not process enough semantics in the moment when search queries are formulated. This research proposes a semantic selection of internet sources, through SWRL enabled OWL ontologies. the research focuses on SWT and its Stack because they (a)secure the semantic interpretation of the environments where internet searches take place and (b) guarantee reasoning that results in the selection of suitable internet sources in a particular moment of internet searches. Therefore, it is important to model the behaviour of users through OWL concepts and reason upon them in order to address IO when searching the internet. Thus, user behaviour is itemized through user preferences, perceptions and expectations from internet searches. The proposed approach in this research is a Software Engineering (SE) solution which provides computations based on the semantics of the environment stored in the ontological model