Emergency network prototype

Telecommunications is first and foremost an exchange of information in any given space. Traditional communication networks are always vulnerable to destruction during natural disasters which often lead to the death and injury of thousands of people where rescue teams are unable to locate the victims on right time. This work presents a proposal about the possibility of building a wireless mobile network to exchange emergency messages when the damage affects the most existing telecommunication networks. The practical part of this study includes develop an android application using Wi-Fi peer-to-peer (P2P)

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

Extended WIFI network design model for ubiquitous emergency events

Telecommunication is the exchange of information and data over significant distance by electronic means. During extreme events such as natural disasters and urgent events it becomes more and more important to preserve the communication devices and infrastructure to exchange information between rescue teams and persons in damaged zone based on their area. When extreme event happens, many communication scenarios can be considered. We focus on a the case of destruction of traditional communication networks during an emergency event such as natural disasters in which it is important to find an alternative network architecture to prevent the death and injury of thousands of people. The rescue teams are unable to locate and communicate with victims on right time. This work presents network architectural design model to extend the range of WIFI networks and help people access to Internet or get rescue when the damage affects the most existing telecommunication networks. This model is validated by analyzing two communication scenarios

Survey of health care context models : prototyping of healthcare context framework

HealthCare system is considered a key element in ubiquitous computing, which means health care services are recommended at any time and at any places to monitor patients based on their context. This study aims to define a simple framework that could be guidelines when you start thinking about building a health context-awareness system in ubiquitous environment. This paper starts by defining the concept of context and then presenting a comprehensive list of context models. Outcome of the work of this research is an ontology healthcare model based on current context of patient which makes monitoring process more accurate. This study includes an Android application in order to prove the concept of this hypothesis

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

Context Relevant Prediction Model for COPD Domain Using Bayesian Belief Network

In the last three decades, researchers have examined extensively how context-aware systems can assist people, specifically those suffering from incurable diseases, to help them cope with their medical illness. Over the years, a huge number of studies on Chronic Obstructive Pulmonary Disease (COPD) have been published. However, how to derive relevant attributes and early detection of COPD exacerbations remains a challenge. In this research work, we will use an efficient algorithm to select relevant attributes where there is no proper approach in this domain. Such algorithm predicts exacerbations with high accuracy by adding discretization process, and organizes the pertinent attributes in priority order based on their impact to facilitate the emergency medical treatment. In this paper, we propose an extension of our existing Helper Context-Aware Engine System (HCES) for COPD. This project uses Bayesian network algorithm to depict the dependency between the COPD symptoms (attributes) in order to overcome the insufficiency and the independency hypothesis of naïve Bayesian. In addition, the dependency in Bayesian network is realized using TAN algorithm rather than consulting pneumologists. All these combined algorithms (discretization, selection, dependency, and the ordering of the relevant attributes) constitute an effective prediction model, comparing to effective ones. Moreover, an investigation and comparison of different scenarios of these algorithms are also done to verify which sequence of steps of prediction model gives more accurate results. Finally, we designed and validated a computer-aided support application to integrate different steps of this model. The findings of our system HCES has shown promising results using Area Under Receiver Operating Characteristic (AUC = 81.5%)

Ontology-based model to support ubiquitous healthcare systems for COPD patients

Over the past 30 years, information technology has gradually transformed the way health care is provisioned for patients. Chronic Obstructive Pulmonary Disease (COPD) is an incurable malady that threatens the lives of millions around the world. The huge amount of medical information in terms of complex interdependence between progression of health problems and various other factors makes the representation of data more challenging. This study investigated how formal semantic standards could be used for building an ontology knowledge repository to provide ubiquitous healthcare and medical recommendations for COPD patient to reduce preventable harm. The novel contribution of the suggested framework resides in the patient-centered monitoring approach, as we work to create dynamic adaptive protection services according to the current context of patient. This work executes a sequential modular approach consisting of patient, disease, location, devices, activities, environment and services to deliver personalized real-time medical care for COPD patients. The main benefits of this project are: (1) adhering to dynamic safe boundaries for the vital signs, which may vary depending on multiple factors; (2) assessing environmental risk factors; and (3) evaluating the patient’s daily activities through scheduled events to avoid potentially dangerous situations. This solution implements an interrelated set of ontologies with a logical base of Semantic Web Rule Language (SWRL) rules derived from the medical guidelines and expert pneumologists to handle all contextual situations

A pervasive healthcare system for COPD patients

Chronic obstructive pulmonary disease (COPD) is one of the most severe public health problems worldwide. Pervasive computing technology creates a new opportunity to redesign the traditional pattern of medical system. While many pervasive healthcare systems are currently found in the literature, there is little published research on the effectiveness of these paradigms in the medical context. This paper designs and validates a rule-based ontology framework for COPD patients. Unlike conventional systems, this work presents a new vision of telemedicine and remote care solutions that will promote individual self-management and autonomy for COPD patients through an advanced decision-making technique. Rules accuracy estimates were 89% for monitoring vital signs, and environmental factors, and 87% for nutrition facts, and physical activities

Adaptive mechanism model for the prevention of SLA violation in the context of COPD patient monitoring

In this paper, we introduce a new kind of Service Level Agreement(SLA) Template to better control dynamically quality of medical monitoring platform service. Our approach is based on Health care system and Health Information Technology (HIT) research area, specifically the field of telemonitoring system for patients who suffer from chronic obstructive pulmonary disease (COPD). According to WHO statistics, COPD is the third leading cause of death worldwide. To this end, several solutions or platforms exist today to monitor COPD. Most of these platforms manage large volume of patient data. This can bring about quality and lost data problems. To address these issues, control mechanisms must be proposed and designed to improve the quality of service (QoS) on these platforms. A platform with continuously monitored QoS can save patients’ lives and reduce data quality risk. In this article, we propose an ontology that uses SLAs data from COPD monitoring platforms with dynamic data from a patient context. We dynamically calculate the number of patient data incidents and the number of service request incidents from two dynamic contexts: SLA and the patient context. If the number of incidents is higher than what is expected in the SLA, then alerts are sent to the interface parties in real time. Finally, the contribution of this article is the proposed virtual SLA template to better control SLA violation and improve quality of medical monitoring platforms services