Ami-deu : un cadre sémantique pour des applications adaptables dans des environnements intelligents

Cette thèse vise à étendre l’utilisation de l'Internet des objets (IdO) en facilitant le développement d’applications par des personnes non experts en développement logiciel. La thèse propose une nouvelle approche pour augmenter la sémantique des applications d’IdO et l’implication des experts du domaine dans le développement d’applications sensibles au contexte. Notre approche permet de gérer le contexte changeant de l’environnement et de générer des applications qui s’exécutent dans plusieurs environnements intelligents pour fournir des actions requises dans divers contextes. Notre approche est mise en œuvre dans un cadriciel (AmI-DEU) qui inclut les composants pour le développement d’applications IdO. AmI-DEU intègre les services d’environnement, favorise l’interaction de l’utilisateur et fournit les moyens de représenter le domaine d’application, le profil de l’utilisateur et les intentions de l’utilisateur. Le cadriciel permet la définition d’applications IoT avec une intention d’activité autodécrite qui contient les connaissances requises pour réaliser l’activité. Ensuite, le cadriciel génère Intention as a Context (IaaC), qui comprend une intention d’activité autodécrite avec des connaissances colligées à évaluer pour une meilleure adaptation dans des environnements intelligents. La sémantique de l’AmI-DEU est basée sur celle du ContextAA (Context-Aware Agents) – une plateforme pour fournir une connaissance du contexte dans plusieurs environnements. Le cadriciel effectue une compilation des connaissances par des règles et l'appariement sémantique pour produire des applications IdO autonomes capables de s’exécuter en ContextAA. AmI- DEU inclut également un outil de développement visuel pour le développement et le déploiement rapide d'applications sur ContextAA. L'interface graphique d’AmI-DEU adopte la métaphore du flux avec des aides visuelles pour simplifier le développement d'applications en permettant des définitions de règles étape par étape. Dans le cadre de l’expérimentation, AmI-DEU comprend un banc d’essai pour le développement d’applications IdO. Les résultats expérimentaux montrent une optimisation sémantique potentielle des ressources pour les applications IoT dynamiques dans les maisons intelligentes et les villes intelligentes. Notre approche favorise l'adoption de la technologie pour améliorer le bienêtre et la qualité de vie des personnes. Cette thèse se termine par des orientations de recherche que le cadriciel AmI-DEU dévoile pour réaliser des environnements intelligents omniprésents fournissant des adaptations appropriées pour soutenir les intentions des personnes.Abstract: This thesis aims at expanding the use of the Internet of Things (IoT) by facilitating the development of applications by people who are not experts in software development. The thesis proposes a new approach to augment IoT applications’ semantics and domain expert involvement in context-aware application development. Our approach enables us to manage the changing environment context and generate applications that run in multiple smart environments to provide required actions in diverse settings. Our approach is implemented in a framework (AmI-DEU) that includes the components for IoT application development. AmI- DEU integrates environment services, promotes end-user interaction, and provides the means to represent the application domain, end-user profile, and end-user intentions. The framework enables the definition of IoT applications with a self-described activity intention that contains the required knowledge to achieve the activity. Then, the framework generates Intention as a Context (IaaC), which includes a self-described activity intention with compiled knowledge to be assessed for augmented adaptations in smart environments. AmI-DEU framework semantics adopts ContextAA (Context-Aware Agents) – a platform to provide context-awareness in multiple environments. The framework performs a knowledge compilation by rules and semantic matching to produce autonomic IoT applications to run in ContextAA. AmI-DEU also includes a visual tool for quick application development and deployment to ContextAA. The AmI-DEU GUI adopts the flow metaphor with visual aids to simplify developing applications by allowing step-by-step rule definitions. As part of the experimentation, AmI-DEU includes a testbed for IoT application development. Experimental results show a potential semantic optimization for dynamic IoT applications in smart homes and smart cities. Our approach promotes technology adoption to improve people’s well-being and quality of life. This thesis concludes with research directions that the AmI-DEU framework uncovers to achieve pervasive smart environments providing suitable adaptations to support people’s intentions

Ubiquitous Robotics System for Knowledge-based Auto-configuration System for Service Delivery within Smart Home Environments

The future smart home will be enhanced and driven by the recent advance of the Internet of Things (IoT), which advocates the integration of computational devices within an Internet architecture on a global scale [1, 2]. In the IoT paradigm, the smart home will be developed by interconnecting a plethora of smart objects both inside and outside the home environment [3-5]. The recent take-up of these connected devices within home environments is slowly and surely transforming traditional home living environments. Such connected and integrated home environments lead to the concept of the smart home, which has attracted significant research efforts to enhance the functionality of home environments with a wide range of novel services. The wide availability of services and devices within contemporary smart home environments make their management a challenging and rewarding task. The trend whereby the development of smart home services is decoupled from that of smart home devices increases the complexity of this task. As such, it is desirable that smart home services are developed and deployed independently, rather than pre-bundled with specific devices, although it must be recognised that this is not always practical. Moreover, systems need to facilitate the deployment process and cope with any changes in the target environment after deployment. Maintaining complex smart home systems throughout their lifecycle entails considerable resources and effort. These challenges have stimulated the need for dynamic auto-configurable services amongst such distributed systems. Although significant research has been directed towards achieving auto-configuration, none of the existing solutions is sufficient to achieve auto-configuration within smart home environments. All such solutions are considered incomplete, as they lack the ability to meet all smart home requirements efficiently. These requirements include the ability to adapt flexibly to new and dynamic home environments without direct user intervention. Fulfilling these requirements would enhance the performance of smart home systems and help to address cost-effectiveness, considering the financial implications of the manual configuration of smart home environments. Current configuration approaches fail to meet one or more of the requirements of smart homes. If one of these approaches meets the flexibility criterion, the configuration is either not executed online without affecting the system or requires direct user intervention. In other words, there is no adequate solution to allow smart home systems to adapt dynamically to changing circumstances, hence to enable the correct interconnections among its components without direct user intervention and the interruption of the whole system. Therefore, it is necessary to develop an efficient, adaptive, agile and flexible system that adapts dynamically to each new requirement of the smart home environment. This research aims to devise methods to automate the activities associated with customised service delivery for dynamic home environments by exploiting recent advances in the field of ubiquitous robotics and Semantic Web technologies. It introduces a novel approach called the Knowledge-based Auto-configuration Software Robot (Sobot) for Smart Home Environments, which utilises the Sobot to achieve auto-configuration of the system. The research work was conducted under the Distributed Integrated Care Services and Systems (iCARE) project, which was designed to accomplish and deliver integrated distributed ecosystems with a homecare focus. The auto-configuration Sobot which is the focus of this thesis is a key component of the iCARE project. It will become one of the key enabling technologies for generic smart home environments. It has a profound impact on designing and implementing a high quality system. Its main role is to generate a feasible configuration that meets the given requirements using the knowledgebase of the smart home environment as a core component. The knowledgebase plays a pivotal role in helping the Sobot to automatically select the most appropriate resources in a given context-aware system via semantic searching and matching. Ontology as a technique of knowledgebase representation generally helps to design and develop a specific domain. It is also a key technology for the Semantic Web, which enables a common understanding amongst software agents and people, clarifies the domain assumptions and facilitates the reuse and analysis of its knowledge. The main advantages of the Sobot over traditional applications is its awareness of the changing digital and physical environments and its ability to interpret these changes, extract the relevant contextual data and merge any new information or knowledge. The Sobot is capable of creating new or alternative feasible configurations to meet the system’s goal by utilising inferred facts based on the smart home ontological model, so that the system can adapt to the changed environment. Furthermore, the Sobot has the capability to execute the generated reconfiguration plan without interrupting the running of the system. A proof-of-concept testbed has been designed and implemented. The case studies carried out have shown the potential of the proposed approach to achieve flexible and reliable auto-configuration of the smart home system, with promising directions for future research

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

QoS awareness and adaptation in service composition

The dynamic nature of a Web service execution environment generates frequent variations in the Quality of Service offered to the consumers, therefore, obtaining the expected results while running a composite service is not guaranteed. When combining this highly changing environment with the increasing emphasis on Quality of Service, management of composite services turns into a time consuming and complicated task. Different approaches and tools have been proposed to mitigate the impacts of unexpected events during the execution of composite services. Among them, self-adaptive proposals have stood out, since they aim to maintain functional and quality levels, by dynamically adapting composite services to the environment conditions, reducing human intervention. The research presented in this Thesis is centred on self-adaptive properties in service composition, mainly focused on self-optimization. Three models have been proposed to target self-optimization, considering various QoS parameters, the benefit of performing adaptation, and looking at adaptation from two perspectives: reactive and proactive. They target situations where the QoS of the composition is decreasing. Also, they consider situations where a number of the accumulated QoS values, in certain point of the process, are better than expected, providing the possibility of improving other QoS parameters. These approaches have been implemented in service composition frameworks and evaluated through the execution of test cases. Evaluation was performed by comparing the QoS values gathered from multiple executions of composite services, using the proposed optimization models and a non-adaptive approach. The benefit of adaptation was found a useful value during the decision making process, in order to determine if adaptation was needed or not. Results show that using optimization mechanisms when executing composite services provide significant improvements in the global QoS values of the compositions. Nevertheless, in some cases there is a trade-off, where one of the measured parameters shows an increment, in order to improve the others

Reminder Care System: An Activity-Aware Cross-Device Recommendation System

© 2019, Springer Nature Switzerland AG. Alzheimer’s disease (AD) affects large numbers of elderly people worldwide and represents a significant social and economic burden on society, particularly in relation to the need for long term care facilities. These costs can be reduced by enabling people with AD to live independently at home for a longer time. The use of recommendation systems for the Internet of Things (IoT) in the context of smart homes can contribute to this goal. In this paper, we present the Reminder Care System (RCS), a research prototype of a recommendation system for the IoT for elderly people with cognitive disabilities. RCS exploits daily activities that are captured and learned from IoT devices to provide personalised recommendations. The experimental results indicate that RCS can inform the development of real-world IoT applications

An Autonomic Cross-Platform Operating Environment for On-Demand Internet Computing

The Internet has evolved into a global and ubiquitous communication medium interconnecting powerful application servers, diverse desktop computers and mobile notebooks. Along with recent developments in computer technology, such as the convergence of computing and communication devices, the way how people use computers and the Internet has changed people´s working habits and has led to new application scenarios. On the one hand, pervasive computing, ubiquitous computing and nomadic computing become more and more important since different computing devices like PDAs and notebooks may be used concurrently and alternately, e.g. while the user is on the move. On the other hand, the ubiquitous availability and pervasive interconnection of computing systems have fostered various trends towards the dynamic utilization and spontaneous collaboration of available remote computing resources, which are addressed by approaches like utility computing, grid computing, cloud computing and public computing. From a general point of view, the common objective of this development is the use of Internet applications on demand, i.e. applications that are not installed in advance by a platform administrator but are dynamically deployed and run as they are requested by the application user. The heterogeneous and unmanaged nature of the Internet represents a major challenge for the on demand use of custom Internet applications across heterogeneous hardware platforms, operating systems and network environments. Promising remedies are autonomic computing systems that are supposed to maintain themselves without particular user or application intervention. In this thesis, an Autonomic Cross-Platform Operating Environment (ACOE) is presented that supports On Demand Internet Computing (ODIC), such as dynamic application composition and ad hoc execution migration. The approach is based on an integration middleware called crossware that does not replace existing middleware but operates as a self-managing mediator between diverse application requirements and heterogeneous platform configurations. A Java implementation of the Crossware Development Kit (XDK) is presented, followed by the description of the On Demand Internet Computing System (ODIX). The feasibility of the approach is shown by the implementation of an Internet Application Workbench, an Internet Application Factory and an Internet Peer Federation. They illustrate the use of ODIX to support local, remote and distributed ODIC, respectively. Finally, the suitability of the approach is discussed with respect to the support of ODIC

Towards formalisation of situation-specific computations in pervasive computing environments

We have categorised the characteristics and the content of pervasive computing environments (PCEs), and demonstrated why a non-dynamic approach to knowledge conceptualisation in PCEs does not fulfil the expectations we may have from them. Consequently, we have proposed a formalised computational model, the FCM, for knowledge representation and reasoning in PCEs which, secures the delivery of situation and domain specific services to their users. The proposed model is a user centric model, materialised as a software engineering solution, which uses the computations generated from the FCM, stores them within software architectural components, which in turn can be deployed using modern software technologies. The model has also been inspired by the Semantic Web (SW) vision and provision of SW technologies. Therefore, the FCM creates a semantically rich situation-specific PCE based on SWRL-enabled OWL ontologies that allows reasoning about the situation in a PCE and delivers situation specific service. The proposed FCM model has been illustrated through the example of remote patient monitoring in the healthcare domain. Numerous software applications generated from the FCM have been deployed using Integrated Development Environments and OWL-API

Expert System for Nutrition Care Process of Older Adults

This paper presents an expert system for a nutrition care process tailored for the specific needs of elders. Dietary knowledge is defined by nutritionists and encoded as Nutrition Care Process Ontology, and then used as underlining base and standardized model for the nutrition care planning. An inference engine is developed on top of the ontology, providing semantic reasoning infrastructure and mechanisms for evaluating the rules defined for assessing short and long term elders’ self-feeding behaviours, to identify unhealthy dietary patterns and detect the early instauration of malnutrition. Our expert system provides personalized intervention plans covering nutrition education, diet prescription and food ordering adapted to the older adult’s specific nutritional needs, health conditions and food preferences. In-lab evaluation results are presented proving the usefulness and quality of the expert system as well as the computational efficiency, coupling and cohesion of the defined ontology