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Semantic Reasoning for Ubiquitous Smart Living Framework for Well-being and Digital Health

Abstract : Connected objects of everyday living have made their way into our lives. Known as Internet of Things, the various technologies inspire a vast variety of applications. One of the pioneer applications is the concept and development of a smart home. This is now spreading outdoors; making vehicles, buildings, and even large cities smart. Moreover, the technology is getting more personal as well – as wearing smart clothes and other self-tracking devices become increasingly common and popular. This is often referred to as the quantified self.One particular case of a smart environment is ambient assisted living, which is designed to enhance elderly people’s day-to-day life. Such a ubiquitous and unobtrusive computer system can also be ported to other domains and age groups. For instance, the tracking of daily activities can also help younger adults to improve their lifestyle. Everyone can be encouraged to maintain a healthy lifestyle, perform sufficient physical activity, and make more informed decisions about their mobility. These are direct factors in preventing health risks, such as metabolic diseases like the type 2 diabetes, and allow a better control over respiratory diseases like the asthma.Driven by these ideas, this thesis explores the possibilities of a web-based platform with a semantic rule-based reasoning. The thesis details the work on technical improvements, enhancements in activity recognition, extensions for data analysis, and a mobility-oriented application.Following a user-centric approach, a real life deployment of the described technologies is necessary. Two use cases are examined. First, I enhanced and built upon a pre-existing system, which consists of sensors and a gateway placed into elderly participants' homes. The second use case is the deployment of a mobile phone application for active mobility assistance. Collecting relevant and timely data, the application then outputs a level of recommendation for every type of mobility. The recommendations are based on each user’s exercise tracking device, which incorporates their goals, their profiles, and other publicly available data sources such as weather and air quality.This thesis describes the outcomes and lessons learnt from these deployments. In addition, this thesis provides an in-depth discussion as well as analytical insights on the results of the deployments.
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Submitted on : Monday, November 30, 2020 - 6:09:09 PM
Last modification on : Friday, December 18, 2020 - 3:04:36 AM


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  • HAL Id : tel-03032152, version 1


Martin Kodys. Semantic Reasoning for Ubiquitous Smart Living Framework for Well-being and Digital Health. Artificial Intelligence [cs.AI]. Université Grenoble Alpes [2020-..], 2020. English. ⟨NNT : 2020GRALM033⟩. ⟨tel-03032152⟩



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