Smart Emergency Alert System Using Internet of Things and Linked Open Data for Chronic Disease Patients

International audienceNowadays, the widespread deployment of more powerful devices (sensors, smartphones, tablets, etc.) has provided us with great number sources of sensing data that are exploited in several domains namely the healthcare domain. Chronic diseases are the most common causes of death and disability worldwide. These types of diseases require more and more studies to help patients and notify cases of crises that lead to death. Representing knowledge through building an ontology for emergency alert system is important to achieve semantic interoperability among health information, predict the patient real-time context and to better execute decision notification. Linked Open Data services are used in our paper in order to provide with the semantic description of collected data from different sources (wearable sensors, environmental sensors, etc.)

Low-cost mobile personal clouds

We propose a mobile peer to peer personal cloud architecture which allows users to capture, store, analyse, interact with and share different types of personal and context data with no privacy leakage. Our mobile personal cloud can host multiple different services which are intelligent, distributed, dynamic and operate in real time. In this paper we describe one service that we designed and deployed on our mobile personal cloud called Mobile Wellbeing Companion Cloud (MWCC). Using low-cost, off-the-shelf hardware components and open-source software, our MWCC combines several sensor network technologies to allow users to monitor and interact with their personal data and environment in real time without privacy leakage. MWCC augments heterogeneous sensors data with state of the art machine learning algorithms for signal filtering, fast classification and analysis and provides interactive data visualisation for transparent user interaction. We show that our MWCC is easy to use and highly accurate while managing to keep resource costs low

Data semantic enrichment for complex event processing over IoT Data Streams

This thesis generalizes techniques for processing IoT data streams, semantically enrich data with contextual information, as well as complex event processing in IoT applications. A case study for ECG anomaly detection and signal classification was conducted to validate the knowledge foundation

First steps of asthma management with a personalized ontology model

Asthma is a chronic respiratory disease characterized by severe inflammation of the bronchial mucosa. Allergic asthma is the most common form of this health issue. Asthma is classified into allergic and non-allergic asthma, and it can be triggered by several factors such as indoor and outdoor allergens, air pollution, weather conditions, tobacco smoke, and food allergens, as well as other factors. Asthma symptoms differ in their frequency and severity since each patient reacts differently to these triggers. Formal knowledge is selected as one of the most promising solutions to deal with these challenges. This paper presents a new personalized approach to manage asthma. An ontology-driven model supported by Semantic Web Rule Language (SWRL) medical rules is proposed to provide personalized care for an asthma patient by identifying the risk factors and the development of possible exacerbations

Modèle ontologique contextuel pour les patients atteints de la maladie pulmonaire obstructive chronique

L'informatique ubiquitaire est considérée comme l'une des réalisations scientifiques les plus marquantes de la dernière décennie. Cette vision a créé une révolution dans les interactions des utilisateurs finaux à partir le concept de sensibilité au contexte. L'informatique ubiquitaire offre une nouvelle opportunité pour remodeler la forme des solutions conventionnelles en fournissant des services personnalisés en fonction des situations contextuelles de chaque environnement. Des centaines d'architectures théoriques ont été développées dans le but de mettre en oeuvre l'idée de systèmes sensible au contexte. Cependant, l'informatique ubiquitaire est encore pratiquement non applicable en raison de nombreux défis, surtout que les architectures proposées se présentent toujours comme une solution générale qui permet de satisfaire n'importe quel type d'application et toutes sortes d'utilisation. OBJECTIFS: Cette thèse vise à concevoir et valider un modèle contextuel pour les systèmes de soins de santé ubiquitaires et spécifiquement destinés à aider les patients souffrant de la maladie pulmonaire obstructive chronique (MPOC). LA MÉTHODE: Les informations contextuelles sont très importantes pour les applications de soins de santé sensibles au contexte, en particulier celles utilisées pour surveiller les patients atteints de maladies chroniques qui sont affectées par des conditions concevables. Dans cette thèse, nous proposons une nouvelle classification de contexte pour le domaine médical qui couvre tous les aspects influençant la santé des patients. La grande échelle de cette classification le rend apte pour être une référence générale pour de divers projets de recherche s'intéressant au contexte médical. Ensuite, nous proposons un modèle contextuel à base d’ontologies capable de gérer la structure complexe du domaine de la MPOC de manière cohérente, en proportion de la nature dynamique de cet environnement. Ce nouveau modèle ontologique constitue le noyau de notre perception pour la mise en oeuvre de la solution de soins de santé ubiquitaire. Le modèle présenté examine son efficacité dans la gestion de l’une des maladies les plus vulnérables au contexte, où il prouve ainsi sa capacité à adapter les services de soins de santé à titre personnel et en fonction des conditions actuelles et prévues. Le modèle proposé a montré des résultats prometteurs dépassant 85% approuvé par un groupe de spécialistes expérimentés dans le domaine des maladies pulmonaires. Ubiquitous computing is considered one of the most impactful scientific achievements in the last decade. This conception created tremendous revolution in the end-user interactions through the concept of context-awareness. Ubiquitous computing offers a new opportunity to redesign the pattern of conventional solutions where it can easily tailor its processes upon existing contextual situations. Hundreds of theoretical architectures have been developed to enable context-awareness computing in pervasive settings. However, ubiquitous computing is still practically not feasible due to many challenges, but most importantly, that the proposed models always present themselves as a general solution to all kinds of real-life applications. OBJECTIVES: This thesis aims to design and validate a contextual model for health-care context-aware systems to support patients suffer from Chronic Obstructive Pulmonary Disease (COPD). METHODS: The contextual information is important for developing Context-Aware Healthcare Applications, especially those used to monitor patients with chronic diseases which are affected by perceived conditions. In this thesis, we propose a novel context categorization within the medical domain which covers all the context aspects. Then, we propose an ontology-based model able to handle the complex contextual structure of the COPD domain coherently, and in proportion to the dynamic nature of that environment. This new ontological context is the core of our perception for implementing the ubiquitous healthcare solution. The presented model examines its effectiveness in managing one of the most context-sensitive diseases, thereby demonstrating its ability to adapt health care services on a personal basis and in accordance with current and projected events. The proposed model has shown promising results exceeding 85% approved by a group of experienced specialists in respiratory and lung diseases