Desing and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.

Services and Policies for Care at Home

It is argued that various factors including the increasingly ageing population will require more care services to be delivered to users in their own homes. Desirable characteristics of such services are outlined. The Open Services Gateway initiative has been adopted as a widely accepted framework that is particularly suitable for developing home care services. Service discovery in this context is enhanced through ontologies that achieve greater flexibility and precision in service description. A service ontology stack allows common concepts to be extended for new services. The architecture of a policy system for home care is explained. This is used for flexible creation and control of new services. The core policy language and its extension for home care are introduced, and illustrated through typical examples. Future extensions of the approach are discussed

A novel context ontology to facilitate interoperation of semantic services in environments with wearable devices

The LifeWear-Mobilized Lifestyle with Wearables (Lifewear) project attempts to create Ambient Intelligence (AmI) ecosystems by composing personalized services based on the user information, environmental conditions and reasoning outputs. Two of the most important benefits over traditional environments are 1) take advantage of wearable devices to get user information in a nonintrusive way and 2) integrate this information with other intelligent services and environmental sensors. This paper proposes a new ontology composed by the integration of users and services information, for semantically representing this information. Using an Enterprise Service Bus, this ontology is integrated in a semantic middleware to provide context-aware personalized and semantically annotated services, with discovery, composition and orchestration tasks. We show how these services support a real scenario proposed in the Lifewear project

Personalized Recommendations for Physical Activity e-Coaching (OntoRecoModel): Ontological Modeling

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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

Survey on virtual coaching for older adults

Virtual coaching has emerged as a promising solution to extend independent living for older adults. A virtual coach system is an always-attentive personalized system that continuously monitors user's activity and surroundings and delivers interventions - that is, intentional messages - in the appropriate moment. This article presents a survey of different approaches in virtual coaching for older adults, from the less technically supported tools to the latest developments and future avenues for research. It focuses on the technical aspects, especially on software architectures, user interaction and coaching personalization. Nevertheless, some aspects from the fields of personality/social psychology are also presented in the context of coaching strategies. Coaching is considered holistically, including matters such as physical and cognitive training, nutrition, social interaction and mood.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 769830