Browsing by Author "Donnelly, Mark P."

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    A Conceptual Framework for Supporting Adaptive Personalized Help-on-Demand Services
    (Springer, 2012-11) Burns, William; Chen, Liming; Nugent, Chris; Donnelly, Mark P.; Skillen, Kerry-Louise; Solheim, Ivar
    Mobile applications that encompass personalization and context-aware components are increasingly becoming more prevalent. The ability to offer personalized content and User Interfaces to the users of these applications, however, has still not been fully addressed. In this paper we describe a conceptual framework that establishes a User Profile and aims to monitor the usage patterns of users of a mobile application and, based on these patterns, provide both personalized, context aware content and user interfaces. The framework consists of four components that together contribute towards an overall Help on Demand service that is targeted at older age Smartphone users. A usage scenario is presented to describe the typical usage of the help on demand service.
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    A dynamic annotation tool to support in-home autism intervention
    (2012) Donnelly, Mark P.; Cruciani, F.; Galway, L.; Nugent, Chris; Paggetti, C.; McCullogh, P.; Tamburini, E.; Chen, Liming
    The Congress sets out to be an international forum for the exchange of ideas and opinions in which different parties (people with autism, families, professionals of the intervention, investigators and developers) are able to debate on the subject of applied technologies in the world of autism.
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    Formal Modeling Techniques for Ambient Assisted Living
    (Springer, 2010-11-23) Parente, G.; Nugent, Chris; Hong, X.; Donnelly, Mark P.; Chen, Liming; Vicario, E.
    In the development of systems of ambient assisted living (AAL), formalized models and analysis techniques can provide a ground that makes development amenable to a systematic approach. We consider the following formal modeling tools and techniques: fault trees, evidential reasoning, evidential ontology networks, temporal logic, hidden Markov models and partially observable Markov models. We review them in the perspective of their potential in the realm of AAL, recalling the general traits and potential of each of them, and highlighting how this can be concretely deployed within the AAL realm. To this end, we present a number of scenarios providing insight on how each technique can match the needs of different types of problem in the application domain.
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    A Generic Upper-Level Ontological Model for Context-aware Applications within Smart Environments
    (Springer, 2013-12) McAvoy, Laura M.; Chen, Liming; Donnelly, Mark P.
    Context modeling has attracted increasing attention due to the prevalence of context-aware applications within smart environments. Whilst upper-level context ontologies exist for use within smart environments, none offer a single generalized model covering all high-level elements that exist across all types of smart environments. This paper presents an upper-level context ontology for smart environments which aims to incorporate all factors deemed important for context in smart environments. Specifically, the proposed model considers key factors that include User, Object, Location, Application, Event, Natural Element and Temporal. The model is able to represent daily routines encompassing both open-world and closed-world activities and this is presented in a short vignette.
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    Learning Behaviour for Service Personalisation and Adaptation
    (Springer, 2014-12-05) Chen, Liming; Skillen, Kerry-Louise; Burns, William; Quinn, Susan; Rafferty, Joseph; Nugent, Chris; Donnelly, Mark P.; Solheim, Ivar
    Context-aware applications within pervasive environments are increasingly being developed as services and deployed in the cloud. As such these services are increasingly required to be adaptive to individual users to meet their specific needs or to reflect the changes of their behavior. To address this emerging challenge this paper introduces a service-oriented personalisation framework for service personalisation with special emphasis being placed on behavior learning for user model and service function adaptation. The paper describes the system architecture and the underlying methods and technologies including modelling and reasoning, behavior analysis and a personalisation mechanism. The approach has been implemented in a service-oriented prototype system, and evaluated in a typical scenario of providing personalised travel assistance for the elderly using the help-on-demand services deployed on smartphone.
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    Managing Sensor Data in Ambient Assisted Living
    (The Korean Institute of Information Scientists and Engineers, 2011-11) Nugent, Chris; Galway, L.; McClean, S.I.; Zhang, S.; Scotney, L.; Chen, Liming; Donnelly, Mark P.; Parr, G.
    The use of technology within the home has gained wide spread acceptance as one possible approach to be used in addressing the challenges of an ageing society. A number of rudimentary assistive solutions are now being deployed in real settings but with the introduction of these technology-orientated services come a number of challenges, which to date are still largely unsolved. At a fundamental level, the management and processing of the large quantities of data generated from multiple sensors is recognised as one of the most significant challenges. This paper aims to present an overview of the types of sensor technologies used within Ambient Assisted Living. Subsequently, through presentation of a series of case studies, the paper will demonstrate how the practical integration of multiple sources of sensor data can be used to improve the overall concept and applications of Ambient Assisted Living
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    Mining usage data for adaptive personalisation of smartphone based help-on-demand services
    (ACM, 2013-05-29) Burns, William; Chen, Liming; Nugent, Chris; Donnelly, Mark P.; Skillen, Kerry-Louise; Solheim, Ivar
    Mobile computing devices and their applications that encompass context aware components are becoming increasingly more prevalent. The context-awareness of these types of applications typically focuses on the services offered. In this paper we describe a framework that supports the monitoring and analysis of mobile application usage patterns with the goal of updating user models for adaptive services and user interface personalisation. This paper focuses on two aspects of the framework. The first is the modelling and storage of the usage data. The second focuses on the data mining component of the framework, outlining the five different capabilities of the adaptation in addition to the algorithms used. The proposed framework has been evaluated through specific case studies, with the results attained demonstrating the effectiveness of the data mining capabilities and in particular the adaptation of the User Interface. The accuracy and efficiency of the algorithms used are also evaluated with three users. The results of the evaluation show that the aims of the data mining component were achieved with the personalisation and adaptation of content and user interface, respectively.
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    A Novel Approach for the Population and Adaptation of Ontology-Based User Profiles
    (Springer, 2014-12) Skillen, Kerry-Louise; Nugent, Chris; Donnelly, Mark P.; Chen, Liming; Burns, William; Solheim, Ivar
    User personalisation within context-aware applications has become increasingly prevalent in recent years. The use of ontologies enriched with semantics has enabled the creation of highly relevant user profiles, which have been used to facilitate the personalisation of assistive services. Existing work highlights the challenge of aiding non-expert users to intuitively manage their own profiles. This paper details a new approach to help enable the automatic creation, population and adaptation of ontology-based user profiles. Primarily, the research aims to create and enrich ontological profiles over time, for the purposes of user personalisation. The approach has been realised through the development of an intuitive desktop application, which has been evaluated through a series of experiments.
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    Ontological characterization and representation of context within smart environments
    (Computer Systems Science and Engineering, 2015-01) McAvoy, Laura M.; Chen, Liming; Donnelly, Mark P.; Nugent, Chris; McCullagh, Paul J.
    Contextual information within smart environments varies greatly. Whilst upper-level ontologies for contextual information relating to smart environments have been previously proposed, they have typically only been applicable to specific domains. As such, a wide range of entity names are used, overlooking other important relevant entities. This paper presents a conceptualisation and generation of an upper-level ontology,which encompasses the key factors, deemed important for context within smart environments. These factors include User, Object, Location, Natural Element, Application, Event and Temporal. The use of the model to support high-level context generation is also discussed in the form of an indicative short vignette (an envisaged smart environment)accompanied with the results from a real smart environment implementation (intelligent meeting room).
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    ItemOpen Access
    Ontological user modelling and semantic rule-based reasoning for personalisation of Help-On-Demand services in pervasive environments
    (Elsevier, 2013-11-15) Skillen, Kerry-Louise; Chen, Liming; Nugent, Chris; Donnelly, Mark P.; Burns, William; Solheim, Ivar
    Existing context-aware applications are limited in their support of user personalisation. Nevertheless, the increase in the use of context-aware technologies has sparked the growth in assistive applications resulting in a need to enable adaptation to reflect the changes in user behaviours. This paper introduces a systematic approach to service personalisation for mobile users in pervasive environments and presents a service-oriented distributed system architecture. The developed approach makes use of semantic technologies for user modelling and personalisation reasoning. In the paper we characterise user behaviours and needs in pervasive environments upon which ontological user models are created with special emphasis being placed on ontological modelling of dynamic and adaptive user profiles. We develop a rule-based personalisation mechanism that exploits semantic web rule mark-up language for rule design and a combination of semantic and rule-based reasoning for personalisation. We use two case studies focusing on providing personalised travel assistance for people using Help-on-Demand services deployed on a smart-phone to contextualise the discussions within the paper. The proposed approach is implemented in a prototype system, which includes Help-on-Demand services, content management services, user models and personalisation mechanisms in addition to application specific rules. Experiments have been designed and conducted to test and evaluate the approach with initial results demonstrating the functionality of the approach.
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    Ontological User Profile Modelling for Personalization of Context-Aware Applications
    (Springer, 2012-12) Skillen, Kerry-Louise; Chen, Liming; Nugent, Chris; Burns, William; Solheim, Ivar; Donnelly, Mark P.
    Existing context-aware adaptation techniques are limited in their support for user personalization. There is relatively less developed research involving adaptive user modeling for user applications in the emerging areas of mobile and pervasive computing. This paper describes the creation of a User Profile Ontology for context-aware application personalization within mobile environments. We analyze users’ behavior and characterize users’ needs for context-aware applications. Special emphasis is placed in the ontological modeling of dynamic components for use in adaptable applications. We illustrate the use of the model in the context of a case study, focusing on providing personalized services to older people via smart-device technologies.
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    An Ontology Based Context Management System for Smart Environments
    (XPS (Xpert Publishing Services), 2012-09) McAvoy, Laura M.; Chen, Liming; Donnelly, Mark P.
    This paper proposes an ontology-enabled system for context management for smart environments. Central to the system is ontological sensor modelling, which attaches metadata and meaning to sensor data, thus supporting data repurposing and high-level content recognition. In addition, semantic sensor descriptions allow sensors to be automatically identified whenever they are put into an environment. Based on this, a novel plug-n-measure data acquisition mechanism has been developed to automatically detect and recognise new devices and update the contextual data relating to these devices on a real-time basis. The context management system has been developed based on the latest semantic technologies and deployed in an intelligent meeting room. The paper describes an experiment and presents initial results, which has demonstrated that the system is working.
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    Requirements for the Deployment of Sensor Based Recognition Systems for Ambient Assistive Living
    (Springer, 2010-06-22) Biswas, J.; Baumgarten, M.; Tolstikov, A.; Phyo Wai, A.A.; Nugent, Chris; Chen, Liming; Donnelly, Mark P.
    The deployment, replication and adaptation of sensor environments at various scales and for various purposes is one of the challenges academia as well as industry are faced with today. Individual user requirements, the heterogeneity of devices, the often non-standardized communication protocols in addition to proprietary-related aspects are just some of the problems, which must be addressed in order to establish flexible, efficient and maybe most importantly, cost-effective smart environments that are capable to facilitate Ambient Assisted Living (AAL). This paper discusses some of the requirements for the design and deployment of activity recognition systems and also addresses some of the problems that arose during the replication and adaptation of such a system along with a reflection on the lessons learnt.
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    A User Profile Ontology Based Approach for Assisting People with Dementia in Mobile Environments
    (IEEE, 2012-08) Skillen, Kerry-Louise; Chen, Liming; Nugent, Chris; Donnelly, Mark P.
    Personalization and context-aware applications have attracted increasing amounts of attention over recent years due to the emergence of pervasive computing applications. Nevertheless, it still remains a challenge to meet the needs of users while they are on the move. This paper introduces a novel approach for providing personalized, context-aware assistance services for users in mobile environments. Central to the approach is the use of ontological user profile modeling which captures various characteristics of a user in order to create a unique set of profile information. In addition, user profiles can adapt to changing user behavior, thus enabling services to respond to evolving user needs and preferences. We describe the overall system architecture of the proposed approach with special emphasis being placed on the user profile modelling and its expected utility based on a typical use case scenario, i.e., using a smart-phone to address the problem of the outdoor mobility of a person with Dementia. A prototype based on the Android OS is used to illustrate the application. The use of everyday technology for a real world problem highlights the potential and utility of our approach.
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    Using Ontologies for Managing User Profiles in Personalised Mobile Service Delivery, Health Monitoring and Personalized Feedback using Multimedia Data
    (Springer, 2015-09) Skillen, Kerry-Louise; Nugent, Chris; Donnelly, Mark P.; Chen, Liming; Burns, William
    We are now living in a technological world where the adoption of pervasive technologies is becoming more prevalent. This has sparked growth in the development of services for delivery in pervasive environments, across a number of application domains including healthcare. User personalisation, in particular, has become an important element for delivering pervasive healthcare, which has coincided with the rapid increase in the use of smart-phone technologies. Increased user dependence on technology has resulted in a need to provide personalised service delivery, in the form of adaptive technology. Many studies have explored the use of ontological user modelling techniques to facilitate mobile service personalisation. Ontological user models have been developed for use within personalised web information retrieval systems, adaptive user interface design and within public services. Nevertheless, these models have not been adopted to implement the personalisation of assistive services for mobile users within pervasive environments. Every person is unique and therefore, will exhibit unique behaviours, wants and needs, which will also change over time. Adaptive technologies must be able to cater for human behavioural changes, and change to suit them via on-demand service delivery. This Chapter focuses on two key perspectives. Firstly, the modelling of different users within pervasive environments is introduced and critiqued and secondly, the topics of ontological modelling and user profile representation are contextualised within a discussion surrounding previous research undertaken by the authors.
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    Using SWRL and ontological reasoning for the personalization of context-aware assistive services
    (ACM Press, 2013-05-29) Skillen, Kerry-Louise; Chen, Liming; Nugent, Chris; Donnelly, Mark P.; Burns, William; Solheim, Ivar
    The prevalence and advancements of existing context-aware applications are limited in their support of personalization for the user. The increase in the use of context-aware technologies has sparked growth in assistive applications and there is now a need to enable the adaptation of such technologies to reflect the changes in user behaviors. This paper describes the conceptualization and development of a personalization mechanism that can be integrated into a context-aware application for the purposes of providing an adaptable, mobile-based service to a user. We highlight the use of an ontological User Profile Model to provide a detailed representation of a user for use within adaptive applications. Special emphasis is placed on the use of rule-based reasoning using the Semantic Web Rule Language (SWRL). The paper details how these rules are created and used alongside the User Profile for the purposes of application personalization. We present a case study to illustrate the use of SWRL within the User Profile Model. Specifically, the case study focuses on providing personalized travel assistance to older users, with the use of self-service ticket machines via an `on-demand' context-aware smart-phone.