An Approach to Dynamic Knowledge Extension and Semantic Reasoning in Highly-Mutable Environments

J Ambient Intell Human Comput

et al. 2018

Self Cite

As citizens' age increases, smart cities must adapt to help them to age properly. The objective of the City4Age project is to create the future ambient assisted cities that will help the citizens to deal with mild cognitive impairments (MCI) and frailty. In this paper we present two of the tools developed during the project. The first one is a city-wide context-manager, which allows to store the citizens information using a semantic representation and share it following the linked open data paradigm. The second one are the individual care monitoring dashboards, which use the stored information to help the caregivers to analyze and interpret the citizens' behaviour, allowing to detect risks related to MCI and frailty.

Section: Introductionmentioning

confidence: 99%

Towards ambient assisted cities using linked data and data analysis

Mulero

Urošević

J Ambient Intell Human Comput

et al. 2018

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“…In 2008 Almeida et al presented an enriched ontology-based context model which takes into account the available semantic knowledge (served as rules) provided by dynamically discovered devices (Almeida et al, 2009). The presented semantic infrastructure has the ability of dynamically discover new and previously unknown objects in the environment and reason over the new situation.…”

Section: Ontology Based Modelsmentioning

confidence: 99%

“…There are several situations where the adaptation process is not obvious (Almeida et al, 2009) (Almeida et al, 2012 (Calvary et al, 2002) (Gu et al, 2004) (Nilsson et al, 2006). For example:…”

Section: Incoherent Adaptationsmentioning

confidence: 99%

Modelling users, context and devices for adaptive user interface systems

Castillejo

Int J of Pervasive Comp & Comm

López-de-Ipiña

2014

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Purpose – The purpose of this paper is to review the state-of-the-art in adaptive user interface systems by studying their historical development over the past 20 years. Moreover, this paper contributes with a specific model combining three main entities (users, context and devices) that have been demonstrated to be always represented in these environments. Novel concepts that should be taken into account in these systems are also presented. Design/methodology/approach – The authors first provide a review and a comparison of current user interface adaptive systems. Next, the authors detail the most significant models and the set of techniques used to, finally, propose a novel model based on the studied literature. Findings – Literature solutions for adaptive user interface systems tend to be very domain dependant. This situation restricts the possibility of sharing and exporting the information between such systems. Furthermore, the studied approaches barely highlight the dynamism of these models. Originality/value – The paper is a review of adaptive user interface systems and models. Although there are several reviews in this area, there is a lack of research for modelling users, context and devices simultaneously in this domain. The paper also presents several significant concepts that should be taken into account to bring an adaptive and dynamic perspective to the studied models.

“…In the Smartlab project [ 22 ] none of this information was used, which led to a loss of important data like the certainty of the measures taken by the sensors. In the Imhotep framework ( http://www.morelab.deusto.es/imhotep/ ) [ 23 ] we started using fuzzy terms to describe a small part of the context (the capabilities of mobile devices and users) in a human-friendly manner. Our objective with the work presented in this paper was to develop a framework capable of managing the ambiguity and incertitude that often characterizes the reality.…”

Section: Ambi 2 Ont: An Ontology For the Ambiguousmentioning

confidence: 99%

Assessing Ambiguity of Context Data in Intelligent Environments: Towards a More Reliable Context Managing System

López-de-Ipiña

2012

Sensors

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Modeling and managing correctly the user context in Smart Environments is important to achieve robust and reliable systems. When modeling reality we must take into account its ambiguous nature. Considering the uncertainty and vagueness in context data information it is possible to attain a more precise picture of the environment, thus leading to a more accurate inference process. To achieve these goals we present an ontology that models the ambiguity in intelligent environments and a data fusion and inference process that takes advantage of that extra information to provide better results. Our system can assess the certainty of the captured measurements, discarding the unreliable ones and combining the rest into a unified vision of the current user context. It also models the vagueness of the system, combining it with the uncertainty to obtain a richer inference process.