Sensory semantic user interfaces (SenSUI)

Rapid evolution of the World Wide Web with its underlying sources of data, knowledge, services and applications continually attempts to support a variety of users, with different backgrounds, requirements and capabilities. In such an environment, it is highly unlikely that a single user interface will prevail and be able to fulfill the requirements of each user adequately. Adaptive user interfaces are able to adapt information and application functionalities to the user context. In contrast, pervasive computing and sensor networks open new opportunities for context aware platforms, one that is able to improve user interface adaptation reacting to environmental and user sensors. Semantic web technologies and ontologies are able to capture sensor data and provide contextual information about the user, their actions, required applications and environment. This paper investigates the viability of an approach where semantic web technologies are used to maximize the efficacy of interface adaptation through the use of available ontology

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

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing

Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.Comment: This paper will appear on AIMS'19 (International Conference on Artificial Intelligence and Mobile Services) on June 2

A user-centric vision of service-oriented Pervasive Information Systems

International audienceInformation Systems (IS) have massively adopted service orientation by exposing their functionalities as services. With the evolution of mobile technologies (smartphones, 3G/4G networks, etc.), such systems are now confronted with a new pervasive environment for which they were not originally designed. Indeed, pervasive environments are characterized by their heterogeneity and dynamicity due to their evolving context and their need for transparency. None of these features are particularly considered in traditional IS designed for stable and controlled office environments. In our new vision for service- oriented Pervasive Information Systems (PIS), the user becomes the center of these systems. This paper presents a user-centric service-oriented vision for PIS based on a context-aware intentional approach, which considers the user intention and the context in which this intention arises as a guiding principle for service description, discovery, prediction and recommendation

Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback

Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector

UBIDEV: a homogeneous service framework for pervasive computing environments

This dissertation studies the heterogeneity problem of pervasive computing system from the viewpoint of an infrastructure aiming to provide a service-oriented application model. From Distributed System passing through mobile computing, pervasive computing is presented as a step forward in ubiquitous availability of services and proliferation of interacting autonomous entities. To better understand the problems related to the heterogeneous and dynamic nature of pervasive computing environments, we need to analyze the structure of a pervasive computing system from its physical and service dimension. The physical dimension describes the physical environment together wit the technology infrastructure that characterizes the interactions and the relations within the environment; the service dimension represents the services (being them software or not) the environment is able to provide [Nor99]. To better separate the constrains and the functionalities of a pervasive computing system, this dissertation classifies it in terms of resources, context, classification, services, coordination and application. UBIDEV, as the key result of this dissertation, introduces a unified model helping the design and the implementation of applications for heterogeneous and dynamic environments. This model is composed of the following concepts: • Resource: all elements of the environment that are manipulated by the application, they are the atomic abstraction unit of the model. • Context: all information coming from the environment that is used by the application to adapts its behavior. Context contains resources and services and defines their role in the application. • Classification: the environment is classified according to the application ontology in order to ground the generic conceptual model of the application to the specific environment. It defines the basic semantic level of interoperability. • Service: the functionalities supported by the system; each service manipulates one or more resources. Applications are defined as a coordination and adaptation of services. • Coordination: all aspects related to service composition and execution as well as the use of the contextual information are captured by the coordination concept. • Application Ontology: represents the viewpoint of the application on the specific context; it defines the high level semantic of resources, services and context. Applying the design paradigm proposed by UBIDEV, allows to describe applications according to a Service Oriented Architecture[Bie02], and to focus on application functionalities rather than their relations with the physical devices. Keywords: pervasive computing, homogenous environment, service-oriented, heterogeneity problem, coordination model, context model, resource management, service management, application interfaces, ontology, semantic services, interaction logic, description logic.Questa dissertazione studia il problema della eterogeneit`a nei sistemi pervasivi proponendo una infrastruttura basata su un modello orientato ai servizi. I sistemi pervasivi sono presentati come un’evoluzione naturale dei sistemi distribuiti, passando attraverso mobile computing, grazie ad una disponibilit`a ubiqua di servizi (sempre, ovunque ed in qualunque modo) e ad loro e con l’ambiente stesso. Al fine di meglio comprendere i problemi legati allintrinseca eterogeneit`a dei sistemi pervasivi, dobbiamo prima descrivere la struttura fondamentale di questi sistemi classificandoli attraverso la loro dimensione fisica e quella dei loro servizi. La dimensione fisica descrive l’ambiente fisico e tutti i dispositivi che fanno parte del contesto della applicazione. La dimensione dei servizi descrive le funzionalit`a (siano esse software o no) che l’ambiente `e in grado di fornire [Nor99]. I sistemi pervasivi vengono cos`ı classificati attraverso una metrica pi `u formale del tipo risorse, contesto, servizi, coordinazione ed applicazione. UBIDEV, come risultato di questa dissertazione, introduce un modello uniforme per la descrizione e lo sviluppo di applicazioni in ambienti dinamici ed eterogenei. Il modello `e composto dai seguenti concetti di base: • Risorse: gli elementi dell’ambiente fisico che fanno parte del modello dellapplicazione. Questi rappresentano l’unit`a di astrazione atomica di tutto il modello UBIDEV. • Contesto: le informazioni sullo stato dell’ambiente che il sistema utilizza per adattare il comportamento dell’applicazione. Il contesto include informazioni legate alle risorse, ai servizi ed alle relazioni che li legano. • Classificazione: l’ambiente viene classificato sulla base di una ontologia che rappresenta il punto di accordo a cui tutti i moduli di sistema fanno riferimento. Questa classificazione rappresenta il modello concettuale dell’applicazione che si riflette sull’intero ambiente. Si definisce cos`ı la semantica di base per tutto il sistema. • Servizi: le funzionalit`a che il sistema `e in grado di fornire; ogni servizio `e descritto in termini di trasformazione di una o pi `u risorse. Le applicazioni sono cos`ı definite in termini di cooperazione tra servizi autonomi. • Coordinazione: tutti gli aspetti legati alla composizione ed alla esecuzione di servizi cos`ı come l’elaborazione dell’informazione contestuale. • Ontologia dell’Applicazione: rappresenta il punto di vista dell’applicazione; definisce la semantica delle risorse, dei servizi e dell’informazione contestuale. Applicando il paradigma proposto da UBIDEV, si possono descrivere applicazioni in accordo con un modello Service-oriented [Bie02] ed, al tempo stesso, ridurre l’applicazione stessa alle sue funzionalit`a di alto livello senza intervenire troppo su come queste funzionalit` a devono essere realizzate dalle singole componenti fisiche